14th International Symposium on Process Systems Engineering

14th International Symposium on Process Systems Engineering

1st Edition - June 10, 2022

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  • Editors: Yoshiyuki Yamashita, Manabu Kano
  • Hardcover ISBN: 9780323851596
  • eBook ISBN: 9780323853668

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Description

14th International Symposium on Process Systems Engineering, Volume 49 brings together the international community of researchers and engineers interested in computing-based methods in process engineering. The conference highlights the contributions of the PSE community towards the sustainability of modern society and is based on the 2021 event held in Tokyo, Japan, July 1-23, 2021. It contains contributions from academia and industry, establishing the core products of PSE, defining the new and changing scope of our results, and covering future challenges. Plenary and keynote lectures discuss real-world challenges (globalization, energy, environment and health) and contribute to discussions on the widening scope of PSE versus the consolidation of the core topics of PSE.

Key Features

  • Highlights how the Process Systems Engineering community contributes to the sustainability of modern society
  • Establishes the core products of Process Systems Engineering
  • Defines the future challenges of Process Systems Engineering

Readership

Chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries

Table of Contents

  • Cover image
  • Table of Contents
  • Copyright
  • Preface
  • International Program Committee
  • Conference Chairs
  • Member
  • Copyright
  • Copyright
  • Invited Papers and Extended Abstracts
  • Actions toward carbon-neutral society with fuel cell technology
  • Abstract
  • 1: The world trend of carbon neutrality and hydrogen energy
  • 2: Fuel cell development for various applications and usages
  • 3: Collaboration for developing fuel cells and expectations for PSE
  • Conclusions
  • References
  • Challenges and Opportunities for Process Systems Engineering in a Changed World
  • Abstract
  • 1: Introduction
  • 2: PSE methods and tools
  • 3: Challenges and roles of PSE
  • 4: Perspectives (Opportunities)
  • 5: Conclusions
  • References
  • PSE Tools and Challenges in the Development of Advanced Pharmaceutical Manufacturing
  • Abstract
  • 1: Introduction
  • 2: Application in solid-based drug and biologics manufacturing
  • Acknowledgement
  • References
  • Experience and Perspectives on our Journey towards Deep Decarbonization
  • Abstract
  • 1: Introduction
  • 2: Reduce
  • 3: Recycle / Reuse
  • 4: Replace
  • 5: Conclusions
  • Acknowledgements
  • References
  • Surrogate Modeling and Surrogate-Based Optimization with Stochastic Simulations
  • Abstract
  • 1: Introduction
  • 2: Framework for Training Surrogate Models for Stochastic Simulations
  • 3: Computational Experiments
  • 4: Results and Discussion
  • 5: Conclusions
  • References
  • Application of PSE into social changes: biomass-based production, recycling systems, and regional systems design and assessment
  • Abstract
  • 1: Introduction
  • 2: Reviews on application of PSE
  • 3: Application of PSE into social changes
  • 4: Conclusions
  • Acknowledgement
  • References
  • Q-MPC: Integration of Reinforcement Learning and Model Predictive Control for Safe Learning
  • Abstract
  • 1: Introduction
  • 2: Q-model predictive control
  • 3: Simulation studies
  • 4: Conclusions
  • References
  • Presentation abstract: Optimization formulations for machine learning surrogates
  • Abstract
  • 1: Main Text
  • References
  • Pharma PSE: a multiscale approach for reimagining pharmaceutical manufacturing
  • Abstract
  • 1: Introduction
  • 2: Multiscale research viewpoint
  • 3: Research example on cryopreservation of hiPS cells
  • 4: Lessons learnt towards future research
  • 5: Conclusions
  • Acknowledgement
  • References
  • Artificial Intelligence and Process Systems Engineering
  • Abstract
  • Contributed Papers: Process and Product Design/Synthesis
  • Reinventing the Chemicals/Materials Company: Transitioning to a Sustainable Circular Enterprise
  • Abstract
  • 1: The Chemicals and Materials Industry (CMI)
  • 2: GHG and Materials Emissions from CMI
  • 3: Towards the Circularization of CMI
  • 4: The Research Scope of Sustainable Circular CMI (S-CCMI)
  • 5: Conclusions
  • Acknowledgements
  • References
  • Value Chain Optimization of a Xylitol Biorefinery with Delaunay Triangulation Regression Models
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Application
  • 4: Conclusion
  • Acknowledgments
  • References
  • Evaluating the Impact of Model Uncertainties in Superstructure Optimization to Reduce the Experimental Effort
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case study
  • 4: Conclusion and Outlook
  • Acknowledgement
  • References
  • Retrosynthesis Pathway Design Using Hybrid Reaction Templates and Group Contribution-Based Thermodynamic Models
  • Abstract
  • 1: Introduction
  • 2: Retrosynthetic analysis framework using hybrid reaction templates and GC-based thermodynamic models
  • 3: Case studies
  • 4: Conclusions
  • References
  • Optimization-based Design of Product Families with Common Components
  • Abstract
  • 1: Introduction
  • 2: Product Family Design Formulation
  • 3: Process Case Study
  • 4: Conclusion
  • Acknowledgements and Disclaimer
  • References
  • Economic evaluation and analysis of electricity and nano-porous silica productions from rice husk
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Methodology of techno-economic analysis
  • 4: Results
  • 5: Conclusions
  • References
  • Future biofuels: A Superstructure-Based Optimization Framework Integrating Catalysis, Process Synthesis, and Fuel Properties
  • Abstract
  • 1: Introduction
  • 2: Superstructure description
  • 3: Mathematical model
  • 4: Results
  • 4: Conclusions
  • References
  • Superstructure Optimization of Biodiesel Production from Continuous Stirred Tank and Membrane Reactors
  • Abstract
  • 1: Introduction
  • 2: Superstructure development
  • 3: Results and discussion
  • 4: Conclusions
  • References
  • Process Design and Techno-Economic Analysis of Biomass Pyrolysis By-Product Utilization in the Ontario and Aichi Steel Industries
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results
  • 4: Conclusions
  • References
  • Optimal design of solar-aided hydrogen production process using molten salt with CO2 utilization for ethylene glycol production
  • Abstract
  • 1: Introduction
  • 2: Problem description
  • 3: Mathematical formulation
  • 4: Solution algorithm
  • 5: Computational studies
  • 6: Conclusion
  • References
  • Design of a novel hybrid process for membrane assisted clean hydrogen production with CO2 capture through liquefaction
  • Abstract
  • 1: Background
  • 2: Hybrid process concepts
  • 3: Modelling approach and design basis
  • 4: Key performance indicators (KPIs)
  • 5: Results and discussion
  • 6: Conclusions
  • Acknowledgements
  • References
  • Analysis and design of integrated renewable energy and CO2 capture, utilization, and storage systems for low-cost emissions reduction
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Case Study
  • 4: Conclusions
  • References
  • Techno-economic-environmental assessment for optimal utilisation of CO2 in the Fischer-Tropsch gas-to-liquid process
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • References
  • Machine Learning-based Hybrid Process Design for the Recovery of Ionic Liquids
  • Abstract
  • 1: Introduction
  • 2: Design method
  • 3: Case studies
  • 4: Conclusions
  • References
  • A Short-Cut Method for Synthesis of Solvent-based Separation Processes
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • References
  • Modeling and Optimization of Ionic-Liquid-Based Carbon Capture: Impact of Thermal Degradation Kinetics
  • Abstract
  • 1: Introduction
  • 2: Flowsheet description
  • 3: Process economic optimization
  • 4: Conclusions
  • 5 Acknowledgments
  • References
  • Process Design of Formic Acid and Methanol Production from CO2 Promoted by Ionic Liquid: Techno-Economic Analysis
  • Abstract
  • 1: Introduction
  • 2: Process Description
  • 3: Process Simulation
  • 4: Techno-Economic Assessment
  • 5: Results and Discussion
  • 6: Conclusions
  • Acknowledgments
  • References
  • Synthesis of Distillation Sequence with Thermally Coupled Configurations Using Reinforcement Learning
  • Abstract
  • 1: Introduction
  • 2: Distillation sequence
  • 3: Reinforcement learning
  • 4: Results and discussion
  • 5: Conclusion
  • Acknowledgements
  • References
  • Optimal Design of Heat Integrated Reduced Vapor Transfer Dividing Wall Columns
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Study
  • 4: Conclusions
  • References
  • A Model-Data Driven Chemical Analysis System for Products and Associated Processes
  • Abstract
  • 1: Introduction
  • 2: Database and Methodology
  • 3: Case studies
  • 4: Conclusions
  • References
  • Construction of Database and Data-driven Statistical Models for the Solubility of Nanomaterials in Organic Solvents
  • Abstract
  • 1: Introduction
  • 2: Solubility database for nanomaterials
  • 3: Selection of solvent features and data-driven solubility models
  • 4: Conclusions
  • Acknowledgement
  • References
  • Fast, efficient and reliable problem solution through a new class of systematic and integrated computer-aided tools
  • Abstract
  • 1: Introduction
  • 2: Methodology & Associated Tools
  • 3: Case Studies
  • 4: Conclusions
  • References
  • Design of Bio-Oil Solvents using Multi-Stage Computer-Aided Molecular Design Tools
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Study
  • 4: Conclusion
  • Acknowledgements
  • References
  • Synthesis of azeotropic distillation processes without using a decanter
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Mathematical formulation
  • 4: Case Study
  • 5: Results and Discussions
  • 6: Conclusions
  • References
  • Reduce Environmental Impact and Carbon Footprint for Cost Competitive Process Plant Design: Integrating AVEVATM Process Simulation with modeFRONTIER®
  • Abstract
  • 1: Introduction
  • 2: Simulation model and Design condition
  • 3: Objective function
  • 4: Optimization-driven design
  • 5: Case Study
  • 6: Result
  • 7: Conclusions
  • References
  • Reliability incorporated optimal process pathway selection for sustainable microalgae-based biorefinery system: P-graph approach
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Development of P-graph model
  • 4: Results and discussion
  • 5: Conclusions
  • Acknowledgements
  • References
  • Marine flue gas desulfurization processes: recent developments, challenges, and perspectives
  • Abstract
  • 1: Introduction
  • 2: SWFGD systems in a coastal area
  • 3: Maritime SWFGD systems
  • 4: Improvement of water and SWFGD systems
  • 5: Challenges
  • 6: Conclusion
  • 7 Acknowledgement
  • 8. References
  • Framework for Designing Solid Drug Product Manufacturing Processes Based on Economic and Quality Assessment
  • Abstract
  • 1: Introduction
  • 2: Developed assessment tools
  • 3: Design framework
  • 4: Conclusions
  • Acknowledgment
  • References
  • A Novel Process Synthesis of a Dehydrating Unit of Domestic Natural Gas Using TEG Contactor and TEG Regenerator
  • Abstract
  • 1: Introduction
  • 2: Process Description
  • 3: Method
  • 4: Proposed Configurations
  • 5: Results and Discussion
  • 6: Conclusions
  • Acknowledgements
  • References
  • A new trust-region approach for optimization of multi-period heat exchanger networks with detailed shell-and-tube heat exchanger designs
  • Abstract
  • 1: Introduction
  • 2: Heat Exchanger Model
  • 3: Trust Region Algorithm
  • 4: Case Study
  • 5: Conclusions
  • References
  • A mathematical technique for utility exchanger network synthesis and total site heat integration
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3: Model formulation
  • 4: Case study
  • 5: Conclusions
  • References
  • Synthesis and Assessment of NOx to Ammonia Conversion Process in Combined Cycle Power Generation Systems
  • Abstract
  • 1: Introduction
  • 2: Analysis for introducing two-stage NTA process system to CCGT system
  • 3: Design of CCGT system with single-stage NTA process system
  • 4: Conclusions
  • Acknowledgement
  • References
  • Knowledge integrated, deep neural network-based prediction of stress-strain curves of polymer matrix composites for AI-assisted materials design
  • Abstract
  • 1: Introduction
  • 2: Background
  • 3: Prediction of mechanical behavior based on chemical/mechanical information of components
  • 4: Predicting mechanical behaviour based on structural information of components
  • 5: Results
  • 6: Conclusion
  • References
  • Evaluation of Economic Performance of Co2 Separation Process Using Mixed Matrix Membrane
  • ABSTRACT
  • 1: Introduction
  • 2: Modelling
  • 3: Result and discussion
  • 4: Conclusions
  • Acknowledgment
  • References
  • Nature vs engineering: Production of methanol from CO2 capture
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Modelling approach
  • 4: Optimization procedure
  • 5: Results
  • 6: Conclusions
  • Acknowledgment
  • References
  • Superstructure Optimization for the Design of an Algae Biorefinery Producing Added Value Products
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusion
  • References
  • Process simulation of continuous biodiesel production catalysed by a high stability solid in a reactive distillation
  • Abstract
  • 1: Introduction
  • 2: Description of RD and methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • 5 References
  • Generative Approaches for the Synthesis of Process Structures
  • Abstract
  • 1: Introduction
  • 2: Recent prospective works on “Generative Approaches”
  • 3: Discussions on generative aspects
  • 4: Conclusive remarks
  • References
  • Metal-Organic Framework Targeting for Optimal Pressure Swing Adsorption Processes
  • Abstract
  • 1: Introduction
  • 2: Workflow of Descriptor-based MOF Targeting
  • 3: Descriptor-based MOF Screening
  • 4: Construction of MOF Building Blocks
  • 5: Computational MOF Synthesis and MOF Targeting
  • 6: Conclusions
  • References
  • Energy integration through retrofitting of heat exchanger network at Equinor Kalundborg Oil Refinery
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • References
  • Modeling and Optimization of Ionic Liquid Enabled Extractive Distillation of Ternary Azeotrope Mixtures
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Economic Performance Evaluation
  • 4: Conclusions
  • 5 Acknowledgments
  • 6 References
  • Optimal Design of Hybrid Distillation/ Pervaporation Processes
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Study
  • 4: Conclusions
  • References
  • Design and analysis of a single mixed refrigerant natural gas liquefaction process integrated with ethane recovery and carbon removal using cryogenic distillation
  • Abstract
  • 1: Introduction
  • 2: Process simulation and optimization
  • 3: Results and discussion
  • 4: Conclusion
  • Acknowledgement
  • References
  • A new decomposition approach for synthesis of heat exchanger network with detailed heat exchanger sizing
  • Abstract
  • 1: Introduction
  • 2: Mythologies
  • 3: Case study
  • 4: Conclusions
  • References
  • A mathematical approach for the synthesis of a wastewater treatment plant using the concept of circular economy
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3: Circular economy optimization model
  • 4: Case study
  • 5: Conclusions
  • References
  • Contributed Papers: Process Dynamics and Control
  • Convex Q-learning: Reinforcement learning through convex programming
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusion and Future Work
  • References
  • Differential Dynamic Programming Approach for Parameter Dependent System Control
  • Abstract
  • 1: Introduction
  • 2: Background
  • 3: Methodology
  • 4: Simulation Results
  • 5: Conclusions
  • ACKNOWLEDGEMENT
  • References
  • Optimization of an air-cooler operation in an industrial distillation column
  • Abstract
  • 1: Introduction
  • 2: Method for optimizing the number of fixed fans in operation
  • 3: Application example using operation data from the process industry
  • 4: Conclusions
  • References
  • Dynamic Operability Analysis for the Calculation of Transient Output Constraints of Linear Time-Invariant Systems
  • Abstract
  • 1: Introduction
  • 2: Dynamic Operability Problem Background
  • 3: Calculation of Transient Output Constraints
  • 4: Numerical Example
  • 5: Conclusions
  • References
  • Effective Re-identification of a Multivariate Process under Model Predictive Control Using Information from Plant-Model Mismatch Detection
  • Abstract
  • 1: Introduction
  • 2: Problem setting
  • 3: Proposed Method
  • 4: Case study
  • 5: Conclusions
  • References
  • Model Predictive Control of Grade Transition with Attention Base Sequence-to-Sequence Model
  • Abstract
  • 1: Sequence-to-Sequence Model
  • 2: Attention Mechanism
  • 3: Elastic Net and Systematic Model Improvement
  • 4: A High-Density Polyethylene Reactor
  • 5: Dynamic Modelling
  • 6: Grade Transition Navigation
  • 7: Conclusion
  • Acknowledgment
  • References
  • Real Time Optimization of series of fixed bed catalytic reactors
  • Abstract
  • 1: Introduction
  • 2: Digital Twin Development
  • 3: Online Implementation
  • 4: Results
  • 5: Conclusions
  • References
  • Self-triggered MPC for Perturbed Continuous-time Non-linear Systems
  • Abstract
  • 1: Introduction
  • 2: Preliminary
  • 3: Description for OCP and Triggering Mechanism
  • 4: Simulation
  • 5: Conclusions
  • References
  • A comparative study between MPC and selector-based PID control for an industrial heat exchanger
  • Abstract
  • 1: Introduction
  • 2: Heat exchanger system
  • 3: Simulation studies
  • 4: Conclusions and future work
  • References
  • MILP Formulation for Dynamic Demand Response of Electrolyzers
  • Abstract
  • 1: Introduction
  • 2: MILP Formulation for Electrolyzer Scheduling
  • 3: Case Study
  • 4: Results
  • 5: Conclusion
  • Acknowledgements
  • References
  • Real-Time Optimal Operation of a Chlor-Alkali Electrolysis Process under Demand Response
  • Abstract
  • 1: Introduction & Motivation
  • 2: Methodology
  • 3: Case Study
  • 4: Conclusions & Outlook
  • 5 Acknowledgements
  • References
  • Explicit Multi-Objective and Hierarchical Model Predictive Control
  • Abstract
  • 1: Main Text
  • 2: Multi-Objective Model Predictive Control Structure
  • 3: Hierarchical Model Predictive Control Structure
  • 4: Case-study: Continuous Stirred Tank Reactor
  • 5: Conclusion
  • Acknowledgements
  • References
  • A Robust Optimization Strategy for Explicit Model Predictive Control
  • Abstract
  • 1: Introduction
  • 2: Problem Formulation
  • 3: Methodology
  • 4: Results
  • 5: Conclusions
  • 6 Acknowledgements
  • 7 References
  • Data-driven Design of a Feed-forward Controller for Rejecting Measurable Disturbance
  • Abstract
  • 1: Introduction
  • 2: Design Scheme of Disturbance Rejection Controller
  • 3: Numerical examples
  • 4: Conclusions
  • References
  • Optimal Operation of Heat Exchanger Networks with Changing Active Constraint Regions
  • Abstract
  • 1: Introduction
  • 2: Case study modeling
  • 3: Proposed control structure
  • 4: Simulation results and discussion
  • 5: Conclusion
  • References
  • Iterative Feedback Tuning for Regulatory Control Systems Using Estimate of Sensitivity Function
  • Abstract
  • 1: Introduction
  • 2: IFT for regulatory control
  • 3: Controller parameter tuning via IFT
  • 4: Estimate of sensitivity function
  • 5: Numerical Example
  • 6: Conclusions
  • References
  • D-RTO as Enabler for Green Chemical Processes – Systematic Application and Challenges in Reactive Liquid Multiphase Systems
  • Abstract
  • 1: Introduction and Motivation
  • 2: System Information and Technical Application
  • 3: Model Development and D-RTO Framework
  • 4: Case Study
  • 5: Conclusion and Outlook
  • Acknowledgements
  • References
  • Design of PID controllers using semi-infinite programming
  • Abstract
  • 1: Introduction
  • 2: Numerical examples
  • 3: Conclusions
  • 4 Acknowledgments
  • References
  • Safe Chance Constrained Reinforcement Learning for Batch Process Optimization and Control
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Study
  • 4: Results and Discussion
  • 5: Conclusions
  • References
  • Contributed Papers: Scheduling and Planning
  • Combining Machine Learning with Mixed Integer Linear Programming in Solving Complex Scheduling Problems
  • Abstract
  • 1: Introduction
  • 2: Modeling
  • 3: Solution efficiency
  • 4: Main Challenges
  • 5: Conclusions
  • References
  • Knowledge-guided Hybrid Approach for Scheduling Multipurpose Batch Plants
  • Abstract
  • 1: Introduction
  • 2: Sequence-based MILP formulation
  • 3: Genetic algorithm
  • 4: Hybrid algorithm
  • 5: Computational Results
  • 6: Conclusions
  • Acknowledges
  • References
  • Scheduling of Electrical Power Systems under Uncertainty using Deep Reinforcement Learning
  • Abstract
  • 1: Introduction
  • 2: MDP Formulation and Safety
  • 3: Actor-Critic Method for Policy Learning
  • 4: Case Study: IEEE 39-Bus System
  • 5: Conclusion
  • References
  • A Reinforcement Learning Approach to Online Scheduling of Single-Stage Batch Chemical Production Processes
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Study
  • 4: Results and Discussion
  • 5: Conclusions
  • References
  • An adaptive multi-cut decomposition based algorithm for integrated closed loop scheduling and control
  • Abstract
  • 1: Main Text
  • 2: Problem formulation and decomposition
  • 3: Decomposition based solution algorithm
  • 4: Adaptive multicut algorithm
  • 5: Case study
  • 6: Conclusions
  • References
  • Uncertainty Evaluation of Biorefinery Supply Chain’s Economic and Environmental Performance Using Stochastic Programming
  • Abstract
  • 1: Introduction
  • 2: Modular Biorefinery Supply Chain Model
  • 3: Results and discussion
  • 4: Conclusions
  • Acknowledgements:
  • References
  • An Improved Optimization Model for Scheduling of an Industrial Formulation Plant based on Integer Linear Programming
  • Abstract
  • 1: Introduction
  • 2: Indutrial Formulation Plant
  • 3: Solution Approach
  • 4: Results
  • 5: Conclusion and Outlook
  • Acknowledgements
  • References
  • Optimal Sourcing, Supply and Development of Carbon Dioxide Networks for Enhanced Oil Recovery in CCUS Systems
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Mathematical Formulation
  • 4: Results
  • 5: Conclusions
  • 6 References
  • Production scheduling in multiproduct multistage semicontinuous processes. A constraint programming approach
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: CP model
  • 4: Results
  • 5: Conclusions and future work
  • References
  • Maintenance scheduling optimization for decaying performance nonlinear dynamic processes
  • Abstract
  • 1: Introduction
  • 2: Maintenance scheduling of decaying performance processes
  • 3: Maintenance scheduling of reverse osmosis networks (RONs)
  • 4: Future directions for maintenance scheduling optimization
  • 5: Conclusions
  • References
  • Cleaning schedule for heat exchanger networks subjected to maintenance constraints
  • Abstract
  • 1: Introduction
  • 2: MILP problem formulation description
  • 3: Case study
  • 4: Conclusion and future work
  • Acknowledgement
  • References
  • Estimating Energy Market Schedules using Historical Price Data
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results and Discussion
  • 4: Conclusions and Future Work
  • Acknowledgements
  • References
  • Scheduling of Material and Information Flows in the Manufacturing of Chemicals for the Order-to-Cash Process of a Digital Supply Chain
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Mathematical Model
  • 4: Illustrative Example
  • 5: Conclusions
  • References
  • Optimization of Maximum Completion Time of Polymerization Section Based on Improved Estimation of Distribution Algorithm
  • Abstract
  • 1: Introduction
  • 2: Scheduling model of PVC polymerization section
  • 3: Improved estimation of distribution algorithm
  • 4: Case analysis
  • 5: Conclusions
  • Reference
  • Evolutionary Algorithm-based Optimal Batch Production Scheduling
  • Abstract
  • 1: Introduction
  • 2: Case Study
  • 3: Methodology
  • 4: Results
  • 5: Summary, Conclusion and Outlook
  • Acknowledgements
  • References
  • Cream Cheese Fermentation Scheduling
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • References
  • Contributed Papers: Supply Chain Management and Logistics
  • Multi-Objective Optimization of Production Cost and Carbon Loss in the U.S. Petrochemicals Industry
  • Abstract
  • 1: Introduction
  • 2: Background and Problem Definition
  • 3: Solution Strategies
  • 4: Case Study
  • 5: Conclusions
  • Acknowledgement
  • References
  • Mapping Anthropogenic Carbon Mobilization through Chemical Process and Manufacturing Industries
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • 5. Acknowledgments
  • References
  • Optimal Designing and Planning of Ethiopia’s Biomass-to-Biofuel Supply Chain Considering Economic and Environmental Dimensions under Strategic and Tactical Levels
  • Abstract
  • 1: Introduction
  • 2: Methodologies
  • 3: Result and Discussion
  • 4: Conclusions
  • References
  • A Novel Integrated Optimal Scheduling Framework for Holistic Refinery Supply Chain Management
  • Abstract
  • 1: Introduction
  • 2: CM&RM&MOPD model
  • 3: Case study
  • 4: Conclusions
  • Acknowledgements
  • References
  • Roadmap to digital supply chain resilience
  • Abstract
  • 1: Introduction
  • 2: Stages towards the digital transformation
  • 3: Continuous evolution towards the digital supply chain resilience
  • 4: Conclusions
  • References
  • Development of Flexible Framework for Biomass Supply Chain Optimisation
  • Abstract
  • 1: Introduction
  • 2: Assumptions during model development
  • 3: Generalised representation of the supply chain elements
  • 4: Concept of site and path
  • 5: Formulation of the optimisation problem
  • 6: System development
  • 7: Conclusions
  • Acknowledgements
  • References
  • Lagrangean Decomposition for Integrated Refinery-Petrochemical Short-term Planning
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case study
  • 4: Conclusions
  • Acknowledgments
  • References
  • Green Ammonia Supply Chain Design for Maritime Transportation
  • Abstract
  • 1: Introduction
  • 2: Mathematical Formulation
  • 3: Computational Case Study
  • 4: Conclusions
  • References
  • Optimal agriculture residues revalorization as a biofuel alternative in electric power grids
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3. Methodology
  • 4: Results
  • 5: Conclusions
  • Acknowledgements
  • References
  • Global Supply Chain Optimization for COVID-19 Vaccine under COVAX initiative
  • Abstract
  • 1: Introduction
  • 2: Challenges faced by COVAX
  • 3: Problem Statement
  • 4: Supply chain optimization
  • 5: Case study
  • 6: Results
  • 7: Conclusions
  • References
  • Optimal Liquefied Natural Gas (LNG) Annual Delivery Program Reflecting both Supplier and Customer Perspectives
  • Abstract
  • 1: Introduction
  • 2: Problem Description
  • 3: Mathematical Model
  • 4: Results
  • 5: Conclusions
  • References
  • The Waste-to-Resource Game: Informed Decision-Making for Plastic Waste Transformers
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Bargaining Game
  • 4: Pyrolysis Model
  • 5: Case Study
  • 6: Results and Discussion
  • 7: Conclusions
  • Acknowledgements:
  • References
  • Implications of Optimal BECCS Supply Chains on Absolute Sustainability
  • Abstract
  • Introduction
  • Methods
  • Results
  • Conclusions
  • References
  • A Multi-disciplinary Assessment of Innovations to Improve Grocery Bag Circularity
  • Abstract
  • 1: The need for more circular grocery bags
  • 2: Baseline model
  • 3: Life cycle assessment
  • 4: Policy
  • 5: Economics
  • 6: Supply chain management
  • 7: Conclusion
  • Acknowledgements
  • References
  • Process Sustainable Supply Chain: integrating monetization strategies in the design and planning
  • Abstract
  • 1: Introduction
  • 2: Environmental and social monetization methodologies
  • 3: Problem description and model characterization
  • 4: Case study
  • 5: Conclusions
  • Acknowledgements
  • References
  • Contributed Papers: Process Intensification
  • Systematically Identifying Energy-Efficient and Attractive Multicomponent Distillation Configurations
  • Abstract
  • 1: Introduction
  • 2: Optimization Model
  • 3: Case Study
  • 4: Conclusions
  • Acknowledgments
  • References
  • Synthesis of Advanced Reactive Distillation Technologies: Early-Stage Assessment Based on Thermodynamic Properties and Kinetics
  • Abstract
  • 1: Introduction
  • 2: Advanced reactive distillation technologies
  • 3: Research approach, conceptual framework and scope
  • 4: Decision-making methodology applied to two case studies
  • 5: Results and discussion
  • 6: Conclusions
  • Acknowledgements
  • References
  • Process Synthesis and Intensification for Upgrading Natural Gas Liquids in Shale Gas
  • Abstract
  • 1: Introduction
  • 2: Base Case Flowsheet
  • 3: Systematic Analysis and Evolution of Process Configurations
  • 4: Conclusions
  • References
  • Energy-Efficient Direct Cyclohexene to Cyclohexanol Process by Heat Pump Assisted Reactive Distillation
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Reaction kinetics and phase equilibrium model
  • 4: Process Simulation
  • 5: Process Evaluation
  • 6: Conclusion
  • Acknowledgements
  • References
  • Sustainable Process Intensification of Refrigerant Mixture Separation and Management: A Multiscale Material Screening and Process Design Approach
  • Abstract
  • 1: Introduction
  • 2: Problem Representation
  • 3: Extractive Distillation Process Synthesis for R-410A Separation
  • 4: Conclusions
  • 5 Acknowledgment
  • References
  • A systematic methodology for the optimisation, control and consideration of uncertainty of reactive distillation
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case study
  • 4: Results and Discussion
  • 5: Conclusions
  • References
  • Equation Oriented Optimization of Multi Stream Heat Exchanger Design and Operation in Natural Gas Liquefaction Process
  • Abstract
  • 1: Introduction
  • 2: Model
  • 3: Methodology
  • 4: Optimization Results
  • 5: Conclusions
  • References
  • Optimal Design of Extractive Dividing-Wall Column Using an Improved Sequential Least Squares Programming Algorithm
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Mathematical Model
  • 4: Solution method
  • 5: Case study
  • 6: Conclusions
  • Acknowledgements
  • References
  • Biphasic Dehydration of Sugars to 5-Hydroxymethylfurfural and Furfural—Multiscale Modeling for Easier Optimization and More Accurate Solvent Selection
  • Abstract
  • 1: Introduction
  • 2: Multiscale modeling approach
  • 3: Biphasic system
  • 4: Results and discussion
  • 5: Current limitations
  • 6: Conclusions
  • References
  • Study of Mass Transfer Coefficient of CO2 Capture in different Solvents using Microchannel: A Comparative Study
  • Abstract
  • 1: Introduction
  • 2: Selection of system
  • 3: Results and discussion
  • 4: Conclusions
  • References
  • Techno-Economic Study of Intensified Ethylene Oxide Production Using High Thermal Conductivity Microfibrous Entrapped Catalyst
  • Abstract
  • 1: Introduction
  • 2: Process Description and Design
  • 3: Optimization Algorithm
  • 4: Results and Discussion
  • 5: Conclusions
  • References
  • Contributed Papers: Integration of Process Operation and Design/Synthesis
  • Power Systems Infrastructure Planning with High Renewables Penetration
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Transmission Expansion Formulation
  • 4: Proposed Algorithms
  • 5: Results
  • 6: Conclusions
  • References
  • An Optimization Model for the Design and Operation of Reliable Power Generation Systems
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3: Model formulation
  • 4: Illustrative example
  • 5: Sensitivity analysis
  • 6: Conclusions
  • Acknowledgement
  • References
  • Rule-based Method for Retrofitting Conventional Processes with Integrated Units
  • Abstract
  • 1: Introduction
  • 2: Method
  • 3: Case Studies
  • 4: Conclusion
  • References
  • Integration of Design and Operation for the CO2-based Methanol Synthesis
  • Abstract
  • 1: Introduction
  • 2: Framework
  • 3: Model
  • 4: Results and discussion
  • 5: Conclusion and outlook
  • References
  • Blue Syngas Synthesis via the Integration of Gasification and Reforming Processes
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Results
  • 4: Conclusions
  • References
  • Network optimization of the electrosynthesis of chemicals from CO2
  • Abstract
  • 1: Introduction
  • 2: Modeling and techno-economic assessment of ECO2R processes
  • 3: Optimization model
  • 4: Case study
  • 5: Results
  • 6: Conclusions
  • References
  • A robust design of heat exchanger network for high temperature electrolysis systems
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Result and discussion
  • 4: Conclusions
  • References
  • Techno-economic Assessment of Upstream and Downstream Process Alternatives for the Production of Monoclonal Antibodies
  • Abstract
  • 1: Introduction
  • 2: Simulation of process alternatives
  • 3: Results and discussion
  • 4: Conclusions
  • Acknowledgements
  • References
  • Biomethane liquefaction followed by CO2 solidification based biogas upgrading process
  • Abstract
  • 1: Introduction
  • 2: Process design and simulation
  • 3: Process optimization
  • 4: Results and discussion: Process analysis
  • 5: Conclusions
  • Acknowledgements
  • References
  • Importance of interannual renewable energy variation in the design of green ammonia plants
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Historical Data Analysis
  • 5: Conclusions
  • References
  • Integrating Carbon Negative Technologies in Industrial Clusters
  • Abstract
  • 1: Introduction
  • 2: Approach
  • 3: Illustrative example
  • 4: Conclusion
  • References
  • Flexibility analysis of chemical processes considering overlaying uncertainty sources
  • Abstract
  • 1: Introduction
  • 2: Flexibility index and suggested reformulations
  • 3: Illustrative Example
  • 4: Industrial case study
  • 5: Influence of operational flexibility target value
  • 6: Conclusion
  • References
  • Flexible and Sustainable Methanol Production Including Option with Green Hydrogen
  • Abstract
  • 1: Introduction
  • 2: Results and Discussion
  • 3: Conclusions and Outlook
  • References
  • Optimization and Heat Exchanger Network Design of Diethyl Carbonate Two-step Synthesis Process from CO2 and Propylene Oxide
  • Abstract
  • 1: Introduction
  • 2: Process description and optimization
  • 3: CO2 emission calculation
  • 4: Process intensification and heat integration
  • 5: Conclusion
  • References
  • Characterization of Industrial Flaring under Uncertainty for the Design of Optimum Flare Recovery and Utilization Systems
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3: Flare streams characterization and optimization model
  • 4: Results
  • 5: Conclusions
  • References
  • Development of Micro Scale PRC Using Low Grade Geothermal Thermal Energy
  • ABSTRACT
  • 1: Introduction
  • 2: Modeling
  • 3: Simulation results and discussion
  • 4. Conclusion
  • 5 Reference
  • Scenario Outcomes for Electric Power Generation Expansion Planning considering the State of Indiana as a Case Study
  • Abstract
  • 1: Main Text
  • 2: Research Methods
  • 3: Results and Discussion
  • 4: Conclusions
  • References
  • Requirements for the quality assessment of virtual commissioning models for modular process plants
  • Abstract
  • 1: Introduction
  • 2: State of the art
  • 3: Requirements for third-party model integration
  • 4: Quality assessment for virtual commissioning models
  • 5: Conclusion
  • References
  • Contributed Papers: Modeling, Analysis, and Simulation
  • A combinatorial tool for monitoring flocculation processes: Using non-invasive measurements and hybrid deep learning assisted modelling
  • Abstract
  • 1: Introduction
  • 2: Modelling framework
  • 3: Application example
  • 4: Conclusions
  • Acknowledgements
  • References
  • Optimal Design of Experiments Based on Artificial Neural Network Classifiers for Fast Kinetic Model Recognition
  • Abstract
  • 1: Introduction
  • 2: Proposed framework and methods
  • 3: Case study description
  • 4: Results
  • 5: Conclusions
  • References
  • Modelling of the Rice Bran Protein Extraction using Response Surface Methodology
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and discussion
  • Conclusions
  • Acknowledgement
  • References
  • Weibull Reliability Regression Model for Prediction of Bearing Remaining Useful Life
  • Abstract
  • 1: Background
  • 2: Methodology
  • 3: Result and Discussion
  • 4: Conclusions
  • References
  • Supporting Hyperparameter Optimization in Adaptive Sampling Methods
  • Abstract
  • 1: Introduction
  • 2: Hydroformylation
  • 3: Methodology
  • 4: Results
  • 5: Conclusion
  • Acknowledgment
  • References
  • Optimal Catalyst-Reactor Design for Load-Flexible CO2 Methanation by Multi-Period Design Optimization
  • Abstract
  • 1: Introduction
  • 2: Fixed-Bed Reactor and Catalyst Particle Model
  • 3: Multi-Period Design Optimization
  • 4: Results
  • 5: Conclusions
  • 6 Acknowledgment
  • References
  • Data-Driven Modeling of Long-Term Performance Degradation in Solid Oxide Electrolyzer Cell System
  • Abstract
  • 1: Background
  • 2: Modeling strategy
  • 3: Discussion and Future Work
  • 4: Conclusions
  • References
  • Modeling and Optimal Design of Pressure Swing Adsorber for Carbon Dioxide and Hydrogen Separation from Industrial Waste Gas
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Mathematical model
  • 4: Results and Discussion
  • 5: Conclusions
  • Acknowledgement
  • References
  • Membrane Characterization with Model-Based Design of Experiments
  • Abstract
  • 1: Introduction
  • 2: Mathematical model, materials, and methods
  • 3: Fisher Information Matrix (FIM)
  • 4: Results and discussions
  • 5: Conclusions
  • Acknowledgements
  • References
  • Systematic Modelling of Distillation Columns based on Topologies and Ontologies
  • Abstract
  • 1: Motivation
  • 2: Structural model design
  • 3: Mathematical model design
  • 4: Results and discussion
  • 5: Conclusions
  • Acknowledgements
  • References
  • Sensitivity Analysis of an Electrospray Dehumidification System
  • Abstract
  • 1: Introduction
  • 2: Electrospray System Computational Fluid Dynamics (CFD) Model
  • 3: Surrogate-based Sobol Sensitivity Analysis
  • 4: Results
  • 5: Conclusions and Future Work
  • Acknowledgments
  • References
  • Rigorous modelling for comparing batch and flow syntheses of a drug substance using heterogeneous hydrogenation
  • Abstract
  • 1: Introduction
  • 2: Materials and methods
  • 3: Results and discussion
  • 4: Conclusions and outlook
  • References
  • Assessment on the heat integration potential for different pressure thermally coupled distillation structures
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Mathematical formulation
  • 4: Case Study: n-butanol/isobutanol separation
  • 5: Results and Discussions
  • 3: Conclusions
  • References
  • Python platform for Tennessee Eastman Process
  • Abstract
  • 1: Introduction
  • 2: Different versions of TEP
  • 3: Connect TEP to Python
  • 4: Conclusions
  • References
  • Computational Modeling of Lube-Oil Flows in Pipelines to Study the Efficacy of Flushing Operations
  • Abstract
  • 1: Introduction
  • 2: Optimal Control Problems and Applications
  • 3: Viscosity Blending Equations
  • 4: Modeling the Flushing Operation
  • 5: Solution Methodology
  • 6: Results and Discussions
  • 7: Conclusion
  • References
  • Comparison of ammonia synthesis plants of different scale with a dynamic model
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusion
  • References
  • Simulation Analysis of Gas Feed Method for Development of Ru-Based Catalyst for Ammonia Production
  • Abstract
  • 1: Introduction
  • 2: Derivation of reaction rate equation for developed Ru-based catalyst
  • 3: Simulation analysis for application of methods for split feed of gas
  • 4: Conclusions
  • References
  • Estimation of the effect of liquid viscosity on gas-liquid mass transfer in a bioreactor using CFD-PBM coupled model
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Numerical strategy
  • 4: Results and discussion
  • 5: Conclusions
  • Acknowledgements
  • References
  • Knowledge-matching based computational framework for genome-scale metabolic model refinement
  • Abstract
  • 1: Introduction
  • 2: Knowledge-matching based framework for GEM analysis
  • 3: SID-based GEM refinement
  • 4: Conclusions
  • References
  • Multi-Regional Surrogate Model Selection (MRSMS) approach for the analysis and optimal fitting of univariate responses
  • Abstract
  • 1: INTRODUCTION
  • 2: METHODOLOGY
  • 3: Case Study
  • 5: Conclusion
  • 6 Acknowledgements
  • 7 References
  • A Digital Reality Pilot Plant for Research and Learning
  • Abstract
  • 1: Introduction
  • 2: Existing Course Offering
  • 3: A Cognitive Framework for the design of digital reality learning tools
  • 4: Design Study: The PID
  • 5: Conclusion
  • Acknowledgements
  • References
  • Soft sensors development for industrial reactive distillation processes under small training datasets
  • Abstract
  • 1: Introduction
  • 2: Statement of problem and its analysis
  • 3: Soft sensor evaluation based on the sample extension
  • 4: Conclusions
  • 5: Acknowledgements
  • References
  • Comprehensive Quantification of Model Prediction Uncertainty for Simulated Moving Bed Chromatography
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Experimental
  • 4: Results
  • 5: Conclusions
  • References
  • A predictive model for multi-criteria selection of optimal thermochemical processing pathways in biorefineries
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • References
  • Numerical Investigation of the Shear Rate Variation in Cooling Crystallization
  • Abstract
  • 1: Introduction
  • 2: Numerical model
  • 3: Results and discussion
  • 4: Conclusions
  • Acknowledgements
  • References
  • Application of machine learning model to optimization of the hydrogen liquefaction process
  • Abstract
  • 1: Introduction
  • 2: Hydrogen liquefaction Process
  • 3: Machine learning application result
  • 4: Conclusions
  • Acknowledgment
  • References
  • Density Functional Theory on the CO2 Absorption Process with Ionic Liquids
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • Acknowledgments
  • References
  • Transport of CO2/CH4 through PEBA membranes: experiments and mass transfer modelling
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Mathematical Model
  • 4: Results
  • 5: Conclusions
  • References
  • Mathematical modelling, simulation and optimisation of an indirect water bath heater at the Takoradi distribution station (TDS)
  • Abstract
  • 1: Introduction
  • 2: Model development
  • 3: Results and discussion
  • 4: Conclusions
  • References
  • Marine SOx Scrubber: Mass transfer Analysis, Design, Simulation and Experiment
  • Abstract
  • 1: Introduction
  • 2: Closed-Loop Square Scrubber With Spray
  • 3: Materials And Methods
  • 4: Results and Discussion
  • 5: Conclusions
  • 6 Acknowledgement
  • References
  • Connecting the Simulation Model to the Digital Twin to help drive Sustainability
  • Abstract
  • 1: Introduction
  • 2: The Digital Twin
  • 3: Unified Engineering
  • 4: Process Simulation lifecycle
  • 5: Conclusion
  • References
  • Development of predictive model for the size of gas and liquid slugs formed in millimeter scaled T- junctions
  • Abstract
  • 1: Introduction
  • 2: Method
  • 3: Experimental
  • 4: Results and discussion
  • 5: Conclusions
  • References
  • Enviro-economic assessment of DME synthesis using carbon capture and hydrogen from methane pyrolysis
  • Abstract
  • 1: Introduction
  • 2: Material and methods
  • 3: Results and discussion
  • Conclusions
  • Acknowledgements
  • References
  • Operational Envelopes of Cost-effective Sour Gas Desulfurization Processes
  • Abstract
  • 1: Introduction
  • 2: Process Simulations and Desulfurization Cost Calculations
  • 3: Results & Discussion
  • 4: Conclusions
  • References
  • Process Alternatives for the Co-Production of Hydrogen and Methanol using Fuel Switch and Energy Mix Systems
  • Abstract
  • 1: Introduction
  • 2: Modelling and Simulation
  • 3: Process Description
  • 4: Results and Discussion
  • 5: Economic Analysis and Project Feasibility
  • 6: Conclusions
  • Acknowledgements
  • References
  • Documenting Models Comprehensively Using a Minimal Graphical Language
  • Abstract
  • 1.1: Background
  • 2: Foundation: Reductionism
  • 3: Language as paper-and-pencil tool and documentation
  • 1.2: Conclusions
  • Acknowledgments:
  • References
  • Simulation and CO2 emission analysis for co-processing of bio-oil and vacuum gas oil
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Aspen Simulation
  • 3.1: Component provision and material method
  • 4: Results and discussion
  • 5: Conclusion
  • References
  • Dynamic Simulation and Optimization of a Subcritical Coal-Fired Power Plant During Load- Ramping Operations
  • Abstract
  • 1: Introduction
  • 2: Dynamic model description
  • 3: Dynamic simulations
  • 4: Dynamic optimization
  • 5: Conclusions
  • Acknowledgement & Disclaimer
  • References
  • Solvent Screening Methodology considering Techno-Economic and Environmental Sustainability criteria for Algae Lipid Extraction
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • References
  • Modelling and simulation of the production of n- butyl lactate in a reactive distillation column at pilot plant scale
  • Abstract
  • 1: Introduction
  • 2: Process Modelling
  • 3: Model simulation
  • 4: Conclusions
  • Reference
  • Optimal Design of Offshore Wind Power Farm Considering Wind Uncertainty
  • Abstract
  • 1: Introduction
  • 2: Problem definition
  • 3: Problem formulation
  • 4: Case study
  • 5: Conclusions
  • References
  • Economic and environmental impact of fouling in produced water re-injection
  • Abstract
  • 1: Introduction
  • 2: Motivating example
  • 3: Results and Discussion
  • 4: Conclusion
  • 5 Acknowledgement
  • References
  • Mathematical Modelling of Reactive Inks for Additive Manufacturing of Charged Membranes
  • Abstract
  • 1: Introduction
  • 2: Dynamic mathematical model for reactive-ink formulation
  • 3: Materials and method
  • 4: Results and discussion
  • 5: Conclusions
  • Acknowledgments
  • References
  • Economic Analysis of a Hydrogen Liquefaction Process Based on Techno-Economic and Energy Optimization
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Process optimization
  • 4: Results
  • 5: Discussion
  • 6: Conclusions
  • References
  • How Digital Twins are Propelling Metals Industry to Next Generation Decision-Making: A Practitioner’s View
  • Abstract
  • 1: Introduction
  • 2: Understand Digital Twin Technology
  • 3: An Industrial Example: Blast Furnace Digital Twin
  • 4: Development Approach and Lessons Learned
  • 5: Conclusion
  • References
  • The study on feasibility of HFO refrigerants in BOG re-liquefaction process
  • Abstract
  • 1: Introduction
  • 2: Process design
  • 3: Results and discussion
  • 4: Conclusion
  • References
  • Novel Design of Optimum Heat Exchanger Networks for Textile Dyeing Process to Maximize Wastewater Heat Recovery Efficiency
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Methodology
  • 4: Results and discussion
  • 5: Conclusions
  • Acknowledgements
  • References
  • Study on the Kinetic Parameters of Crystallization Process Modelled by Partial Differential Equations
  • Abstract
  • 1: Introduction
  • 2: Data for snowflake formation process: CA simulation
  • 3: The dynamic equation of snowflake formation based on data: the establishment of partial differential equations
  • 4: The influence of process parameters on snowflakes morphology: from the perspective of the reaction-diffusion system
  • 5: Conclusions
  • Acknowledgements
  • References
  • Graphical user interface for development of dynamics model of fermentation process applying long short-term memory networks
  • Abstract
  • 1: Introduction
  • 2: Program overview and technical description
  • 3: The Graphic User Interface (GUI)
  • 4: Network performance and results visualization
  • 5: Availability
  • 6: Conclusions
  • Acknowledgments
  • References
  • The biorefinery concept for the industrial valorization of pineapple leaves co-producing ethanol, citric acid, and xanthan gum: a techno- economic analysis
  • Abstract
  • 1: Introduction
  • 2: Biorefinery process description
  • 3: Economic Analysis
  • 4: Results
  • 5: Conclusions
  • References
  • First Principles Based Development of Hybrid Models of Distillation Towers
  • Abstract
  • 1: Background
  • 2: Case study
  • 3: Modeling approach
  • 4: Results and discussion
  • 5: Conclusions
  • 6 References
  • Model-Based Development of Fuel Cell Stack and System Controllers
  • Abstract
  • 1: Introduction
  • 2: FC-system controller and closed-loop simulation of the entire FC system
  • 3: Simulation results and discussion
  • Conclusions
  • Acknowledgement
  • References
  • Contributed Papers: Optimization Methods and Computational Tools
  • A Nested Schur Decomposition Approach for Multiperiod Process Optimization
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3: Solution strategy
  • 4: Implementation
  • 5: Case study
  • 6: Conclusions
  • References
  • Design and Optimisation of Boil-off Gas Recycling Strategy in Liquefied Natural Gas Production
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • References
  • An Implicit Function Formulation for Nonlinear Programming with Index-1 Differential Algebraic Equation Systems
  • Abstract
  • 1: Introduction
  • 2: Background and Implementation
  • 3: Case Studies
  • 4: Conclusions
  • References
  • Multi-objective optimization of NH3 and CO2 separation with ionic liquid process
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results and discussion
  • 4: Conclusion
  • References
  • Primal-dual Feedback-optimizing Control with Direct Constraint Control
  • Abstract
  • 1: Introduction
  • 2: Recent Works and Problem Statement
  • 3: Proposed Control Structure
  • 4: Implementation in Subsea Oil Production Network
  • 5: Conclusions
  • Acknowledgment
  • References
  • Data-driven coordination of expensive black-boxes
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusion
  • Acknowledgements
  • References
  • Data-Driven Adaptive Robust Unit Commitment Assisted by Machine Learning Techniques
  • Abstract
  • 1: Introduction
  • 2: Data-driven robust unit commitment with disjunctive uncertainty sets
  • 3: Case study based on IEEE 39-bus systems
  • 4: Conclusions
  • References
  • Heat integration for superstructure models: A MILP formulation for easy implementation and fast computing
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Model evaluation
  • 4: Applied case study
  • 5: Conclusion
  • 6: Funding
  • References
  • A Software Framework for Optimal Multiperiod Carbon-Constrained Energy Planning
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Mathematical Optimisation Formulation
  • 4: Case Study
  • 5: Conclusions
  • References
  • Superstructure optimisation in various carbon capture and utilisation supply chains
  • Abstract
  • 1: Introduction
  • 2: System description
  • 3: CCU optimisation model
  • 4: Results
  • 5: Conclusions
  • References
  • Crude Oil Blending Process Optimization with Precise Consideration of Fraction Properties
  • Abstract
  • 1: Introduction
  • 2: Model description
  • 3: Simulation case
  • 4: Conclusions
  • Acknowledgements
  • Reference
  • Efficient Scenario Generation for Stochastic Programs with Extreme Events
  • Abstract
  • 1: Introduction
  • 2: Optimization Model – Screening Plan for Colorectal Cancer
  • 3: Scenario Generation Methods and Their Application to the Model
  • 4: Results and Discussion
  • 5: Conclusions and Future Directions
  • References
  • A Sustainable Framework for Optimal and Flexible Design Under Uncertainty in Separation Processes: Exergy, Energy, Economic, and Environmental Aspects
  • Abstract
  • 1: Introduction
  • 2: Case study
  • 3: Framework description
  • 4: Results
  • 5: Conclusion
  • Acknowledgments
  • References
  • Application of nonlinear surrogate models on optimization of carbon capture and utilization network
  • Abstract
  • 1: Introduction
  • 2: Optimization problem formulation
  • 3: Case study
  • 4: Results and discussion
  • 5: Conclusions
  • References
  • Systematic process energy optimization via multi-level heat integration: A case study on low-temperature reforming for methanol synthesis
  • Abstract
  • 1: Introduction
  • 2: Background on heat integration and optimization
  • 3: Method for process energy optimization via multi-level heat integration
  • 4: Implementation for Methanol Synthesis
  • 5: Conclusions
  • Acknowledgements
  • References
  • Bayesian Optimization for Automobile Catalyst Development
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • Acknowledgements
  • References
  • Capacity Planning for Sustainable Process Systems with Uncertain Endogenous Technology Learning
  • Abstract
  • 1: Introduction
  • 2: Stochastic programming model
  • 3: Industrial case study
  • 4: Conclusions
  • References
  • Development of a Bi-Objective Optimisation Framework for Mixed-Integer Nonlinear Programming Problems and Application to Molecular Design
  • Abstract
  • 1: Introduction
  • 2: Background and motivation
  • 3: Proposed Algorithm
  • 4: Performance of the SDNBI algorithm
  • 5: Results and Discussions
  • 6: Conclusions
  • Acknowledgements
  • References
  • Data-Driven Scenario Generation for Two-Stage Stochastic Programming
  • Abstract
  • 1: Motivation
  • 2: Literature review
  • 3: Methodology and mathematical developments
  • 4: Case studies – Capacity Planning under uncertainty
  • 5: Conclusions and future work
  • References
  • Joint Chance Constrained Process Optimization through Neural Network Approximation
  • Abstract
  • 1: Introduction
  • 2: Problem formulation
  • 3: Neural network approximation-based optimization
  • 4: Case Study
  • 5: Conclusions
  • References
  • Gaussian Processes for Simulation-Based Optimization and Robust Design
  • Abstract
  • Introduction
  • Gaussian Processes
  • Method
  • Results
  • Conclusions
  • Acknowledgements
  • References
  • Machine Learning-Enabled Optimization of Force Fields for Hydrofluorocarbons
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results
  • 4: Conclusions
  • 5 Acknowledgements
  • 6 References
  • Design of an Event-Driven Rescheduling Algorithm via Surrogate-based Optimization
  • Abstract
  • 1: Introduction
  • 2: Bike sharing rebalancing
  • 3: Surrogate-based optimization
  • 4: Results
  • 5: Conclusions
  • Acknowledgement:
  • References
  • A two-stage network optimization for sustainable treated wastewater planning
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • 5 References
  • Surrogate Modeling for Superstructure Optimization with Generalized Disjunctive Programming
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Study
  • 4: Results
  • 5: Conclusions
  • References
  • Educational Computer-Aided Tools Towards Industry 4.0: Recommendations and BioVL
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results & discussion: BioVL
  • 4: Conclusions & Future perspectives
  • References
  • Process Superstructure Optimization through Discrete Steepest Descent Optimization: a GDP Analysis and Applications in Process Intensification
  • Abstract
  • 1: Introduction
  • 2: Generalized Disjunctive Programming
  • 3: Discrete Steepest Descent Optimization
  • 4: Discrete-steepest descent optimization as a disjunctive algorithm LD-SDA
  • 5: Numerical Experiments
  • 6: Conclusions
  • References
  • Advances in Generalized Disjunctive and Mixed- Integer Nonlinear Programming Algorithms and Software for Superstructure Optimization
  • Abstract
  • 1: Introduction
  • 2: Mixed-Integer Nonlinear Programming
  • 3: Generalized Disjunctive Programming
  • 4: GDPLib, the library for GDP models
  • 5: Conclusions
  • References
  • Designing Novel Structured Packings by Topology Optimization and Additive Manufacturing
  • Abstract
  • 1: Introduction
  • 2: Generative Packing Design
  • 3: Results
  • 4: Conclusions
  • Acknowledgement
  • References
  • Multi-Objective Bayesian Optimization for Design and Operating of Fluidized Bed Reactor
  • Abstract
  • 1: Introduction
  • 2: Mathematical model : Fluidized Bed Reactor
  • 3: Methodology : Multi-objective Bayesian optimization
  • 4: Results
  • 5: Conclusions
  • 6 Acknowledgement
  • References
  • Analysis of Optimization Algorithms for Real-Time Optimization Applied on the Model of a Fluid Catalytic Cracking Unit
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and analysis
  • 4: Conclusions
  • References
  • Scalable Stochastic Programming with Bayesian Hybrid Models
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results
  • 4: Conclusions
  • Acknowledgement
  • References
  • A Combined Particle Swarm Optimization and Outer Approximation Optimization Strategy for the Optimal Design of Distillation Systems
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Studies
  • 4: Conclusions
  • References
  • A semantic based decision support framework to enable model and data integration
  • Abstract
  • 1: Introduction
  • 2: Theoretical formulation of model/data integration
  • 3: Implementation
  • 4. Demonstration
  • 5. Conclusion
  • References
  • Contributed Papers: Process Monitoring and Safety
  • Design of Non-Redundant Sensor Networks for Reliable Estimation in Nonlinear Systems
  • Abstract
  • 1: Introduction
  • 2: Problem Definition
  • 3: Proposed Methodology
  • 4: Example
  • 5: Case Study
  • 6: Conclusions
  • References
  • A Novel Global-Local Feature Preserving Projection Method Based on Adaptive Linear Local Tangent Space Alignment for Process Monitoring
  • Abstract
  • 1: Introduction
  • 2: NGLFPP Algorithm
  • 3: NGLFPP-Based Process Monitoring
  • 4: Case Study
  • 5: Conclusion
  • References
  • Prognostics on Noisy and Uncertain Dynamic Systems using Cumulative Sum Chart of Inferential Sensors
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Case Study
  • 4: Results – Discussion
  • 5: Conclusions
  • References
  • Quantifying Subsea Gas Leakages using Machine Learning: a CFD-based study
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • Acknowledgments
  • References
  • Dynamic Risk Analysis for Process Safety
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Application of the proposed methodology
  • 4: Conclusions
  • References
  • Monitoring of smart chemical processes: A Sixth Sense approach
  • Abstract
  • 1: Introduction
  • 2: System architecture
  • 3: Results
  • 4: Conclusions
  • References
  • Fault detection in a benchmark simulation model for wastewater treatment plants
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results
  • 4: Conclusion
  • References
  • Formulation of integrated key performance indicator dashboard for chemical plants
  • Abstract
  • 1: Introduction
  • 2: Integrated KPI
  • 3: KPI tree graph
  • 4: KPI balance graph
  • 5: KPI trend graph
  • 6: Case Study
  • 7: Conclusion
  • References
  • Evaluation of risk in the biodiesel production process with supercritical ethanol
  • Abstract
  • 1: Introduction
  • 2: Case study
  • 3: Process simulation
  • 4: Risk assessment
  • 5: Results
  • 6: Conclusions
  • Acknowledgments
  • References
  • Process Monitoring Based on Deep Neural Networks with Continuous Wavelet Transform
  • Abstract
  • 1: Introduction
  • 2: Method
  • 3: Case study
  • 4: Result
  • 5: Discussion
  • 6: Conclusions
  • References
  • Methyl sec-butyl ether content estimation in MTBE products via clustering-based adaptive nonlinear soft sensors
  • Abstract
  • 1: Introduction
  • 2: Industrial plant description and problem formulation
  • 3: Methods used for model evaluation
  • 4: Description of the proposed adaptation algorithm
  • 5: Results and discussion
  • 6: Conclusions
  • Acknowledgements
  • References
  • Early Identification of Abnormal Deviations in Nonstationary Processes by Removing Non- Stationarity
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: The proposed monitoring strategy by removing process non-stationarity
  • 4: Case studies on Tennessee Eastman process (TEP)
  • 5: Conclusions
  • References
  • AI System for Substance Identification Based on Chemical Substance-Symptom Knowledge Graph
  • Abstract
  • 1: Introduction
  • 2: Proposed System: SEARCH
  • 3: Chemical-symptom knowledge base generation
  • 4: Knowledge verification using knowledge graph embedding
  • 5: Identification of symptom-based exposure substances
  • 6: Symptom knowledge expansion using DNN
  • 7: Conclusions
  • References
  • Model-based monitoring of an intensified unit for continuous pharmaceutical filtration-drying
  • Abstract
  • 1: Introduction
  • 2: Continuous filtration-drying of paracetamol/ethanol slurries
  • 3: Monitoring system: implementation and proof of concept
  • Conclusions
  • Acknowledgements
  • References
  • Plant Fault Diagnosis System using Negative Selection Algorithm
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Simulations Results
  • 4: Conclusions
  • References
  • Digital Twin of a pilot-scale bio-production setup
  • Abstract
  • 1: Introduction
  • 2: Digital Models
  • 3: Proposed Framework
  • 4: Lessons learnt
  • 5: Conclusions
  • Acknowledgements
  • References
  • Plant OandM Support System Based on Supervised Data-Clustering Technology
  • Abstract
  • 1: Introduction
  • 2: Proposed system
  • 3: Data analysis and results
  • 4: Conclusions
  • References
  • A Novel Cycle Partitioning Approach to Reliability Based Optimal Sensor Placement for Linear Flow Processes
  • Abstract
  • 1: Introduction
  • 2: Preliminaries related to reliability based sensor placement design
  • 3: Proposed cycle partitioning based sensor placement design
  • 4: Case Study
  • 5: Conclusions
  • References
  • The impact of sampling frequency on chemical process monitoring
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Selection of optimal sampling frequency and its application on Tennessee Eastman Process (TEP)
  • 4: Results and discussion
  • 5: Conclusions
  • References
  • Autoregressive Distributed Lag Model Based Cointegration Analysis for Batch Process Monitoring
  • Abstract
  • 1: Introduction
  • 2: ADL model based cointegration analysis
  • 3: ADL cointegration test based batch process monitoring approach
  • 4: Case study on penicillin process
  • 5: Conclusion
  • Acknowledgements
  • References
  • A Data-Driven Fault Detection and Diagnosis by NSGAII-t-SNE and Clustering Methods in the Chemical Process Industry
  • Abstract
  • 1: Introduction
  • 2: Theory
  • 3: Results and discussion
  • 4: Conclusion
  • References
  • Contributed Papers: Cyber-Physical Systems and Security
  • Cyberattack Detectability-Based Controller Screening: Application to a Nonlinear Process
  • Abstract
  • 1: Introduction
  • 2: Controller Screening Methodology
  • 3: Application to a Nonlinear Chemical Process
  • 4: Conclusions
  • References
  • OPC UA information transfer via unidirectional data diode for ICS cyber security
  • Abstract
  • 1: Improved security by combining data diode and OPC UA
  • 2: OPC UA secure communication via the unidirectional data diode
  • 3: Conclusions
  • References
  • Study on Device Authentication System for Dynamic Zoning of Industrial Control Systems
  • Abstract
  • 1: Introduction
  • 2: Device Authentication System for Dynamic Zoning
  • 3: System Implementation and Results
  • 4: Discussion
  • 5: Conclusions
  • References
  • Designing Framework for Tabletop Exercise to Promote Resilience Against Cyber Attacks
  • Abstract
  • 1: Introduction
  • 2: Exercises for improving resilience developed
  • 3: Card-Type Incident Response Exercise
  • 4: Pilot Exercise
  • 5: Conclusions
  • References
  • Self-Organizing Map Based Approach for Assessment of Control Room Operator Training
  • Abstract
  • 1: Introduction
  • 2: Experimental Studies and Methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • Acknowledgments:
  • References
  • Digital Twin of Alkaline Water Electrolysis Systems for Green Hydrogen Production
  • Abstract
  • 1: Introduction
  • 2: Alkaline Water Electrolysis System
  • 3: Model Description
  • 4: Simulation Results
  • 5: Conclusions
  • Acknowledgements
  • References
  • Cyber Security Risks of aspects of operations of OPC Unified Architecture
  • Abstract
  • 1: Introduction
  • 2: Related Research
  • 3: Proposed approach
  • 4: Evaluation Result
  • 5: Recommendation for secure practice using OPC UA
  • 6: Conclusions
  • References
  • Managing Experimental-Computational Workflows in Robotic Platforms using Directed Acyclic Graphs
  • Abstract
  • 1: Introduction
  • 2: Experimental-computational Workflows
  • 3: Case study
  • 4: Airflow-based implementation environment
  • 5: Concluding remarks
  • References
  • Development of cyber incident exercise to be widely adopted in supply chains
  • Abstract
  • 1: Introduction
  • 2: Imane Card
  • 3: Online IMANE Card
  • 4: Conclusions
  • References
  • Requirements to a digital twin-centered concept for smart manufacturing in modular plants considering distributed knowledge
  • Abstract
  • 1: Introduction
  • 2: Simulation in the life cycle of conventional and modular plants
  • 3: The digital twin and the distribution of knowledge in modular plants
  • 4: A digital twin-centered concept for smart manufacturing in MPs
  • 5: Conclusion
  • References
  • Contributed Papers: Machine Learning and Big Data
  • Equivalence Judgment of Equation Groups Representing Process Dynamics
  • Abstract
  • 1: Introduction
  • 2: Proposed Method
  • 3: Case Studies
  • 4: Conclusion
  • Acknowledgments
  • References
  • Data-driven operation support for equipment deterioration detection in drug product manufacturing
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case study
  • 4: Results & Discussion
  • 5: Conclusion
  • References
  • Pilot Plant 4.0: A Review of Digitalization Efforts of the Chemical and Biochemical Engineering Department at the Technical University of Denmark (DTU)
  • Abstract
  • 1: Introduction
  • 2: Overall Framework and Infrastructure
  • 3: Database Design
  • 4: Digital Twin Integration
  • 5: Conclusions
  • References
  • Identification Method of Multiple Sequential Alarms that Occurred Simultaneously in Plant-operation Data
  • Abstract
  • 1: Introduction
  • 2: Proposed method
  • 3: Case study
  • 4: Conclusions
  • References
  • Understand how CNN diagnoses faults with Grad-CAM
  • Abstract
  • 1: Introduction
  • 2: Explainable CNN and Grad-CAM
  • 3: Understand how CNN diagnoses faults
  • 4: Conclusions
  • References
  • A Comprehensive Framework for the Modular Development of Condition Monitoring Systems for a Continuous Dry Granulation Line
  • Abstract
  • 1: Introduction
  • 2: Condition Monitoring Framework Development
  • 3: Results and Discussion
  • 4: Conclusions
  • 5 References
  • Framework for Suppressing Transient Fault Alarms Online
  • Abstract
  • 1: Introduction
  • 2: Algorithm for suppressing transient fault alarms online
  • 3: Case study
  • 4: Conclusions
  • References
  • Using Reinforcement Learning in a Game-like Setup for Automated Process Synthesis without Prior Process Knowledge
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • References
  • Generation and Benefit of Surrogate Models for Blackbox Chemical Flowsheet Optimization
  • Abstract
  • 1: Introduction
  • 2: Case Study
  • 3: Framework for Flowsheet Optimization
  • 4: Evaluation and generation of surrogate-models
  • 5: Results
  • 6: Conclusions
  • Acknowledgement
  • References
  • Flowsheet Recognition using Deep Convolutional Neural Networks
  • Abstract
  • 1: Introduction
  • 2: Deep Convolutional Neural Networks
  • 3: Method
  • 4: Results and Discussions
  • 5: Conclusions
  • References
  • Active learning for multi-objective optimization of processes and energy systems
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Application
  • Results
  • 4: Conclusion and outlook
  • Acknowledgements
  • References
  • Data-driven Stochastic Optimization of Numerically Infeasible Differential Algebraic Equations: An Application to the Steam Cracking Process
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • References
  • Tensor-Based Autoencoder Models for Hyperspectral Produce Data
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Experimental Results
  • 4: Conclusions
  • 5 Acknowledgements
  • References
  • Molecular Representations in Deep-Learning Models for Chemical Property Prediction
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Case Study: Predicting the enthalpy of formation of organic compounds
  • 4: Conclusions
  • References
  • Deep Reinforcement Learning for Continuous Process Scheduling with Storage, Day-Ahead Pricing and Demand Uncertainty
  • Abstract
  • 1: Introduction
  • 2: Soft Actor-Critic (SAC) Method
  • 3: System Formulation and Description
  • 4: Case Study Results
  • 5: Conclusions
  • References
  • Convolutional Neural Network based Detection and Measurement for Microfluidic Droplets
  • Abstract
  • 1: Introduction
  • 2: Experiment
  • 3: Method
  • 4: Results and discussions
  • 5: Conclusions
  • References
  • Deep Reinforcement Learning Based Controller for Modified Claus Process
  • Abstract
  • 1: Introduction
  • 2: Seq2Seq and A2C Networks
  • 3: Industrial Example
  • 4: Conclusions
  • References
  • Process performance prediction based on spatial and temporal feature extraction through bidirectional LSTM
  • Abstract
  • 1: Introduction
  • 2: Reactor network process
  • 3: Feature extraction by bidirectional Long short-term memory networks
  • 4: Results
  • 5: Conclusions
  • Acknowledgement
  • References
  • Exploring the Potential of Fully Convolutional Neural Networks for FDD of a Chemical Process
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results and Discussion
  • 4: Conclusions
  • References
  • Data-driven online scenario selection for multistage NMPC
  • Abstract
  • 1: Introduction
  • 2: Sensitivity assisted multistage NMPC
  • 3: Data driven sensitivity assisted multistage NMPC
  • 4: Case study
  • 5: Conclusions
  • References
  • Data-driven Robust Model Predictive Control with Disjunctive Uncertainty for Building Control
  • Abstract
  • 1: Introduction
  • 2: Model formulation
  • 3: Control strategy
  • 4: Case study
  • 5: Conclusions
  • 6: Nomenclature
  • References
  • Low-Dimensional Input and High-Dimensional Output Modelling Using Gaussian Process
  • Abstract
  • 1: Introduction
  • 2: Related works
  • 3: High-dimensional-output modelling method
  • 4: Case studies
  • 5: Conclusions
  • References
  • Piecewise Smooth Hybrid System Identification for Model Predictive Control
  • Abstract
  • 1: Introduction
  • 2: Hybrid System Identification
  • 3: Local Predictive Clustering
  • 4: Case Study
  • 5: Conclusions
  • References
  • Distillation Column Temperature Prediction Based on Machine-Learning Model Using Wavelet Transform
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: WT-LSTM model development
  • 4: Results and discussion
  • 5: Conclusion
  • Acknowledgement
  • References
  • Moisture Estimation in Woodchips Using IIoT Wi-Fi and Machine Learning Techniques
  • Abstract
  • 1: Introduction
  • 2: Data collection and feature engineering
  • 3: Results and discussion
  • 4: Conclusions
  • References
  • Transfer Learning for Quality Prediction in a Chemical Toner Manufacturing Process
  • Abstract
  • 1: Introduction
  • 2: Chemical toner manufacturing process
  • 3: Prediction using transfer learning
  • 4: Comparison of prediction methods
  • 5: Application to a mass-production plant
  • 6: Conclusions and future tasks
  • References
  • Towards An Automated Physical Model Builder: CSTR Case Study
  • Abstract
  • 1: Introduction
  • 2: Automated Physical Model Builder
  • 3: Case Study
  • 4: Conclusions
  • Acknowledgments
  • References
  • Forward physics-informed neural networks for catalytic CO2 methanation via isothermal fixed-bed reactor
  • Abstract
  • 1: Introduction
  • 2: Isothermal fixed-bed reactor for CO2 methanation
  • 3: Forward PINN structure
  • 4: Results and discussion
  • 5: Conclusions
  • References
  • Hashing-based just-in-time learning for big data quality prediction
  • Abstract
  • 1: Introduction
  • 2: Preliminaries
  • 3: Hashing-based just-in-time (HbJIT) modeling method
  • 4: Case studies
  • 5: Conclusions
  • References
  • Physics-Constrained Autoencoder Neural Network for the Prediction of Key Granule Properties in a Twin-Screw Granulation Process
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results
  • 4: Conclusions
  • References
  • CSTR control with deep reinforcement learning
  • Abstract
  • 1: Introduction
  • 2: Reinforcement Learning and Deep Reinforcement Learning
  • 3: Case study
  • 4: Simulation results
  • 5: Conclusions and further work
  • References
  • Application of machine learning and big data for smart energy management in manufacturing
  • Abstract
  • 1: Introduction
  • 2: Results
  • 3: Conclusion
  • References
  • Adaptive least-squares surrogate modeling for reaction systems
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3: Surrogate model building: an adaptive sampling algorithm
  • 4: Example
  • 5: Conclusions
  • References
  • Machine Learning and Inverse Optimization Approach for Model Identification of Scheduling Problems in Chemical Batch Plants
  • Abstract
  • 1: Introduction
  • 2: Problem description
  • 3: Proposed approach
  • 4: Computational experiments
  • 5: Application to petrochemical batch plant
  • 6: Conclusion and future works
  • References
  • Decision-Focused Surrogate Modeling with Feasibility Guarantee
  • Abstract
  • 1: Introduction
  • 2: Mathematical Formulation
  • 3: Solution Strategy
  • 4: Computational Case Study
  • 5: Conclusions
  • References
  • A multi-output machine learning approach for generation of surrogate models in process engineering
  • Abstract
  • 1: Introduction
  • 2: Multi-output machine learning strategy
  • 3: Case studies
  • 4: Numerical results and discussion
  • 5: Conclusions and future directions
  • Acknowledgements
  • References
  • Grade transition optimization by using gated recurrent unit neural network for styrene-acrylonitrile copolymer process
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Data-driven GRU dynamic model
  • 4: Improvement of grade transition
  • 5: Conclusions
  • References
  • Development of Estimating Algorithm for Biodegradation of Chemicals Using Clustering and Learning Algorithm
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results and Discussions
  • 4: Conclusions
  • Acknowledgements
  • References
  • Surrogate Classification based on Accuracy and Complexity
  • Abstract
  • 1: Introduction
  • 2: Data sets, Surrogate Forms, and Performance Metrics
  • 3: Similarity Assessment and Families Identification
  • 4: Families for NNR2, NNSQS, NR2, and NSQS
  • 5: Conclusions
  • References
  • Training Stiff Dynamic Process Models via Neural Differential Equations
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results
  • 4: Conclusions
  • References
  • Wiz 4.0: A Novel Data Visualisation and Analytics Dashboard for a Graphical Approach to Industry 4.0
  • Abstract
  • 1: Background
  • 2: Methods
  • 3: Results and Discussion
  • 4: Conclusion
  • Acknowledgements:
  • References
  • About data reduction techniques and the role of outliers for complex energy systems
  • Abstract
  • 1: Introduction
  • 2: Method
  • 3: Case study
  • 4: Results and Discussion
  • 5: Conclusion
  • References
  • DeepGSA: Plant Data-Driven Global Sensitivity Analysis using Deep Learning
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: DeepGSA: Toolbox for plant data-driven and DL-assisted GSA
  • 4: Case Study
  • 5: Conclusions & Future work
  • References
  • Analysing Different Dynamically Modelled Data Structures and Machine Learning Algorithms to Predict PM2.5 Concentration in China
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusion
  • Acknowledgement
  • References
  • Practical Human Interface System for Transition Guidance in Chemical Plants using Reinforcement Learning
  • Abstract
  • 1: Introduction
  • 2: Related work
  • 3: Proposed method
  • 4: Experiment
  • 5: Conclusions
  • Acknowledgements
  • References
  • Surrogate modeling for nonlinear gasoline blending operations
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3: Surrogate modeling methodology
  • 4: Results and discussion
  • 5: Conclusion
  • References
  • Continuous Manufacturing Process Sequential Prediction using Temporal Convolutional Network
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Result and discussion
  • 4: Conclusions
  • Acknowledgment
  • References
  • Surrogate modeling for mixed refrigerant streams in the refrigeration cycle of an LNG plant
  • Abstract
  • 1: Introduction
  • 2: Problem Statement
  • 3: Methodology
  • 4: Results
  • 5: Conclusion
  • References
  • Prediction for heat deflection temperature of polypropylene composite with Catboost
  • Abstract
  • 1: Introduction
  • 2: Method
  • 3: Results and discussions
  • 4: Conclusion and future work
  • Acknowledgements
  • References
  • A New Machine Learning Framework for Efficient MOF Discovery: Application to Hydrogen Storage
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Case Study
  • 4: Conclusions
  • References
  • Data-driven Modeling for Magma Density in the Continuous Crystallization Process
  • Abstract
  • 1: Introduction
  • 2: Preliminaries
  • 3: Development of the magma density prediction model
  • 4: Results and discussion
  • 5: Conclusion
  • Acknowledgement
  • References
  • Gaussian Process Regression Machine Learning Models for Photonic Sintering
  • Abstract
  • 1: Introduction
  • 2: Method
  • 3: Results
  • 4: Conclusion
  • References
  • Development of Dye Exhaustion Behavior Prediction Model using Deep Neural Network
  • Abstract
  • 1: Introduction
  • 2: Process description
  • 3: Methodology
  • 4: Results and discussion
  • 5: Conclusions
  • Acknowledgements
  • References
  • Guaranteed Error-bounded Surrogate Modeling and Application to Thermodynamics
  • Abstract
  • 1: Introduction
  • 2: Theoretical Bounded Approximation Of Blackbox Models
  • 3: Gems Framework
  • 4: Application To Surrogate Thermodynamic Modeling
  • 5: CONCLUSIONS
  • 6 Acknowledgment
  • References
  • Development of an ANN-based soft-sensor to estimate pH variations in Intelligent Packaging Systems with visual indicators
  • Abstract
  • 1: Introduction
  • 2: Materials and methods
  • 3: Results
  • 4: Conclusions
  • Acknowledgments
  • References
  • Process Systems Engineering Guided Machine Learning for Speech Disorder Screening in Children
  • Abstract
  • 1: Introduction
  • 2: Materials and Methods
  • 3: Results and discussion
  • 4: Conclusions
  • References
  • Contributed Papers: Energy, Food and Environmental Systems
  • Emission and mitigation of CO2 and CH4 produced by cattle: a case study in the Brazilian Pantanal
  • Abstract
  • 1: Introduction
  • 2: Livestock in the Brazilian Pantanal region
  • 3: The system dynamics (SD) model
  • 4: Material and methods
  • 5: Results
  • 6: Conclusion
  • 7 References
  • Promoting phosphorus recovery at livestock facilities in the Great Lakes region: Analysis of incentive policies
  • Abstract
  • 1: Introduction
  • 2: Framework for the assessment of incentive policies
  • 3: Results and discussion
  • 4: Conclusions
  • Disclaimer
  • References
  • Production of ethanol, xylitol and antioxidants in a biorefinery from olive tree wastes: process economics, carbon footprint and water consumption
  • Abstract
  • 1: Introduction
  • 2: Materials and Methods
  • 3: Results and Discussion
  • 4: Conclusions
  • References
  • Application of CAPE Tools into Prospective Life Cycle Assessment: A Case Study in Acetylated Cellulose Nanofiber-Reinforced Plastics
  • Abstract
  • 1: Introduction
  • 2: Materials and methods
  • 3: Results and discussion
  • 4: Conclusions
  • Acknowledgement
  • References
  • Climate Control in Controlled Environment Agriculture Using Nonlinear MPC
  • Abstract
  • 1: Introduction
  • 2: Dynamic model formulation
  • 3: Nonlinear model predictive control
  • 4: Case studies on simulated CEA
  • 5: Conclusions
  • References
  • Thermodynamic Analysis of an Integrated Renewable Energy Driven EWF Nexus: Trade-off Analysis of Combined Systems
  • Abstract
  • 1: Introduction
  • 2: System Description
  • 3: Thermodynamic Analysis & Results
  • 4: Conclusion
  • 5: Acknowledgment
  • References
  • Low-Carbon Hydrogen Production in Industrial Clusters
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results & Discussion
  • 4: Conclusions
  • References
  • Thermoacoustic Flow-Through Cooler for Cryogenic Hydrogen
  • Abstract
  • 1: Introduction
  • 2: Mathematical Model
  • 3: Sample Results
  • 4: Conclusions
  • References
  • Life Cycle Assessment of Green Hydrogen Transportation and Distribution Pathways
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and discussion
  • 4: Conclusions
  • References
  • Sector Coupling of Green Ammonia Production to Australia’s Electricity Grid
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Grid Connectivity Results
  • 4: Impacts of Scale
  • 5: Operating Considerations
  • 6: Conclusions
  • References
  • Development of Multi-Purpose Dynamic Physical Model of Fuel Cell System
  • Abstract
  • 1: Introduction
  • 2: Physical modeling methods of FC system
  • 3: Model validation and verification
  • Conclusions
  • Acknowledgement
  • References
  • Embracing the era of renewable energy: model-based analysis of the role of operational flexibility in chemical production
  • Abstract
  • 1: Introduction
  • 2: Case study 1: methanol production
  • 3: Case study 2: aluminium production
  • 4: Conclusions
  • References
  • Hollow Fiber-based Rapid Temperature Swing Adsorption (RTSA) Process for Carbon Capture from Coal-fired Power Plants
  • Abstract
  • 1: Introduction
  • 2: Process Description
  • 3: Economic Analysis
  • 4: Conclusions
  • References
  • Determining Accurate Biofuel System Outcomes: Spatially Explicit Methods for Combined Landscape-Feedstock and Supply Chain Design
  • Abstract
  • 1: Background
  • 2: Landscape Design Model
  • 3: Model and Data Integration
  • 4: Results
  • 5: Conclusions
  • References
  • Assessing the Environmental Potential of Hydrogen from Waste Polyethylene
  • Abstract
  • 1: Introduction
  • 2: Methods description
  • 3: Results and Discussion
  • 4: Conclusions
  • Acknowledgments
  • References
  • A Systematic Comparison of Renewable Liquid Fuels for Power Generation: Towards a 100% Renewable Energy System
  • Abstract
  • 1: Introduction
  • 2: Process Description
  • 3: Results
  • 4: Conclusions
  • References
  • Guiding innovations and Value-chain improvements using Life-cycle design for Sustainable Circular Economy
  • Abstract
  • 1: Introduction
  • 2: Life Cycle Assessment (LCA) framework
  • 3: SCE Design Framework
  • 4: Sensitivity optimization for innovation discovery
  • 5: Conclusions
  • 6 Acknowledgments
  • References
  • Simultaneous Optimal Operation and Design of a Thermal Energy Storage Tank for District Heating Systems with Varying Energy Source
  • Abstract
  • 1: Introduction
  • 2: Case Study
  • 3: Methodology
  • 4: Results
  • 5: Conclusions and Future Work
  • Acknowledgements
  • References
  • A flexible energy storage dispatch strategy for day-ahead market trading
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case study
  • 4: Conclusions
  • References
  • Monetizing Flexibility in Day-Ahead and Continuous Intraday Electricity Markets
  • Abstract
  • 1: Introduction
  • 2: Method for optimal bidding strategies in day-ahead and intraday markets
  • 3: Case study: market participation of a multi-energy system
  • 4: Conclusions
  • Acknowledgements
  • References
  • Planetary boundaries analysis of Fischer-Tropsch Diesel for decarbonizing heavy-duty transport
  • Abstract
  • 1: Introductions
  • 2: Methodology
  • 3: Results
  • 4: Conclusions
  • Acknowledgements
  • References
  • Renewable Power Systems Transition Planning using a Bottom-Up Multi-Scale Optimization Framework
  • Abstract
  • 1: Introduction
  • 2: Multi-scale bottom-up energy transition optimization framework
  • 3: Case study for New York State
  • 4: Conclusion
  • References
  • Design and Operation of Urban Energy Network: Integration of Civic, Industrial, and Transportation Sectors
  • Abstract
  • 1: Introduction
  • 2: Optimization problem formulation
  • 3: Case study description
  • 4: Results and discussion
  • 5: Conclusions
  • References
  • Sustainable Design of Hybrid Energy Systems for Net Zero Carbon Emission
  • Abstract
  • 1: Introduction
  • 2: Problem Statement and Model Summary
  • 3: Global Optimization Strategy
  • 4: Application to Cornell University Campus Energy Systems
  • 5: Conclusion
  • References
  • Prediction of Charge / Discharge Behavior of Tri-Electrode Zinc-air Flow Battery Using Linear Parameter Varying Model
  • Abstract
  • 1: Introduction
  • 2: Description of tri-electrode ZAFB and experimental data
  • 3: LPV modeling
  • 4: Results and discussion
  • 5: Conclusion
  • References
  • An optimized resource supply network for sustainable agricultural greenhouses: A circular economy approach
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results
  • 4: Conclusion
  • 5 References
  • Exergoeconomic optimization of a double effect evaporation process of coffee extract
  • Abstract
  • 1: Introduction
  • 2: Materials and Methods
  • 3: Results and Discussion
  • 4: Conclusions
  • References
  • Ecohydrological modeling and dynamic optimization for water management in an integrated aquatic and agricultural livestock system
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Numerical results
  • 4: Conclusions
  • References
  • Parametric Analysis of Ortho-to-Para Conversion in Hydrogen Liquefaction
  • Abstract
  • 1: Introduction
  • 2: Ortho–to–Para Conversion
  • 3: Research Methods
  • 4: Further Discussion
  • 5: Conclusions
  • Acknowledgment
  • References
  • Model agnostic framework for analyzing rainwater harvesting system behaviors
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results and discussion
  • 4: Conclusions
  • Acknowledgements
  • References
  • Global assessment and optimization of renewable energy and negative emission technologies
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusion
  • Acknowledgment
  • References
  • The Trade-Off between Spatial Resolution and Uncertainty in Energy System Modelling
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • References
  • Designing a Resilient Biorefinery System under Uncertain Agricultural Land Allocation
  • Abstract
  • 1: Introduction
  • 2: Problem formulation
  • 3: Stochastic optimization
  • 4: Case study details
  • 5: Results and discussion
  • 6: Conclusions
  • References
  • LCA modelling as a decision-tool for experimental design: the case of extraction of astaxanthin from crab waste
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results & Discussion
  • 4: Conclusions
  • References
  • Decomposition of Organic Compounds in Water from Oil Refineries
  • Abstract
  • 1: Introduction
  • 2: Proposed process for the treatment of water from oil refineries
  • 3: Methods
  • 4: Results and Discussion
  • 5: Conclusion
  • References
  • Energy Harvesting Wireless Sensors Using Magnetic Phase Transition
  • Abstract
  • 1: Introduction
  • 2: Energy harvesting using magnetic phase transition and sensors
  • 3: Experimental procedure and set-up
  • 4: Experimental results
  • 5: Conclusion
  • Acknowledgement
  • References
  • Competitive Adsorption of Copper, Nickel, and Chromium Ions onto Amine Functionalized SBA-15
  • Abstract
  • 1: Introduction
  • 2: Materials and methods
  • 3: Results and discussion
  • 4: Conclusions
  • References
  • Use of Environmental Assessment and Techno Economic Analysis (TEA) to Evaluate the Impact and Feasibility of Coatings for Manufacturing Processes
  • Abstract
  • 1: Introduction
  • 2: Goal and scope
  • 3: Data collection and inventory
  • 4: Cost and environmental assessment
  • 5: Conclusions
  • 6 References
  • Forecasting Operational Conditions: A case-study from dewatering of biomass at an industrial wastewater treatment plant
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results
  • 4: Conclusion
  • 5 Acknowledgement
  • 6 References
  • Plant wide modelling of a full-scale industrial water treatment system
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results
  • 4: Conclusion
  • 5 References
  • A Systematic Framework for the Integration of Carbon Capture, Renewables and Energy Storage Systems for Sustainable Energy
  • Abstract
  • 1: Introduction
  • 2: THESEUS Framework
  • 3: Results and Discussion
  • 4: Conclusions
  • 5 Acknowledgements
  • References
  • Integration of experimental study and computer-aided design: A case study in thermal energy storage
  • Abstract
  • 1: Introduction
  • 2: Material and Methodology
  • 3: Case study in thermal energy storage
  • 4: Conclusions
  • Acknowledgement
  • References
  • Design support toolbox for renewable-based regional energy systems; The concept, data integration, and simulator development
  • Abstract
  • 1: Introduction
  • 2: Case studies of designing renewable-based regional energy systems
  • 3: Requirement definition of the design support toolbox
  • 4: Development of modules in the toolbox
  • 5: Conclusions
  • Acknowledgement
  • References
  • Circular Economy Integration into Carbon Accounting Framework for Comprehensive Sustainability Assessment
  • Abstract
  • 1: Introduction
  • 2: Circular Economy Actions Selection Framework
  • 3: Case Study
  • 4: Conclusions
  • 5 Acknowledgement
  • References
  • Design and analysis of fuel-assisted solid oxide electrolysis cell combined with biomass gasifier for hydrogen production
  • Abstract
  • 1: Introduction
  • 2: Models of Gasifier and Fuel-Assisted Solid Oxide Electrolysis Cell
  • 3: Integrated System process description
  • 4: Results and Discussions
  • 5: Conclusions
  • 6 Reference
  • Plasma-Based Pyrolysis of Municipal Solid Plastic Waste for a Robust WTE Process
  • ABSTRACT
  • 1: Introduction
  • 2: Materials and Methods
  • 3: Results and Discussion
  • 4: CONCLUSION
  • Acknowledgements
  • References
  • Contributed Papers: Pharma and Healthcare Systems
  • Hybrid Modelling Strategies for Continuous Pharmaceutical Manufacturing within Digital Twin Framework
  • Abstract
  • 1: Introduction
  • 2: Hybrid Multi-zonal Compartmentalization
  • 3: Hybrid Adaptive Modelling
  • 4: Conclusions
  • Acknowledgement
  • References
  • Determination of probabilistic design spaces in the hybrid manufacture of an active pharmaceutical ingredient using PharmaPy
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Study
  • 4: Results
  • 5: Conclusions
  • 6 Acknowledgement
  • References
  • Hybrid Modelling of CHO-MK Cell Cultivation in Monoclonal Antibody Production
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and Discussion
  • 4: Conclusions
  • Acknowledgements
  • References
  • Multimodal modelling of uneven batch data
  • Abstract
  • 1: Introduction
  • 2: Materials and Methods
  • 3: Case Study: Industrial Simulation of Penicillin Fermentation
  • 4: Results and Discussions
  • 5: Conclusions
  • References
  • Application of MHE-based NMPC on a Rotary Tablet Press under Plant-Model Mismatch
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case Study
  • 3.2: Applying MHE to tablet press: Comparison of fixed model and adaptive model
  • 4: Conclusions
  • Acknowledgement
  • References
  • Gray-box modelling of pharmaceutical roller compaction process
  • Abstract
  • 1: Introduction
  • 2: Materials and Methods
  • 3: Results
  • 4: Conclusions
  • References
  • Multi-objective optimisation for early-stage pharmaceutical process development
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Results and discussion
  • 4: Conclusions
  • Acknowledgments
  • References
  • Quality by design and techno-economic modelling of RNA vaccine production for pandemic-response
  • Abstract
  • 1: Introduction
  • 2: The AVV, mRNA and saRNA vaccine production platform technologies
  • 3: Techno-economic modelling of the AVV, mRNA and saRNA platforms
  • 4: Integration of QbD and techno-economic modeling with the RNA platform
  • 5: Conclusions
  • Acknowledgements
  • References
  • Design of Value Function Trajectory for State of Control in Continuous Manufacturing System
  • Abstract
  • 1: Introduction
  • 2: Process control with a priori knowledge
  • 3: Reactor Simulation Model
  • 4: Design Space
  • 5: Trajectory Tracking Control
  • 6: Conclusions
  • References
  • A Thermodynamic Approach for Simultaneous Solvent, Coformer, and Process Optimization of Continuous Cocrystallization Processes
  • Abstract
  • 1: Introduction
  • 2: Approach
  • 3: Results and Discussion
  • 4: Conclusions
  • Acknowledgment
  • References
  • Optimizing the selection of drug-polymer-water formulations for spray-dried solid dispersions in pharmaceutical manufacturing
  • Abstract
  • 1: Introduction
  • 2: Design Methodology
  • 3: Case study: optimal binary and ternary blends for the SSD of naproxen
  • 4: Conclusions
  • Acknowledgments
  • References
  • Integrated design of injectable manufacturing processes considering characteristics of process-and discrete-manufacturing systems
  • Abstract
  • 1: Introduction
  • 2: Methodology
  • 3: Case study
  • 4: Conclusion
  • 5 References
  • A bi-level decomposition approach for CAR-T cell therapies supply chain optimisation
  • Abstract
  • 1: Introduction
  • 2: Materials and methods
  • 3: Results and discussion
  • 4: Conclusions
  • 5 Acknowledgements
  • References
  • An agent-based model for cost-effectiveness analysis in the manufacture of allogeneic human induced pluripotent cells in Japan
  • Abstract
  • 1: Introduction
  • 2: Methods
  • 3: Results and discussion
  • 4: Conclusions and outlook
  • Acknowledgements
  • References
  • Design and operation of healthcare facilities using batch-lines: the COVID-19 case in Qatar
  • Abstract
  • 1: Introduction
  • 2: Problem statement
  • 3: Mathematical modeling
  • 4: Results
  • 5: Conclusions
  • References
  • Application of PSE Methods on Monoclonal Antibody Productivity Improvement and Quality Control
  • Abstract
  • 1: Introduction
  • 2: Flowsheet modeling and techno-economic analysis
  • 3: Predictive modeling of cell culture and protein glycosylation processes
  • 4: Fed-batch bioreactor modeling and design space identification
  • 5: Conclusions
  • References
  • Image classification of experimental yields for cardiomyocyte cells differentiated from human induced pluripotent stem cells
  • Abstract
  • 1: Introduction
  • 2: Methods and Materials
  • 3: Results and Discussion
  • 4: Conclusions
  • 5 Acknowledgments
  • References
  • Prediction of API concentration using NIRS measured offline and in-line instruments
  • Abstract
  • 1: Introduction
  • 2: Experimental
  • 3: Model development and validation
  • 4: Results
  • 5: Conclusions
  • References
  • Author Index

Product details

  • No. of pages: 2298
  • Language: English
  • Copyright: © Elsevier 2022
  • Published: June 10, 2022
  • Imprint: Elsevier
  • Hardcover ISBN: 9780323851596
  • eBook ISBN: 9780323853668

About the Editors

Yoshiyuki Yamashita

Yoshiyuki Yamashita is a professor and a chair of the Department of Chemical Engineering at Tokyo University of Agriculture and Technology (TUAT) in Tokyo. His main areas of expertise include process monitoring and control, as well as artificial intelligence and smart manufacturing. He received his BS, MS and PhD degrees in chemical engineering all from Tohoku University (Sendai, Japan) and subsequently became an assistant professor and associate professor at Tohoku University before joining TUAT in 2007. Dr. Yamashita chairs the Industry-University Research Committee on Process Systems Engineering, Japan Society for the Promotion of Science, since 2016. He is the recepient of the Young Investigator Award of the Society of Chemical Engineers, Japan in 1993, and Outstanding Paper Award of the Journal of Chemical Engineering of Japan in 2000, 2008, 2019 and 2020.

Affiliations and Expertise

Professor and Chair of Department of Chemical Engineering, Tokyo University of Agriculture and Technology (TUAT), Tokyo, Japan

Manabu Kano

Dr. Manabu Kano is a professor of the Department of Systems Science, Kyoto University. He received BS, MS, and PhD degrees from the Department of Chemical Engineering, Kyoto University, in 1992, 1994, and 1999. He has been working at Kyoto University since 1994. From 1999 to 2000, he was a Visiting Scholar with Ohio State University, U.S. His research interest has focused on applying systems approach and data analytics to various problems related to manufacturing processes and medical and healthcare services. He started a medical venture company ‘Quadlytics Inc.’ in 2018. Dr. Kano was a recipient of many awards, including the Best Paper Awards and the Technology Awards from the Society of Instrument and Control Engineers (SICE), the Sawamura Paper Award from the Iron and Steel Institute of Japan (ISIJ), and the Outstanding Paper Awards of J. Chem. Eng. Japan and the Technology Award from the Society of Chemical Engineers, Japan (SCEJ).

Affiliations and Expertise

Professor, Department of Systems Science, Kyoto University, Kyoto, Japan

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