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A Pattern-based Method for Scheduling of Energy-integrated batch Process Networks

IFAC-PapersOnLine 2016年第7期49卷 669-674页

作者： Mete, Shrikant Jogwar, Sujit S. Department of Chemical Engineering Institute of Chemical Technology Mumbai400019 India

This paper describes a pattern-based method for the generation of flexible-horizon production schedules for energy-integrated batch systems using a benchmark reactor-distillation system. The proposed methodology consists of structural decomposition of an already existing schedule for a fixed time horizon to identify repetitive patterns. It is found that such a schedule can be divided into three sections - initial, final and an intermediate section - of manipulable sizes. Based on such a decomposition, it is possible to generate an extended (or shorter) horizon schedule by increasing (or decreasing) the sizes of these sections. The proposed method allows for the generation of new schedules without solving mathematically rigorous mixed integer programming problems. The key advantage of the proposed method is the significant reduction in the time required for solving large scheduling problems, especially for online rescheduling applications. The effectiveness of the proposed methodology is illustrated through the same benchmark scheduling problem. © 2016

关键词： Scheduling algorithms batch data processing Distillation Distillation equipment Integer programming Problem solving Production control Scheduling batch rescheduling batch scheduling Distillation systems Heat integration Mixed integer programming Pattern based method Pattern identification Structural decomposition

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Phase partition for nonlinear batch process monitoring

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IFAC-PapersOnLine 2016年第7期49卷 1181-1186页

作者： Liu, Jingxiang Liu, Tao Zhang, Jie Institute of Advanced Control Technology Dalian University of Technology Dalian116024 China School of Chemical Engineering and Advanced Materials Newcastle University Newcastle upon Tyne NE1 7RU United Kingdom

A window-based step-wise sequential phase partition method is proposed for monitoring nonlinear batch processes with multiphase operations. The three-dimensional batch data are unfolded in the batch-wise direction to facilitate establishing the kernel principle component analysis (KPCA) models. A moving window is introduced to maintain the kernel parameters unchanged for computation while preserving the time sequence of different phases, thus capable of significantly reducing the storage space of kernel matrices and the computation complexity. A numerical case and a penicillin fermentation process are used to demonstrate the effectiveness and merit of the proposed method. © 2016

关键词： batch data processing Digital storage Drug products Numerical methods Principal component analysis Process control Process monitoring batch process batch process monitoring Computation complexity Kernel principle component analysis Moving window Penicillin fermentation process Phase partition Phase partition methods

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Dynamic optimization of fixed bed chemical-looping combustion systems integrated in thermal power plants

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IFAC-PapersOnLine 2016年第7期49卷 115-120页

作者： Han, Lu Bollas, George M. Department of Chemical & Biomolecular Engineering University of Connecticut Storrs 191 Auditorium Road Unit 3222 CT06269-3222 United States

Optimization methods can be used to improve the design and operation of batch processes. In this work, we illustrate the application of dynamic simulation and optimization for power generation in chemical-looping combustion systems, carried out in batch reactors. We present a framework for the optimization strategy, in which the objective is to maximize a measure of the energy efficiency, bounded by inequality constraints reflecting the industry standards. Several case studies are used to illustrate the applicability of the present problem formulation to enhance the process performance. © 2016

关键词： Combustion batch data processing batch reactors Constraint theory Dynamic models Energy efficiency Fuel systems Power generation Thermoelectric power plants Chemical looping combustion Design and operations Dynamic optimization Inequality constraint Optimization problems Optimization strategy Simulation and optimization Thermal power plants

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Improving the software engineering of brew house plants by modularizing the control software

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IFAC-PapersOnLine 2018年第10期51卷 241-248页

作者： Brunner, Benjamin Aicher, Thomas Gemein, Fabian Vogel-Heuser, Birgit Institute of Automation and Information Systems Technische Universität München Germany

The development of control software for automation plants is a time-consuming task. With a modular structure of the control software, which is derived from a functional decomposition of plant and process, this paper presents an alternative approach to the widely used procedure “Copy, paste, modify” of the control software of a similar plant. The approach is applied on batch process plants, in particular 2-vessel brew house plants. Their plant topologies are modularized with regard to hardware, process and control. Based on the established modular structure of the plant control, software modules are developed. Generating the control software of new plants from an assembly of these software modules will reduce implementation effort and improve software reusability. As a proof of concept, a prototypical test plant is constructed and run with control software, which was automatically generated from a prototypical tool implementation. © 2016

关键词： Computer control Automatic test pattern generation batch data processing Computer software reusability Process control Programmable logic controllers Reusability Software testing Structure (composition) Automatically generated Control software Functional decomposition Model driven Engineering Modular structures Proof of concept Software modules Time consuming tasks

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Semi-virtual Plant for the Modelling, Control and Supervision of batch-processes. An example of a greenhouse irrigation system

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IFAC-PapersOnLine 2015年第29期48卷 123-128页

作者： Rodríguez, F. Castilla, M. Sánchez, J.A. Pawlowski, A. Department of Computer Science Automatic Control Robotics and Mechatronics Research Group University of Almería Agrifood Campus of International Excellence CeiA3 Spain Department of Computer Science and Automatic Control ETSII UNED Madrid Spain

In this work, a hardware-software architecture for control engineering education is proposed and a case of study regarding a greenhouse irrigation virtual process has been implemented. This specific process is especially useful for subjects related to industrial automation, since it is characterized by mixed dynamics (continuous/discrete) and can be controlled by a Programmable Logic Controller (PLC). In such a case, there is no need to access to the real process that is not always available for practical exercises. Moreover, the developed scheme eliminates the maintenance costs related to real process, being a very important advantage for academic institutions. The developed architecture for the industrial process simulation uses Labview, OPC, MODBUS, SolidWorks and Schneider Modicon M340 PLC for the control of virtual processes. The developed example is applied to the greenhouse fertirrigation control that enables the agricultural engineering students to design the irrigation control system. The control strategy is implemented on the PLC which interacts with the virtual process by carrying out the necessary actions in order to control the appropriate variables of the process. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Process control batch data processing Engineering education Greenhouses Irrigation Academic institutions Control strategies Industrial automation Industrial process simulation Irrigation controls Irrigation systems Programmable Logic Controller (PLC) Virtual plants

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Fault diagnosis model of batch process based on improved KFDA

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IFAC-PapersOnLine 2017年第1期50卷 14758-14763页

作者： Fu, Yuanjian Zhang, Yingwei Feng, Lin College of Information Science and Engineering Northeastern University ShenyangLiaoning110819 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University ShenyangLiaoning110819 China

For complex batch processes, it is possible to encounter the problem of singularity of kernel matrix during the calculation of kernel Fisher discriminatory analysis (KFDA) model. In this paper, an improved KFDA algorithm is proposed for fault diagnosis of nonlinear batch processes. Firstly, the original data is projected from the original space to high dimensional space by kernel functions. Secondly, in the calculation of KFDA, the orthogonal matrix is obtained by singular value decomposition for kernel within-class scatter degree matrix. Finally, the processed data and kernel within-class scatter degree matrix is projected onto a nonsingular orthogonal matrix after the decomposition. The feasibility and efficiency of the proposed method is demonstrated through beer fermentation process. © 2017

关键词： Singular value decomposition batch data processing Beer Brewing Failure analysis Fault detection Beer fermentations Discriminatory analysis Fault diagnosis model High dimensional spaces Kernel function KFDA Orthogonal matrix Within class scatter

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Container selection processing implementing extensive neural learning in cloud services

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Materials Today: Proceedings 2023年 80卷 1868-1871页

作者： Muthakshi, S. Mahesh, K. Department of Computer Applications Alagappa University India

The container selection processing performance analyses huge data with minimal resources and the lowest latency. The elastic management applications execute the containers with the specific hierarchy of virtual processing and machine management. The container that has performance degradation implicit provision of least expensive containers with minimal resources helps to increase the performance of containers. The specific data and stream processing prompts scrutinizing of data through the container selection process through different methodologies. To exterminate the bottleneck problem that selects efficient and required size, processing speed, and its reliability of guiding the batch processing of containers. The extensive neural learning handles container optimality involves a dynamic selection of appropriate containers in cloud service providers. The cloud service providers along with container selection contain batch processing and stream processing allocates efficient container-specific selection appropriately. In the huge data segregation of data processed data that emphasizes multiple data scrutinizing. © 2021

关键词： batch data processing

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Minimising makespan of batch processing machine with unequal ready times

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International Journal of Industrial and Systems Engineering 2022年第4期40卷 496-512页

作者： Ghrayeb, Leena Muthuswamy, Shanthi Damodaran, Purushothaman Department of Industrial and Systems Engineering Northern Illinois University De KalbIl-60115 United States Department of Engineering Technology Northern Illinois University De KalbIl-60115 United States

This research considers scheduling a single batch processing machine at a contract electronics manufacturer. The processing times, ready times and the sizes of the jobs are given and the total size of the batch should not exceed the machine capacity. The batch ready time is equal to the latest ready time of all the jobs in the batch. The objective is to minimise the makespan. The commercial solver used to solve the mathematical formulation proposed requires long run times. Consequently, several heuristics and lower bounding procedures are proposed. Through an experimental study, it is shown that one of the lower bounds is within 40% of the best known integer solution from CPLEX for the 200-job instances. The heuristics are very effective in finding good quality solutions with short run times. For smaller problem instances, the quality of the heuristic solution is within 10% of the best known solution from CPLEX. © 2022 Inderscience Enterprises Ltd.

关键词： batch data processing

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KPIs as the interface between scheduling and control

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IFAC-PapersOnLine 2016年第7期49卷 687-692页

作者： Bauer, Margret Lucke, Matthieu Johnsson, Charlotta Harjunkoski, Iiro Schlake, Jan C. University of the Witwatersrand Johannesburg2050 South Africa ABB Corporate Research Wallstadter Str. 59 Ladenburg68526 Germany Department of Automatic Control Lund University Lund22100 Sweden

The integration of scheduling and control has been discussed in the past. While constructing an integrated plant model that may still seem out of reach, scheduling and control systems are increasingly more intertwined. We argue that they are in fact already integrated and give the example of two key performance indicators (KPIs) that are defined in the recent international standard ISO 22400. The focus of this study is on KPIs that consider both planned times and actual times. An amino acid production plant is used in the study, and the production is described from both the scheduling and the control perspective. To illustrate the integration, a schedule is computed containing the planned production times. Resulting measurements from the control system are analyzed for their actual production times using a proposed procedure that detects the start and end time of batches. Using KPIs as the interface between scheduling and control can be used as a strategy for maximizing the plant performance. The study focuses on the process industry. © 2016

关键词： Process control batch data processing Benchmarking Control engineering Distributed parameter control systems Integration Scheduling Supply chain management Waste disposal Amino acid production batch process Control perspective International standards Key performance indicators Planning and scheduling Process industries Scheduling and controls

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Distributional Uncertainty Analysis in Transient Heterogeneous Multiscale Catalytic Flow Reactors

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IFAC-PapersOnLine 2016年第7期49卷 436-441页

作者： Chaffart, Donovan R.G. Ricardez-Sandoval, Luis A. Department of Chemical Engineering University of Waterloo N2L 3G1 Waterloo Canada

This work explores the effects of parameter uncertainty and model-plant mismatch on a transient, spatially heterogeneous multiscale catalytic reactor system. Uncertainty in key system parameters is propagated into the concentration of the reactor product species using power series expansion (PSE). The reactor model is constructed through the combination of continuum equation modeling, to describe mass transport within the reactor, with kinetic Monte Carlo (kMC) simulations that predicts the behavior of the catalyst surface. The uncertainty analysis illustrated in this study is employed to evaluate the effects of uncertainty on the reactor product concentration as it evolves in time and space. © 2016

关键词： Uncertainty analysis batch data processing batch reactors Identification (control systems) Models Monte Carlo methods Transient analysis batch process Catalytic reactor systems Continuum equation Flow reactors Kinetic monte carlo simulation Parameter uncertainty Power series expansions Product concentration

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