Operation Of Batch Processes Research Articles

Integration in hierarchical structures for batch process operations

This paper presents an application of a recent methodology for the automatic transfer of information among different decision making levels in the operation of flexible manufacturing plants. The value that integration adds to the performance of a hierarchical decision making structure is discussed. The main aspects of a single modelling approach to ease integration and a software prototype under current development are also analyzed. In particular, results from a recent extension of the proposal for deriving optimal operating procedures in the event of a breakdown in batch plants are shown on a semiconductor fab case study.

A framework for batch-operation analysis within the context of disturbance management

Schedule optimization is an effective strategy to improve the performance of batch process operations, especially in multi-purpose and multi-product facilities. In large segments of the batch process industry, however, disturbances necessitate constant rescheduling. Any improvement strategy must therefore include a strategy for dealing with disturbances. This paper presents a framework for disturbance management in the batch process industry, aimed at identifying causes and consequences of disturbances, so that the causes may be eliminated and negative consequences may be reduced. The framework is designed to draw an integrated picture of those parts of the process and the business organization that contribute to disturbances, and to be applicable to any batch process. Its effectiveness as a diagnosing instrument was tested and confirmed in the steel industry.

Development of a batch manager for dynamic scheduling and process management in multiproduct batch processes

A batch manager is developed for the dynamic scheduling and on-line management of process operations. The developed system consists of a process monitoring module and a dynamic scheduling module. When a deviation from the initial schedule is detected in a process monitoring module, dynamic scheduling is performed in the dynamic scheduling module and the initial schedule is adjusted to the proper schedule by using rescheduling algorithms presented in this paper. The adjusted schedule is shown in the process monitoring module. The dynamic scheduler in the batch manager copes with several unexpected process events of batch process operations by adjusting the EST (Earliest Start Time) of equipment, redetermining the batch path and reassigning tasks to equipment. This study focuses on the implementation of a batch manager with on-line dynamic scheduling for batch process management. Examples of fodder production batch processes illustrate the efficiency of the algorithms.

Monitoring a PVC Batch Process with Multivariate Statistical Process Control Charts

Multivariate statistical process control charts (MSPC charts) are developed for the industrial batch production process of poly(vinyl chloride) (PVC). With these MSPC charts different types of abnormal batch behavior were detected on-line. With batch contribution plots, the probable causes of these abnormalities were located. Examples are given for two different types of abnormalities, i.e., a bias in the batch loading and a control valve problem during polymerization. These examples show that MSPC charts in combination with batch contribution plots are a simple and powerful method for fault detection and identification of their cause in the operation and control of batch processes.

Disturbances and their impact on scheduling

Various disturbances may upset batch production schedules during execution, necessitating frequent corrections. These disturbances have a negative impact on the performance of batch process operations. The goal of our research is to improve this performance by providing production schedulers with a disturbances management system. This system helps schedulers to find a better schedule, to find it quicker and to adjust it adequately to disturbances during its execution. The functions of the system supporting scheduling initialisation and adjustment result in, amongst others, more robust schedules. To achieve this, we introduce a performance indicator and an effectuation indicator indicating the quality of the operation and the effectuation of the planned operation, respectively.

Process Monitoring Using Principal Component Analysis in Different Operating Time Processes

Based on principal component analysis, a method for the multivariate statistical process control is developed to analyze and monitor batch processes at the different operating time. In most batch process operations, operators often need to adjust the different operating time in each batch run to get the desired product quality since the input specifications provided are different. The proposed method is the combination of the orthonormal function approximation and the multiway principal component analysis (MPCA). The only information needed to exploit the procedure is the historical data collected from the past successful batches. Like the philosophy of statistical process control in the traditional MPCA, this method leads to simple monitoring charts, easy tracking of the progress in each batch run and monitoring the occurrence of observable upsets. Two examples illustrate the effectiveness of the proposed methodology.

Batch process design and operation using operational envelopes

We consider the problem of determining the details of the design and operation of batch processes as relevant to the pharmaceuticals and fine and specialty chemicals sectors. The aim is to improve the early phase process development activity to result in more efficient processes and plants in a much shorter period of time, thus reducing both the time to market and capital and operating costs. The particular component described here is the use of “operational envelopes” in the process design activity. This recognises that existing processes never operate as specified through the design intent, but rather in some region around the design specifications. Instead of designing processes to operate at a fixed point and then implicitly allow variation, we aim to design processes to operate within an explicit operational envelope. Bounds on desired dimensions of the envelope are specified and an optimisation procedure is utilised to generate processes with desired characteristics.

Completion times algorithm and optimal scheduling of single line multi-purpose batch process

For study of engineering facts, generally the operation of batch plants was classified into two types. One is the operation of multi-product batch process which produce multiple products with the same processing paths, the other is that of multi-purpose batch process which produce multiple products through the different production routes ( Reklaitis, (1990)). Also, according to Voudouris (1996), the multi-purpose batch plants are divided into two categories, sequential plants and non-sequential batch plants. In this paper we develop the completion times algorithm of nonsequential multi-purpose batch plants which have one unit in each stage under UIS policy. We also propose an efficient scheduling method for those plants. The proposed scheduling method composed two step approaches. In the first step, modified-RAES heuristics for initial solution of multi-purpose batch process scheduling was developed. At the second step, we suggested the Modified Simulated Annealing (MSA) method with adjusting parameters of Simulated Annealing (SA) by Ku and Karimi (1991). To evaluate the performance and efficiency of this study, we have tested about 200 problems and could get the outperformed results.

RMBatch: Intelligent real-time monitoring and diagnosis system for batch processes

Batch Process-generally exhibits batch-to-batch variation that makes it difficult to produce a uniform high quality product. The variation arises from sources such as: composition disturbances, deviations from specified trajectories. equipment malfunction and heat transfer limitation. Extensive research has been done to develop a model for the efficient and reliable monitoring and diagnosis for these batch processes. Various algorithms such as multivariate statistical process control based on multhvay principal component analysis and partial least square have been proposed for the monitoring of batch processes. A prototype of intelligent Real-time Monitoring and diagnosis system for Batch process (“RMBatch”) has been developed as a tool that offers real-time monitoring and diagnosis for batch processes. Our developed RMBatch is composed of plant information module, data preprocessing module, data analysis and modeling module, monitoring and diagnosis module. The design and the various functions of RMBatch will be illustrated using its application to an industrial batch process. The application has shown that RMBatch can help operators monitor, diagnose and improve the operation of batch processes.

Multiway covariates regression models

An abundance of methods exist to regress a y variable on a set of x variables collected in a matrix X. In the chemical sciences a growing number of problems translate into arrays of measurements X and Y, where X and Y are three-way arrays or multiway arrays. In this paper a general model is described for regressing such a multiway Y on a multiway X, while taking into account three-way structures in X and Y. A global least squares optimization problem is formulated to estimate the parameters of the model. The model is described and illustrated with a real industrial example from batch process operation. An algorithm is given in an appendix. Copyright (C) 1999 John Wiley & Sons, Ltd.

Multiway covariates regression models

An abundance of methods exist to regress a y variable on a set of x variables collected in a matrix X. In the chemical sciences a growing number of problems translate into arrays of measurements X and Y , where X and Y are three-way arrays or multiway arrays. In this paper a general model is described for regressing such a multiway Y on a multiway X , while taking into account three-way structures in X and Y . A global least squares optimization problem is formulated to estimate the parameters of the model. The model is described and illustrated with a real industrial example from batch process operation. An algorithm is given in an appendix. Copyright © 1999 John Wiley & Sons, Ltd.

Overview of Planning and Scheduling of Batch Process Operations

Batch production is used for the manufacture of fine chemicals and is particularly appropriate when production quantities are small, or when the procedure or the product demand is likely to change. Batch processes are usually carried out in relatively standard items of equipment whose operating conditions can be adjusted to accommodate a variety of products. Plants for batch operations can be arranged as multiproduct, multipurpose under campaign mode and general multipurpose. In this study, all the three types of batch plants are examined under planning and scheduling. Planning stage is the macrolevel where the problem is outlined and scheduling stage is the microlevel where the production lines are set and the batch sizes determined within the given time horizons to satisfy the product demands. These three problems are examined under different objective functions.

A hybrid neural network-first principles approach to batch unit optimisation

Achieving an optimal operation of batch processes is a difficult problem due to issues such as imperfect modelling, scarcity of information and delayed access to key measurements of process states. In this paper, a hybrid approach for batch process optimisation that integrates together inductive learning (neural networks) and first principles knowledge is proposed. The latter is expressed as derivative constraints that impose learning bias for inductive modelling and generalisation. The result of such integration is a value function that is incrementally learned, and later used to implement a near-optimal control policy that is geared to guarantee product quality and to improve process performance. Artificial batch runs are simulated by means of a predictive process model to help constrain and speed up the learning procedure for the value function. The efficacy of the proposed methodology is demonstrated using a semi-batch autocyclic reactor.

Rule-based reactive rescheduling system for multi-purpose batch processes

In this paper, we propose a rule-based reactive rescheduling system to cope with several unexpected process events for multi-purpose batch process operations. The developed system consists of two major modules. The first module continuously monitors production status whether a processing task starts at the scheduled starting time and completes at the scheduled ending time. When a deviation from the initial schedule is detected by the first module, a delay index defined in this research is evaluated to determine whether the second module must be activated. The delay index is used to measure the effect on the remain scheduled operations by several unexpected events. If the second module is fired, it determines appropriate actions to minimize the effect of the event on the remaining initial schedule. Here, all process components in a plant are described by object-oriented programming paradigm.

5554657 Process for recycling mixed polymer containing polyethylene terephthalate : Brownscombe Thomas F; Fong Howard L; Diaz Zaid; Chuah Hoe; June Raymond L; Rollick Kevin L; Semple Thomas C; Tompkin Mark R Houston, TX, United States assigned to Shell Oil Company

As emphasis changes away from end-of-pipe control technologies to cleaner production technologies, industrial processors seeking to identify and prioritize process changes need first to identify significant sources of waste, both in the form of air emissions as well as in energy and solid waste production. To this end, this paper presents a summary of methods of quantifying and characterizing air pollutants, specifically volatile organic compounds, from batch processing operations as well as from ancillary equipment such as storage tanks, leaking piping components, and wastewater treatment processes. In addition to presenting the basis for the methodologies, some discussion of the degree of confidence that should be imparted on the obtained values is provided.

A generic framework for an on-line scheduling and control system in batch process management

On-line scheduling and control systems, which dynamically adjust production schedules according to changes in scheduling conditions, are a vital issue in modern batch processes because of their dynamic behavior and the unpredictable market situation. In this paper, we propose a generic on-line scheduling and control framework to handle a wide variety of uncertainties by utilizing proven external scheduling algorithms. The framework provides fundamental mechanisms to define schedule modification timing and a modification space according to the changes of scheduling conditions, and dynamically modifies a schedule to minimize the effect of the changes by using adequate scheduling algorithms for each situation. The basic structure and mechanisms of the framework are described. Performance of the framework against typical fluctuations in ordinary batch process operations is demonstrated via simulation experiments with a multiproduct batch plant.

CMAC-Based Learning Control for a Batch Reactor

Nowadays, batch process operations are going important in the chemical industry and more precise tracking is required for batch chemical reactors. To improve the control performance, Cerebellar Model Articulation Controller (CMAC) based learning control is adopted for a batch chemical reactor. Analyzing the Albus' algorithm, the paper points out its drawback in batch updating. An improved algorithm and its convergence are discussed. Simulations of three types of control schemes for batch reactor are compared, which shows that the improved CMAC-based learning control has quick convergence and satisfied control characteristic.

Global strategy for energy and waste analysis in scheduling and planning of multiproduct batch chemical processes

Energy integration and waste minimization have received increasing attention in the chemical industry. Recent studies have addressed the specific problems that arise in batch chemical processes. However, a production plan built up using schedules developed beforehand may become inefficient or even fail to attain its production targets. Furthermore, production plans satisfying demand objectives may reduce or even eliminate energy integration or waste minimization opportunities. In this work, waste and energy minimization are treated as an integral part of the constrained production scheduling problem with limited resources. The methodology developed is based on a comprehensive and rigorous modelling framework used to describe the detailed batch process operations as a preliminary step towards their optimization. The methodology will be presented and results from case studies will be provided to illustrate the complex interaction between energy integration, waste minimization and production planning in multiproduct batch processes.

Methods for estimating volatile organic compound emissions from batch processing facilities

As emphasis changes away from end-of-pipe control technologies to cleaner production technologies, industrial processors seeking to identify and prioritize process changes need first to identify significant sources of waste, both in the form of air emissions as well as in energy and solid waste production. To this end, this paper presents a summary of methods of quantifying and characterizing air pollutants, specifically volatile organic compounds, from batch processing operations as well as from ancillary equipment such as storage tanks, leaking piping components, and wastewater treatment processes. In addition to presenting the basis for the methodologies, some discussion of the degree of confidence that should be imparted on the obtained values is provided.

Recipe Initialization for a Batch Process

Model-based techniques appear to have found few, if any, application in batch-wise industry. The presented approach for the operation of batch processes, supported by the FRIS package, offers a systematic and fast way to develop, improve and adapt recipes and therefore, to increase the profit. In this paper the adaptation of a recipe on the basis of the deviations in the initial process conditions or changes in maiket situation is described. This kind of adaptation, called recipe initialization, is used for the feed-forward control of a batch process. This technique and its quantitative effects will be illustrated by a pilot plant production of epoxide resins.