Jae Hak Jung

Completion times and optimal scheduling for serial multi-product processes with transfer and set-up times in zero-wait policy

Abstract Calculation of completion times and optimal scheduling for serial multi-product, multi-unit problems have been studied for the different types of intermediate storage options. In this study, a set of simple recurrence relations for serial multi-product multi-batch processes in ZW policy is suggested, which calculates completion times with or without non-zero transfer times and non-zero sequence dependent set-up times of the last unit ( j = M ) for each product ( i = 1, 2, … N ). An algorithm is also proposed which calculates completion times of each unit ( j = 1, 2, …, M - 1) for a given product i , not recursively but independently in ZW policy. For the case of zero transfer times and zero sequence dependent set-up times, a mixed-integer linear programming (MILP) formulation is developed, and for the case of non-zero transfer times and non-zero sequence dependent set-up times, a mixed-integer nonlinear programming (MINLP) formulation is developed for optimal scheduling in ZW policy using newly proposed algorithm which calculates completion times of each product at each stage.

Intelligent scheduling and monitoring for multi-product networked batch processes

Abstract In this paper, we suggest a scheduling and on-line reactive rescheduling mechanism for networked batch processes that are the frequently appeared batch process type in chemical industry. In addition, an on-line process monitoring mechanism is also considered. We analyze the properties of the networked batch processes with suggestion of a rule-based completion time algorithm for a given processing sequence and production paths. We have studied on finding the initial optimized scheduling with almost satisfying the considered objective function by genetic algorithm. The used objective function in this problem is the minimization of the earliness and tardiness penalty cost function. The constructed reactive rescheduling mechanism is activated when the process deviate from the initial schedule. The deviation of the process is caught out by the monitoring system. The rescheduler modifies the processing times for the remaining batches after the deviation to minimize the effect of the deviation.

Completion times algorithm of multi-product batch processes for common intermediate storage policy (CIS) with nonzero transfer and set-up times

Abstract Common intermediate storage policy (CIS) is suggested for flexible use of various intermediate storage policies. CIS can accomplish the complete flexible intermediate storage operations to satisfy more frequent changes of ordered item sets by customers. In this paper, two kinds of CIS system are discussed. One is a conventional pipe-valve, pump intermediate storage system and the other is a pipeless scheme of intermediate storage system. A completion time algorithm of the CIS system is also developed with two steps and it is applicable to both kinds of CIS systems. At the first step, we suggest a simplified CIS operation to make the problem easier, and in the second step we proposed the complete CIS operation as a complete flexible intermediate storage policy by inserting the ZW block in the simplified CIS operation system. Finally, we develop the completion time algorithm for the CIS policies with nonzero transfer, set-up times.

A HYBRID SYSTEM OF HEURISTICS AND SIMULATED ANNEALING FOR LARGE SIZE SCHEDULING PROBLEMS OF BATCH PROCESSES WITH PIPELESS INTERMEDIATE STORAGE

This paper describes a new scheduling solution for large number multi-product batch processes with complex intermediate storage system. Recently many batch chemical industries have turned their attention to a more efficient system known as a pipeless batch system. But existing plants need to change their systems to pipeless systems, piece by piece. In this case, current systems are changed to pipeless systems by way of non critical process operations such as through the use of intermediate storage. We have taken the conventional batch plant with a pipeless storage system as an objective process. Although the operation of a pipeless storage system becomes more complex, its efficiency is very high. With this system, all of the storage should be commonly used by any batch unit. For this reason, solving the optimal scheduling problem of this system with a mathematical method is very difficult. Despite the attempts of many previous researches, there has been no contribution which solves the scheduling of intermediate storage for complex batch processes. In this paper, we have developed a hybrid system of heuristics and Simulated Annealing (SA) for large multi-product processes using a pipeless storage system. The results of this study show that the performance and computational time of this method are superior to that of SA and Rapid Access Extensive Search (RAES) methods.

An evolutionary approach to optimal synthesis of multiproduct batch plant

Abstract In case of adding new equipment in parallel to the synthesized batch processes, there are two operating modes for the added equipment. One is “out-of-phase (in-sequence)” mode and the other is “in-phase” mode. However, previous approaches in solving the synthesis problem as a MINLP (Mixed Integer NonLinear Programming) problem so far have considered only the out-of-phase mode. In this paper, using MINLP, heuristics and NLP (nonlinear programming) formulation, we deal with the problems where the in-phase mode is also considered. The effectiveness of this approach is verified by solving three literature problems.

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

Abstract 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.

A Tuning of the Nonlinear PI Controller and Its Experimental Application

Many industrial chemical process control systems consist of conventional PID and nonlinear controllers, even though many advanced control strategies have been proposed. In addition, nonlinear control methods are widely used even for linear processes to achieve better control performance compared with linear PID controllers. However, there are few tuning methods for these nonlinear controllers. In this work, we suggest new controller tuning methods for the error square type of nonlinear PI controller. These control methods can be applied to a large number of linear and nonlinear processes without changing control structures. We also propose new tuning rules for integrating processes. In addition, we suggest application guidelines for performing the proposed tuning rules at the pilot scale multistage level control system. Finally, in this work we confirmed good control performances of the proposed tuning methods through both simulation studies and experimental studies.

Periodical replanning with hierarchical repairing for the optimal operation of a utility plant

The integration methodology of periodical replanning and hierarchical repairing is proposed to handle the prediction errors of energy demands in the multiperiod operational planning. The periodical replanning is implemented by the decomposition method. The hierarchical repairing is triggered during the execution interval when prediction errors in energy demands exist. The hierarchical repairing uses the heuristic knowledge. The efficiency indices for utility pumps are introduced to determine the optimal configuration of motors and turbines for running utility pumps without integer programming. Case studies show that the proposed method is more profitable than the periodical replanning. The operational cost is reduced by 0.9–4.0% compared with the cost by the periodical replanning. r 2002 Elsevier Science Ltd. All rights reserved.