Using Simulation for Scheduling and Rescheduling of Batch Processes

Girish Joglekar

doi:10.3390/pr5040066

Abstract

The problem of scheduling multiproduct and multipurpose batch processes has been studied for more than 30 years using math programming and heuristics. In most formulations, the manufacturing recipes are represented by simplified models using state task network (STN) or resource task network (RTN), transfers of materials are assumed to be instantaneous, constraints due to shared utilities are often ignored, and scheduling horizons are kept small due to the limits on the problem size that can be handled by the solvers. These limitations often result in schedules that are not actionable. A simulation model, on the other hand, can represent a manufacturing recipe to the smallest level of detail. In addition, a simulator can provide a variety of built-in capabilities that model the assignment decisions, coordination logic and plant operation rules. The simulation based schedules are more realistic, verifiable, easy to adapt for changing plant conditions and can be generated in a short period of time. An easy-to-use simulator based framework can be developed to support scheduling decisions made by operations personnel. In this paper, first the complexities of batch recipes and operations are discussed, followed by examples of using the BATCHES simulator for off-line scheduling studies and for day-to-day scheduling.

Highlights

The problem of scheduling multiproduct and multipurpose batch processes has been studied extensively over the past 30 years [1]
The underlying recipes are modeled using either a State-task network (STN) or resource-task network (RTN), and a mixed integer linear programming (MILP) formulation based on discrete time or continuous time representation is used for solving the optimization problem
This paper demonstrates a simulation based methodology, which incorporates allbased the complexities batch processes described above, for generating schedules which incorporates all the complexities of batch processes described above, for generating schedules that are very realistic or ‘actionable’, and verifiable

Summary

Introduction

The problem of scheduling multiproduct and multipurpose batch processes has been studied extensively over the past 30 years [1]. In some problems where orders can be treated as individual batches, each order moves through various production stages as a discrete entity, and a sequential MIP formulation with order-indexed decision variables for assignments to equipment units and precedence decisions are used to solve the problem. In both the approaches, the manufacturing recipes are greatly simplified in order to keep the problem size to a manageable level so that it can be solved in a reasonable amount of time

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