Human Performance in Planning and Scheduling

By Bart MacCarthy; John Wilson | Go to book overview

CHAPTER EIGHT

Decision Support for Production Scheduling Tasks in Shops with Much Uncertainty and Little Autonomous Flexibility

Kenneth N. McKay and Vincent C.S. Wiers


8.1

INTRODUCTION

Computerized decision support systems have been advocated as useful tools for schedulers to use and there have been many systems developed (e.g., Hess, 1995; Melnyk, 1995; Friscia, 1997; Weil, 1997). Unfortunately, the number of shops using such tools is relatively meager and there has not been widespread implementation and sustained use (Wiers 1997a).

For a scheduling tool to be successfully used it should match the type of scheduling the scheduler does. If the tool does not support the scheduler's decision-making, the scheduler will be forced to revert to past behavior and thereby ignore any automatically-generated plans. In any scheduling situation, the decision support system must: i) support an appropriate model of the manufacturing system, ii) present the scheduler with an adequate representation of the supply and demand problem, iii) provide the automatic or manual functions with which to generate a schedule/plan, and iv) give the user tools to help evaluate the quality of the result. The specific nature of these requirements will depend on the scheduling task.

In this paper, we will firstly review types of scheduling situation: the smooth, social, sociotechnical and stress shops. Subsequently, we will discuss the requirements associated with what we consider to be the most demanding situation: reactive scheduling in a stress shop. A system designed for reactive scheduling will be used to illustrate the design issues inherent in such a problem. We will conclude with recommendations for further research into reactive scheduling support systems.

The paper is structured as follows: Section 8.2 explains a typology of scheduling situations based on characteristics of shops. Section 8.3 presents a cognitive model of information processing that will be used to categorize human decision behavior. In Section 8.4, a case study is presented where a decision support system is implemented for a specific type of shop. Section 8.5 gives the conclusions and outlines areas for future research.

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