Intelligently helping the human planner in industrial process planning

Author:

Famili A.,Turney P.

Abstract

The function of a process planning system is to determine the methods by which a product is to be manufactured economically and competitively. In a modern manufacturing environment, a process planning system consists of highly trained people and complex software. The plans prepared by a process planning system are not always executed as planned. It is useful if the system can discover why plans fail, when they do fail. In order to learn why plans fail, the system must analyse a number of plans, both successful and unsuccessful, to find patterns in the failures of plans. This type of analysis is difficult for people, who are much better at analysing single events than multiple events.The aim of the project described here is to design and implement a computer program which will help human planners in a process planning system to understand why plans fail. To achieve this aim, a program called IMAFO (Intelligent MAnufacturing FOreman) has been developed. IMAFO uses decision tree induction to analyse examples of both successful and unsuccessful plans.The difficulties presented by this application are discussed and solutions are presented. Problems addressed include finding an appropriate set of attributes for describing the plans, using data efficiently, consolidating input from distinct sources, and presenting decision trees in an understandable form. Potential applications and directions for future research are considered.

Publisher

Cambridge University Press (CUP)

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. On plexus representation of dissimilarities;Community Ecology;2000-07

2. Comparative performance of rule quality measures in an induction system;Applied Intelligence;1997

3. Development of a knowledge-driven constructive induction mechanism;Advances in Intelligent Data Analysis Reasoning about Data;1997

4. Annotated bibliography on computer-aided process planning;The International Journal of Advanced Manufacturing Technology;1996-09

5. Technical note: Bias and the quantification of stability;Machine Learning;1995

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