GOALI: Principle-Based Knowledge Management System for Cellular Manufacturing

Northwestern University, Evanston IL

Investigators

Abstract

This research project has two thrusts. First, the research aims to develop a set of benchmarking and diagnostic modes based on queuing, material flow, and stochastic optimization models for generic manufacturing cells. These will be used to evaluate the current performance of a system relative to both external (industry) and internal (theoretical) standards. Second, the research will use models to classify improvement areas into broad categories and use these to develop a fundamentally new framework for organizing experiential information related to the design and improvement of cellular production systems. The ultimate goal is to create a prototype web-based knowledge management tool that will diagnose problems, suggest improvement options, and accumulate and classify information for future shared use by the organization. In theory, modern information technology makes it possible to place information previously available only to experts in the hands of users throughout the firm. But converting data to useful information presumes an ability to capture, organize, and link knowledge to the practical concerns of decision-makers. Evolving methods of artificial intelligence provide exciting new ways to search and retrieve text-based information, based largely on matching documents to user interests on the basis of keywords. However, such an approach is not entirely suited to many production environments because users do not necessarily know what keywords they should be interested in to find help with their problems. What is needed is a more proactive system for diagnosing problems and leading users to relevant information. The need for knowledge creation and sharing systems is becoming even more crucial as manufacturing systems emphasize highly customized products and quick response to customer demands. Agile manufacturing relies on production in small scale, often modular, flexible manufacturing cells that use multi-functional machinery and cross-trained workers. While there has been some recent modeling research into the design and control of agile manufacturing systems, almost nothing has been done on linking models to the information needs of managers trying to evaluate and improve their systems. This research will develop models of cellular systems and use them to establish a framework for organizing information in a knowledge management system to support the process of continual improvement in agile manufacturing systems