The development of knowledge for maintenance management using simulation

Abstract

The management of maintenance is an area of great concern for any industry that depends on the smooth running of equipment to produce a product or carry out a mission at a profit or at low cost. Manufacturing industries clearly fall into this category, but so do many others. For example, the mission of the strategic air command is to keep the required number of bombers in the air at all times in a costeffective manner. Maintenance management is an important component of Total Productive Maintenance (TPM) (Nakajima, 1988). The principal features of TPM are the pursuits of: economic efficiency or profitability, maintenance prevention, improving maintainability, the use of preventive maintenance, and total participation of all employees. Maintenance managers must have access to advanced information systems to help them plan their work forces and control operating costs more efficiently. This research results in a methodology to develop a knowledge base for a Maintenance Supervisor Assistant System (MSAS). MSAS is to interact with · the maintenance manager on a periodic basis in order to select for the next period of operations the proper policies and techniques to meet management objectives.

Management objectives deal with meeting deadlines, efficient utilization of resources, and rapid response to demands and changes in demands. The first stage of this research is the knowledge acquisition phase. An objectoriented computer simulation model is developed as a testbed for examining different scheduling heuristics and manning policies in a range of maintenance environments. Knowledge for an expert maintenance supervisor is acquired from studying the simulation experiments. The dimensions of the maintenance environment which are considered include: preventive maintenance policies, staffing policies, downtime costs, simultaneous downtime practices, travel time impacts, and backlog policies. The dependent variables of interest include: overall machine availability, critical machine availability, worker utilization, cost of the maintenance function, and work order completion time. The second stage of the research is a knowledge engineering effort to codify what is learned from the stage one simulation experiments into a knowledge base for a Maintenance Supervisor Assistant System (MSAS). A methodology for deriving expert system rules from simulation experiments is demonstrated. This is followed by validation of the knowledge base through re-employment of the simulation model. In addition to the declarative rules which are developed, considerable procedural knowledge is a product of this study.

Notes

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Graduation Date

1992

Semester

Summer

Advisor

Rogers, Ralph

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering

Department

Industrial Engineering and Management Systems

Format

PDF

Pages

272 p.

Language

English

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Identifier

DP0029749

Subjects

Dissertations, Academic -- Engineering; Engineering -- Dissertations, Academic

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