OPTIMIZATION OF MAINTENANCE, INSPECTION AND PRODUCTION DECISIONS IN INTEGRATED SYSTEMS

Abstract

A model is developed to integrate production planning, preventive maintenance, and process/product quality inspection decisions. The integrated model objective is to minimize the total costs of the three decisions subject to constraints on production availability, preventive maintenance economical limitations, and system reliability constraints. Genetic Algorithms (GAs) are utilized to solve the problem with constraints considered. In this thesis, the integration via the Design of Experiment (DOE) and Search Graph Techniques is developed to find the most significant variables affecting the total cost incurred at specified confidence levels. The treatment of preventive maintenance via DOE is novel and adds wealth to existing studies. Optimization is used twice in this thesis: the first using GAs and the second using MILP formulation and CPLEX software. Two case studies in local industries are presented for validation purposes.