Machine loading in a flexible manufacturing system

Abstract

The following project thesis addresses a vital pre-release decision that directly affects the operational effectiveness of a flexible manufacturing system- the machine-loading problem. Flexible manufacturing is a concept that allows manufacturing systems to be built under high customized production requirements. Issues such as cutting down of inventories and shortened product life cycles, reducing the cost of products and services to grab more market shares, etc have made it almost compulsory for many companies to switch over to flexible manufacturing systems (FMSs) as a viable means to accomplish the above goals while producing consistently good quality and cost effective products. The combinatorial and NP-hard nature of this problem makes it arduous to secure the best solutions. The objectives are minimization of the system unbalance and maximization of throughput, whereas the system’s technological constraints are determined by the availability of machining time and tool slots. Due to the large number of random sequences generated as the number of jobs increase, an eliminator function displays and computes the system unbalance and throughput only for a fixed number of sequences, thus improving the quality of the solution and reducing the computational burden. The proposed algorithm is tested on three problems sourced from literatures and shows promising results and optimal solutions.