Modified NEH Algorithm for Multi-Objective Sequencing in Mixed-Model Assembly Lines

Abstract

Assembly lines are usually used for the mass production. The dawn of mass customization has forced the industries to shift to MMAL (Mixed-Model Assembly Lines). ALBP (Assembly Line Balancing Problem) and MSP (Model Sequencing Problem) are two major problems in MMAL. Sequencing of models is an important aspect of MMAL because improper sequencing can lead to the production loses. This paper dealt with the MSP in MMAL. A modified INEH (Intelligent Nawaz, Enscore, and Ham) algorithm was developed to solve multi-objective MSP. For this purpose, a MCDM (Multi-Criteria Decision Making) techniquewas integrated with NEH. A mathematical model was presented for three performance measures; Idle time, Make-span and Flow Time. A case study of pumps assembly line was conducted. Proposed INEH simultaneously optimized all performance measures (Flow Time= 123.47min, Make-Span= 156.95min and Idle Time=1.67 min) while the traditional NEH variants only optimized single performance measure and ignoring the others. Performance of the proposed algorithm was compared with traditional NEH algorithm and its variants using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), a MCDM technique. Results showed that proposed INEH outperformed rest of the NEH algorithms as TOPSIS ranked INEH first with the relative closeness of 97.3% while the NEH variant for flow time is worse algorithm with the relative closeness of 2.8%.