A Model for Comparison of Job Sequencing Techniques and Generation of an Alternate Route Path

Abstract

Planning and scheduling are two key tasks to run a manufacturing system at the optimal level of productivity. In a practical industrial environment, a manufacturing system typically has different batches of jobs to manufacture using a given number of machines, which are flexible in performing operations but have certain constraints. With the sequence and time of operations known, the real challenge is to find the most suitable planning and scheduling approach for the given case. Furthermore, any machine failure during the production of a job batch poses an additional challenge of resorting to the most suitable alternative route. This study addresses these two challenges by presenting a dual-function model. The first part of the model, called the Job Sequencing and Scheduling Model (JSSM), is designed to compare the different job sequencing approaches to find out which approach is most suitable for the required application. The second part of the model, called the Alternating Route Path Model (ARPM), suggests the most suitable alternate route path for completing the job in case of a machine failure. Hamiltonian path is used in the design of ARPM. Both Computer-Aided Process Planning (CAPP) models are designed using MatLab® programming code. The function of the presented models is demonstrated using a valid dataset.