A modified binary bat algorithm for machine loading in flexible manufacturing systems: a case study

Abstract

The machine loading (ML) problem of flexible manufacturing systems (FMS) has been recognised as one of the most important planning problems in the industry. This study aims to minimise the system unbalance by developing and testing a modified binary bat algorithm (MBBA), which satisfies the technological constraints such as the availability of machine time and tool slots. The proposed algorithm, coded in Matlab®, is tested on a case study referring to a major Italian company, which manufactures equipment and plants for the food industry. Two scenarios are evaluated to this end: an AS IS scenario, reflecting the current configuration of the production system, and a TO BE one, in which the MBBA is implemented for improving the system’s performance, by determining a new sequence of jobs, able to minimise the variance of the processing time across the various machines. The application of the MBBA reveals significant improvements in processing time compared to the approach currently used by the company. The results of the TO BE scenario allow deriving useful indications to operations managers, helping them to identify an alternative strategy to enhance the efficiency of the targeted production department.

KEYWORDS:

• Machine loading problem
• flexible manufacturing systems
• modified binary bat algorithm
• system unbalance

Disclosure statement

No potential conflict of interest was reported by the author(s).