Optimisation of cost efficient robotic assembly line using metaheuristic algorithms

Abstract

Robotic assembly lines (RALs) are utilised due to the flexibility it provides to the overall production system. Industries mainly focus on reducing the operation costs involved. From the literature survey it can be seen that only few research has been reported in the area of cost related optimisation in RALs. This paper focuses on proposing a new model in RALs with the main objective of maximising line efficiency by minimising total assembly line cost. The proposed model can be used production managers to balance a RAL in an efficient manner. Since simple assembly line balancing problem is classified as NP-hard, proposed problem due to additional constraints also falls under the same category. Particle swarm optimisation (PSO) and differential evolution (DE) are applied as the optimisation tool to solve this problem. The performances of this proposed algorithm are tested on a set of reported benchmark problems. From the comparative study, it is found that the proposed DE algorithm obtain better solutions for the majority of the problems tested. [Received: 2 July 2018; Revised: 16 December 2018; Revised: 8 May 2019; Accepted: 2 August 2019]