Differential evolution algorithm for solving RALB problem using cost- and time-based models

J. Mukund Nilakantan,S. Venkataramanaiah,Izabela Nielsen,S. G. Ponnambalam

doi:10.1007/s00170-016-9086-2

Abstract

Assembly process is one of the important aspects in manufacturing industries. Industries are extensively using advanced technologies in assembly lines recently such as robots instead of human labor. Cost associated with human labor such as wages, training, safety, and employee management are eliminated with the help of robots. Investments on assembly lines are cost intensive, and industries continuously need to maximize their utilization. In this paper, a cost-based robotic assembly line balancing (RALB) problem with an objective of minimizing assembly line cost and cycle time is addressed. Moreover, there is no research reported on concurrently optimizing cycle time and assembly line cost for a robotic assembly line system to date. The objective of this paper is to propose models with dual focus on time and cost to minimize the cycle time and total assembly line cost simultaneously. Time-based model with the primary focus to optimize cycle time and the cost-based model with the primary focus to optimize total assembly line cost are developed. Due to NP-hard nature, differential evolution (DE) is the algorithm used to solve the RALB problem. Straight and U-shaped robotic assembly line problems are solved using the proposed algorithm, and the detailed comparisons of the results obtained are presented. While comparing straight and U-shaped RALB problems, assembly line cost and cycle time obtained by U-shaped RALB problems are better than the straight RALB problems. The proposed models have significant managerial implications, and these have been discussed in detail.

Highlights

In a manufacturing sector, assembly process is considered to be one of the most critical tasks.Assembly lines are developed for cost-efficient mass production to make full use of labor and resources available [1]
From the results reported it is concluded that PWWD and Wage Rate Smoothing-Method (WRS) are superior to Positional Weight Method (PW) and Wage Rate Method (WR)
The proposed models are coded in C++ and the performances of Differential evolution (DE) are tested on Intel core i5 processor (2.3 GHz)

Summary

Introduction

Assembly process is considered to be one of the most critical tasks. Lines are developed for cost-efficient mass production to make full use of labor and resources available [1]. Stiff competitive environment requires the industries using assembly lines to produce products at a very low cost without comprising on the quality of the product in a reasonable time. The manufacturers need to speed up the time to market and at the same time to minimize the manufacturing cost [2]. Different set of tasks are to be executed in a set of predefined workstations in a time efficient manner in an assembly line. Lines are to be designed in such a way that tasks are grouped to workstations in an orderly manner so that line efficiency is maximized and this problem of dividing the tasks to the workstation in a balanced manner is classified as assembly line balancing (ALB) problem [3]

Results

Discussion

Conclusion