A Cost-Based Methodology for Stochastic Line Balancing with Intermittent Line Stoppages

Abstract

This paper examines the effect of stochastic task times on the total operating costs of a continuously paced assembly line under the assumption that the line is stopped whenever at least one work station requires more time than allotted. A comprehensive stochastic cost function is integrated into an efficient balancing algorithm to enable an approximately minimum cost balance to be obtained. An experiment was conducted to determine the cost savings resulting from using the stochastic method as compared to two deterministic methods. The stochastic method of this paper produced lower cost balances in most cases studied.production/scheduling: line balancing, facilities/equipment planning: design, costing

Second order conic approximation for disassembly line design with joint probabilistic constraints

“…Task times were assumed to be random variables with either known continuous probability distributions (Zhao, Liu, Ohno, & Kotani, 2007), or known or unknown symmetric probability distributions (Betts & Mahmoud, 1989;Raouf & Tsui, 1982), or known independent normal probability distributions. This third case has received quite some attention: earlier papers have focused on optimizing straight assembly lines where heuristic (Carter & Silverman, 1984;Chakravarty & Shtub, 1986;Fazlollahtabar, Hajmohammadi, & Es'haghzadeh, 2011;Kao, 1979;Lyu, 1997;Shin, 1990;Silverman & Carter, 1986), metaheuristic (Cakir, Altiparmak, & Dengiz, 2011;Erel, Sabuncuoglu, & Sekerci, 2005) and exact solution methods (Henig, 1986;Kao, 1976;Sarin, Erel, & Dar-el, 1999) were proposed. The case of ALBP with station paralleling was studied in (McMullen & Frazier, 1997).…”

Stochastic assembly line balancing using beam search

“…We take standard deterministic test problems from the literature: means of the task times are taken as the deterministic task times of these problems whereas the standard deviation of the task times are generated by multiplying the means by a coefficient of variation (CV) term. Silverman and Carter (1986) have used 0.1 and 0.25 for low and high CV values, respectively. We also use these two levels to set the standard deviations of the task times.…”

“…Assuming that the on-line labour rate is unity, the off-line completion rate can be taken as a multiple of the mean task time. Silverman and Carter (1986) use the levels of 1.5, 5, and 10 for low, medium, and high off-line rates, respectively. Note that a rate of 1.5 implies that the off-line completion cost is 50% higher than the on-line completion cost.…”

A multi-objective method for solving assembly line balancing problem

“…There are also several heuristics (Shin, 1990) and metaheuristics to solve this type problem including genetic algorithm (Rubinovitz & Levitin, 1995;Kim et al, 1996;Levitin et al, 2006;Tasan, & Tunali, 2008), Simulated annealing (Simaria & Vilarinho, 2001;Özcan, 2010;Seyed-Alagheband et al, 2011), tabu search (Lapierre et al, 2006), Ant Colony (Chica et al, 2011;McMullen & Tarasewich, 2003), differential evolution algorithm (Nourmohammadi & Zandieh, 2011;Zhang et al, 2016), There are also different techniques to tackle uncertainty associated with parameters in SALB (Reeve & Thomas, 1973;Andres et al, 2008;Silverman & Carter, 1986). Moreover, a class of SALB problem can be analyzed using simulation methods (Driscolla & Abdel-Shafi, 1985).…”