Balancing mixed-model assembly lines using adjacent cross-training in a demand variation environment

Yang, Caijun; Gao, Jie

doi:10.1016/j.cor.2015.07.007

Cited by 26 publications

(17 citation statements)

References 42 publications

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“…Different product models are manufactured in an arbitrarily mixed sequence (not in batches) in mixed-model ALs (Bukchin et al, 2002). Twenty-five percent of the works were mixedmodel in the reviewed ALRBP publications (Altemeier et al, 2010;Antoine et al, 2014;Fattahi and Samouei, 2016;Grangeon et al, 2011;Ishigaki, 2018;Lai et al, 2015;Oliveira et al, 2012;Yang et al, 2013;Yang and Gao, 2016;Zhang et al, 2016).…”

Section: Type Of Product MIX In the Assembly Linementioning

confidence: 99%

“…In the reviewed papers, worker-dependent task times occur in two studies (Çimen et al, 2022;Fattahi and Samouei, 2016). Moreover, the worker assignment problem was also incorporated in the ALRBP in nine publications (Budak and Chen, 2020;Çimen et al, 2022;Corominas et al, 2008;Fattahi and Samouei, 2016;Karas and Ozcelik, 2021;Michels and Costa, 2021;Sikora et al, 2017;Yang et al, 2013;Yang and Gao, 2016). Corominas et al (2008) tried to minimize the number of temporary (unskilled) workers who should work alongside skilled workers and cannot perform some tasks, leading to worker assignment restrictions.…”

Section: Variability Of Task Timesmentioning

confidence: 99%

“…Fattahi and Samouei (2016) had workers with different skill levels in their study who had different task processing times for each task. Yang and Gao (2016) had workers with different skills who could only perform the tasks in the rebalanced AL, which had previously been assigned to them or their adjacent workstations. Sikora et al (2017) tried to solve traveling worker ALRBP, in which a worker can operate in more than one workstation.…”

Section: Variability Of Task Timesmentioning

confidence: 99%

“…The first column of Table 4 indicates the related references. The second column states the papers whose objective is minimizing the cycle time (Çimen et al, 2022;Fattahi and Samouei, 2016;Girit and Azizo glu, 2021;Hu et al, 2020;Karas and Ozcelik, 2021;Li et al, 2016;Li, 2017;Sancı and Azizo glu, 2017;Sikora et al, 2017;Zhang et al, 2018cZhang et al, , 2018bZhang et al, , 2018aZhang et al, , 2020 Otto and Scholl, 2011;Yang et al, 2013;Yang and Gao, 2016). The fourth column of Table 4 shows the articles whose objective is to maximize the efficiency of the AL.…”

Section: Objective Functionsmentioning

confidence: 99%

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A detailed review and analysis of assembly line rebalancing problems

Çimen

Baykasoğlu²,

Akyol³

2022

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Purpose Various approaches and algorithms have been proposed since the 1950s to solve the assembly line (AL) balancing problem. These methods have established an AL configuration from the beginning. However, a prebalanced AL may have to be rebalanced in real life for many reasons, such as changes in the cycle time, production demand, product features or task operation times. This problem has increasingly attracted the interest of scientists in recent years. This study aims to offer a detailed review of the assembly line rebalancing problems (ALRBPs) to provide a better insight into the theoretical and practical applications of ALRBPs. Design/methodology/approach A structured database search was conducted, and 41 ALRBP papers published between 2005 and 2022 were classified based on the problem structure, objective functions, problem constraints, reasons for rebalancing, solution approaches and type of data used for solution evaluation. Finally, future research directions were identified and recommended. Findings Single model, straight lines with deterministic task times were the most studied type of the ALRBPs. Eighteen percent of the studies solved worker assignment problems together with ALRBP. Product demand and cycle time changes were the leading causes of the rebalancing need. Furthermore, seven future research opportunities were suggested. Originality/value Although there are many review studies on AL balancing problems, to the best of the authors’ knowledge, there have been no attempts to review the studies on ALRBPs.

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Section: Type Of Product MIX In the Assembly Linementioning

confidence: 99%

Section: Variability Of Task Timesmentioning

confidence: 99%

Section: Variability Of Task Timesmentioning

confidence: 99%

Section: Objective Functionsmentioning

confidence: 99%

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A detailed review and analysis of assembly line rebalancing problems

Çimen

Baykasoğlu²,

Akyol³

2022

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“…Sepahi and Jalali Naini (2016) modelled a two-sided assembly line balancing problem considering parallel performance of tasks. A typical twosided assembly line balancing problem (see also Tuncel and Aydin, 2014) with mixedmodel products (see also Kucukkoc and Zhang, 2014;Ramezanian and Ezzatpanah, 2015;Yang and Gao, 2016) was studied by Kucukkoc and Zhang (2016) where they used a flexible agent-based ant colony optimization solution approach. Buyukozkan et al (2016) applied artificial bee colony and tabu search meta-heuristic approaches for a typical two-sided assembly line balancing problem.…”

Section: Introductionmentioning

confidence: 99%

An Effective Hybrid Fuzzy Programming Approach for an Entropy-Based Multi-Objective Assembly Line Balancing Problem

Mahmoodirad¹,

Heydari²,

Niroomand³

2019

Informatica

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In cases where the balance problem of an assembly line with the aim to distribute the work loads among the stations as equal as possible, the concept of entropy function can be used. In this paper, a typical assembly line balancing problem with different objective functions such as entropy-based objective function plus two more objective functions like equipment purchasing cost and worker time-dependent wage is formulated. The non-linear entropy-based objective function is approximated as a linear function using the bounded variable method of linear programming. A new hybrid fuzzy programming approach is proposed to solve the proposed multi-objective formulation efficiently. The extensive computational experiments on some test problems proves the efficiency of the proposed solution approach comparing to the available approaches of the literature.

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ALBP Under Learning Effect and Uncertain Demand

2022

Engineering Applications of Computational Methods

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Balancing mixed-model assembly lines using adjacent cross-training in a demand variation environment

Cited by 26 publications

References 42 publications

A detailed review and analysis of assembly line rebalancing problems

A detailed review and analysis of assembly line rebalancing problems

An Effective Hybrid Fuzzy Programming Approach for an Entropy-Based Multi-Objective Assembly Line Balancing Problem

ALBP Under Learning Effect and Uncertain Demand

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