An integrated model for assembly line re-balancing problem

Belassiria, Imad; Mazouzi, Mohamed; Elfezazi, Saïd; Cherrafi, Anass; ELMaskaoui, Zakaria

doi:10.1080/00207543.2018.1467061

Cited by 23 publications

(15 citation statements)

References 36 publications

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“…Belassiria et al [6] proposed an integrated model for assembly line rebalancing problem (I-ALRP). After the occurrence of a disturbance, tasks have to be reassigned to stations according to a new cycle time that is derived from a new demand pattern.…”

Section: Related Workmentioning

confidence: 99%

A Demand-Driven Model for Reallocating Workers in Assembly Lines

Perez-Wheelock

Yenradee

et al. 2022

IEEE Access

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This paper introduces the demand-driven assembly line rebalancing problem (DDALRP) and proposes a non-linear, multi-objective, combinatorial optimization model to solve it. A DDALRP arises whenever the production output of the assembly line (AL) must be continuously readjusted along a planning horizon in order to satisfy as much as possible a given demand forecast; thus, dealing not with a one-time rebalance, but with a multi-period rebalance, fact that exponentially increases the complexity and combinatorial nature of the problem. Adapting or regulating the production output of the AL to some demand forecast or production plan is a relatively new idea in the assembly line balancing (ALB) / rebalancing (ALR) literature; and we address this problem by reallocating workers to stations, taking into consideration their learning and forgetting (L&F) curves. Our proposed model was solved by implementing a genetic algorithm (GA) in 162 cases (three problem instances under 54 scenarios each), obtaining useful insights about the dynamic of worker reallocation under different scenarios: optimistic, most-likely, pessimistic L&F coefficients; experienced and inexperienced workers; and different demand scenarios.

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Section: Related Workmentioning

confidence: 99%

A Demand-Driven Model for Reallocating Workers in Assembly Lines

Perez-Wheelock

Yenradee

et al. 2022

IEEE Access

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“…A single product model is manufactured in single model ALs (Becker and Scholl, 2006). The AL was considered as single model in 75% of the works in ALRBP literature (Antoine et al, 2016;Belassiria et al, 2018;Celik et al, 2014;Çimen et al, 2022;Corominas et al, 2008;Fattahi and Samouei, 2016;Gamberini et al, 2006Gamberini et al, , 2009Li, 2017;Li and Boucher, 2017;Makssoud et al, 2013Makssoud et al, , 2015Mokhtari and Mozdgir, 2015;Otto and Scholl, 2011;Rahman, 2010;Samadhi and Sumihartati, 2016;Sancı and Azizo glu, 2017;Serin et al, 2019;Sikora et al, 2017;Yılmaz and Erol, 2005;Zha and Yu, 2014;Zhang et al, 2018aZhang et al, , 2018bZhang et al, , 2018c.…”

Section: Type Of Product MIX In the Assembly Linementioning

confidence: 99%

“…The researchers try to assign tasks among workstations as smoothly as possible. In other words, they aim for each worker to work at workstations with nearly identical station times (Belassiria et al, 2018;Çimen et al, 2022;Grangeon et al, 2011;Lai et al, 2015;Makssoud et al, 2013;Mokhtari and Mozdgir, 2015;Zhang et al, 2016). Finally, the last column states whether there is an additional objective.…”

Section: Objective Functionsmentioning

confidence: 99%

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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“…In the simplest way, the production plan is adapted accordingly by reactive scheduling (Herroelen andLeus 2004, 2005;Valledor et al 2018). Further approaches for handling disruption in production planning can be found in Belassiria et al (2018); and Yue et al (2018). But optimisation times must not be too long therefor.…”

Section: Problems and Possible Improvementsmentioning

confidence: 99%

Production planning optimisation for composite aerospace manufacturing

Hueber

Fischer

Schwingshandl

et al. 2018

International Journal of Production Research

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Composite materials proved highly successful for aerospace applications in the last decades, but increased cost pressure forces the composite industry to become more efficient. This requires new manufacturing technologies and optimised processes as raw material costs and labour costs are basically fixed when wanting to keep production on site. Probably the most defining process for aerospace composite production is manual layup of prepreg material with subsequent curing in an autoclave. From production planning view, this combination poses the challenge of transition from discrete layup manufacturing to batch curing processing with the restriction of limited allowed storage time of the prepreg material prior to cure. In this paper, a new approach for production order optimisation at the conjunction of discrete and batch processing is presented. The APOLLO named tool is designed to decrease throughput times, streamline production and increase autoclave utilisation in the composite aerospace industry.

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An integrated model for assembly line re-balancing problem

Cited by 23 publications

References 36 publications

A Demand-Driven Model for Reallocating Workers in Assembly Lines

A Demand-Driven Model for Reallocating Workers in Assembly Lines

A detailed review and analysis of assembly line rebalancing problems

Production planning optimisation for composite aerospace manufacturing

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