Cross-training in a cellular manufacturing environment

Slomp, Jannes; Bokhorst, Jos; Molleman, Eric

doi:10.1016/j.cie.2003.03.004

Cited by 54 publications

(26 citation statements)

References 24 publications

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“…Aksin et al [57] reviewed the literature of cross-training for call center applications. Different from × × [58,59] × × × [60][61][62][63][64] × × [65][66][67][68][69][70][71][72][73][74][75][76][77][78] × × × [79][80][81] × × × × [82] × × × [83][84][85][86][87][88] × × [89][90][91][92][93][94][95][96][97][98][99][100][101][102][103][104][105][106][107] other review papers dedicated to cross-train...…”

Section: Cross-trainingmentioning

confidence: 99%

“…In contrast to pooling, each worker may have a unique subset of skills with proximity. Detailed studies of chaining strategies for cross-training were presented in [53,59,69,76,85,86,89,95]. The chaining strategy is found to be an effective, robust configuration of cross-training if, for example, cross-training is costly, systems are of high variability or uncertainty, and WIP is required to be low.…”

Section: Cost Type Literaturementioning

confidence: 99%

“…A related stream of research uses constrained optimization models to identify an optimal crosstraining configuration. IP is a commonly used model for these investigations (see [58,62,66,77,86,87,89,90,92,93,99,101,106]). In these IP models, the determination of optimal cross-training configurations is formulated with a variety of decision variables.…”

Section: Cost Type Literaturementioning

confidence: 99%

“…A mathematical programming model is often used for this purpose, which minimizes the total cost or maximizes the total profit subject to a set of constraints. The most commonly used model is IP (e.g., [77,80,86,89,92,99,106]). In addition to IP, others have used Goal Programming (GP) (e.g., [91]), Integer Goal Programming (IGP) (e.g., [62]), and MIP (e.g., [67,88,101]).…”

Section: Cost Type Literaturementioning

confidence: 99%

See 3 more Smart Citations

Workforce flexibility in operations management

Qin

Nembhard

Barnes

2015

Surveys in Operations Research and Management Science

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Section: Cross-trainingmentioning

confidence: 99%

Section: Cost Type Literaturementioning

confidence: 99%

Section: Cost Type Literaturementioning

confidence: 99%

Section: Cost Type Literaturementioning

confidence: 99%

See 2 more Smart Citations

Workforce flexibility in operations management

Qin

Nembhard

Barnes

2015

Surveys in Operations Research and Management Science

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“…Cesani and Steudal (2005) studied labor flexibility in CMS, particularly in cell implementations allowing intra-cell operator mobility. Slomp and Molleman (2000), Slomp et al (2005) and Molleman and Slomp (1999) discussed training and cross-training policies and their impact on shop floor performance. Nembhard (2001a, b), Nembhard and Mustafa (2000) and Scott et al (2001) proposed a heuristic approach to assign workers to tasks based on individual learning rates and discussed the correlation between learning and forgetting rates.…”

Section: Introductionmentioning

confidence: 99%

A hybrid genetic algorithm-TOPSIS-computer simulation approach for optimum operator assignment in cellular manufacturing systems

Azadeh

Kor

Hatefi

2011

Journal of the Chinese Institute of Engineers

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This article presents a decision-making approach based on a hybrid genetic algorithm (GA) and a technique for order performance by similarity to ideal solution (TOPSIS) simulation (HGTS) for determining the most efficient number of operators and the efficient measurement of operator assignment in cellular manufacturing systems (CMS). The objective is to determine the labor assignment in a CMS environment with the optimum performance. We use HGTS for getting near optimum ranking of the alternative with best fit to the fitness function. Also, this approach is performed by employing the number of operators, average lead time of demand, average waiting time of demand, number of completed parts, operator utilization, and average machine utilization as attributes. Also, the entropy method is used to determine the weight of attributes. Furthermore, values of attributes are procured by means of computer simulation. The unique feature of this model is demonstration of efficient ranks of alternatives by reducing the distance between neighborhood alternatives. The superiority and advantages of the proposed HGTS are shown through qualitative and qualitative comparisons with TOPSIS, data envelopment analysis (DEA), and principal component analysis (PCA).

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A Human‐Oriented Simulation Approach for Labor Assignment Flexibility in Changeover Processes of Manufacturing Cells

Zhang

Qiu

Zhao

et al. 2014

Hum Ftrs & Erg Mfg Svc

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Skilled operators are the most decisive key factors in manufacturing cells. An optimal assignment of operators is crucial for flexibility and productivity. Although there are many publications dealing with labor assignment problems, different forms of human cooperation on the shop floor and decentralized decision making, which are the main factors for system flexibility, are seldom concerned in existing models. In this article, a human‐oriented methodology to analyze, simulate, and evaluate labor assignment flexibility in changeover processes in manufacturing cells is introduced, which is characterized by an agent‐based approach. First, the problem architecture is presented along with the concepts of labor flexibility. Then, different types of human behavior in the changeover process are modeled. Furthermore, a human–machine interaction model is developed to integrate the human agent models into a generalized discrete event dynamic system (DEDS) process model. In this way, work process dynamics and cooperative behavior can be explicitly modeled and simulated. Third, the model is verified on the basis of a motorcycle engine manufacturing cell, and simulation experiments with different labor assignment schemes are designed and conducted. The simulation results show that assignment strategies incorporating different skill levels and cooperation styles have a significant impact on system performance. The agent‐based approach in conjunction with the human–machine interaction model can be used to analyze and solve a large class of assignment problems in flexible manufacturing systems, especially when human cooperation and collaboration are key factors shaping overall system performance.

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Cross-training in a cellular manufacturing environment

Cited by 54 publications

References 24 publications

Workforce flexibility in operations management

Workforce flexibility in operations management

A hybrid genetic algorithm-TOPSIS-computer simulation approach for optimum operator assignment in cellular manufacturing systems

A Human‐Oriented Simulation Approach for Labor Assignment Flexibility in Changeover Processes of Manufacturing Cells

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