Integrated dynamic cell formation with operator assignment and inter-cell layout problems: A mathematical model

Sadeghi, Saeed; Forghani, Mohammad Ali; Seidi, Masoud

doi:10.1177/0954405415604314

Cited by 9 publications

(10 citation statements)

References 22 publications

(22 reference statements)

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“…To solve the problem, a hybrid genetic algorithm augmented ε -constraint method was proposed. Learning effect and flexibility of workers were discussed by Sadeghi et al 34 where a nonlinear mathematical model was proposed to solve the dynamic CF problem. Inter-/intracellular movements, machine relocation cost and worker-related costs such as hiring/firing/training were considered in the model.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Another symmetric solution may occur when the number of parts assigned to the cells is equal as in example 2 in Table 1. In this case, constraint (34) does not help to prevent the symmetry since the part numbers are already equal. For a situation like this, constraint (35) ranks the number of machine assignments to the cells in the descending order to prevent the formation of identical solutions such as in example 2.…”

Section: Symmetry Breaking Constraintsmentioning

confidence: 99%

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Manufacturing cell formation with flexible processing capabilities and worker assignment: Comparison of constraint programming and integer programming approaches

Baykasoğlu

Topaloğlu

Şenyüzlüler

2017

Proceedings of the Institution of Mechanical Engineers, Part B:

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Cell formation deals with grouping of machines and parts in manufacturing systems according to their compatibility. Manufacturing processes are surrounded with an abundance of complex constraints which should be considered carefully and represented clearly for obtaining high efficiency and productivity. Constraint programming is a new approach to combinatorial optimization and provides a rich language to represent complex constraints easily. However, the cell formation problems are well suited to be solved by constraint programming approach since the problem has many constraints such as part-machine requirements, availabilities in the system in terms of capacity, machine and worker abilities. In this study, the cell formation problem is modeled using machine, part processing and worker flexibilities via resource element–based representation. Resource elements define the processing requirements of parts and processing capabilities of machines and workers, which are resource-independent capability units. A total of 12 case problems are generated, and different search phases of constraint programming are defined for the solution procedure. The cell formation problem is modeled in both constraint programming and integer programming, and a comparative analysis of constraint programming and integer programming model solutions is done. The results indicate that both the models are effective and efficient in the solution of the cell formation problem.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Symmetry Breaking Constraintsmentioning

confidence: 99%

Manufacturing cell formation with flexible processing capabilities and worker assignment: Comparison of constraint programming and integer programming approaches

Baykasoğlu

Topaloğlu

Şenyüzlüler

2017

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…The design of a CM usually starts with the CF and then follows by the Facility Layout (FL) and scheduling. 8 The majority of the studies conducted on the CM design have only focused on one of these decisions; examples of studies in this relation can be found. 9–17 However, it should be noted that these decisions are highly inter-dependent.…”

Section: Introductionmentioning

confidence: 99%

Concurrent scheduling and layout of virtual manufacturing cells considering assembly aspects

Forghani

Ghomi

Kia

2020

Proceedings of the Institution of Mechanical Engineers, Part B:

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Cell formation, scheduling, and facility layout are three main decisions in designing manufacturing cells. In this paper, we address the integration of these decisions in virtual manufacturing cells considering assembly aspects and process routing. We develop a mathematical model to determine the machine cells, the layout of machines and workstations on the shop floor, the processing route of parts, and the production sequence of operations on the machines. In this mathematical model, material handling costs and cycle time are minimized. To the best of our knowledge, this is the first paper that concurrently addresses the scheduling and layout of virtual manufacturing cells with assembly aspects and so-called criteria. To effectively solve the problem, a Population-based Simulated Annealing (PSA) combined with linear programming is proposed. The practical usability of the developed model is demonstrated in a case study. Finally, instances from the literature are solved to evaluate the performance of the PSA. The comparison results showed the superior performance of the PSA in comparison with CPLEX solver and standard simulated annealing.

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“…The robustness and performance of the mathematical model are explained in terms of an industrial case from a typical equipment manufacturer. Sadeghi et al 56 minimized machine relocation cost, inter-intra cell part movements as well as firing, hiring, training and salary costs using a proposed mathematical model. Their model considered operator assignment, cell formation and inter-cell layout problems, simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Integrating multi-dynamic virtual cellular manufacturing systems into multi-market allocation and production planning

Aalaei

Kayvanfar

Davoudpour

2017

Proceedings of the Institution of Mechanical Engineers, Part B:

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This article presents a two-stage approach to solve a multi-dynamic virtual cellular manufacturing system in multi-market allocation and production planning. The first stage identifies the plant locations and grouping parts–machines–workers’ assignment to virtual cells, while the second stage determines the production volume for each plant, the allocated amounts to each market and the operations’ allocation to the virtual cells. The goal of the proposed mathematical model is to minimize total expected cost consisting of holding, outsourcing, inter-cell material handling, external transportation, fixed cost for producing each part in each plant as well as machine and labour salaries. It is assumed that the parts’ processing times on each machine with workers as well as the products’ demands are stochastic and described by discrete scenario enrichment using the sample average approximation and Latin hypercube sampling techniques. To solve such a stochastic model, an efficient method based on the genetic algorithm is then utilized. Also, Taguchi method is employed so as to evaluate the effects of different operators and parameters on the performance of genetic algorithm. Finally, computational experiments on randomly generated test problems are presented to demonstrate the performance and power of developed model in handling uncertainty.

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Integrated dynamic cell formation with operator assignment and inter-cell layout problems: A mathematical model

Cited by 9 publications

References 22 publications

Manufacturing cell formation with flexible processing capabilities and worker assignment: Comparison of constraint programming and integer programming approaches

Manufacturing cell formation with flexible processing capabilities and worker assignment: Comparison of constraint programming and integer programming approaches

Concurrent scheduling and layout of virtual manufacturing cells considering assembly aspects

Integrating multi-dynamic virtual cellular manufacturing systems into multi-market allocation and production planning

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