A multi-objective procedure for labour assignments and grouping in capacitated cell formation problems

Slomp, Jannes

doi:10.1080/00207540110072966

Cited by 41 publications

(17 citation statements)

References 54 publications

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“…Dimopoulos (2006), and Yasuda et al (2005) proposed and developed genetic programming algorithms to solve the multi objective cell formation problem. A hierarchical methodology for the design of manufacturing cells was proposed by Suresh and Slomp (2001) which included labour-grouping considerations in addition to part-machine grouping; they developed a multi-objective procedure for considering important labour-related issues to reassign the work force into a cellular structure.…”

Section: Multi Objective Reviewmentioning

confidence: 99%

Radio frequency identification system optimisation models for lifecycle of a durable product

Osman

Ram

Stanfield

et al. 2010

International Journal of Production Research

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We address the implementation of radio frequency identification (RFID) technology to support and manage durable products over their entire lifecycle with a focus on optimising the RFID tagging system. We develop general models that optimise the placement of RFID tags on an end product and its components, the allocation of the data on tags, and the selection of RFID tags and their configuration. The primary criteria for optimisation are to maximise the value of RFID data, and to minimise the total cost of the RFID tag system. The total cost of RFID tags comprises costs associated with memory capacity, tag type, software acquisition and maintenance, and number of tags used; the total value for a piece of data is determined by the data usage frequency and the fixed and variable value of data per use across the product lifecycle. The tag placement and data allocation model involves making a decision about these two different objectives-cost and value, which we develop in the form of a multi-objective optimisation problem. The tag selection model aids in the proper selection of RFID tags and their configuration for individual components for a given end product. Given a durable product's characteristics along with its billof-materials, a system of RFID tags can efficiently be determined for the product and its components, to help manage and support its lifecycle. Keywords: RFID | optimisation | value of information | lifecycle management | maintenanceArticle:

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Section: Multi Objective Reviewmentioning

confidence: 99%

Radio frequency identification system optimisation models for lifecycle of a durable product

Osman

Ram

Stanfield

et al. 2010

International Journal of Production Research

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“…Each type is composed of several machines able to achieve a type of operation. One process plan corresponds to alternative routings (=sequence of machines) (Askin et al, 1997); (Suresh and Slomp, 2001), (Yin and Yasuda, 2002), (Vin and al., 2005).…”

Section: Alternative Routes/processesmentioning

confidence: 99%

“…With time, the problem has evolved with the data complexity. The authors took progressively into account new production parameters such as sequence operation (Gupta, 1993), cost (Choobineh, 1988), alternative process plans (Gupta 1993), part volumes (Logendran and al., 1994) , machine capacity (Sofianopoulou, 1999), labor-related factor (Suresh and Slomp 2001), flexibility (Defersha and Chen, 2006), … Suresh (Suresh and Slomp, 2001) proposes a classification and a review based on the parameters used for a more complex cell formation problem.…”

Section: Introductionmentioning

confidence: 99%

An adapted Genetic Algorithm to solve Generalized Cell Formation

Vin

Francq

Delchambre

2009

IFAC Proceedings Volumes

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This paper addresses the cell formation problem with alternative process plans and machine capacity constraints. Given alternative process plans, machine capacities and quantities of parts to produce, the problem consists in defining preferential process and routing for each part (grouping of operations into machines) optimizing machines grouping into manufacturing cells. The problem can be decomposed in two distinct sub-problems: operations grouping on resources, yielding flows between the machines, and grouping of these latter into independent cells. The objective of the proposed method is to optimize both groupings (operations on machines and machines into cell) minimizing of the inter-cellular moves. To solve simultaneously both grouping interdependent problems, we propose a modified grouping genetic algorithm (SIGGA). In our adapted grouping genetic algorithm, each chromosome is composed of two parts, one part for each problem. According to different application rates, the genetic operators are applied on the first, on the second problem, or on both problems. Finally, the population chromosomes simultaneously evolve in both problems.

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“…Another effort (Suresh and Gerard, 2000) has emphasized the importance of considering workers as a second constraining resource in VCMS environments. Worker assignments into virtual cells require due attention on worker skills and capacities, load distribution, and cross-training needs to sustain cellular operations with adequate levels of worker flexibility (Suresh and Slomp 2001). Among the models developed for worker assignments, heuristics and mathematical formulations take the central role while non-mathematical models such as ANNs are not attempted.…”

Section: Introductionmentioning

confidence: 99%

Artificial neural networks based predictive model for worker assignment into virtual cells

Mural¹,

Puri²,

Prabhakaran³

2010

Int. J. Eng. Sci. Tech

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Virtual cellular manufacturing systems (VCMS) have come into existence, replacing traditional cellular manufacturing systems (CMS), to meet highly dynamic production conditions in terms of demand, processing times, product mix and processing sequence. While cell formation phase of VCMS has been dealt quite voluminously, worker assignments phase has gained momentum recently after researchers started realizing the importance of workers' role during implementation of cell-based manufacturing. In the past, worker assignments have been analyzed with development of various heuristics/mathematical models in order to achieve reduced worker costs, improved productivity and quality, effective utilization of workforce and providing adequate levels of worker flexibility. In this paper, a new approach based on artificial neural networks (ANNs) has been proposed to assign workers into virtual cells since ANNs have the ability to model complex relationships between inputs and outputs and find similar patterns effectively. A framework of multilayered perceptron with feed forward (MLP-FF) neural network has been formulated on worker assignment for VCMS under dual resource constrained (DRC) context and its performance under two cell configurations with different time periods is analyzed. A worker assignment model has been developed and applied with cell formation solutions available in the literature in order to generate simulated datasets that drive the training process of proposed ANN framework.

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A multi-objective procedure for labour assignments and grouping in capacitated cell formation problems

Cited by 41 publications

References 54 publications

Radio frequency identification system optimisation models for lifecycle of a durable product

Radio frequency identification system optimisation models for lifecycle of a durable product

An adapted Genetic Algorithm to solve Generalized Cell Formation

Artificial neural networks based predictive model for worker assignment into virtual cells

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