Fuzzy ART/RRR-RSS: a two-phase neural network algorithm for part-machine grouping in cellular manufacturing

Won, Youkyung; Currie, Kenneth R.

doi:10.1080/00207540600635227

Cited by 36 publications

(18 citation statements)

References 40 publications

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“…Many studies only considered limited information, ignoring other important factors, such as operation sequence, machine capacity, and part demand, need to be incorporated to obtain more realistic results [20,21]. Genetic algorithm approach is used by researchers [19,20].…”

Section: Literature Reviewmentioning

confidence: 99%

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Concurrently part-machine groups formation with important production data

Kumar¹,

Jain²

2010

Int. j. simul. model.

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This work presents an algorithm for design of cellular manufacturing system. It considers sequence of operation for every component as ordinal level data. The ratio level data includes operation time per unit, production volume and machine capacity. A matrix model is developed to incorporate ordinal level data and ratio level data. Model is then standardized. From this, Part -Part correlation model is formed. This is undergone through principle component analysis. Now, Feature-Vector and New Standardized Sequence Part Load matrices are formed. These are used for grouping purpose. Part-machine orthographic view is used for concurrent part-machine family formation. Performance of algorithm is comparable and of good quality with existing methods in its class. To facilitate industrial application, it can be implemented by using free software, Scilab and/or commercial softwares.

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Section: Literature Reviewmentioning

confidence: 99%

“…Genetic algorithm approach is used by researchers [19,20]. Fuzzy ART neural network algorithm is also used [17,21]. Among many methods utilized in machine cells formation, the similarity coefficient method is most widely used.…”

Section: Literature Reviewmentioning

confidence: 99%

Concurrently part-machine groups formation with important production data

Kumar¹,

Jain²

2010

Int. j. simul. model.

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“…Among those new manufacturing philosophies, group technology (GT) has been used to reduce throughput and material handling times, to decrease work in progress and finished goods inventories and to increase the ability to handle forecast errors (Won and Currie 2007). Among those new manufacturing philosophies, group technology (GT) has been used to reduce throughput and material handling times, to decrease work in progress and finished goods inventories and to increase the ability to handle forecast errors (Won and Currie 2007).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy ART K-Means Clustering Technique: a hybrid neural network approach to cellularmanufacturing systems

Sengupta

Ghosh

Dan

2011

International Journal of Computer Integrated Manufacturing

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Cellular manufacturing system (CMS) is regarded as an efficient production strategy for batch type of production. Literature suggests, since the last two decades neural network has been intensively used in cell formation while production factor such as operation time is merely considered. This paper presents a new hybrid neural network approach, Fuzzy ART K-Means Clustering Technique (FAKMCT), to solve the part machine grouping problem in CMS considering operation time. The performance of the proposed technique is tested with problems from open literature and the results are compared to the existing clustering models such as simple K-means algorithm and modified ART1 algorithm as found in the recent literature. The results support the better performance of the proposed algorithm. The novelty of this study lies in the simple and efficient methodology to produce quick solutions with least computational efforts.

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“…Well-known methods for single-period cell and part family formation include: hierarchical similarity coefficient-based clustering by authors such as Seifoddini and Djassemi [8]; non-hierarchical clustering methods by Srinivasan and Narendran [9]; and matrix manipulation techniques, such as the modified rank order clustering (MODROC) developed by Chandrasekharan and Rajagopalan [10]. Recently, metaheuristics and artificial intelligence methods have been applied to the single-period GT problem; works include the application of a fuzzy adaptive resonance theory (ART) neural network by Won and Currie [11], and a bacteria foraging optimisation (BFO) algorithm by Nouri and Hong [12].…”

Section: Literature Surveymentioning

confidence: 99%

A Multi-Period Group Technology Method for Dynamic Cellular Manufacturing Systems

Padayachee

Bright

2016

SAJIE

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A dynamic cellular manufacturing system is a system where cell configurations change in order to respond to changing production requirements. This paper proposes methods for multi-period cell and part family formation. The method of fuzzy C-means clustering is used for part family formation while balancing the part load between cells in each period; a genetic algorithm is presented to solve the model. An integer programming model is presented for multi-period cell formation with the objective of determining an optimal trade-off between reconfiguration cost and the cost of deficit capacity. OPSOMMINGŉ Dinamies sellulêre vervaardigingstelsel is ŉ stelsel waarbinne selkonfigurasies verander in reaksie op veranderende produksie vereistes. ŉ Metode van multi-periode sel en onderdeel familie formasie word voorgestel. Die wasige C-gemiddelde groeperingsmetode word gebruik vir onderdeel familie vorming terwyl die onderdeel vereiste tussen die selle in elke periode gebalanseer word. ŉ Genetiese algoritme word gebruik om die model op te los. ŉ Heelgetal programmeringsmodel word voorgehou vir die multiperiode selformasie om die optimale kompromie tussen herkonfigurasie koste en die koste van tekorte in kapasiteit te bereik.

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Fuzzy ART/RRR-RSS: a two-phase neural network algorithm for part-machine grouping in cellular manufacturing

Cited by 36 publications

References 40 publications

Concurrently part-machine groups formation with important production data

Concurrently part-machine groups formation with important production data

Fuzzy ART K-Means Clustering Technique: a hybrid neural network approach to cellularmanufacturing systems

A Multi-Period Group Technology Method for Dynamic Cellular Manufacturing Systems

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