CARI – a heuristic approach to machine-part cell formation using correlation analysis and relevance index

Gupta, Neha; Devika, D.; Valarmathi, B.; Sowmiya, N.; Shinde, Apoorv

doi:10.1080/00207543.2014.922709

Cited by 18 publications

(7 citation statements)

References 44 publications

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“…GT algorithms can be used to group similar parts or machines [41,42], meaning that GT provides a method of sorting machines into machine cells and parts into part families [43][44][45][46][47][48][49]. Several algorithms have been developed to solve the component standardization problem, such as heuristics [50][51][52][53][54][55], genetic algorithms [56][57][58][59][60], and closed neighbor algorithms [43,44,61].…”

Section: Gtmentioning

confidence: 99%

Standardizing Components and Rotating Workers Using GT-Based Algorithm—A Case Study

2021

Sustainability

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In both manufacturing and remanufacturing systems, exploiting bulk buying and avoiding delivery delays due to material shortages are crucial. One method that aids in these processes is component standardization. Additionally, company managers seek to reduce labor costs and mitigate the risk of sudden worker resignation or absence due to, for example, reasons associated with the COVID-19 pandemic. The aforementioned problems could be solved using the sorting algorithm proposed in this study. The concept of the proposed algorithm is based on group technology. One numerical example and two case studies are presented to demonstrate the utility of the proposed algorithm. The first example suggested that the performance of the algorithm proposed in this study is superior to another one in the literature. The second one demonstrated that the algorithm in this work achieves component standardization by reducing an initial number of 12 components down to 6. The final case study provides an effective means of grouping workers with similar operational abilities and suggests how to assign new tasks to other skilled workers if a worker resigns suddenly or cannot attend work due to pandemic prevention measures.

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Section: Gtmentioning

confidence: 99%

Standardizing Components and Rotating Workers Using GT-Based Algorithm—A Case Study

2021

Sustainability

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“…Zolfaghari et al [14] carried out a comparative study of effectiveness of GA, SA, and tabu search in cell formation problems and they found that SA is superior to other existing methods. Recently, hybrid heuristics and meta-heuristics are being applied in MPCF problems such as hybrid grouping GA (HGGA) [16], randomized greedy algorithm from scratch by partially (GRASP) [17], hybrid GA (HGA) [18], correlation analysis and relevance index (CARI) [19], hybrid grouping based PSO (HGBPSO) [15]. The methodology of GRASP was first introduced by Feo and Resende [20].…”

Section: Literature Reviewmentioning

confidence: 99%

“…• HGGA-hybrid grouping genetic algorithm [16] • SACF-simulated annealing to cell formation [11] • GLCA-grouping league championship algorithm [26] • HGBPSO-hybrid grouping based PSO [15] • CARI-correlation analysis and relevance index [19] • GRASP-randomized greedy algorithm from scratch by partially [17] TABLE IV shows the grouping efficacies of above mentioned methods and the proposed GA for the all problems. It is seen from the TABLE IV that comparing with the existing algorithms, the proposed GA produces improved or same GC for 16 problems, whereas, it is inferior in solution quality for only 4 problem sets.…”

Section: F Adopted Parametersmentioning

confidence: 99%

Machine-part cell formation for maximum grouping efficacy based on genetic algorithm

Hazarika

Laha

2015

2015 IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (WCI)

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Cellular manufacturing system (CMS) makes use of application of group technology. The objective of cell formation problems (CFP) in CMS is to identify part families and machine cells in order to minimize the intercellular movement and to maximize the machine utilization within a cell. Previous study in CFP generally focused on maximizing grouping efficacy (GC) by minimizing exceptional elements as well as void elements. In this paper, a genetic algorithm heuristic is presented. Computational experiments were carried out with 20 benchmark problem sets. Computational results show that the proposed heuristic has shown to produce solutions in terms of GC that are either better than or competitive with the existing algorithms.

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“…El modelo presentado en [19], busca la conformación de equipos en ambientes educativos y grupos de investigación donde no se requiera un líder y donde una de las premisas es que todos los integrantes de un equipo tengan un conocimiento similar respecto a un recurso o temática. A partir del modelo Machine-Part Cell Formation (MPCF) [56], se hace una extensión con el fin de aplicarlo al ámbito educativo y de investigación. Un algoritmo genético de agrupación es utilizado en la conformación de los equipos.…”

Section: Página 27unclassified

“…Un grupo de tecnología representa una unidad organizacional que se responsabiliza de una familia de productos. El trabajo presentado emplea el modelo denominado Machine-Part Cell Formation (MPCF) [56], donde máquinas y partes son empleadas en un proceso de fabricación. El objetivo es maximizar el uso de las máquinas en las celdas y minimizar el movimiento de las partes entre celdas.…”

Section: Pontificia Universidad Javerianaunclassified

PA1710-5-macet : Make-modelo adaptativo para la conformación de equipos de trabajo

Torres¹

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El modelo adaptativo para la conformación de equipos de trabajo (MAKE), está basado en problemáticas relacionadas con la cohesión, composición, comunicación y el tiempo de conformación. Las competencias, conocimientos, personalidad y roles son las características definidas en MAKE. Se establecieron tres (3) sistemas: conformación, evaluación e incorporación. Se construyó un prototipo funcional como soporte a los sistemas planteados implementando dos (2) algoritmos: distancias y grafos. Se validó el modelo en el ámbito educativo y el sector productivo. El resultado de los procesos de conformación de equipos fue evaluado respecto a los requerimientos de cada organización. Finalmente, se presentan conclusiones y trabajo futuro.

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CARI – a heuristic approach to machine-part cell formation using correlation analysis and relevance index

Cited by 18 publications

References 44 publications

Standardizing Components and Rotating Workers Using GT-Based Algorithm—A Case Study

Standardizing Components and Rotating Workers Using GT-Based Algorithm—A Case Study

Machine-part cell formation for maximum grouping efficacy based on genetic algorithm

PA1710-5-macet : Make-modelo adaptativo para la conformación de equipos de trabajo

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