Determination of a flexibility range for cellular manufacturing systems under product mix variations

Seifoddini, Hamid; Djassemi, Manocher

doi:10.1080/002075497194110

Cited by 21 publications

(4 citation statements)

References 9 publications

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“…It has been shown that the performance advantages of cellular systems with a static design, deteriorates when the part mix or volume changes over different periods (Morris and Tersine, 1990;Seifoddini and Djassemi, 1997). But here the adaptive cellular design can be seen to maintain a superior performance in measures such as average WIP inventory, average MLT, average waiting time of jobs, and production cost, than process layout, even in the dynamic demand environment in which part mix and volume was subjected to significant changes.…”

Section: Conclusion and Scope For Further Workmentioning

confidence: 99%

“…The effect of demand changes has also been a subject of study (Flynn and Jacobs, 1986;Morris and Tersine, 1990;Seifoddini and Djassemi, 1997;Canel et al, 2005;Drolet et al, 2008). It was generally concluded that the performance of cellular systems deteriorate when demand becomes unstable or dynamic (Morris and Tersine, 1990;Seifoddini and Djassemi, 1997).…”

Section: Introductionmentioning

confidence: 99%

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Performance comparison of process and adaptive cellular layouts using simulation

Job

Joseph

Pillai

2011

IJAOM

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Group technology and cellular manufacturing have renovated the method of manufacturing of mid-volume, mid-variety products. Many researchers have compared the performances of cellular manufacturing systems with those systems using process layouts. Such studies have brought out the merits and de-merits of both the systems and have helped in determining the suitable system for a given demand environment. They also give valuable information about the effect of factors like batch size, setup time, demand fluctuations, etc., on the performance of a manufacturing system and help in organising a selected system for better results. Previous studies suggest that the advantages of cellular manufacturing systems diminish in unstable demand. But the performance of adaptive cellular designs, which are suitable for dynamic demands, has not been tested. The best way to analyse the performance of manufacturing systems is by using simulation. This study compares, using simulation, the performance of an adaptive cellular layout with a process layout in dynamic demand. It is found that the adaptive cell design outperforms the process layout in average work-in-process inventory, average manufacturing lead-time and average waiting time of jobs. He has around 20 years of teaching experience and the courses taught includes subjects such as production planning and control, inventory and supply chain management, and group technology and FMS. Also, he has developed several exercises to gain better insight for the students in the area of manufacturing management. He has around 50 publications in international journals and conferences. His research interest includes probabilistic and deterministic modelling of cellular manufacturing systems, and modelling of problems in operations management -material requirement planning, scheduling, facility layout planning, inventory control, supply chain management, lean manufacturing, and manpower planning -annualised hours.

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Section: Conclusion and Scope For Further Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance comparison of process and adaptive cellular layouts using simulation

Job

Joseph

Pillai

2011

IJAOM

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“…Early papers have identified that changes in part demands can alter the relative performance of functional and cellular layouts [24][25][26]. Seifoddini and Djassemi [27] characterized the percentage of product mix change and showed that the cellular layout tends to perform weakly with increasing product mix variations. Djassemi [28] followed a similar characterization of changes for a system with flexible cross-trained operators and obtained a similar observation that the cellular layout tends to be more sensitive to demand changes.…”

Section: Literature Review 21 Comparison Studies Of Functional and Ce...mentioning

confidence: 99%

Simulation-Based Study of the Resilience of Flexible Manufacturing Layouts Subject to Uncertain Demands of Product Variants

Li,

Eshragh,

Ebufegha

2023

Sustainability

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Due to market competition, manufacturers typically produce their products with different customized features, leading to the production of product variants (or a product family). Since the market trend can change swiftly, the demands of individual product variants can be difficult to predict. Two flexible manufacturing layouts are commonly considered: functional and cellular layouts. While the functional layout is more resilient to demand changes due to better resource pooling, the cellular layout can be more productive on some occasions due to better routing efficiency. In this context, the purpose of this paper is to quantify and study the criticality of product variants. The criticality score of a product variant can estimate and rank which product variants can sensitively cause bottlenecks in the functional and cellular layouts. The proposed criticality analysis starts with the estimation of bottleneck machines. Through the dependency information of machines and parts, we can estimate the criticality of product variants. The criticality analysis is demonstrated and examined through a simulation study with a study case involving the production of five furniture products with 16 unique parts using 11 machines. The simulation results show that the productions with more critical product variants tend to deteriorate the completion time of the cellular layout more severely. In practice, manufacturers can use the proposed criticality analysis to evaluate the criticality of product variants and support their facility layout decision. For example, if more demand for critical products is expected, the layout should support more resource pooling (e.g., functional layouts).

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“…Among the clustering algorithms, those based on the similarity coe cient method are more widely accepted by the researchers in the ® eld. The similarity coe cient method provides a quantitative basis for machine-component grouping and is¯exible in incorporating various production data into the machine-component grouping process (Seifoddini andWolfe 1986, Seifoddini andDjassemi 1997). In addition, with the similarity coe cient method, it is possible to identify part-families and form the associated machine cells even when a large number of exceptional parts (parts requiring operations in more than one machine cell) exist.…”

Section: Introductionmentioning

confidence: 99%

Part-family formation for cellular manufacturing: A case study at Harnischfeger

Seifoddini¹,

Tjahjana²

1999

International Journal of Production Research

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In this paper, a procedure for part-family formation in a manufacturing situation with high part variety is discussed, a new similarity coe cient based on batch size is introduced, and a case study at Harnischfeger is reviewed. The component variety at Harnischfeger is in hundred thousands of parts, and poses a problem for the traditional methods of gathering data for machine-part matrices. The development of a procedure for dealing with this problem has been a part of this work as well as a step-by-step re® nement of he ® nal block-diagonal machinepart matrix for adaptation to the speci® c requirements of the manufacturing system at Harnischfeger.

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Determination of a flexibility range for cellular manufacturing systems under product mix variations

Cited by 21 publications

References 9 publications

Performance comparison of process and adaptive cellular layouts using simulation

Performance comparison of process and adaptive cellular layouts using simulation

Simulation-Based Study of the Resilience of Flexible Manufacturing Layouts Subject to Uncertain Demands of Product Variants

Part-family formation for cellular manufacturing: A case study at Harnischfeger

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