On the Relative Performance of Functional and Cellular Layouts‐ an Analysis of the Model‐based Comparative Studies Literature

Abstract

Paralleling the increased interest in cellular manufacturing in recent years, a large number of studies have emerged that focus on the relative performance of cell systems and the functionally organized systems they replace. This paper is an analysis of studies that use model‐based, controlled experimentation to seek answers to the questions of if, when, and why cellular layouts outperform their functional counterparts. Twenty‐four model‐based studies are analyzed with respect to their definitions of cellular versus functional layouts, the experimental factors that have been investigated, the results concerning relative performance, and the findings' relevance to layout choice. We conclude that although the comparative studies have been very valuable in their efforts at identifying the factors that embody the essence of cells and shape performance improvements, most of the basic findings are known from past research. Furthermore, the studies' findings cannot assist practitioners in making specific choices between existing layouts and alternative cell systems. However, the totality of the findings reinforce our knowledge of how work systems in general can be designed and organized to reduce throughput time, and can also be used to identify environments and conditions for which conversions to cells may have more or less potential.

Εφαρμογές Εννοιών Λιτής Παραγωγής Σε Περιβάλλον Υπηρεσιών

“…The performance improvement of the cellular structure is attributed to a number of factors: a) the reduced need for setups (66% probability to perform setups in the functional structure versus 44% in the cellular); b) the eliminated hand-off steps (operators able to rework their own errors); c) one reduced decision layer in customer queries (due to the elimination of the investigation team leader role); and finally d) the fact that load is better balanced in the cellular structure. The latter point confirms past evidence from manufacturing regarding the role of bottlenecks in system congestion (Garza and Smunt, 1991;Johnson and Wemmerlöv, 1996;Shambu et al, 1996;Agarwal and Sarkis, 1998;Assad et al, 2003). Indicatively (Figure 5.4), in the functional structure average utilization and queue time are higher in the informationprocessing unit, than in Cells A, B and C. This is attributed to the fact that in the cellular structure more operators are available to execute the Information Processing job, hence workload is better balanced.…”

“…Their behavior is becoming more dysfunctional especially in systems with significant bottlenecks. In line with past evidence in manufacturing (Garza and Smunt, 1991;Johnson and Wemmerlöv, 1996;Shambu et al, 1996;Agarwal and Sarkis, 1998;Assad et al, 2003), our results imply that the adoption of cells should prevent the emergence of bottlenecks and their adverse impact on the behavior of operators. In contrast to past studies though, our results indicate that operators' dysfunctional behavior requires particular consideration in service systems since it can congest a system faster and at a greater extent.…”

“…Regarding demand stability, market-mix changes typically result in workload imbalances, which are more pronounced in the cellular structure. In this structure, resources are dedicated to certain service groups configured to address the nominal demand mix, in contrast to the traditional functional structure in which the load of all service groups is shared by all resources in a department (Garza and Smunt, 1991;Johnson and Wemmerlöv, 1996). To address this challenge, service organizations may need to apply additional practices to overcome the inflexibility of cellular operations in market-mix changes, such as the establishment of floating teams that can pick up extra load, demand management, and the frequent reconfiguration of resource grouping (Pagell and Melnyk, 2004).…”

“…The first condition concerns the initial state of the system, as expressed via key operational parameters (such as utilization, batch size, setup and process time and variability), and the extent that this state may be improved by the cellular transformation to overcome reduced efficiencies stemming from the loss of pooling synergy. The latter is a direct result of assigning to individual cells the resources previously shared in the functional structure, and thus distributing the queue of the latter to several cell queues (Johnson and Wemmerlöv, 1996;Shambu et al, 1996;Agarwal and Sarkis, 1998;Assad et al, 2003). The second condition concerns the dynamics of the demand, i.e.…”

Moving From Job-Shop to Production Cells Without Losing Flexibility: A Case Study From the Wooden Frames Industry

“…Also, this type of layout is difficult to schedule [2]. It is generally considered that moving from a job-shop configuration to a cell configuration brings benefits in productivity and throughput time [3], but also brings disadvantages through loss of flexibility and machine use. In fact, most traditional literature dedicated to operations management states that the job-shop is the most appropriate solution for production that requires a high variety of products [1,4,5].…”