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STRATEGIC IMPLICATIONS OF MANUFACTURING CELL FORMATION DESIGN

Investigates the linkage and relationships between specified cell design issues and the firm’s competitive advantage in the marketplace.

Strategic Implications of Manufacturing Cell Formation Design Jiaqin Yang and Richard H. Deane

Integrated Manufacturing Systems, Vol. 5 No. 4/5, 1994, pp. 87-96 © MCB University Press Limited, 0957-6061

Introduction Cellular manufacturing systems (CMS) have been viewed as a “bridge” from conventional manufacturing to computer integrated manufacturing (CIM) and the factory of the future. CMS offers the potential to move from inflexible, repetitive batch, mass production to more flexible small-lot production at reasonable costs. The advantages of CMS have been extensively discussed in the literature[1]. Conversion of the conventional production facility layout into a cellular layout has been attacked through both the adoption of just-in-time (JIT) production principles and through the advanced production technology of flexible manufacturing systems (FMS). Cell formation design is obviously a key issue in CMS design. In general, for a production facility with a given number of machines and part mix to be processed in the facility, there are three specific decisions in cell formation design:

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(1) the number of manufacturing cells to be established; (2) the machines constituting each cell; and (3) the parts assigned to each cell. Significant research has been reported on part group formation principles and part-machine grouping algorithms[2]. Most of these algorithms have been based on either a part-oriented approach, also called “part geometry similarity” (i.e. parts are grouped based on the similarity in shape, size, material, etc.), or a routingoriented approach, also called “part processing similarity” (i.e. parts are grouped based on the similarity of processing routings). There are two important assumptions on which most cell formation algorithms are developed. First, it is presumed that machine set-up time between successive jobs will be eliminated or significantly reduced. Second, a controlled job arrival stream to each manufacturing cell is generally assumed. That is, most reported cell formation algorithms are based on the assumption of a “perfect” production environment where set-up times are eliminated and job arrivals are controlled in a deterministic fashion. However, such a perfect production environment is rarely attained. There are several practical and specific decisions that must be made during the cell formation design process. For example, a choice must be made concerning average cell size (part mix size). That is, managers must choose a design along a continuum between a small number of large cells (i.e. more parts and machines in each cell) vs. a large number of small cells (i.e. less parts and machines in each cell). Another key cell formation design decision involves the choice between a part-oriented approach formation vs. a routing-oriented approach formation. In most reported cell formation research, the strategic impact of these design decisions is either not explicitly considered or totally ignored[3]. Intuitively, these design decisions certainly affect shop manufacturing focus and performance, which will in turn impact the firm’s competitive advantage in the marketplace. Perhaps more questionable is the use of a single, tactical criterion to evaluate cell formation designs. Under the assumption of a “perfect” production environment, explicitly or implicitly, most reported cell formation techniques are designed and evaluated based on a single algorithmic criterion – the number of exceptional parts/machines that cannot be placed in the constructed cells, rather than on the strategic consequences resulting from the designs. Likewise, system performance measures, such as cell flow time, resource utilization, and other criteria directly related to the firm’s strategy are ignored. A cell formation design which generates a minimum number of exceptional parts/machines may not necessarily result in a minimum cell flow time, a maximum resource

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INTEGRATED MANUFACTURING SYSTEMS 5,4/5

utilization, or an enhancement of the firm’s competitive advantage in the marketplace. Finally, several additional factors that have a strong impact on shop manufacturing focus and system performance are also ignored in most of the reported cell formation techniques. These factors include machine capacity constraints, complexity of job routing requirements, demand pattern and volume, and part mix characteristics (i.e. the similarity among part processing times or set-up times, and the size of part mix). Therefore, it is not surprising that many suggested benefits of CMS are not realized after implementation, or the performance of a converted cellular shop is even worse than the original functional job shop layout[4,5]. Recognizing the limitation of existing cell formation design research, this article addresses the relationships between several specific cell formation design decisions and major system performance criteria, which in turn are linked with the firm’s strategic objectives and competitive advantages in the marketplace. From a broader perspective, the issues addressed in this article can be viewed as the important linkage between a firm’s CMS and cell formation design decisions and its ultimate mission – to satisfy dynamic and changing customer requirements in the marketplace. This linkage is accomplished by considering the firm’s competitive advantage and strategic objectives in the CMS and cell formation design process, as depicted in Figure 1. Recent reports indicate that world class firms are simultaneously competing on a variety of competitive dimensions[6]. As such, the narrow manufacturing focus strategy has been challenged by an emerging paradigm that argues that firms can and must compete, simultaneously, on a broad variety of competitive dimensions in order to be successful in today’s complex and constantly changing global marketplace[7]. This new manufacturing focus paradigm brings forward a new and significant challenge for CMS design (and manufacturing system design in general). As shown in Figure 1, manufacturers are facing complex and dynamic customer requirements in terms of product quality, price, customization and delivery. The firm’s critical CMS design decisions (e.g. average cell size and cell construction approach) must be more directly related to the firm’s competitive priorities and long-term strategic objectives (e.g. product and production flexibility, reduced manufacturing lead time, product quality assurance and production cost). Within this article, the next section presents a literature review on cell formation design issues. In the following sections, strategic considerations of three specific cell formation design issues are addressed: part mix characteristics (e.g. part set-up time similarity and part

Figure 1. Linkage between CMS Design Decisions and Customer Requirements Cellular manufacturing systems design decisions

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Cell formation approach (part-oriented versus routeing-oriented) Average part mix size Similarity of part set-up and processing time requirements

Firm's competitive priorities and strategic objectives

Customer requirements

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Cost reduction

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Price leadership

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Product design quality

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High quality

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New product offerings

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Production flexibility

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Fast delivery

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Reliable delivery

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Product customization

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Reduced manufacturing leadtime

processing time similarity); part mix size; and the effects of set-up time reduction. Conclusions and suggestions are summarized in the final section.

Literature Review By recognizing similarities among parts to be processed in the same facility, GT (group technology) principles have provided the basis for converting the conventional job shop into a cellular layout with several manufacturing cells, each with a dedicated part mix. With the advanced technologies of robotics, automated guided vehicles (AGVs), automated storage/retrieval system (AS/RS), and computer-aided design/manufacturing (CAD/CAM), FMS emerged in the 1970s with the advantages of production flow line efficiency as well as the flexibility and technical competence of job shop production. Publications on the development of GT, CMS, and FMS are numerous[8-10]. Applications of GT, CMS, and FMS have been reported worldwide[1,11-15]. The reported benefits from GT and CMS include: cost reduction, decreased production flow time, increased utilization, reduced inventory level, better quality control, and fast response to product change[1]. For example, Meredith[16] reports that on average, the firms (with CMS/FMS) have achieved improvements of 200 per cent in direct labour productivity, an 80 per cent reduction in manufacturing lead time, a 150 per cent improvement in machine utilization, a 60 per cent decrease in inventory level, and a 90 per cent reduction in scrap and defect rate. It is suggested that these improvements contribute to related improvements in innovation rate, production cost, quality assurance, delivery promises, customization and market image. A recent industry survey is provided by Wemmerlov and Hyer[17] about the CMS applications in the US companies. There are also less successful reports, even complaints, concerning below-expectation performances of


CMS[4,18,19]. Such reports have motivated research efforts addressing a variety of issues in the applicability, justification, system design and implementation of CMS[3,20]. Studies on the applicability of CMS are reported by Dale[21], Gerwin[22], Ham and Reed[23] and Willey and Dale[24]. CMS justification issues are addressed in Gold[25], Kaplan[26], Michael and Miller[27], Rosenthal[28] and Tepsic[29]. The implementation of CMS has also attracted broad attention from both industry and academia in terms of human behaviour and organizational sciences[30,31]. In general, there are two categories of CMS design issues reported in the literature: structural issues (e.g. cell formation design), and operational issues (e.g. cell operational procedures and policies)[3]. The structural issues are primarily focused on the cell formation design (i.e. part-machine grouping procedures) along with the selection of tools, fixtures, pallets and material handling equipment. A considerable number of cell formation techniques and algorithms have been developed[32-36]. Most of these algorithms, heuristics or analytical formulations, are based on cluster and matrix analysis. Major CMS operational issues include cell production planning, scheduling and control procedures as well as maintenance and inspection policies. Many reported models and techniques for planning and scheduling in the CMS/FMS environment are reviewed in Burgam[37], Hyer and Wemmerlov[38], Kalkunte et al.[39], Mosier et al.[40], Vaithianathan and McRoberts[41] and Whitney[42]. There are significant issues remaining in the area of CMS and structural cell formation design. Research relating a firm’s strategic objectives and competitive priority considerations to the cell formation design decision has been practically nonexistent. Wei and Gaither[43] do consider intercell capacity imbalance and the cost and distance of intercell shipments in an integer programming cell formation model. Aronson and Klein[44] formulate cell capacity, processing precedence, and the compatibility of part mix into a mathematical programming clustering model. A tactical treatment of these issues is offered rather than a strategic analysis. Finally, several important production factors such as cell capacity constraints, stochastic job arrivals, characteristics of part mix, and the effects of set-up time reduction have been essentially ignored in the cell formation design research, although these factors are certainly present in most production environments and directly impact system performance. Under more realistic assumptions of stochastic job arrivals, analytical queueing models and computer simulation have been used as important tools in the evaluation of the CMS design and system performance. In a series of articles, Karmarker et al.[45-47] model a

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manufacturing cell as a single facility queueing system to investigate the impact of product lot size and set-up time on single machine queueing time behaviour and other related system performance measures. Kekre[48] reports a study examining the impact of changes in part mix size on cell queueing time. As an extension of Karmarker’s earlier work, Zipkin[49] offers a discussion on the effect of batch size on cell batch flow time. Jha[50] presents a study addressing set-up time reduction in the manufacturing cell. Modelling a closed manufacturing cell as an M/G/1 queueing system, Yang and Deane[51] investigate the impact of batch size on manufacturing cell flow time performance for a heterogeneous part mix. Deane and Yang[52] further examine the relationships between the similarity of part set-up and processing time requirements and the improvements in major flow time related performance. Yang and Deane[53] demonstrate that set-up time reduction has a compounding effect on the cell flow time improvement. Computer simulation studies of CMS systems have also been reported. Seidman et al.[54], for example, examine the relationship between the variability of job flow time and part batch size for a manufacturing cell. Carrie[55] offers a comprehensive review on CMS computer simulation studies. In summary, the following issues should be further addressed in the cell formation design literature: (1) Cell formation techniques must be related to a firm’s manufacturing focus, strategic objectives, system performance measures and competitive advantage in the marketplace – not simply the minimum number of exceptional parts/machines generated by a design. (2) CMS design guidelines must be developed to address more practical and realistic,but often very complicated situations, such as stochastic job arrivals and machine set-up times. (3) Specific guidelines to answer the following practical design questions are needed: ● How can other production factors, such as part mix characteristics and the effects of set-up time reduction be incorporated into the cell formation design process? ● What strategic guidelines can be offered to determine when a design incorporating a large number of small cells will be desirable over a design incorporating a small number of large cells considering the firm’s desired manufacturing focus and competitive priorities? ●

Under what conditions would the partoriented design approach be preferable over the routeing-oriented design approach?


Part Mix Characteristics and Competitive Priorities In general, part mix has been shown to have an important impact on a number of cell performance measures. Part set-up time similarity and part processing time similarity are two specific part mix characteristics that have been specifically related to cell performance measures such as cell flow time. In the following discussion, part set-up time similarity and part processing time similarity refer to the variances of part set-up times and part processing times among the part mix. A homogeneous part mix is one in which part set-up times and processing times have a high degree of similarity. Flow time (or cell throughput time) reduction is one of the major objectives for the CMS management. Among three major components of flow time through a manufacturing cell – batch set-up time before processing, batch processing time, and batch waiting time in queue – CMS management must focus efforts on reducing the queueing time within the cell, which will in turn generate reductions in batch flow time and improvement on other flow time related performance measures. As demonstrated in the M/G/1 queueing model for a manufacturing cell, cell queueing time is in general a function of part batch size, part set-up and processing times, and part mix size[51]. Traditionally, manufacturing cells in a CMS are constructed based on a coding scheme of part geometry similarity or part routing similarity. That is, part set-up time similarity and part processing time similarity are normally not considered in cell formation design. However, Deane and Yang[52] demonstrate that for a manufacturing cell that processes a heterogeneous part mix and has a manufacturing focus on reducing production flow time, the cell manager may considerably improve cell flow time and related performance measures by considering part set-up time similarity and part processing time similarity in cell formation design decisions. Specifically, four propositions are developed in Deane and Yang[52] to show that as the part set-up time similarity and part processing time similarity increase: (1) the variance of part batch processing time will decrease; (2) the batch flow time through the cell will decrease; (3) the variance of batch flow time through the cell will decrease; and (4) the optimal part batch sizes that minimize cell flow time will decrease. These relationships are depicted in Figure 2. These results can be explained by the fact that in a manufacturing cell, similar part set-up times and processing times will result in smaller and similar part batch sizes since the variance of part batch sizes is

Figure 2. System Performance vs. Similarity of Part Set-up and Processing Times

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High Similarity of part set-up and processing times

derived from the deviations of part set-up times and processing times. Further, similar part set-up times and processing times plus similar part batch sizes will generate a smaller variation in part batch processing times. Since part queueing times result from the variations in part batch arrival intervals and batch processing times, reduced cell queueing time and flow time are thus a direct consequence of increased part setup time similarity and part processing time similarity. Improvements in cell flow time, the variance of cell flow time, and optimal part batch sizes have a direct impact on the firm’s manufacturing focus and competitive advantage. More specifically, reduced cell flow time will result in improvements in firm’s delivery speed, level of work-in-process inventory, and response to market changes. In addition, a reduction in the variance of cell flow time will improve delivery reliability, stabilize production scheduling and control activities, and reduce the requirements for safety stock inventory. Smaller part batch sizes will result in better control of work flow, faster feedback for quality control, more efficient utilization of tooling and transportation devices, and greater flexibility in production planning and scheduling. As a result, the production environment for JIT manufacturing will be enhanced. A summary of the strategic relationship between these key cell formation design decisions and the firm’s competitive priorities is shown in Figure 3. In practice, it is possible that considerations of part set-up time similarity and part processing time similarity in the


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Figure 3. Part Set-up Time and Processing Time Similarity

The Part Mix/Cell Size Decision

and Competitive Priorities

The literature offers little guidance to the manager attempting to select an appropriate cell size during the cell formation design process. For example, a larger number of smaller cells (e.g. ten cells of four machines each) might be considered by a manager as a cell formation design alternative to a smaller number of larger cells (e.g. five cells of eight machines each). The manager is generally instructed by the literature to evaluate the two competing cell formation designs based on the number of exceptional parts that cannot be processed within each design. However, other factors such as cell capacity constraints, part processing capability, tooling and associated devices, and other engineering considerations, may also be important factors in this trade-off decision. In reality, each of the two hypothetical designs offers different strategic advantages that must be considered in light of a firm’s objectives and competitive priorities.

Competitive priorities (Intermediate consequences)

Part set-up time similarity

Similar batch processing times Reduced variance of batch processing times

Part processing time similarity

Similar product batch sizes

Reduced variance of flow times

Improved delivery reliability Stabilized production flow Reduced safety stock level

Improved queueing and cell flow time performance

Improved delivery speed Fast response to market changes Fast feedback to quality control

Reduced optimal product lotsize

More flexibility in planning Better control of work flow

cell formation design decision may conflict with other cell formation principles such as part geometry similarity or part routing similarity. Considering the firm’s strategic objectives and competitive priorities, this cell formation design conflict may suggest two design alternatives: (1) Incorporating part set-up time similarity and part processing time similarity into the traditional clustering/matrix analysis (or mathematical programming) models along with the part geometry similarity/part routing similarity. In this approach, a key issue involves the appropriate “weighting” of part set-up time similarity and part processing time similarity in comparison with part geometry similarity/part routing similarity (or other design factors such as: intercell capacity, part processing compatibility, etc.). (2) From the results of a traditional clustering/matrix analysis model, adjusting the final cell construction based on part set-up time similarity and part processing time similarity. Ex post facto “trade-offs” would be evaluated when part set-up time similarity and part processing time similarity results in a conflict with other cell formation principles. From a managerial decision-making perspective, it will be methodologically difficult to consider part set-up time similarity and part processing time similarity in the cell formation design. However, as illustrated in this section, such factors must not be ignored because of methodological difficulties. The suggestions above will allow a CMS manager to recognize when part set-up time similarity and part processing time similarity should be further addressed in the cell formation design decision.

The impact of part mix size on single-machine cell performance for a homogeneous product mix (i.e. all parts in the mix have identical set-up and processing time requirements) was originally examined by Kekre[48] and extended for a general heterogeneous product mix (i.e. parts in the mix have different set-up and processing time requirements) by Deane and Yang[52]. Based on a simulation result, Kekre shows that cell queueing time and flow time will increase at a decreasing rate as the size of a homogeneous part mix increases. Kekre explains his results based on the fact that a manufacturing cell with a smaller part mix will result in more “savings” in terms of job set-ups when consecutive batches of arrivals at the cell are of same part type. The reduced number of job setups directly translates into a reduction in cell queueing time and cell flow time and an increase in effective cell utilization. The part batch sizes can also be reduced as the number of job set-ups is reduced, since it is the job setups which force the parts to be processed in relatively larger batch sizes. For a general heterogeneous part mix, Deane and Yang[52] develop two propositions regarding the impact of part mix size on cell performance: cell queueing time and flow time will increase as part mix size increases; and the optimal part batch sizes that minimize cell queueing time and flow time will increase as part mix size increases. These relationships are depicted in Figure 4. Based on an empirical demonstration, Yang and Deane[53] further show that improved cell flow time performance is not only the result of the savings from processing consecutive part batches of the same type, but more important, from improvements arising from the fact that more machine time must be allocated to job set-ups as part mix size increases under a fixed cell processing workload level. As a consequence, either the cell work

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for quality control, and stabilization of production scheduling and control activities. The suggested savings in job set-ups in such smaller sized cells may help ensure a cost reduction in labour and material handling, and an upgraded quality management process.

Figure 4. System Performance vs. Cell Part Mix Size

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intensity level must increase or the effective processing time must decrease, either of which will result in a longer cell queueing time and flow time, and force the part batch sizes to increase. That is, as the part mix size increases, it is the increased proportion of machine time devoted to job set-ups that results in the major deterioration of cell flow time performance. The results from Kekre[48] and Deane and Yang[52] provide managerial insights in deciding whether to build a CMS facility with a larger number of smaller cells or a smaller number of larger cells. First, the propositions developed by Deane and Yang[52] indicate that when other factors (e.g. cell capacity constraints, part processing compatibility, tooling requirements, etc.) do not dictate a preference between the two approaches, a CMS facility with a larger number of smaller cells will ensure better performance in terms of flow time and other related measures as compared to a CMS facility with a smaller number of larger cells. Another managerial implication is evident when considering prospective “new” parts to be added to an existing CMS. As cell flow time and delivery performance (i.e. delivery speed and reliability) become more important to a firm’s competitive strategy, the formation of new cells in the system to process new parts becomes a more attractive alternative than adding the new parts (and new machines) to existing cells. As a result of improved flow time performance and smaller part batch sizes, the potential competitive advantage from the “larger number of smaller cells” type design may include improvements in delivery speed and reliability, response to market changes, faster feedback

However, there are also strategic disadvantages associated with the “larger number of smaller cells” type design, compared with its alternative – the “smaller number of larger cells” type design. For example, by constructing smaller cells with fewer parts and machines in each cell, the system may lose flexibility in terms of product change, part redesign, and potential volume expansion. In addition, increased cost from additional duplication of machines and tools must also be considered, since a lower utilization will be realized on duplicate machines and tools and some of these duplications may be avoided in the “smaller number of larger cells” type design. Conversely, a smaller number of larger cells will allow more flexibility for product change, part redesign, engineering change, new product introductions, product volume expansion, and cell production planning and scheduling. There are also potential cost savings from a reduction in machine and tool duplication, maintenance for machines and equipment, planning and control activities, and employee training. The overall strategic comparison between the two design approaches is summarized in Figure 5. Since many other factors must also be considered in the structural cell formation design decision, there may, in practice, not be a dominant design choice. However, important strategic guidelines can be offered. Unless there are strong contravening factors, the “larger number of smaller cells” design approach, as suggested in Figure 5, will be more appropriate for firms that have a narrow and stable product mix and a high priority on minimal production lead time. Such a design choice can offer the firm competitive advantages associated with delivery speed and delivery reliability. In contrast, the “smaller number of larger cells” design approach will be more appropriate for firms that have a broad and changing product mix with competitive priorities associated with production flexibility, product innovation and customization. In general, the “larger number of smaller cells” approach is more supportive of production systems where simplified work flow and fast feedback from a short manufacturing lead time will also enhance product conformance quality and inventory cost reduction. Comparatively, the “smaller number of larger cells” approach is more appealing to small-to-medium batch production systems where flexibility in product change, part redesign, and frequent engineering changes will improve product design quality and cost reduction by eliminating duplication of machines and tools. Product life cycle considerations may certainly play a role in this cell formation design decision, as a firm’s


Figure 5. Part Mix Size – Design Approach and Competitive Priorities Design approach

Competitive priorities

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In summary, managers must make the part mix/cell size structural design decision based on the consideration of all relevant factors, especially the firm’s long-term strategic objectives and competitive advantage in the marketplace.

(Intermediate consequences) Improved delivery speed and reliability Reduced part batch flow time

A larger number of smaller cells

Stabilized production scheduling and control activities Fast feedback to quality control Reduced work in progress inventory

Reduced job set-ups

High utilization of system resources

Reduced part batch sizes

Reduced cost in labour and material handling Better control of work flow Efficient utilization transportation

New product introduction flexibility Engineering change flexibility More flexible to changes

Volume expansion flexibility Planning and scheduling flexibility

A smaller number of larger cells

Cost reduction in equipment investment Less duplication of machines and tools

Cost reduction in equipment maintenance Cost reduction in employee training Efficient utilization system resources

manufacturing priorities may change as groups of products evolve through their life cycles. For example, at the introduction and growth stages, production flexibility (i.e. flexibility in part redesign and product volume expansion) may be a key competitive priority as the firm competes on the basis of new product introduction and high product design quality. The “smaller number of larger cells” design approach may thus be a preferable choice at these early product life cycle stages. Such an approach increases production flexibility and reduces risk should new products not be well-received by customers. However, for products that have succeeded in the marketplace and are in more maturity product life cycle stages, the firm is facing more stable production requirements. Such a firm usually has a competitive priority that is focused on reduced production lead time and cost effectiveness. Customer requirements for such firms usually include delivery performance (both delivery speed and delivery reliability), product conformance quality, and price leadership. Such a firm may find that the “larger number of smaller cells” design approach is more appropriate.

Set-up Time Reduction Effects: Part-oriented vs. Routeing-oriented The importance of reducing job set-up times to achieve JIT manufacturing is well recognized[56]. Set-up time reduction is particularly important to firms attempting to convert traditional job shops into CMS cellular shops. Research efforts addressing specific set-up time reduction techniques, the benefits from set-up time reduction, and the cost trade-offs involved in set-up time reduction decisions have been widely reported in the literature[5763]. The suggested potential benefits from set-up time reduction include reduced job flow time, smaller batch sizes, improved quality control, increased flexibility, and reduced inventory and backorder costs[58]. Given its significant impact on the firm’s strategic objectives and competitive priorities, the consideration of set-up time reduction effects must be actively addressed during cell formation design. Specifically, the consideration of potential effects from set-up time reduction efforts in a key cell formation design choice – the part-oriented cell construction vs. the routingoriented cell construction – is discussed in this section. In the existing literature, the decision to construct manufacturing cells based on the part-oriented approach or the routing-oriented approach has been addressed in terms of the dominance between part geometry similarity and part routing similarity. That is, this design choice is primarily viewed as an industrial engineering issue, rather than a strategic managerial concern. However, as suggested by Wemmerlov and Hyer[3], such a favourable dominance may not exist in most practical industrial settings, especially for those in the conversion process from traditional job shops into CMS cellular shops. Instead, such a design choice in the cell formation process must be made based on more comprehensive information that includes not only part processing compatibility and part geometry similarity, but also part demand volume and pattern, machine capacity, and other related production factors. This section suggests that the firm’s strategic objectives must also be considered in this key cell formation design decision. The linkage between the potential effects of set-up time reduction and this key cell formation design decision is addressed through two specific considerations: set-up time commonalty and setup time reduction method. Set-up Time Commonalty “Set-up time commonalty” refers to the homogeneity among part set-up time requirements so that a single setup time reduction effort (e.g. a procedure innovation, or

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the use of a new set-up device) will result in reductions in set-up time for all related parts. In general, set-up operations between job changeovers are required due to changes in job geometry (e.g. changes in part material type, shape, or size) or the changes in processing procedures (e.g. changes in tools and fixtures), or both, depending on the specific nature of the operation and the industry. As a result, the degree of part set-up time commonalty will normally be strongly related to the selection of the design approach (i.e. part-oriented or routing-oriented) by which cells are constructed. Specifically, the part-oriented cell construction approach should be preferable when part set-up time commonalty derives from part geometry similarity, while the routingoriented cell construction approach should be favoured when the part set-up time commonalty results from part processing similarity. It may be possible that the part setup time commonalty is dominated by part geometry similarity in one subset of parts and dominated by part processing similarity in another subset of parts. In such instances, a combination of the two cell construction approaches may be a preferred choice. That is, parts with geometrical part set-up time commonalty are placed in cells based on a part-oriented technique, and parts with processing part set-up time commonalty are placed into cells with a routing-oriented procedure. Set-up Time Reduction Method Research addressing the more technical issues in set-up time reduction has been reported in the literature[62]. In general, reported set-up time reduction methods can be classified into two categories: adoption of new technologies; and incremental industrial engineering improvements. Set-up time reduction through the adoption of new technology is usually accomplished through the implementation of advanced manufacturing systems (e.g. FMS). While the advantages of adopting new technologies have been widely reported, the initial investment in implementing new technologies can be quite high. Accordingly, incremental set-up time reduction through a series of relatively low-cost industrial engineering improvements has been observed as an increasing trend in many industries, especially for firms that are in the process of converting traditional functional layout job shops into CMS cellular shops[50]. Managerial considerations of the two set-up time reduction methods provide insights in choosing between a part-oriented design approach vs. a routing-oriented design approach. First, for a new manufacturing system with advanced technologies, the routing-oriented design approach should prove more advantageous since the effects of new technologies on set-up time reduction is normally realized through innovative processing devices and procedures. In contrast, for a CMS where set-up time reduction is to be achieved through a series of incremental industrial engineering improvements, the design choice will depend more on the technical details of the planned set-up time reduction procedures. That is, if the planned series of setup time reduction techniques is based on the commonalty

Figure 6. Set-up Time Reducation Effects: Cell Formation Design Approach and Competitive Priorities Consideration of set-up time reduction effects Geometrical part set-up time commonalty Set-up time reduction through incremental improvement Processing oriented part set-up time commonalty Set-up time reduction through new technology

Cell formation design approach

Competitive priorities Improved delivery reliability Stabilized production scheduling and control activities Reduced safety stock requirements

Partoriented approach Enhance set-up time reduction effects Routeingoriented approach

Improved delivery speed Reduced work in progress inventory Fast response to market changes Fast feedback to quality control More flexibility in production scheduling Better control of work flow Efficient utilization of tooling and transportation

of part geometrical characteristics (e.g. material type, shape of part), the part-oriented approach will be preferable. These set-up time reduction relationships are shown in Figure 6. For firms converting traditional job shops into CMS cellular shops, consideration of set-up time commonalty and set-up time reduction method should be related to this key cell construction design choice between a partoriented cell design approach and a routing-oriented cell design approach. These choices in turn have a direct impact on the firms’ desired manufacturing focus and competitive priorities. For example, when converting a job shop which has a wide part mix range and processing oriented part set-up time commonalty, the design choice of a routing-oriented cell construction approach may provide the firm with the opportunity to reduce job set-up times significantly on a continuing basis. Such an advantage will enhance the firm’s manufacturing focus on minimal production lead time and competitive priorities associated with delivery speed and delivery reliability, and market-oriented production flexibility.

Conclusions and Future Research Needs Cell formation design is one of the critical issues in CMS design. Recognizing limitations in the existing literature, this article addresses the importance of considering firm’s strategic objectives and competitive priorities in the cell formation design decision. Specifically, three practical cell formation design issues are discussed: considerations of part set-up time similarity and part processing time similarity, part mix size determination


(i.e. a smaller number of larger cells vs. a larger number of smaller cells), and considerations of set-up time reduction effects in choosing between a part-oriented and a routingoriented cell construction approach. This research does not suggest that cell formation design decisions should be made exclusively on the basis of the factors highlighted in this article. In contrast, this article suggests that cell formation design decisions must not be made only on the basis of more tactical, although perhaps more convenient decision criteria. Rather, cell design decisions must be viewed as multi-criteria decision-making problems, including strategic considerations. Discussion of cell formation as a tactical decision is a disservice to CMS and to management. This article does offer insights for the development of guidelines to the cell formation design on a more broad and practical basis. The investigation of other consequential factors (e.g. part routing flexibility, part demand pattern and volume, intercell capacity balance, etc.) and their strategic impact on the CMS and cell formation design also need to be addressed further. The CMS and cell formation design literature is continuously growing, especially with regard to methodological expansion. Examples of recent developments that are likely to have an impact in cell formation design include computerized expert systems (ES) and the application of neural computing techniques. The strategic considerations in the CMS and cell formation design should also be addressed along with these new methodological developments. Comprehensive and distinctive studies must be undertaken in order to offer decision makers a more diverse set of guidelines for CMS design in the often very complicated situations that occur in industry. References 1. Hyer, N.L., “The Potential of Group Technology for US Manufacturing”, Journal of Operations Management, Vol. 4 No. 3, 1984, pp. 183-202. 2. Wemmerlov, U. and Hyer, N.L., “The Part Family/Machine Group Identification Problem in Cellular Manufacturing”, Journal of Operations Management, Vol. 6, 1986, p. 125. 3. Wemmerlov, U. and Hyer, N.L., “Research Issues in Cellular Manufacturing”, International Journal of Production Research, Vol. 25, 1987, pp. 413-31. 4. Crookall, J. and Lee, J., “Computer Aided Performance Analysis and Design of Cellular Manufacturing Systems”, CIRP Journal of Manufacturing Systems, Vol. 6, 1977, p. 177. 5. Flynn, B.B. and Jacobs, R.F., “A Simulation Comparison of Group Technology with Traditional Job Shop Manufacturing”, International Journal of Production Research, Vol. 23, 1985, pp. 1171-92. 6. Krajewski, L.J. and Ritzman, L.P., Operations Management: Strategy and Analysis, 2nd ed., AddisonWesley, Reading, MA, 1990. 7. Hill, T., Manufacturing Strategy: Text and Cases, Richard Irwin, Boston, MA, 1989.

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Jiaqin Yang is Assistant Professor of Management, University of North Dakota, Grand Forks, ND and Richard H. Deane is in the Department of Management, Georgia State University, Atlanta, Georgia, USA.