Issues in Managing Manufacturing Flexibility : A Review

Sharma, O P

Abstract

This paper attempts at surveying the available literature on issues related to management of manufacturing flexibilities in the context of flexible manufacturing technology (FMT), comprising chiefly of advanced manufacturing systems (AMSs) such us flexible manufacturing systems (FMSs), computer integrated manufacturing (CIM) systems, intelligent manufacturing machines etc. In the preamble, the paper discusses various connotations of flexibility in general, manufacturing flexibility, measures of flexibility, opinions and trends in flexibe and agile manufacturing, and the types, suitability, and justification of FMSs.Then the issues directly related to managing manufacturing flexibility - such as the technological, system-integration, organizational, managerial, strategic, interfacing, economic, and social - are discussed. State of the research and limitations of the existing approaches are outlined next and the paper concludes pointing out areas for further research.

Keywords : connotations, flexibility, issues, management, manufacturing

Introduction

Management of manufacturing flexibility remains a grey area, notwithstanding the advances made in manufacturing technologies. This becomes all the more pronounced when it comes to managing flexible manufacturing technology (FMT), which chiefly comprises the computer numerically control (CNC) machine tools, robots, transfer mechanisms, automated guided vehicles (AGVs), automated storage and retrieval systems (ASRSs), computer-aided design and computer-aided manufacturing (CAD / CAM) systems, flexible manufacturing cells (FMCs), flexible manufacturing systems (FMSs) and general flexible manufacturing systems (GFMSs). When these physical elements of FMT are completely integrated using computers and different networks, they result in computer-integrated manufacturing (CIM) systems, that are considered to be quite complex and highly advanced manufacturing facilities.

Efficient operation of these FMT elements essentially requires the help of not only highly trained professionals but also that of non-physical elements or systems such as just-in-time (JIT), total quality management (TQM), concurrent engineering manufacturing (CEM), materials requirement planning (MRP), and manufacturing resources planning (MRP II) among others. These non-physical elements are essentially programmes / philosophies / behavioural approaches (Aggarwal, 1995).

However, managing these systems requires careful consideration and handling of the issues involved at two levels: firstly, at the tactical level, requiring professional and technical competence; secondly, and more importantly, at the strategic level, requiring a long term vision and planning at the higher and top management levels.

According to Rachamadugu and Stecke (1994), the design and subsequent operation of FMSs are complex and time consuming tasks. The flexibility, complexibility and the need for system integration of FMSs increases the decision alternatives at both strategic and tactical levels. Operational decisions involve tactical issues, such as part type selection, part input ratios, part input sequencing, and scheduling. Furthermore, the aspects related to their integration, operation, scheduling, sequencing, and maintenance pose challenges that tend to become formidable with an increase in the flexibility and complexity incorporated in these systems. Strategic decisions call for a long-term planning and involve issues like the capital investment, design of the flexible manufacturing sytem(s) to be installed, choice of FMT elements, material handling devices, types of the parts or products to be made using the system, the degree of flexibility required (or perceived to be required) to be built in, incorporating the required changes in the existing organizational structure, interfacing these adavnced systems with the existing conventional manufacturing units if adopting the technology in the first place, training and re-training of the operators and professionals, assessing the degree of competitive edge required to survive, sustain and progress, and keeping abreast of the latest advancements in the technology. It should be obvious that these decisions are far more critical in nature and require a sound understanding of the dynamics of effctively managing FMT.

The paper aims at providing a review of the literature addressing these issues and is organized as follows. In section 2, the connotations and measurement of flexibility, and various aspects related to the FMSs are reported. section 3 is devoted to the issues related to management of manufacturing flexibility and the FMT, whereas in section 4 is reported the state of the research. Outlining limitations of the existing approaches are riven in section 5 and future research directions in section 6, the paper concludes in section 7 followed by references.

Connotations of Rexibility

The meaning of flexibility is flexible enough to denote a plethora of different connotations in different contexts and situations as portrayed in Figure 1 (adapted from Sushil, 1997). The list, however, is only representative in character and is not exhaustive. For example, the concept of flexibility in manufacturing can be added to it.

According to Upton (1994), flexibility in a generic sense can be defined as a quality to change or react with little penalty in time, effort, cost or performance. In a compact sense, it can also be defined as the quality of a system, which allows it to respond to change effectively (Mandelbaum and Buzacott, 1990). Another extension of the concept has been described as the ability to respond rapidly to internal and external changes (Young and Chan, 1990).

The concept of flexible specialization is dealt with in detail by Zairi (1992) and Morales (1994) which was introduced in the 1980s as a strategy of permanent innovation: accommodation of ceaseless change rather than an effort to control it. Boynton (1993) explores the issue of achieving flexible efficiency by combining the best of mass production and innovation.

Vishwanadhan and Narahari (1992) have attempted to discern flexibility from a flexible system by observing that a flexible system is the one that is able to respond to change, whereas the flexibility is the ability of a system to respond effectively to change. Sushil (1997), on the other hand, has proffered a systemic concept of flexibility according to which flexibility is the synthesis or dynamic interplay in the continuum in an interactive and innovative manner with minimum time and effort. The author has also reviewed multiple connotations of flexibility in different spheres of management. Young and Choi (1994) have stated that flexibility is the result of physical characteristics, operating policies and management practices. Upton (1995) has expressed the view that flexibility carries various hues to fit into the imagination of different people. For example, various components of flexibility, like product, range, mobility and uniformity of performance, carry quite diverse meanings depending upon upon situational and environmental contexts.

Turning now to the less generic and more specific area of the types of flexibilities, the work done at the Institute of Management Studies, UK in the area of labour flexibility

is an example where three main types of labour flexibilities have been identified (Sethi and Sethi, 1990). The first is numerical flexibility, which concerns the readiness with which the number of people employed can be adjusted to meet the fluctuations in the level of demand. Functional flexibility is the next, which concerns the readiness with which the tasks performed by workers can be changed in response to varying business demands. The third is financial flexibility, which relates to the extent to which compensation practices encourage and support the other two (previous) flexibilities that the company seeks. Another type is the capability of a manufacturing system to adapt to changes in the demand rate (Young and Park, 1990).

Moving now to the area of variants of flexibility, chiefly concerning the production environment and related aspects, Upton (1994) and others have delineated its multiple facets. These are termed as :

* Product flexibility

* Process flexibility (Chen et. al., 1992)

* Operations flexibility

* Volume flexibility

* Machine and machining flexibility (Chen et.al. 1992, Stecke and Narayan 1995.)

* Routing flexibility (Chen et. al. 1992, Singh et. al. 1992)

* Action flexibility and state flexibility

* Expansion flexibility

* Material handling flexibility

* Design and design change flexibility, and

* Labour flexibility

* Manufacturing operations and strategic flexibility (Beach et. al., 2000)

Thus, flexibility is multidimensional and there exists a parallel between the management of flexibility and management of quality.

In addition to the above, other hues of flexibility in the same realm include material handling flexibility and programming flexibility as the manufacturing based flexibilities, whereas product, volume and mix flexibilities are market based. Chen et. al. (1992) have also proposed a contingency theory based flexibility uncertainty model (FUM) as a conceptual framework to facilitate understanding of interaction between environmental uncertainty and flexibility needs. They have also coined the concept of aggregate production system flexibility as a synthesis of these two broader categories of flexibility.

Assembly system flexibility (Stecke and Narayan, 1995); state, action and job flexibility, loading flexibility, information flow flexibility, and set-up time and data handling flexibility, are some other variations one can talk of.

Manufacturing Flexibility

The importance of flexibility in manufacturing has been well documented (Sethi and Sethi, 1990, Hill and Chambers, 1991, Dixon, 1992, Gupta and Somers, 1992, Kochikar and Narendran, 1992, Gerwin, 1993, Chambers, 1995, and Sushil, 1997) and its effectiveness in providing several benefits like reduction in set-up time, manufacturing lead-time, equipment idle-time and inventory levels, improvement in productivity, and better control of the process have been adequately demonstrated. In fact manufacturing flexibility as a strategy remains high on the agenda of many manufacturing organization (Beach et. al., 2000).

However, manufacturing flexibility too appears to be embracing diverse definitions propounded by different authors. But a centric definition of manufacturing flexibility which emerges, defines it as the ability of a manufacturing system to respond, at a reasonable cost and at an appropriate speed, to planned and unanticipated changes in external and internal environments (Roll, 1992). Another group of researchers have endeavored to delineate various aspects of manufacturing flexibility as well as time frames and stages, where these aspects are of importance (Sethi and Sethi, 1990) whereas Young and Choi (1994), while defining manufacturing flexibility as the capability of a system to cope with internal and external changes, have put forward the concepts of potential and realizable flexibility. Upton (1995), while admitting that flexibility means different things to different people, attempts to define a flexible plant as the one that can perform comparatively well when making any product within a specified range. Das (1996) has coined another interesting connotation of manufacturing flexibility as a facility that is equipped and designed such that it is able to either avoid or adjust to the detrimental effects of internal and external changes. Before a discussion on diverse dimensions of manufacturing flexibility is taken up, it is worth noting that the definition of manufacturing flexibility has not achieved a complete consensus, but it has advanced knowledge to a point where the focus of research should shift to it. After all, adds Dixon (1992), the ability to define manufacturing flexibility is the vital first, and not the last, step in understanding it. Due to the competitive edge that manufacturing flexibility can provide, there has been a number of other attempts to define it, resulting in an interesting array of various types of definitions; their relevance, propensity and frequency of falling into some ten major types (Chen et. al., 1992).

Notwithstanding the inadequacy of a complete definitional consensus, the need to make manufacturing more flexible and use it more effectively has resulted in the evolution of FMT with flexible manufacturing cell as its rudimentary form. The FMSs and CIM are its next hierarchical steps in ascendancy of advancements with intelligent manufacturing systems as the latest.

A flexible cell or flexible workshop can be described as a flexibly automated system assisted by production equipment comprising of one or several multifunctional machines with automatic tool changers (ATCs) coupled with an automatic transfer system for parts, before and after they have been machined.

The concept of FMSs, which is the step next to FMC, was originally developed within the concept of machining piece parts. The FMS combines the existing technology of NC manufacturing, automated material handling and computer hardware and software to create an integrated system for automated random processing of palletized parts across various workstations in the system. Integration of manufacturing activities with advanced technologies to give a higher level of automated production systems can be generally described as FMS (Sharma, 2001).

Another frequently repeated definition of FMS defines it as a production unit capable of producing a range of discrete products with a minimum of manual intervention (Mansfield, 1993).

While recognizing that the FMSs can apply the efficiencies of large-scale production to small batch production, another group of researchers broadly define an FMS as an integrated, computer controlled production process composed of automated material handling equipment and CNC machines that can simultaneously process low to medium volumes on a variety of part types (Gupta et. al., 1997).

Although the first FMSs were installed in the late 1960s and early 1970s by Rockwell International in the US and Fuji Xerox in Japan (Mansfield, 1993), a precise definition of what constitutes an FMS is still open to debate and difficulties are encountered while attempting to define such systems (Roll and Arzi, 1992).

Notwithstanding these difficulties, the current levels of application, the future potential, general design features, layout and range of operations together with some estimates of expected cost savings from the use of FMSs, have been extensively discussed (Sharma, 2001).

Comprehensive surveys of the developments of FMSs in various nations have been documented (Sharma, 2001) Various operational aspects of FMSs as well as of automated manufacturing in general, have also been explored. The ultimate goal of FMSs is to employ no workforce whatsoever and when perfected, they should be extremely flexible in terms of product-mix and volume-mix and should provide high quality, low cost output in a very short lead time. This leads to the concept of CIM in which the boundaries between various functional areas are not clearly defined nor emphasized because the thrust with CIM is on shared information used.

Measures of Flexibility

The need and attempts to compute the value of flexibility may be viewed as a hedge against future uncertainty (Sethi and Sethi 1990). Also, researchers need flexibilities measures to test theories and operations managers need them to facilitate making capital investment decisions and in determining performance levels (Gerwin, 1993).

Though different approaches have been evolved, but the most common measurement approach in practice is to count the number of options at a given point of time (Gerwin,1993). Stecke and Narayan (1995) have set out that aggregate flexibilities are the most visible measures of overall system flexibility as they influence the parameters that are immediately measurable, such as machine utilization, range of products manufactured, customer order turn around time and new product introduction frequency.

Whereas subjective managerial assessment is almost universally applicable in the manufacturing sector (Gerwin and Tarondeau, 1989) some quantitative tools for measurement of flexibility have been developed. For example, one measure of flexibility is based on 'entropy' in thermodynamics and other measures based on mathematical and empirical relations have been reported (Dixon, 1992).

Starting with the abstract intangibles of manufacturing flexibility, a framework for quantifying opportunity costs associated with enhancing or adding to it had been developed much earlier. The opportunity cost consist of non-conventional cost of setup, part waiting, equipment idleness and inventory. Earlier researchers who have attempted to quantify the intangibles associated with manufacturing flexibility have been clustered into three groups, designated as group A, group B, and group C. Group A consists of those authors who have surmised that many intangible parts of flexibility can be treated as a black box (Krinsky and Miltenburg, 1990), whereas group B comprises of researchers who prescribe a surrogate value approach to measure these intangible parts unquantifiable in monetary terms (Toxler and Blank, 1990; Demmel and Askin, 1992; Son, 1991; Stam and Kuula, 1991; Suresh, 1991; Venk., 1990; Wabalickis, 1990; Zahir, 1991).In group C are clustered the researchers who opine that as far as possible, all intangible parts of flexibility should be quantified in capital or money terms (Suresh, 1991).

Turning now to the measures concerning physical elements of the production process, while Roll et. al., (1992) have developed an approach to a quantitative evaluation of processing flexibility in flexible manufacturing cells, Browne et. al. (1984) provide an exposition of some pragmatic methods of measuring machine, process, product, routing, volume, expansion, operations and production flexibility in the context of flexible manufacturing systems. They have further added that the level of automation helps to determine the amount of flexibility.

Flexibility of machinery can be measured as the ratio of the investment's residual value for the next product modes of the original investment, i.e., an index between zero and one. Product flexibility can be measured as the ratio of the residual value of the old model to the new model divided by the original value of the old model.

Although evaluation of system reliability and performance of FMSs is a complex undertaking, some predominantly simulation based procedures have been developed (Young and Murray, 1986) for the same. Through these procedures, it has been demonstrated that various criteria involved in evaluation can not be considered independently and must be examined as part of an interactive group.

Evaluation of other activities associated with FMSs, such as resources allocation, minimization of costs, adjustment to demand, meeting the deadlines, maximizing total benefits and designing a mechanism that potentially can achieve these objectives, has also been addressed. A decentralized pricing mechanism, based on a modeling of FMS with priority queues and general stochastic equilibrium, has been proposed to estimate these activity based costs (Gupta et. al. 1997).

Difficulty of processing different parts on the same equipment where a different setup is required for each product type is known as mix flexibility. A mathematical model for measuring mix flexibility, which is based on the results of a simulation study and has been found to give good results for both single and multiple machine system, has been developed by Bateman et.al.,(1999).

However, the measurement of flexibility and its diverse dimensions, particularly those associated with FMSs, still remains one of the most elusive areas. This aspect has its severe limitations, especially with regard to the difficulty of measuring the economic benefits resulting from manufacturing flexibility (Kalkunte et. al., 1986).

Opinions and Trends in Rexibility

Trends and thoughts in various disciplines, including management of manufacturing flexibility and technologies, have undergone a metamorphosis, especially during the last few decades. Evolution of knowledge in management and production technologies is synonymous with that in the natural sciences and Sushil (1997) has described this phenomenon characterized by ever shifting paradigms.

The transition of paradigm of manufacturing systems from traditional to new has been compared with a family replacing their old car with a helicopter as their primary means of transport, and therefore, in order to benefit from the changeover, it is essential that the family not use the helicopter in the same way it used the family car (Hayes and Jaikumar 1988, Shani et. al. 1992)

A noticeable trend observed in several industries during 1980s was that the strategic emphasis shifted from cost to quality, although the management system remained focussed on costs (Dixon, 1992). But as advances in manufacturing technologies offer an increasing array of equipment choices, the questions that have become more relevant now are: How should a multi product manufacturing organization design its production facilities and how many products should be assigned to each facility and what batch size or scheduling rules are appropriate ? Benjaafar and Gupta (1998) have attempted quantitative models that can help operations managers answer these questions.

Flexibility Assessment Aspects

Lack of insight into and failure to recognize the chasm between in-built and post implementation attainable flexibility of a manufacturing system has contributed to the researchers not being successful in quantifying its strategic benefits (Swamidass and Waller 1990, Gupta and Somers, 1992; Chandra and Tombak, 1992; Dixon, 1992; Young and Choi 1994). While assessment of flexibility dimensions requires consideration of time, cost (of change) and range of states a production system can attain, it has been observed that the companies do not measure all of their competitive capabilities (Dixon, 1992).

Earlier, the focussed manufacturing was replaced with mix flexibility manufacturing, incorporating economies of scope (Goldhar and Jelinek 1983, Stalk and Thomas 1990) and this further facilitated product innovation. Scope in the context of flexible or agile manufacturing has been defined as the magnitude of change which can be accommodated (Meade and Sarkis, 1999)

The issues of appropriate quanta, required, potential and actual flexibility of a manufacturing system and misalignments between them, have been addressed (Gerwin and Tarondeau 1989, Gerwin 1993). These issues assume added significance against the backdrop of shortening life cycles of not only the products, but also of the flexible manufacturing process itself (Sakurai, 1990) and which only stress the dynamic and time dependent nature of the manufacturing flexibility requirements (Stecke and Narayan, 1995)

The FMSs, Their Types, Suitability and Justification

Before taking other FMSs related aspects, it is worth mentioning that there is now a distinction between a general flexible manufacturing system and dedicated flexible manufacturing system (Hedin et. al., 1997). Whereas GFMS is characterized by a large product variety and small unit volume exogenous demand and is prevalent in Japan, the FMS environment is a small product variety and moderate to large part volumes, found in many US firms. Interestingly, while little guidance is available for managing GFMSs, more and more US firms are moving towards implementing them.

Adoption or appropriation of advanced manufacturing technology entails major investments and a high degree of uncertainty, and, as a result, issues encompassing selection and justification procedures have assumed greater importance (Sambasivarao and Deshmukh, 1995).

Several surveys of FMS and FMT installations, worldwide and country specific, have been conducted by researchers (Hill 1985, Margirier 1986, De Meyer et. al. 1989, Ranta and Tchijov 1990, Roller and Tombak 1993, Carlsson 1992, Ettlie and Reza 1992, Upton 1995, Sharma and Sharma 1997) and by institutes (e.g., by the International Institute for Applied Systems Analysis, or IIASA, conducted in 1989) to dwell upon several aspects related to FMT and especially FMSs. It has been discovered that co-ordination of FMS activities is a complex task (Swamidass and Waller 1990, Gupta et. al. 1997) and there is a rapidly growing need to operate these systems efficiently (Pine, et. al., 1993).

Now taking up the issue of suitability of FMSs, it must be understood that an FMS can not only handle low to medium volumes of production with large part types, but can also be successfully implemented in large-scale operations (Rachamadugu and Stecke 1994, Gupta et. al. 1997). But the suitability of FMS operations for companies does require sound procedures for determining accurate estimates of future net returns and accounting procedures consonant with advanced manufacturing techniques.

However, notwithstanding the suitability aspects of flexible manufacturing systems, Swamidass and Waller (1990) observe that although new manufacturing technologies offer many advantages to their users, the associated complexities render process of justification to be muddled, confusing and uncoordinated.

Computer integration (CI), which is a very crucial aspect of flexible manufacturing and can provide critically needed advantage in quality and cost competitiveness, does not necessarily add to the operational flexibility (in some cases it tends to impede it). Rather, a more startling finding of Upton's (1995) survey was that CI did not decrease the change over time; manual changeovers often outsmarted the computer controlled changeovers. The authors have experienced that this is more manifest in the Indian context.

Therefore, now there is a growing realization that people count more than machines (Upton, 1995) and some researchers have developed models of human decision making (Burcher et. al., 1999). This has led to the concept of workforce flexibility defined in terms of multifunctionality and redundancy (Mc Creery and Krajewski 1999, Molleman and Slomp 1999).

Productivity and quality are the two highpoints of FMSs. Gupta and Singh (1997) have suggested that more often, there must be discussion regarding flexibility versus productivity before the production system is designed. Nevins et. al., (1989) have observed that materials flexibility reduces pressures on the upstream activities of FMSs to eliminate quality problems.

We conclude this subsection on a prophetic note that the competitive battle in future will be waged over manufacturers' competence to overcome the age old trade off between efficiency and flexibility and some of the world's best (Japanese) competitors have already moved considerably in this direction (Chen et. al., 1992).

Agile Manufacturing

Agility is a new paradigm in the context of manufacturing and manufacturing agility has been defined as ability of a company to thrive in a competitive environment of continuous and unanticipated change. But how does it differ from flexible manufacturing? Flexible manufacturing per se relates to the functions and / or operations, including automation, tailored to meet the demands of ever growing and sophisticated customers who not only expect quality, reliability, and competitive pricing, but also want customized products with quick deliveries. This is, thus, almost exclusively related to the change of a firm's internal hardware and software characteristics.

Agile manufacturing organizations on the other hand, focus on products and processes rather than on the functions, interdependent on a wide range of external factors conducive to sustaining a symbiotic business environment capable of providing infrastructural, logistical and institutional support at the national, regional and local levels. Agile businesses, in general, compete on the basis of development cycle time, price, quality, flexibility, fast and reliable delivery and after-sales support for their products (Quinn and Hilmer, 1994).

According to Meade and Sarkis (1999), the manufacturing environment has undergone several transitions, from the craft industry, to mass production, and now the newest paradigm, agility. Agile-based competition is destined to displace mass-production-based competition as the form of global commerce. In order to understand this new paradigm, the Agility Forum has introduced four dimensions of agility: Cooperating to Enhance Competitiveness, Enriching the Customer, Mastering Change and Uncertainty, and Leveraging the Impact of People and Information. The authors have discussed these four dimensions in detail.

Issues Related to Management of Manufacturing Rexibility

The issues related to system integration, organizational structure, strategies, decision making, interfacing, and the social and economic aspects of the manufacturing flexibility have attracted a lot of attention and focus during the years. A number of authors have attempted to deliberate on these as discussed in this section.

The Technological Issues

Starting with a conceptual framework, Aggarwal (1995) has distinguished between hard (CAD / CAM, NC / CNC machines, robots and transfer mechanisms, group technology, FMSs and CIMs); soft (JIT, total quality management, concurrent engineering manufacturing, total productivity improvement, continuous improvement programme, total production maintenance approach, process-oriented v/s results-oriented management and scheduling and delivery improvement); and hybrid (materials requirement planning, manufacturing resources planning and optimized production technology) technologies. In this section, the hard (or physical) technological issues are dealt with. Beginning with shop floor activities, Handa et. al. (1995) observed that fixture preparation and NC data generation are the imperatives in effective operation of FMSs. The machining centers require CAD/CAM systems to automatically generate NC programs, and this programmability introduces flexibility into the manufacturing process in several ways (Wang and Veeramani, 1997). However, as has been discussed earlier the implementation and operation of computerized manufacturing systems is a very complex process which is currently not well understood and one reason could be that it (CIM) is very much a technological vision.

Oboth et. al. (1999) have presented an effective network representation to address a whole gamut of issues concerning the AGVs, another critical element of FMT on the shop floor. While the issues of path flow design have been discussed in detail by these authors, Lee and Maneesavet (1999) have developed dispatching strategies of rail guided vehicles (RGVs).

Hedin et. al. (1997) investigate the static and dynamic tooling policies in GFMSs and have recommended several methods to manage these. Other researchers have studied the tool design problems, for example Hsu et. al. (1998) studied the ones encountered in using a punch press FMS for producing flat sheet-metal parts and Singh (1993) studied the design of cellular manufacturing systems. The approach, claim the authors, has applications beyond the tool design aspects. Tool loading problems to minimize the number of tool change over time in order to process several parts on a flexible machine, have been investigated by Hertz et. al. (1998) and Sheikh et. al. (1999). Chowdary et. al. (1997A) have studied issues in the design of technology systems.

The study of production sequencing in an FMC with the objective of maximizing throughput rate has been done by Thensen (1999), Singh et. al. (1992), and Stecke and Tocylowski (1992), whereas Sabuncuoglu and Karabuk (1998) propose new heuristics based algorithm for FMS scheduling and sequencing. The heuristic also considers finite buffer capacity, routing and sequence flexibilities and generates machine and AGV scheduling (Pyung and Jaejin, 2002). A new approach to FMS scheduling with multiple criteria, based on fuzzy interference, has been proposed by Yu et. al. (1999), which, claim the authors, had a very robust performance with respect to shop workload for all performance measures and is especially good when workload is very heavy. Chunwei and Zhiming (2001) have proposed a genetic algorithm for the same type of problems.

Modern flexible production systems exhibit a high degree of resource sharing thet can lead to deadlock conditions. Maria et. al., (2002) have addressed this problem by suggesting an approach to deadlock avoidance which is based on a supervisory control that works by inhibiting or enabling the events involving resource allocation. In the context of FMSs, minimization of the WIP (work in process) is considered as an economical and productivity factor. Ouajdi et. al. (2002), have proposed a new cyclic scheduling algorithm giving the maximum throughput while minimizing WIP.

Analytical models of various FMSs related operations, including the diffusion of FMSs, have been critically assessed by Buzacott and Yao (1986), the research on which appears to have begun around 1972-74. The authors have critically assessed the modelling structures by various groups such as the Purdue, Draper Labs, MIT (LIDS), Harvard, France and Toronto.

Diffusion of FMSs in specific and advanced technology in general, is far from easy (Belassi and Fadlalla, 1998). Earlier Models developed in this respect did not capture factors related to organization, top management, external environment and FMS itself (Mansfield 1993, Handfield and Pagell 1995).

A new class of quantitative models for control of FMSs has been developed which is based on the concept of extended high level evaluation Petrinets (EHLEP-N) (Yan et. al., 1997). Chowdary et. al. (1997) have proposed a framework of a multi-criteria approach to evaluate technological options for organizations working with conventional systems and contemplating adopting FMT. Sangkyun et. al. (2001) have proposed a supervisory control of approach for execution control o FMSs.

Loading on FMSs is affected by the characteristics of the FMS in use, the type of plant where the FMS is operating and the production planning hierarchy of the operating loading module. Antonio et. al. (2001) have proposed analysis of various aspects that influence the problem identification, identifying the alternatives available in real time systems and possible future evolutions.

Increasing industrial implementation of just-in-time (JIT) manufacturing system is a motivating factor for adopting flexible manufacturing technology and there have been attempts at finding JIT schedules for flexible transfer lines and use of Artificial Intelligence (AI) for FMS scheduling and operations. In fact, one of the major requirements of 21st century is to introduce intelligent information technology into manufacturing (Babic, 1999).

The System Integration Issues

Even the best of individual subsystems will fail to deliver goods collectively if they are not fully and functionally integrated. But in practice, achieving integration of subsystems is quite arduous and often extremely difficult task (Aggarwal, 1995).

The concept of system integration has had its existence for long (Shaw et. al., 1992) but some recent trends and developments, especially in the IT, have rendered it crucial enough meriting a serious consideration (Seidman 1993, Sharma and Sushil 1997).

When fully developed, flexible manufacturing technology organizations use computers to integrate functional areas of marketing, design and quality control into a continuous, sometimes unattended, round-the-clock operation. Also, product development groups, marketing, R&D, and manufacturing departments must interact frequently to familiarize with their respective innovative ideas. This knowledge, then must be integrated so that customer preferences, technical design and manufacturing flexibility are part of the product design decisions (Chen et. al., 1992). Worldwide rapid diffusion of the web technology and information highways, are all manifestations of this process which is the harbinger of emerging areas like 'collaborative technology' and 'distributed artificial intelligence' for integrated manufacturing (Shaw and Fox 1993, Gupta et. al. 1997). The use of electronic documentation for coordinating work-flows (Dong et. al., 1995) and using electronic data interchange (EDI) for associating with vendors and suppliers (Seidmann and Wang, 1995), are other examples of the process.

At the physical facility or plant level, the system integration relates to interfacing various organs, such as the CNC machining centers, conveyors, pallets, server and inspection robots, tool monitoring, AGVs, ASRSs, and other elements of FMT, the culmination of which is a CTM plant. While computers play a major role in the control aspects, electronics is the critical and most vital facilitator of the process (Shaw et. al., 1997). Other critical elements of integration at this level include the interface between design and manufacturing; between design engineering and plant control; between manufacturing process and the firm's system of cost management and investment appraisal; and between marketing, design and quality control, and between management practices and CAD technology (Malhotra, et. al., 2001).

While the level of complexity of a computer integrated plant depends upon whether it is a job shop, cellular manufacturing, FMSs, or CIM plant, the correlation between flexibility and computer integration is seen to be highly correlated. Meredith (1987 b) observed this relationship as shown in Figure 2.

The management problems associated with new manufacturing technologies arise from their dependence on integration, not just within the manufacturing process, but across the enterprise as a whole and even extending beyond the enterprise to include suppliers end customers.

On another level is the integration manufacturing and organization strategies; manufacturing and human resources management; and between human knowledge and mechanical systems. However, all these aspects have a co-relation with the integration of maintenance of manufacturing organs because in these systems, wear out and essential failures are unavoidable. However, to reduce the rate of their occurrence, and to prolong the life of the equipment, technological functioning, and servicing, maintenance can be a critical factor, especially for large and complex manufacturing systems. Zineb and Chadi (2001) have proposed an effective way of modeling the integration of maintenance policies in a manufacturing system.

Lastly, a mention can be made that relationships between perceived environmental pressures and structures, and between inflexibility of technology and structure are different under conditions of environmental scarcity and munificence. Also that different process environments tend to align advanced manufacturing technology investments in distinct profiles, which are associated with superior performance (Das and Narsimhan, 2001).

The Organizational Issues

Most managers now realize that only new technology is not enough to increase productivity; organizational and process changes must also be made (Ettlie and Reza, 1992, Benjamin and Levinton 1993) to develop flexible organizations capable of supporting the multidimensionality of flexibility (Bahrami 1992, Duimering et. al. 1993). This is supported by a survey of the US manufacturing establishments wherein evidence was found of significant adoption of innovative work organizations in a large and representative sample of the US plants (Florida, 1996).

But why are these transformations in the organization (also known as business process redesign or business process re-engineering), required? To answer this question, it may be recalled that switching over to mass production and assembly lines (economies of scale), envisioned and practised first by Henry Ford of USA, witnessed organizational fissures mainly due to the enhanced pace of manufacturing activities, causing organizational anxiety and tension.

A plethora of organizational factors, such as: environment, strategy, product life cycle, products, employment arrangements, marketing techniques, innovations, integration, decision making, information flow, managerial power base, behaviour, discipline, standardization, control of the production process, management, and operator skills and rewards, will be touched by the changes brought about through the introduction of flexible manufacturing technology (Wabalickis, 1990, Shani et al, 1992). In the context of high technology industries, size of the organization itself is often a source of dissatisfaction (Cespedes, 1990) because inertial forces inherent in an established and large organization restrict a firm's flexibility, i.e. its ability to change course and maneouver quickly as technological and market conditions change (Bahrami and Evans, 1995).

In addition, the decline of communism, advances in information technology (IT), emergence of new industrial powers and intense global competition are some of the factors that have forced even the large and powerful organizations like the IBM, GM, Eastman-Kodak, AT&T, Cigna RE, Hallmark and Hindustan Lever (in India) among others, to undergo massive restructuring in order to survive in this new age (Teng et. al. 1994).

This explains the imperatives of organizational change or corporate restructuring, which has been defined as adapting to a changing environment, adding more value to clients, increasing return on investment and eliminating waste of resources by rethinking the business (Togt, 1995). This also includes redrawing of hierarchical boundaries and altering expectations (Dorothy, 1992). In actual practice also, there exists a considerable difference between the organizations of companies that have adopted new manufacturing technologies and those that have not (Milgrom and Roberts 1990, Roller and Tombak 1993).

As mentioned in the opening paragraph of this paper, the new technology organization has to be flexible but even against this backdrop what should be the nature or form of these flexible organizations?

An early suggestion is that of an organizational slack that enables an organization to have additional resources to contend with internal and external environmental uncertainties. Sethi and Sethi (1990) refer to an organic structure (as opposed to mechanistic) suggested by Bums and Stalker (1961). Sociotechnical system, high commitment system, some forms of decentralized (Gupta et. al. 1997), divisionalized structures, project management and matrix structures, are some of the models of organizations that have the flexibility to operate in a rapidly changing environment. Other forms suggested are those of ad-hocracy and agile organization (Meade and Sarkis, 1999).

While the early traditionally functional forms of organizations were organized around the input functions and were hierarchical in character, the flexible and newer forms are organized around the output functions, are re-christened as product-focused forms, network or flat organizations and bi-modal organizations have also been suggested (Sethi and Sethi 1990, Bahrami 1992).

Turning now to the methodologies to achieve the objective of transformation to these newer structures, a unifying framework known as sociotechnical systems (STS) has been suggested by Shani et. al., (1992). This framework considers every organization to be made up of a social subsystem (the people) using tools, techniques and knowledge (the technical subsystem) to produce a product or a service valued by the environmental subsystem (of which the customers are a part). Meade and Sarkis (1999) have proposed a framework using the Analytical Network Process (ANP), which is a general form of the Analytic Hierarchy Process (AHP), to achieve the objective of creating agile business processes.

Essentially, it is a continuous process of management of change that is the biggest challenge faced by the organizational leaders (Swamidass and Waller 1990). Now, the thinking is that the problem is no longer the management of change, but the management of surprise (Schein 1993). The leadership and commitment of top management is absolutely essential in this process. Training of the employees is also a major ingredient of this process (Aggarwal and Aggarwal, 1985).

The importance of organizational factors can be gauged by the fact that most AMT failures are due to organizational problems (Michael and Charles, 1996). Successful companies have been those who have developed in-house competence in working and struggling with systems. TELCO of India is one such example. Too much dependence on outsiders has invariably resulted in failures and frustrations. All this, however, requires organizational restructuring, change and flexibility.

Business process reengineering (BPR), through radical redesign of business processes and systems, policies and organizational structures, was introduced in the manufacturing industry to seek performance breakthroughs. Several authors have reported various aspects of BPR (Katz et. al. 1995, Guimaraes 1997, Gunasekaran and Nath 1997, Jones, et. al. 1997, Labib et. al. 1998), but Felix and Bing (2001) have described a novel approach to BPR which applies FMSs design and analysis technologies such as simulation, multicriteria decision support, and artificial intelligence.

However, although there have been successes, BPR is recognized as a high-risk activity, prone to failure. There is a variety of reasons for this and one of these is argued to be the lack of attention that BPR pays to flexibility and its inability to cope with a changing environment. Fitzerald and Siddigui (2002) have suggested a number of proposals, including that of a form of 'flexibility analysis' to be adopted as a stage in BPR projects.

The Managerial Issues

There is a shift of emphasis from process optimization to information management and this defines the new core competency of today's managers (Shaw et. al., 1997). Also, today's executives must shift their orientation from controlling to counselling (Benjamin and Levinson, 1993). But these are formidable challenges as these shift paradigms make the managers feel insecure because the power also shifts with these and therefore, they resist. This puts a pressure on the top managers to understand and manage closely the interaction between the production, marketing and finance functions and this may prompt some senior managers to reject FMSs to avoid this additional burden Further, there is a dearth of knowledge about the management of factory automation, both managing factory of the future and transforming the factory of today into the factory of tomorrow.

This emanates from the prevailing syndrome of viewing the theory and practice of CIM as a technical solution to both organizational and workforce problems, because CIM promises to reduce human discretion and substitute capital for labour. However, this belief may be an illusion and this is one important reason for disappointments encountered in the application of computerized manufacturing system (Chen et. al., 1992). It has been observed that effectiveness of computerized manufacturing depends heavily on the way it is managed. For example, the effective or real flexibility of systems (i.e. FMSs) is not closely linked to their potentialities but rather depends on the way these are managed or used, asserts Margiries (1986). The author surveyed nineteen industries in France during mid-eighties and identified three types of companies: those producing a great diversity of products with a small number of tools (having lesser means but producing greater results); those producing low degree of diversity despite substantial means (having more means but producing poor results); and those having the most impressive equipment and using it best in order to realize a great diversity of products, all because of the way these were managed.

However, these people's problems which are serious enough to be attended to, can be overcome with substantial efforts in terms of training and attitudinal changes of the personnel concerned. Further, experts on change management suggest three critical elements for altering current practices: dissatisfaction with the status quo; a clear model of what changed organization will look like; and a process for reaching that vision of the future (Dorothy, 1992).

The Strategic Issues

Strategy denotes actions or patterns of actions intended for attainment of goals. For example, manufacturing strategy concerns itself with questions such as, should a given manufacturer choose a production strategy that emphasizes flexibility, consumer choice and quality or the one that emphasizes cost? While acquiring manufacturing flexibility is in itself a strategic decision to meet certain objectives, introduction of new manufacturing technologies inevitably requires a redefinition of the technical and environmental subsystems through adjustment to overall business strategy (Venk, 1990; Shani et. al., 1992).

In the context of new technologies, more relevant are the corporate strategy, technology strategy, marketing strategy, manufacturing strategy, competition strategy, investment strategy and a strategy to cope up with both environment and strategic uncertainty itself.

Starting with the observation that what is required is a vision of development path extending three to ten years into the future, for it will take as long as that to fully integrate advanced technologies into an effective element of corporate strategy. Technology strategy of a company is very often a determinant factor in adoption of particular FMS or flexible automation equipment. For example, in France, the industrialists opt for FMSs in order to reduce in process inventory. Another observation is that letting things evolve as new types of systems come into the market, is not satisfactory as a technology strategy. While Albin and Crefeld, (1994) discuss concurrent engineering as a technology strategy appropriate for many large and small companies, Parthasarthy and Sethi (1992) present a framework that explains the technology strategy-structure relationship in the context of current trends towards flexible automation.

In the context of flexible manufacturing systems, there exists a close relationship between different objectives of marketing strategy. For example, the strategic objective of responsiveness to customers' specifications is met by modification flexibility. The objective of maintaining or increasing market share is catered to by volume flexibility; meeting the customers' due dates is answered by rerouting flexibility, and that of product quality is met by material flexibility (Gerwin, 1993).

Some researchers recommend inducing customers by a company to expect more from the industry as a strategic game plan against its rivals (Skinner 1989, Gerwin 1993).

While some researchers have given a framework for manufacturing strategy the Japanese manufacturing strategy for this century is based on the concept of transforming themselves freely as and when the need arises (Hall and Lea, 1990). This is in consonance with the view that manufacturing strategy is about creating operating capabilities a company needs for the future and not about adopting JIT, TQM or some other three letter acronym (Hayes and Pisana, 1994).

The decision to invest in FMS projects is a strategic choice because it involves high costs and moderate risks (Choobineh, 1986). Some researchers have recommended large investments in labour education and organizational adaptation in order to exploit the full potential of a highly automated final assembly (Lindberg et. al., 1988; Sriram and Gupta, 1991).

Whereas Upton (1995) has discussed the role of flexibility as a strategy to acquire competitive advantage, it has been observed that technologies should be chosen on the basis of their contribution to the firm's competitive strategy. Fleury (1999) discusses the roles played by transnational corporations and their subsidiaries in the global competitive strategies chosen by them in the context of a developing country (Brazil).

Bacon et. al., (1994) discuss the strategic importance of early stage decisions in the context of high technology industries and Allaire and Firsirotu (1989) observe that to cope with strategic uncertainty, two things must be done help the firm shape its competitive environment and build in structural ways that make the firm responsive to unpredictable events.

The chronologically arranged exhaustive list of authors and their contributions to the issues discussed so far is given in table 1.

The Economic Issues

Although the traditional concept of economies of scale is being replaced by the notion of economies of scope (Goldhar and Jelinek, 1983 and 1985) and FMSs with high process flexibility could provide ways to eliminate this threat (Chen et. al., 1992), it has been observed that the current practice of justification of investment in the flexible manufacturing technologies is difficult because there exist only extremely weak methods for analysing the economic value of flexibility to the manufacturers. The prevailing practice of justifying investments in automated manufacturing is justification by faith.

Roller and Tombak (1993) observe that new manufacturing systems are changing the face of the manufacturing world and have widespread implications for industrial economics. The authors develop and analyse a model of multiple firms investment in one of two technologies: a technology dedicated to one product, and a new flexible technology. Ioannou and Sullivan (1999) have developed a two-stage approach for justifying capital investment in material handling systems (MHSs).

The Social Issues

A major factor worthy of consideration is the likely effect of implementation of FMS on employment levels within the engineering industry. Since one FMS can replace several stand-alone or dedicated machines, it is likely to reduce requirements for machinists and operators. On the other hand, in several of the companies surveyed, implementing FMSs was considered necessicity and a failure to do so was likely to herald reduced competitiveness and subsequent company decline (Sharma, 2001).

Consequently, the effect of FMT implementation on manufacturing industry employment remains an open question, depending upon whether unemployment in this sector is caused predominantly by labour shedding or plant closure. However, while discussing implementation strategies for automation, it has been observed that the employees should be looking forward to the change rather than fearing the loss of their jobs if it is a company policy that no layoffs will occur because of automation, the employees are even more encouraged. Rather, the expectation of individual and social growth, greater professionalism, more challenge, better fulfillment and other such aspects should be stressed. It thus appears that a balance must be struck between selecting new technologies that are most compatible with the existing social systems, and changing the social subsystems to accommodate requirements of new technology. In fact, this assumes all the more significance in the Indian context in our opinion. During our extensive and intensive surveys (Sharma, 2001), we discovered that the industrial scene has changed drastically during the last decade and it has changed for better. The Indian workers now realize that adopting confrontationist stance is self-defeating. Relative stability of the Indian economy has also contributed to it. We also discovered that layoffs are not much in evidence in the Indian manufacturing industry and at a south India based group (the TVS group of companies) many revolutionary and innovative changes are in progress, including flexible automation, and yet the company has a policy of not laying off its employees. Rather, it gainfully re-employs those employees who cannot be trained for high tech operations, in less demanding jobs.

State of the Research

Advances in computing, information management and communication technologies have made it possible to provide manufacturing system entities such as machines, transport vehicles and pallets, with intelligence and communication capabilities (Dharamraj and Wang, 1997). This allows the consideration of a new paradigm for shop floor control in which the system can be characterized as a collection of intelligent, autonomous entities capable of individual decision making on the basis of local information and communication with other entities. This alternative to shop floor control is also known as hierarchical control.

Another emerging area of the latest research is the development of a distributed control system consisting of a collection of autonomous agents or 'holons' as a model for operating the intelligent manufacturing system of the next century. Holonic Manufacturing System Consortium, which was made in 1993 and consists of companies from leading industrial nations (such as Hitachi Limited of Japan and Alien-Bradley Industrial Automation of US), is actively involved in this field of research for the last ten years. Researchers have investigated a variety of approaches such as game theory, predicate logic, automation theory and queuing theory for the design, analysis and control of distributed systems (Bond and Gasser, 1988; Conry et. al., 1991; Avouris and Gasser 1992, Martial 1992, Takizama et. al. 1993).

Waterson et. al., (1999) describe a survey of the current use and effectiveness of key modern manufacturing practices within the UK. They conclude that supply-chain partnering, TQM, team-based working, and integrated computer-based technology (such as CIM, CAD / CAM, FMS) are the most common, whereas total productive maintenance, outsourcing, concurrent engineering and manufacturing cells are the least used practices in Britain.

It was also found that learning culture, integrated computer based technology and empowerment are expected to be more in future, whereas outsourcing, manufacturing cells and concurrent engineering are predicted to experience less growth.

Limitations of the Existing Approaches

Inspite of having a rich literature, the generic concept of flexibility is not well understood even in the business world and there exists abundant confusion due to numerous definitions of flexibility. Because the measurement of flexibility is still a problem crying for a solution in a general sense, the issue remains unresolved in the context of manufacturing flexibility also.

Also, there is an urgent need to address process flexibility as no well accepted operationalisation of flexibility exists because:

* Multidimensionality of flexibility tangles the effort that must go into creating and testing scales and collecting data.

* Hierarchical levels, though permit the study of their flexibility and interchange of measures developed for one level with other levels, require collection of disparate data. This may mean that research results arrived at one level may not apply to others.

* Operationalisation of flexibility spanning many industries, and thus useful for research purposes, are much more difficult to be created. Often such efforts are confined to single industry only.

* In the Indian context, communication between formal or theoretical researchers and empirical researchers is almost non-existent.

* Measures based on physical characteristic of a manufacturing process often ignore a number of factors that determine flexibility.

* Excessive attention has been apportioned to the benefits of flexibility but little to the cost aspects, and this often results in recommending more flexibility than is economically appropriate.

* Methods of delivery have been scantly treated vis-a-vis the consequences of advanced manufacturing technology.

* It is no easy matter to measure the flexibility of equipment, as there are substantial problems from both a theoretical and purely empirical point of view.

* The difficulty in measuring the economic benefits resulting from manufacturing flexibility still remains one of the major problems.

* Measurement of flexibility in other types of systems is even more daunting as the interfacing of the human element makes it substantially tangled.

Notwithstanding a wide recognition of the momentousness of the requirements and performance of the communication and information systems in the context of FMT and FMSs, the work done in this direction till date can only be termed as nascent (Wang and Veeramani, 1994).

Rachamadugu and Stecke (1994) say that most FMSs do not handle multi parts types and scheduling in these flexible, but dedicated systems has received less attention than they merit.

Areas for Further Research

Further research is needed to the extent to which manufacturing flexibility influences overall company performance and verification of the extent of positive effects of an experience of CNC machines on rapidity of FMT diffusion. That the measure of the flexibility of FMT equipment and other aspects is a grey area crying for further research, needs no repetition.

Other areas related to FMSs and management of manufacturing flexibility and meriting further investigations include :

* FMS implementation in high volume and high variety operations (Rachamadugu and Stecke, 1994).

* FMS optimization models and efficient allocation of resources in such a system (Gupta, et. al. 1997; Tetzlaff, 1990).

* The location and use of FMSs within a multi product, multi echelon production system and the impact of production flexibility on product line design, range and mix, and profitability (Stecke and Naryan, 1995; Gupta et. al., 1997).

* Consideration of limited buffer space in FMS scheduling; impact of simultaneous loading and scheduling decisions on system performance; using artificial intelligence techniques to aid FMS scheduling and control; and investigation of simulated annealing techniques for parts in job shops (Rachamadugu and Stecke, 1994.

* Investigation into the impact of a flexibility of one type upon others (Chen et. al. 1992).

* Static and dynamic tooling policies in a general flexible manufacturing system (GFMS) (Hedin et. al. 1997)

* Dynamic, conflict-free routing of AGVs and rail-guided vehicles (RGVs), including the potential for multiple capacity vehicles (MCVs) (Oboth et. al. 1999; Lee and Maneesavet, 1999).

* Ramifications of emerging information technologies and their impact on manufacturing system development and operations (Shaw et. al. 1997).

Further research is needed in organizational, management of technology and management of change, and social aspects of manufacturing flexibility, which include:

* The gap between theory and practice on the subject of labour organization around the FMSs and establishing sound and normative conclusions on effective organizational forms for FMSs.

* Improving performance, especially with respect to task complexity and product variety, using workforce flexibility (Mc Creery and Krajewski, 1999).

* A very critical and major area of research is the likely effect of adoption and non adoption of flexible manufacturing technology on employment levels in the emerging automobile industry in The Indian context (Sharma, 2001)

* Further explorations into the interaction of human-computer systems with automated manufacturing systems especially in the Indian context (Sharma, 2001) Groover and Zimmers, 1984;

* More case studies to extract more information on the experiences of companies in the design, implementation, operation and future utility of FMSs (Sharma, 2001).

Conclusions

A selective review of available literature in the field brings out a few points relating to management of flexibility in manufacturing quite cogently. These include: paucity of tools to measure flexibility; lack of understanding of what to expect and what not to expect from the physical organs of manufacturing flexibility dearth of data based on actual case studies of organizations using flexibility in manufacturing; and the relatively less general appreciation of the fact that management of FMT and people are more important than the technology itself. Lack of models of local relevance to management of manufacturing flexibility, especially in a developing country like India, is even more conspicuous.

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O. P. Sharma

Assistant Professor

Department of Mechanical Engineering

Delhi College of Engineering

Bawana Road, Delhi-110042 (India)

Sushil

Professor

Department of Management Studies

Indian Institute of Terchnology, Delhi

Hauz Khas, New Delhi 110016 (India)

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