Advanced manufacturing technologies

International Journal of Operations & Production Management Advanced manufacturing technologies: Determinants of implementation success Godwin J. Udo, Ike C. Ehie,

Article information: To cite this document: Godwin J. Udo, Ike C. Ehie, (1996) "Advanced manufacturing technologies: Determinants of implementation success", International Journal of Operations & Production Management, Vol. 16 Issue: 12, pp.6-26, https:// doi.org/10.1108/01443579610151733 Permanent link to this document: https://doi.org/10.1108/01443579610151733

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Advanced manufacturing technologies Determinants of implementation success Godwin J. Udo


Tennessee Technological University, Cookeville, Tennessee, USA, and

Ike C. Ehie Southeast Missouri State University, Cape Girardeau, Missouri, USA

International Journal of Operations & Production Management, Vol. 16 No. 12, 1996, pp. 6-26. © MCB University Press, 0144-3577

Introduction The quest for lower operating costs and improved manufacturing efficiency has forced a large number of manufacturing firms to embark on advanced manufacturing technologies (AMTs) projects of various types. The dramatic developments in AMT at various organizational levels can be attributed to numerous benefits that improve the competitive position of the adopting companies. AMT impact not just manufacturing, but the whole business operations, giving new challenges to a firm’s ability to manage both manufacturing and information technologies. AMT include a group of integrated hardware-based and software-based technologies which, when properly implemented, monitored and evaluated, can improve the operating efficiency and effectiveness of the adopting firms. They encompass a broad range of computer-based technological innovations which include numerical control (NC) machine tools, cellular manufacturing, machining centres, industrial robots, computer-aided design and manufacturing (CAD/CAM) systems, and automated storage and retrieval systems (AS/RS). These “islands of automation” are integrated through advanced computing technology called computer-integrated manufacturing (CIM). AMT has the potential to improve operating performance dramatically and create vital business opportunities for companies which are capable of successfully implementing and managing them[1-4]. AMT can also provide distinctive competitive advantages in cost and process leadership[5]. Events of the last decade, such as the US productivity problems, Japanese manufacturing success stories and the competitive global economy, have moved manufacturing strategy and process technology issues from the bottom to the top of the firm’s priority list. The issues surrounding manufacturing technologies and their implementations have assumed greater importance in the manufacturing strategy debate[6]. Practitioners and researchers have developed strong interest in how AMT can be used as a competitive tool in the global economy. A growing number of organizations are


now adopting AMT to cope with recent phenomena in today’s competitive environment such as fragmented mass markets, shorter product life cycle and increased demand for customization[7]. Although AMT can help manufacturers compete under these challenging circumstances, they often serve as a double-edged sword, imposing organizational challenges while providing distinct competitive advantage when successfully implemented[8-10]. The benefits of AMT have been widely reported in the literature and can be classified as tangible and intangible[11-14]. The tangible benefits, which are easily quantifiable, include: inventory savings, less floor space, improved return on equity (ROE) and reduced unit cost of production. The intangible benefits, which are difficult to quantify, include: an enhanced competitive advantage, increased flexibility, improved product quality and quick response to customer demand. A list of these benefits, along with their literature sources, is presented in Table I. Although the benefits of AMT are numerous and have been found to be indicators of best practices in manufacturing, only a small proportion of companies adopting AMT have taken full advantage of these benefits. The rate at which these benefits are derived varies to a large extent from one company to another. Companies atlarge fall short of achieving those benefits that were perceived as being important in AMT adoption. Beatty[16] concludes that only half of those companies adopting AMT ever attain successful implementation. Among the reasons given for the lack of success include: technology mania, lack of top management’s continued support, poor commitment to shopfloor employees and inadequate managerial training for AMT projects[1,8,16,22]. Success in AMT implementation becomes a reality when the set of goals and objectives stipulated by the adoption strategy are fully realized. There have been discussions centred on AMT being introduced at a rate faster than that at which they can be adequately and realistically implemented. This has been attributed to lack of appreciation of the degree of complexity and challenge that such implementation might entail. Mize[22] strongly argued that AMT can be viewed as a strategy for enhancing and achieving the set goals and objectives of an organization; however, he cautioned that AMT adoption should be the means to an end and not vice versa. Furthermore, AMT should not be viewed as the panacea to all manufacturing problems. Based on the literature, the critical success determinants for AMT implementation were classified into four broad categories as follows: triple “C” factors, self-interest factors, housekeeping factors and literacy factors. These factors are presented in Table II. Among the reasons cited for AMT failures are: lack of developing an effective support system, lack of planning for a high level of system integration, lack of experience with modern technologies, inadequate understanding of new technologies and lack of top-management knowledge and support of AMT[16,43-45]. Total system integration rather than stand-alone technologies should be the key requirement in AMT success. The opportunities offered by AMT to deal with the emerging realities of the 1990s competitive environment are widely recognized, but concerns have also been expressed about the ability of firms to exploit them to their full advantage.

Implementation success in AMT 7

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Benefits Tangible benefits Improved return on equity Reduced inventory costs

8

Reduced set-up times


Reduced throughput times Lower fixtures and jig costs Reduced scrap rate Reduced floor space Reduced labour costs Reduced tooling costs Reduced amount of rework Intangible benefits Enhanced competitive advantage Adjust to shorter product life cycle Developed engineering/ management expertise Lower exposure to labour unrest Viewed as leader in the use of new technology Increased flexibility Improved manufacturing control Improved working conditions Quick response to design or process changeover Ability to introduce new product faster Better data management Quicker response to machine breakdown Improved response time to demand variations Improved product quality Table I. Benefits derived from AMT and their sources

Better control of parts

Literature sources

Gupta and Somer[15]; Choobineh[12]; Wemmerlov and Hyer[4] Kaplan[11]; King and Ramamurthy[1]; Beatty[16]; Sum and Yang[17]; Choobineh[12]; Wemmerlov and Hyer[4]; Redmond[14]; Ahmed et al.[17] Beatty[16]; Gupta and Somer[15]; Choobineh[12]; Wemmerlov and Hyer[4]; Redmond[14] Kaplan[11]; Sum and Yang[18]; Choobineh[12]; Wemmerlov and Hyer[4] Primrose and Leonard[13]; Choobineh[12]; Wemmerlov and Hyer[4]; Ahmed et al.[17] Kaplan[11]; Choobineh[12]; Ramamurthy and King[8]; Redmond[14] Kaplan[11]; Choobineh[12]; Wemmerlov and Hyer[4]; Ramamurthy and King[8] Beatty[16]; Choobineh[12]; Redmond[14]; Wemmerlov and Hyer[4]; Polakoff[19]; Ramamurthy and King[8] Primrose and Leonard[13]; Choobineh[12] Kaplan[11]; Choobineh[12] Sum and Yang[18]; Gupta and Somer[15]; Choobineh[12]; Ramasesh and Jayakumav[20] Choobineh[12] Choobineh[12]; Ahmed et al.[17]; Gunn[21]; Primrose and Leonard[13] Choobineh[12] Choobineh[12] Kaplan[11]; King and Ramamurthy[1]; Sum and Yang[18]; Dimnik and Johnston[3]; Ramasesh and Jayakumav[20] Primrose and Leonard[13]; Choobineh[12]; King and Ramamurthy[1] Beatty[15]; Choobineh[12]; Wemmerlov and Hyer[4]; Ahmed et al.[17] Kaplan[11]; Choobineh[12] Kaplan[11]; Choobineh[12]; Gupta and Somer[15]; Wemmerlov and Hyer[4] Choobineh[12] Choobineh[12]; Beatty[16] Kaplan[11]; Sum and Yang[18]; Primrose and Leonard[13] Choobineh[12]; Ahmed et al.[17] Kaplan[11]; Beatty[15]; Primrose and Leonard[13]; Wemmerlov and Hyer[4]; Ramamurthy and King[8]; Ramasesh and Jayakumav[20]; Gunn[21] Primrose and Leonard[13]; Choobineh[12]; Wemmerlov and Hyer[4]


Determinants Triple “C” factors Effective communications Sound co-ordination Strong co-operation from everyone Strong commitment Self-interest factors Employees’ morale Employees’ satisfaction with the project Belief that the AMT is for general interest Quick response to workers’ concerns Appropriate reward system Housekeeping factors Quality plan of action Teamwork Quality vendor support Quality technical support Detailed cost/benefit report AMT cost justification Business functions integration Effective facilitator Literacy factors Clear understanding of AMT capabilities Clear understanding of the business principles Understanding of the business system Effective training Clarity of AMT goals and objectives Appropriate level of expectations of the AMT

Sources

Badiru[23]; Green[24]; Helmes[25] Badiru[23]; Helms[25] Badiru[23]; Eckerson[26] Farhooman et al.[27]


Alter[28]; Brown et al.[29] Ramamurthy and King[8] Alter[28] Alter[28] Alter[28]; Snell and Dean[30] Currie[31]; Sarkis[32]; Beckert[33] Beatty[16]; Muscatello and Green[34]; Green[24] Ramamurthy and King[8]; Das and Goyal[32] Das and Goyal[35] Canada and Sullivan[36]; Grant et al.[9]; Attaran[37] Grant et al.[9]; Coulthurst[38] Liker et al.[39]; Gupta and Somers[15]; Attaran[37] Beatty[16]; Adair-Heeley[40] Bowman[41]; Beckert[33] Bowman[41]; Beckert[33] Beckert[33]; Attaran[37] Snell and Dean[30]; Udoka and Nazemetaz[42] Bowman[41] Attaran[37] Attaran[37]

The literature is replete with conceptual studies in support of the critical success factors as requirements for successful AMT implementation. However, to our knowledge, no studies have empirically examined the extent to which the critical success factors result to benefits accrued from AMT implementation. This study therefore proposes to investigate the extent to which the identified factors have effects on the benefits of AMT which ultimately lead to successful AMT implementation. The factors and potential benefits were identified through an extensive review of past studies. Proposed model One of the pioneering frameworks for the general evaluation of manufacturing and information technologies consists of objective measurement, expert observation and subjective judgement[45]. Given the use of a relatively large

Table II. Literature source of determinants of AMT success

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field test, subjective judgement was selected for this research because it requires fewer resources and is less time-consuming than the other methods. Subjective judgement requires AMT users to score their experiences by responding to a list of questions. Adelman and Donnell[45] also identified three phases of information technology evaluation: technical, subjective and empirical phases. The technical evaluation phase addresses the algorithms and input/output procedures in order to identify potential problems prior to actual use. The subjective evaluation phase focuses on evaluating AMT from the users’ perspective with the goals of assessing the effectiveness of the system and determining its strengths and weaknesses. The empirical evaluation phase focuses on measuring AMT performance. The present study represents a combination of the subjective and empirical evaluations phases. It assesses the perceptions of AMT users who are mostly plant or manufacturing managers. There have been conflicting opinions on the degree to which AMT benefits are being achieved by adopting firms. While some companies have been very successful at AMT implementation and therefore realized full benefits from AMT, others have reported less favourable results. It has been reported that as many as 70 per cent of AMT adopters fail in their quest to implement AMT[16,43]. King and Ramamurthy[1] found in their empirical study, involving 222 manufacturing companies, that a considerable gap exists between the firms’ expectations and their actual achievement of AMT benefits. This study proposes a predictive model that seeks to predict the success of AMT implementation by analysing the relationships between the determinants of AMT and the benefits realized from AMT. The proposed model is presented as Figure 1. It comprises 26 variables classified into six broad categories: (1) triple “C” factors; (2) self-interest factors; (3) housekeeping factors; (4) literacy factors; (5) tangible benefits; and (6) intangible benefits. AMT benefits The list of potential AMT benefits shown in Table I leads one to believe that successful AMT implementation can provide a business organization with a distinct competitive edge. In the strategic management area, manufacturing firms have widely accepted the fact that AMT may be useful in implementing leading edge corporate strategy. AMT have become a key part of competitiveness in the marketplace[12,15,18]. Based on the literature sources, there were ten tangible and 15 intangible benefits. Respondents were asked to rate the extent to which these benefits were acheived when implementing AMT using a five-point Likert scale ranging from strongly disagreed to strongly agreed. The benefits were combined into three tangible benefits – return on


Triple C: • Communication • Commitment • Co-ordination

Housekeeping: • Action plan • Effective team • Vendor support • Cost justification • Functions integration • Effective facilitator

Self-interest: • Employee morale • Satisfaction • Belief in AMT • Appropriate award

Literacy: • Understanding of AMT • Understanding of firm business • Training • Clear goals/objectives of AMT • Expectations about AMT

Implementation success in AMT Tangible benefits: • Improved return on equity • Reduced throughput time • Reduced production cost

11

Intangible benefits: • Improved quality • Better control • Quick response time • Improved work conditions • Competitive advantage

equity, reduced throughput time and reduced production costs, and five intangible benefits – improved quality, better operation control, quick response time, improved work conditions and competitive advantage. The coefficient of internal reliability (Cronbach’s alpha) for this construct was 0.96, which indicates a high level of validity construct. AMT determinants The AMT determinants were classified under four broad factors based on their characteristics. These are the triple “C” factors, self-interest factors, housekeeping factors and literacy factors. The triple “C” factors relate to the impact of effective communication, coordination and commitment on AMT implementation. Badiru et al.[23] reaffirm a widely-held view that effective communication, sound co-ordination and strong commitment from all chains of command within the organization are highly critical to successful implementation of an AMT project. This position was further supported by Green[24], Helms[25], Eckerson[26] and Adair-Heeley[40]. Beatty[16], in examining the “rule of the road” in AMT implementation, identified three factors that lead to AMT success, namely: effective project champion, system planning and integration, and organizational integration techniques. It was found that effective communication can have a major influence on AMT implementation. Helms[25]

Figure 1. AMT implementation predictive model

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identifies communication as a key element in successful implementation of JIT. It was further discovered that companies which have long-term perspectives of adopting AMT have better chances of success than companies which embark on AMT on the short term. A variety of environmental, structural and technological factors in a firm can facilitate or inhibit adoption, implementation and successful management of AMT[1]. Bessant[44] concluded that total system integration rather than stand-alone technologies is a key requirement in AMT success. The triple “C” factors were investigated by asking the respondents to indicate the extent to which the factors affect AMT implementation. These factors include: effective communication at the individual, inter-group and intra-group levels; commitment by top management, other managers and other workers; and co-ordination by the AMT project team and co-operation by everyone concerned in the project. The self-interest factors are those which personally affect the employees and relate to the degree to which employees have personal interests in AMT implementation. The factors considered include general employees’ morale, satisfaction levels, personal belief that AMT can lead to personal reward or benefits to the individual and equitable reward structures. Ramamurthy and King[1] maintained that no matter how attractive the benefits or the sophistication of technology, if personnel-related aspects (such as motivation, participation, reward schemes, etc.) are not adequately planned for, the end result of the AMT effort is bound to fail. People-oriented problems could prove to be more difficult to resolve than technical problems and could have serious consequences for AMT implementation. All facets of integrated manufacturing systems are positively related to both external and individual equitable rewards[30]. The economic impact of personal-related issues is higher under AMT than is found in traditional manufacturing systems. Employees’ morale problems can sabotage the effectiveness of AMT[29]. The cause of failure in CIM, an aspect of AMT, can be attributed to the fear and anxiety created in the workers. Alter[28] identified inertia, fear, self-interest and lack of enthusiasm as the four common traits leading to CIM failures. In general, those employees who view CIM as enhancing their individual interests and physical rewards tend to be more co-operative and will work to support and not thwart the efforts of AMT projects. Although AMT involves a great deal of automation, top management needs to provide support to shopfloor employees. These supports may be in the form of boosting the morale of the employees and convincing the workers that AMT can offer personal benefits and equitable rewards. Appropriate supervision and full commitment from all parties involved are also crucial. The self-interest factors include: high employee morale, employee satisfaction with the project, belief that AMT are in the general interest, an appropriate incentive and reward system, and belief that the AMT are timely and relevant. The housekeeping factors are the basic or “hygiene” conditions that must serve as a prelude to successful AMT implementation. Having them may not guarantee AMT success; however, not having these factors will certainly


thwart the efforts of AMT implementation. They involve managerial and technical support mechanisms that must be available to AMT implementors for successful AMT implementation. A major cause of the slow adoption of AMT and the disappointing performance gains by most companies is the failure to adapt to the organizational and work practices required by new technologies[16,46]. New manufacturing technologies have different implications for work design and organizational structures that are likely to necessitate alignment of the entire organization. Most AMT adopters have failed to realize this critical organizational issue[8,47]. Some of the adopters have become near-sighted in their decision making regarding AMT. One example is the traditional financial justification of AMT that is very limiting and restrictive because it has a short-term focus and completely ignores all subjective considerations[11,32,40]. The effectiveness of AMT implementation requires a detailed plan of action that would be based on teamwork and a participative rather than an authoritative style of management. The directed team should be moderated by an effective facilitator who should have the following characteristics: team-coaching abilities; working well through other people; and encouraging participation[16,44]. Liker et al.[39] found that lack of business integration was a major cause of problems in achieving the potential benefits of computer-aided design (CAD). The more the business functional units are integrated, the more the firm can realize the benefits of CAD. The literacy factors pertain to those educational efforts which make the employees become more familiar with AMT and their goals and objectives. The need for training has been greatly emphasized in the AMT literature. AMT success has been found to be correlated positively with comprehensive training and equitable rewards[30]. Bowman[41] investigated the causes of failure in JIT and found that lack of understanding of JIT and its goals and inappropriate expectations were major contributory factors to JIT failures. For AMT implementation to succeed, the employees must have a clear understanding of its principles, capabilities, goals and objectives. This understanding will make it possible for the expectations of AMT to be communicated appropriately to all the employees. Attaran[37] listed clarity of goals and appropriate expectations as prerequisites to the successful implementation of flexible manufacturing technology. Research method The survey instrument was developed based on an extensive review of the literature on AMT determinants and benefits. The instrument was designed to investigate which of the determinants have significant effects on the benefits realized. To improve on the relevance and readability, the instrument was pretested on a group of AMT users and managers located in the Mid-western region of the USA. Each participant in the pretest study demonstrated significant knowledge on AMT. The feedback obtained from the pretest study was used to refine the instrument significantly and make it more relevant to the objective and scope of the study. The survey instrument was subsequently


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mailed, along with a return postage envelope, to manufacturing firms in the USA. Firms were selected from the following three sources: Moody’s Industrial Manual[48], American Association of Manufacturing Technology (AAMT) and, 1993 Harris Directory on manufacturing companies[49]. The questionnaire was addressed to the plant/manufacturing manager of each firm. To ensure that the respondents have appropriate and adequate knowledge on AMT, each respondent was expected to meet the following conditions: to have been with the company for at least one year; and have at least six months’ experience of AMT implementation. Those respondents who did not meet these criteria were asked to indicate so and kindly return the questionnaire. This measure ensured that each respondent was familiar with AMT adoption in their organization and would provide a well-informed evaluation of the system in question. In a cover letter accompanying the questionnaire, the broad areas encompassing AMT were identified in order to place the definition of AMT in proper context. The respondents were assured anonymity to increase the objectivity of their responses. Demographic data Of the 400 questionnaires mailed out within continental USA, 117 responses were received for a response rate of 29 per cent. Twenty-seven questionnaires were discarded because the respondents either failed to complete the questionnaire in its entirety or they did not have sufficient experience and background in AMT. The remaining 90 (22.5 per cent) usable responses were included in the analysis. About 38 per cent of the respondents worked in a process-manufacturing environment while about 30 per cent operated in a repetitive-manufacturing environment. Almost 80 per cent of the respondents reported that AMT projects were initiated mostly by management rather than workers or vendors and, in almost all cases, AMT projects were directed by management rather than a steering committee or appointed individuals. Of the respondents, forty percent were top management, 38 per cent were middle management, and about 19 per cent belonged to ranks other than the senior/top management. Table III shows the descriptive information for the respondents. Data analysis A stepwise regression analysis was used to determine which of the individual variables (in each of the four categories) were significant in explaining each of the benefit measures. Table IV shows the Pearson correlation coefficients for the eight benefits (dependent variables), and each of the 18 factors thought to affect them (independent variables). Table V shows the regression coefficients and the corresponding R2 of the significant ( p < 0.05) factors, which represents the percentage of the variance in each dependent variable explained by the particular independent variable in the presence of other significant variables. For each of the eight benefit measures, the R2 represents the percentage of the variance in the ratings for a particular benefit which is explained by the


Value

Percentage

Manufacturing environment Process Discrete Repetitive Job shop Other

34 8 27 17 4

37.7 8.9 30.0 18.9 4.4

AMT project initiator Top management Other levels of management Worker(s) Vendor(s) Borrowed idea from a competitor Other Do not know

44 28 1 2 2 6 7

48.9 0.1 1.1 2.2 2.2 6.7 7.8

Project director Top management Other levels of management Steering committee Individual, self-appointed workers Do not know

36 36 6 2 10

40.0 40.0 6.7 2.2 11.1

Number of years in business 0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-over

17 15 19 5 5 5 6 18

18.7 16.5 20.9 5.5 5.5 5.5 6.6 19.8

Percentage of business automation 0-9 10-19 20-29 30-39 40-49 50-59 60-69 70 and over

13 15 11 10 6 14 8 13

14.4 16.7 12.2 11.1 6.6 15.4 8.8 14.4

Previous year’s revenue ($) Less than 5 million 5-20 million 21-50 million 51-100 million 101-200 million Over 200 million

6 15 17 15 11 26

6.7 16.7 18.9 16.7 12.2 28.9 (Continued)


Table III. The characteristics of the respondents ( N =90)

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Table III.

Value

Percentage

Number of full-time employees 200 or less 201-400 401-600 601-800 801-1,000 More than 1,000

24 15 16 7 3 25

26.6 16.7 17.8 7.8 3.3 27.8

Respondent’s employment with the firm Less than one year 1-5 years 5-10 years 10-20 years Over 20 years

6 19 23 23 19

6.7 21.1 25.5 25.5 21.1

Respondent’s rank Top management Middle management Lower management Staff/professional Other

36 34 5 12 3

40.0 37.8 5.5 13.3 3.3

ratings of a particular predictor variable. The regression model for predicting the benefit of return on equity has an R 2 factor of 57.57 per cent. The determinants (and their regression coefficients) of this benefit are communication (beta = 0.3732), faith in AMT (beta = 0.2474), action plan (beta = 0.1868), cost justification (beta = 0.1919) and AMT understanding (beta = 0.5093). The regression model for reduced throughput time was the weakest of all the eight models with an R2 factor of 35.01 per cent. The determinants of the benefits are commitment (beta = 0.2614), employee morale (beta = 0.2001), teamwork (beta = 0.1819) and clear goals and objectives (beta = 0.1777). The R2 factor for reduced cost is 54.97 per cent and the determinants include employee morale (beta = 0.3245), faith in AMT (beta = 0.2979), appropriate reward (beta = 0.1783), cost justification (beta = 0.2099), effective facilitator (beta = 0.3353) and business understanding (beta = 0.1983). The improved quality regression model has an R 2 factor of 54.12 per cent with the following determinants: employee morale (beta = 0.4081), appropriate reward (beta = 0.1623), support (beta = 0.1934), AMT understanding (beta = 0.3403) and training (beta = 0.2099). The enhanced competitiveness model has an R2 of 61.74 per cent with the following determinants: commitment (beta = 0.3562), faith in AMT (beta = 0.3722), cost justification (beta = 0.1845), function integration (beta = 0.3105) and business understanding (beta = 0.2190). The R2 factor for improved working conditions is 66.49 per cent and the determinants include commitment (beta = 0.2292), satisfaction (beta = 0.2153), appropriate reward (beta = 0.5803), cost justification (beta = 0.3143), functions integration (beta = 0.1899), effective facilitator (beta = 0.1823), clear goals and

0.1544 0.2869 0.1249

0.2430 0.2315 0.0580

0.1427 0.1024 0.1611 0.1675

0.1684 0.1721 –0.0428 0.1198 0.1314 –0.0947

–0.0802 0.2274 –0.0156 –0.0404 –0.0417

Triple “C” factors Communication Commitment Co-ordination

Self-interest factors Employee morale Satisfaction Faith in AMT Appropriate reward

Housekeeping factors Action plan Teamwork Support Cost justification Functions integration Effective facilitator

Literacy factors AMT understanding Business understanding Training Clear goals/objectives AMT expectations

Correlations ≥ 0.1990 are significant at p ≤ 0.05

0.2284 0.2148 0.0370 0.1211 0.0606

0.0627 0.1206 0.0278 0.0762 0.3091 –0.0717

0.1625 0.1619 0.1809 0.1316

Throughput

ROE

0.2316 0.1505 0.1185 0.1992 0.2530

–0.0746 0.0759 –0.0100 0.1810 0.1406 –0.6031

0.3715 0.1652 0.3899 0.3943

0.1877 0.1762 0.2343

Cost

–0.0023 0.0427 –0.0330 0.0755 –0.0147

0.1033 –0.0691 –0.1092 –0.2058 –0.0669 0.1697

0.0145 0.1141 0.2559 0.1712

0.1827 0.1525 0.2633

Quality

0.2502 0.2017 0.1410 0.2542 1.8200

0.1968 0.2187 0.0309 –0.0085 0.0801 0.3561

0.2785 0.3779 0.4198 0.0461

0.4027 0.3766 0.1775

Competitiveness

0.0434 0.0434 –0.1635 0.0957 –0.1035

–0.1639 –0.1479 –0.1976 –0.1492 –0.1555 0.0785

0.0695 0.1671 0.4057 0.0555

–0.0738 0.0726 –0.0999

Work conditions


0.1616 0.2205 –0.0375 0.1564 0.1522

–0.1231 0.0630 –0.1171 –0.0822 –0.0647 0.0329

0.2324 0.0269 0.3699 0.1300

–0.0035 0.0560 –0.0954

Control

0.0048 0.0709 –0.0392 0.0575 –0.2598

0.0329 0.1676 –0.1931 –0.0539 –0.0685 0.0264

0.0106 0.0096 0.1488 0.1428

0.2469 0.1041 0.0217

Quick response


Table IV. Pearson correlation coefficients of benefit indicators with predictor variables (N = 90)

Table V. Regression coefficients of the significant variables ( p < 0.05) 0.5757 0.3314 2.1110

Multiple R2

R2

Regression constant

0.5093

0.1919

0.1868

0.2474

0.3732

1.7610

0.2110

0.3501

0.1777

0.1819

0.2001

0.2614

Reduced throughput

2.0140

0.3021

0.4797

0.1983

0.2099

0.2979 0.1783

0.3245

2.6290

0.2929

0.5412

0.2099

0.3403

0.1934

0.1623

0.4081

Reduced Improved cost quality

1.9031

0.3812

0.6174

0.2190

0.1845 0.3105

0.3722

0.3562

Enhanced competitiveness

2.6570

0.4421

0.6649

0.3141 0.6737

0.3143 0.1899 0.1823

0.2153 0.5803

0.2292

Improved work conditions

2.6580

0.2674

0.5171

0.2103 0.3404 0.4065

0.1716

0.1986

0.2181

Better control

18

Triple “C ” factors Communication Commitment Co-ordination Self-interest factors Employee morale Satisfaction Faith in AMT Appropriate reward Housekeeping factors Action plan Teamwork Support Cost justification Functions integration Effective facilitator Literacy factors AMT understanding Business understanding Training Clear goals/objectives AMT expectations

Better ROE


3.2080

0.4315

0.6569

0.2429

0.4034 0.1593

0.2660

0.1425

0.1674

Quick response

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objectives (beta = 0.3141) and expectations about AMT (beta = 0.6737). This regression model has the most prediction power. This implies that improvement in work conditions could be the most significant benefit of AMT. It is important for management to commit resources to making the work environment more friendly for the worker. It is also interesting to note that the most important determinants of this benefit are expectations about AMT and appropriate reward structures for performances, both of which are employee-oriented variables. The implication for management is that ensuring a favourable people-oriented work environment can lead to greater benefits in a technologyoriented AMT environment. In this study, the firms that ensured good employees’ perception of the reward system and appropriate expectations about AMT stood to gain more than those firms that were lacking in these areas. The results in Table V also show that the variables included in this study explain 51.71 per cent of variance for better control of the system. These include: co-ordination (beta = 0.2181), faith in AMT (beta = 01986), teamwork (beta = 0.1716), AMT understanding (beta = 0.2103), business understanding (beta = 0.3404) and training (beta = 0.4065). Finally, the quick response model has an R 2 factor of 65.59 per cent and the following determinants: communication (beta = 0.1674), co-ordination (beta = 0.1425), satisfaction (beta = 0.260), teamwork (beta = 0.4034), support (beta = 0.1593) and training (beta = 0.2429). A summary of these factors and their benefits is presented in Table VI. Discussion of results The basic premiss of this study is to determine the predictive abilities of the AMT factors identified in the study in achieving success in AMT implementation as measured by both tangible and intangible benefits. A detailed account of which factors determine which benefits is given under the various factor categories. Triple “C” factors Communication plays a significant role in determining the benefits of improved return-on-equity (ROE) and quick response to customer demand. The more effective the communication during the implementation stages of AMT, the greater the ROE and the quicker the response to customer demand and manufacturing changes. Commitment significantly and positively affected the benefits of reduced throughput time, enhanced competitiveness and improved working conditions. Co-ordination also positively and significantly affected the benefits of better control and quick response. The results indicate that the more co-ordinated the activities are in AMT implementation, the better the manufacturing control, and the quicker the system response to ever-changing customer demands. These results confirm the fact that the triple “C” factors are critical to the successful implementation of AMT. However, it was also noted that the triple “C” factors did not indicate any significant effects on cost reduction.


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Table VI. Variances of the AMT benefit measures and regression coefficient of determinants

Benefit/factor Returning equity (ROE) Communication Faith in AMT Action plan Cost justification AMT understanding Reduced throughput times Commitment Employee morale Teamwork Clear goals/objectives Reduced cost Employee morale Faith in AMT Appropriate reward Cost justification Effective facilitator Business understanding Improved quality Employee morale Appropriate reward Support AMT understanding Training Enhanced competitiveness Commitment Faith in AMT Cost justification Function integration Business understanding Improved working conditions Commitment Satisfaction Appropriate reward Cost justification Functions integration Effective facilitator Clear goals/objectives Expectations about AMT Better control system Co-ordination Faith in AMT Teamwork AMT understanding Business understanding Training Quick response to customer demands Communication Co-ordination Satisfaction Teamwork Support Training

R2

β

0.576 0.373 0.247 0.187 0.192 0.509 0.350 0.261 0.200 0.182 0.178 0.550 0.325 0.298 0.178 0.210 0.335 0.198 0.541 0.408 0.162 0.193 0.340 0.210 0.617 0.356 0.372 0.184 0.310 0.220 0.665 0.229 0.215 0.580 0.314 0.190 0.182 0.314 0.634 0.517 0.218 0.199 0.172 0.210 0.340 0.406 0.656 0.167 0.142 0.266 0.403 0.159 0.243


Self-interest factors All of the self-interest factors were related to some if not all of the benefits. Four of the self-interest factors (employee morale, satisfaction, faith in AMT and appropriate reward) were related positively to all the benefit measures at the 0.05 level of significance. Employee morale related to reduced throughput time, reduced cost and improved quality. When employees’ morale is high, products will get through the manufacturing system faster and with higher quality. Brown et al.[29] observed that employees’ morale problems can sabotage the effectiveness of J IT implementation. Firms that reported high satisfaction with AMT implementation are the same ones that reported improvement in working conditions and quicker response to customer demands. Strong faith in AMT affected more benefits than any other factor in this category, namely: improved ROE, reduced cost, enhanced competitiveness, improved working conditions and better control. The implication of this result is that, before implementing AMT, the firm should spend time and resources to earn the commitment of the employees through positive belief and trust in AMT. Once employees have strong faith in AMT and perceive it to be in their best personal interest, many of the potential benefits can easily be realized. Equity reward structure positively affected the benefits of reduced cost and improved quality. In effect, if the workers perceive the reward system to be equitable and appropriate, their work habits will result in reduced production cost and increased product quality. Alter[28] mentioned that employees who believe CIM can enhance their interest and personal reward will work to aid rather than thwart its implementation. Housekeeping factors All six housekeeping variables were directly related (at the 0.05 level of significance) to every AMT benefit reported. The results clearly show that the housekeeping factors addressed in this study are important determinants of AMT benefits which subsequently would lead to successful implementation. For example, an action plan had a direct effect on improved ROE, while teamwork directly affected reduced throughput time, better control and quick response to the customer. An effective action plan can lead to improved ROE, more organized teamwork, reduced cycle time and quicker response to customer demand. Vendor and technical support directly affected the benefits of improved quality and quick response to customer. There was a general agreement among the respondents that the more robust and clearer the cost justification process, the more the AMT benefits of improved ROE, reduced cost, enhanced competitiveness and improved working conditions can be achieved[11,38]. If the benefits and cost of investment of AMT are properly discussed among all parties involved, the whole picture would be clearer, thereby reducing the odds for failure. The results in Table VI also shows that business functions integration can directly affect the benefits of enhanced competitiveness and improve working conditions. Where the business units work together to achieve the goals of the firm, the competitive position of the firm is likely to be stronger than if no integration and synergy exist among the


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business units. These results confirm those of Liker et al.[39] which indicated that lack of business integration is a major source of problems in achieving the potential benefits of computer-aided design (CAD) and that the more business functions are integrated, the more the firm can realize the benefits of CAD. Effective facilitator, which is the sixth factor in the housekeeping category, positively affected the benefits of reduced cost and improved working conditions. The respondents who perceived effective leadership or project champion also reported a reduction in production cost and positive changes in working conditions. This result is in agreement with the findings of other studies[10,20]. The logical conclusion here is that housekeeping factors are significant determinants of AMT benefits which serve as a precursor to AMT implementation success and, as such, top management needs to pay closer attention to these factors. Literacy factors Each of the five variables of the literacy group was found to be statistically significant to at least one of the eight AMT benefits. AMT understanding, which is a measure of how much of the AMT principles and purposes are understood by the respondents, significantly improved ROE. Business understanding played an important role in determining the benefits of reduced cost, enhanced competitiveness and better control. The greater the business understanding by the respondent, the more these benefits are realized. Training directly affected improved quality, better control and quick response to the customer. The implication here is that quality and effective training on AMT leads to increased knowledge in the areas of product quality, production control and quick response to customer demands and design changes. Furthermore, quality training can lead to mastery of the system and an increased sense of ownership and accomplishment on the part of the users. The results also indicated that those respondents who were made to understand clearly the goals and objectives of AMT were able to achieve reduced throughput time and improved working conditions during AMT implementation. The reasoning for these results could be that, since they had better understanding of the goals and objectives of AMT, the respondents used the system effectively to reduce throughput time while, at the same time, creating a more comfortable work environment for themselves. The last factor in this category, AMT expectations, directly affected the benefit of improved working conditions. In effect, the work environment can be improved if the employees have the correct level of expectations for AMT. Unfavourable working conditions could exist where the expectations of AMT are either overestimated or unclear. Brown et al.[29] came to the same conclusion when they found that one of the main causes of AMT failures was lack of appropriate expectations regarding AMT. Conclusions The objective of this study is to assess the determinants and benefits of AMT and to investigate the extent to which the determinants (identified through an extensive literature review) affect successful AMT implementation. This study


has some limitations common to survey studies. It is based on the subjective perception of the respondents; therefore, one should be careful when generalizing the results. Every attempt was made in the study to ensure that the respondents had an appropriate and adequate knowledge of AMT implementation. It is hoped that the results of this study will provide some insights to the growing body of knowledge on AMT implementation. The AMT determinants identified in this study were found to affect significantly AMT implementation measured through AMT benefits. AMT refer to a family of manufacturing technologies such as CAD/CAM, AS/RS, FMS, etc. Further work is needed to study the critical success factors in stand-alone technologies at the plant floor to determine how comparable the results would be with those presented in this study. Several practical implications can be drawn from the results of the study. Under triple “C” factors, commitment seemed to have a stronger impact than either communication or co-ordination. A likely interpretation is that, even with sound communication and effective co-ordination, without commitment on the part of management and workers to the course of AMT, the full benefit may not be achieved. Commitment is an inward state of mind that could be affected by external forces such as persuasion, involvement and realization of the necessity of the AMT project. The self-interest factor stands out in this study as the most critical determinant of AMT success. Employees’ morale affects the benefits of reduced throughput time, reduced cost and improved quality. Faith in AMT affects five of the eight benefits – namely improved ROE, reduced cost, enhanced competitiveness, work conditions and better control. The lesson for management from these results is that workers should be made to perceive AMT as a system that can yield personal gains to them rather than another technological “white elephant”. It is a mistake for management to assume that workers will find out on their own that AMT serve an individual’s interest as well as the firm’s interest. In firms where workers see reward systems as being equitable and satisfactory, AMT benefits can be achieved more easily and faster than in firms where workers have reasons to doubt the intentions of AMT. The importance of the housekeeping factor for the organization to derive AMT benefits calls for several things: a good action plan, an effective work team, vendor and technical support, robust, clear and believable cost justification, integration of business units and a dynamic facilitator. To achieve the benefits of reduced cost and improved working conditions, management has to appoint carefully a project leader who is capable of adopting a participative management style to create a sense of ownership among employees. Cost justification was found to be the most important predictor of benefit in this category. This is in agreement with Kaplan[11] when he correctly argued whether the benefits of CIM can be justified by faith alone. This factor directly affected four benefits measures: improved ROE, reduced cost, enhanced competitiveness and improved working conditions. A realistic cost-benefit analysis can challenge the workers to cut cost or alert them to the need to use


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the system in such a way as to recover the investment in AMT. A believable cost justification enables workers to become conscious of profit and loss issues and, as a result, the firm’s competitive position in the industry may be enhanced. However, this desirable mind-set can only be possible where integration exists among different units of the firm. The lesson for management, based on these results, is that for full realization of AMT benefits the house must be kept in order (basic hygiene factors must be in place) in terms of availability of work teams, cost justification and integrated business units. Every literacy factor considered in this study was found to be a significant predictor of one or more AMT benefits. This result suggests that educational activities should take place prior to, during and after AMT implementation. Employees with either direct or indirect involvement in the manufacturing system have to be educated on the principles, goals, purposes and capabilities of AMT. The workers should be assisted in setting their expectations about AMT by explaining to them what its capabilities and limitations are. Furthermore, management must raise user expectations of AMT in general and induce a positive attitude about AMT. Contrary to the opinion that AMT technology may be oversold, these results show that higher user explanations are directly related to many AMT benefits. The AMT environment demands that everyone should have a good knowledge of the entire business since all the units are now completely interdependent. The importance of training cannot be overemphasized because an advanced manufacturing factory requires a more educated and skilled workforce than the traditional factory. Investment in training pays off in terms of improved quality and better control. Updating the knowledge of the worker yields dividends in terms of increased ROE, reduced cost and quick response to customer demands. Educational activities must be an ongoing endeavour since AMT represents a dynamic system whose technology will continue to change. The winning firms will be those that keep pace with the changes by updating their workers’ knowledge through in-service and external training. References 1. King, W.R. and Ramamurthy, D., “Do organizations achieve their objectives from computerbased manufacturing technologies?”, IEEE Transactions on Engineering Management, Vol. 39 No. 2, 1992, pp. 129-41. 2. Youssef, M.A, “Getting to know advanced manufacturing technologies”, Industrial Engineering, Vol. 24 No. 2, 1992, pp. 40-42. 3. Dimnik, T.P. and Johnston, D.A., “Manufacturing managers and the adoption of advanced manufacturing technologies”, OMEGA, Vol. 21 No. 2, 1993, pp. 155-62. 4. Wemmerlov, U. and Hyer, N.L., “Cellular manufacturing in the US industry: a survey of users”, International Journal of Production Research, Vol. 27 No. 9, 1989, pp. 1511-30. 5. Hayes, R.H. and Wheelwright, S.C., Restoring Our Competitive Edge: Competing through Manufacturing, Wiley, New York, NY, 1984. 6. Voss, C., “Implementation of manufacturing technologies: a manufacturing strategy approach”, International Journal of Operations & Production Management, Vol. 6 No. 4, 1986, pp. 17-26.


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