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Adoption and implementation of advanced manufacturing technology in Singapore
intemationaljournalof
production economics ELSEVIER
Int. J. Production
Adoption
Economics
48 (1997) 7-19
and implementation of advanced manufacturing technology in Singapore Hongxin
Zhao,
Henry C. Co*
Broyhili School ofManagement, Gardher- Webb University. Boiling Springs, NC 28017. USA Received
1 February
1995; accepted
5 January
1996
Abstract This paper reports a survey of 1000 firms in Singapore about their adoption and impiementation of advanced manufacturing technology (AMT). Statistical analysis such as factor analysis and discriminant analysis were used to identify those “Successful factors” that contribute positively to adoption and implementation of advanced manufacturing technology. From the 27 “successful factors” studied, we showed that project team integrity, strategic planning and project championship, and technical knowledge are significant, and training at all levels is instrumental in reducing uncertainties in AMT implementation. The results also indicated that firm size and financial availability differentiate successful from unsuccessful firms in AMT adoption and implementation. Although firms with large financial resources are likely to be more successful, large firms, in terms of the number of employees, are not necessarily beneficial to AMT and implementation. Keywords: Advanced Technical knowledge.
manufacturing
technology;
Project team integrity;
1. Introduction
Manufacturing has always played a pivotal role in Singapore’s economic development. Today, the manufacturing sector still contributes more than a quarter to Singapore’s gross domestic product. Faced with rising labor cost, and competition from neighboring countries, industries in Singapore have been turning to advanced manufacturing technology (AMT). For example, between 1980 and 1987, the average annual growth rate of industrial robot in Singapore was a remarkable 70%. By
* Corresponding
author.
0925-5273/97/$17.00 Copyright SSDI 0925-5273(96)00042-4
0
Strategic
planning
and project championship;
1992, there were a total of 1600 robots in use. Today, Singapore has the second highest density of industrial robots (number of robots per direct worker) in the world [l, 21. Increasingly, industries have recognized that the timely positioning of advanced manufacturing technologies and improvements in the management of human resources are the key elements in competing favorably in the world market. However, too much attention has been paid to technical development and not enough to the adjustments needed in organizations to accommodate the technology (see, for instance, [3]). Although there is no shortage of qualitative analysis of the critical success factors in the adoption and implementation of AMT (see Section 2)
1997 Elsevier Science B.V. All rights
reserved
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H. Zhuo. H.C. Co./Ini.
J. Production
empirical studies showing any pattern of commonality of factors for successful implementation is still lacking. 1.1. Objectives of this study This research has been motivated by the works of Meredith et al. [4], which accentuated the need for further research in managing advanced manufacturing technology. A large number of factors have been documented in the literature as either facilitating or inhibiting the adoption of AMT. This paper examines these factors in the context of a newly industrialized country (NIC). There are two specific objectives : 1. to test empirically whether or not the critical success factors, identified in the context of developed countries, are relevant in the NICs, and 2. to identify and develop a taxonomy of the critical factors that best distinguish firms who were successful in adopting AMT from those who were less successful, 1.2. Motivation Jbr the study The literature on the implementation of advanced manufacturing technologies have been written in the context of developed countries, primarily the United States and Japan. There are, however, some compelling reasons to suspect that the factors affecting AMT adoption in industrialized countries may be different from those applicable to NICs. The reasons include: (a) Barriers in the transfer oj’ technology. Advanced manufacturing technologies in the NICs come primarily from developed countries. These technologies have been transferred mainly through the multinationals and through technical licensing agreements. The barriers inherent in the process of technology transfer may also hinder the adoption of AMT in the NICs. (b) Lower wage rate. One key benefit of AMT is the reduction of labor requirement. For years the comparative advantage among Asia’s “four little dragons” have been their relatively low cost but highly motivated workforce, and generous supply of raw materials. The low labor cost in these NICs
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often makes economic justification of automation projects difficult. (c) Size of$rms. In developed countries, manufacturing firms active in AMT adoption are typically large companies. The industrial structure in Singapore is very different from the developed countries. The industry is driven by a network of independently owned small manufacturing firms serving as subcontractors for component parts for a few large companies. These small companies are typically family-owned business with conservative views about investment. Large manufacturing firms are relatively rare. In our survey, for example, less than 11 O/oof the firms have 1000 or more employees. Small companies are generally constrained by limited financial resources to undertake ambitious AMT projects. (d) Paradigm of competition. The modern paradigms of competition have shifted from cost to quality, variety, and time (see [5]). Singapore, like the other NICs, generally compete in the global market on the basis of cost. Computercontrolled production systems offer a broader range of competitive advantages than mere cost reduction. In fact, the manufacturing cost may even be higher using these computer-controlled production systems. For example, a US manufacturer invested on two flexible manufacturing cells (FMC) in 1988 [6]. The labor-plus-overhead costs at the FMCs turned out to be 25”/0 higher! However, the FMCs allow the manufacturer to produce in small lots, following the just-in-time system (JIT). A business strategy based on the cost paradigm may discourage many firms in the NICs from implementing advanced manufacturing technologies. The following section reviews the literature pertinent to the management aspect of implementing AMT projects. As noted earlier, these have been written in the context of developed countries, primarily the United States and Japan.
2. Survey of related literature A survey of related literature shows that most studies on AMT adoption have been confined to anecdotal studies of automation projects, case
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analyses of successful implementation, and articles providing various insights on the prerequisites and benefits of successful AMT adoption. Our literature review covers two areas. First, we survey factors commonly documented in the literature as attributable to the successful adoption of AMT. From this survey, we identified twenty-seven “critical success factors” variables (see Appendix A). Because of space constraint, not all factors will be discussed in detail in the literature review. The second part of this literature survey focuses on the benefits of AMT. This survey provides us a list of nine “benefits” variables in our survey questionnaire (see Appendix B). 2.1. Success fuctors
of AMT
Based on a mail survey, Udoka and Nazemetz used cluster analysis to classify 43 AMT projects as successful or failure [7]. The authors used the established groupings to test the effects of 19 success factors on these projects. Out of the 19 success factors, 7 were found to be significant in differentiating the successful projects from the failures. These are: alignment of the core organizational systems with the corporate strategy, strategy formulation, existence of an education program, top-down planning and bottom-up implementation, pace of implementation, relevance of technology to particular application, and the alignment of strategy with the organizational culture. Most of 19 factors have been incorporated in Section A of our survey questionnaire. In a survey of 279 US firms in 1989, Gupta and Somers [8] found that the degree by which the 27 aggregated benefits from factor automation and the level of integration of the firm are significantly correlated Ferraro et al. [9] stressed that an increasing degree of integration in the use of factor information means that greater demands are being placed on the various functional elements in an organization to operate in an integrated manner [9]. Many managers show great foresight in making changes in manufacturing processes, but continue to think of them in terms of traditional organizational arrangements. Ferraro et al. also highlighted that mismatches often occur between the various levels of the organization. For exam-
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ple, manufacturing managers with expertise in operations often do not have adequate understanding of strategic issues. And conversely, top management do not have a full understanding of operational details. This often results in frustration as operation engineers are expected to meet unrealistic demands of top management. Ferraro et al. suggested that the project team should include members from various functional areas. Successful adoption of AMT requires that system planners are designers fully understand the corporate strategic goals and objectives. The system planners must direct factory automation projects to support these goals and objectives [lo]. Meredith [l l] found that the presence of a project champion is critical at the planning and implementing stages of the AMT project. If the leader is established politically in the company’s management structure, and understands the company’s business, then it is easier for the team to obtain the needed resources to ensure the success of the AMT project. A major problem hindering the success of factory automation is the shortage of suitable manpower. According to a mail questionnaire survey conducted by Nihon Keizai Shinbun, Inc. on 93 major manufacturing companies in Japan as report by Takanaka, 78% of the companies reported a shortage of staff capable to make system designs and plans at the corporate level and 69% reported a shortage of personnel for software development [12]. Snyder and Elliott [13] noted that the typical organizational structure of a company does not encourage long-term technical careers. To get the best talent to go into manufacturing related fields, corporations needed to place a new emphasis on manufacturing and put in place a career path that recognizes and rewards the technically minded individual. Technology alone will not improve a firm’s efficiency, it starts with management and people [14]. Education and training are crucial to successful implementation of AMT. Mize [IO] noted that management must recognize the critical nature of proper training and education, as experience has shown that between 25% to 40% of the total cost of an extensive automation project will be spent on education and training.
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H. Zhao, H. C. Co. JInt. J. Production
Many manufacturing firms experience resistance whenever a new technology is introduced. Continuing education and training help to ease the resistance to AMT adoption [15]. Chang [16] also noted that an organization can never realize such a change by simply hiring engineers and technicians with new technical expertise from outside. A long-term educational and training program should be designed and implemented to train the employees so that reallocation of the human resource for jobs requiring advanced technical expertise can be made possible. A common practice among manufacturing firms in the US is to hire external technical consultants to help design, evaluate, select and implement factory automation projects. A study by Huang and Sakurai [17] showed that 85.4% of Japanese companies surveyed do not rely on external consultants. Because of the cultural proximity of Japan and the NICs in Asia, conventional wisdom suggests that these NlCs may not find external consultants critical to the success of AMT. 2.2. Benejits
of’ AMT
Advanced manufacturing technology brings about many benefits. These include reduced labor [18], improved product quality 119, 201, increased product /process flexibility [ 19, 2 11, enhanced time efficiency [ 111, and shortened time-to-market [22]. A study of 20 flexible manufacturing systems (FMS) in the US showed that FMS can reduce the labor requirement by as much as 88% and the product cost by 25-75% [18]. Another study of 573 Japanese manufacturing firms by Huang and Sakurai provided a ranking of benefits realized in implementing factor automation [17]. Labor cost reduction tops the list, followed by quality improvement. Other benefits include flexibility, setup time reduction, utilization, productivity, inventory reduction, lead-time reduction, and marketing advantage. In 1991, Somers and Gupta [23] surveyed 268 US manufacturing firms and compared their results with the finding of Huang and Sakurai [ 171. Labor cost reduction is third on the list, preceded by quality improvement and leadtime reduction.
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Flexible automation enables the manufacturer to offer a far broader range of products by stimulating new product design, simplifying style changes, and making small production runs economical [ 191. A survey of 5 FMS installations indicated a reduction in lead time by 25% [l 11. Adjusting the production rate to accommodate seasonal demand is easier than adjusting the production rate of workers in a less automated, more labor-intensive manufacturing firm [21]. Moreover, AMT also improves product quality by minimizing human error, lightening process control, simplifying problem diagnostics, and automating the quality assurance procedures [24]. Contemporary engineering methods and practices can reduce setup time by as much as 90% or more. For example, at General Motors, automation reduced the time required to change a die in a large punch press from 6 h to 18 min [19]. Reducing setup time increases available capacity and flexibility to meet schedule changes, and lowers the economic order quantity. Computer-aided design (CAD) enhances process accuracy and repeatability, lowers defect rate, and improves product quality [19]. In computer-controlled manufacturing processes, valuable process data can be collected on-line for immediate analysis and for subsequent rectification [20]. Some companies have realized considerable payoffs from investing in advanced manufacturing planning and control (MPC) techniques such as manujhuring resources planning (MRP II). For example, Tennant company, in a two-layer period with its MPC system in place, reduced purchased inventory by 42”/0, increased production rate by 66X, and increased delivery promises met from 60% to 90% [25]. “Time to market” is one of the most critical factors in today’s business. Computer-integrated manufacturing (CIM) shortens the product life cycle by reducing the time required for firms to respond to changes in market demand, and accelerating the customers’ demand for quality to be incorporated into the product. The Allen-Bradley Company invested US $3.5 million on a pilot CIM cell in Twinsburg, OH, in 1986. The adoption of the CIM cell to assemble printed circuit boards (PCBs) for four Geographically remote engineer-
H.Zhao,
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ing departments reduced the engineering from 52 weeks to 26 weeks [22].
3. Methodology
J. Production
cycle time
and analysis
From the literature survey, we identified 27 critical success factors. While the list does not purport to capture all factors that affect successful implementation, it is nevertheless sufficiently comprehensive to provide a greater understanding and a framework within which to develop and empirically test the proposition listed above. 3.1. Survey
instrument
We used mail survey to collect data from companies selected from the directories of the Singapore Manufacturers’ Association (SMA) and the Automation Applications Center (AAC) in Singapore. The questionnaire has three parts. Section A consists of 27 questions covering various critical success factors (See Appendix A. The management variables). In Section B, the respondents were asked to assess the degree by which they have benefited from the implementation of AMT (See Appendix B. The benefits of AMT). Section C serves to profile the respondents, such as number of employees, fixed assets, number of R&D personnel, and annual sales, etc. (See Appendix C). For each item in the questionnaire, subjects responded to a five-point Likert-type scale where 1 = strongly disagree and 5 = strongly agree. The 5point scale provides sufficient alternatives along the continuum for respondents to express their opinion. A reliability analysis was employed to assess the reliability of the scales and to screen the data for clerical errors or misinterpretations. To identify succintly generalizable pattern of factors accountable for differentiating between successful and unsuccessful AMT adoption, the following two-step statistical analysis procedure was employed : Step 1: Factor analysis. Because a fairly large number of variables (There 27 variables listed in Section A of the questionnaire) were collected from the survey, significant intercorrelations among some variables were expected. While these indi-
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vidual variables were useful for comprehending the views shared by the respondents, it would be cumbersome to interpret all 27 variables simultaneously. In order to identify a set of underlying dimensions of the factors, and to increase interpretability, we applied factor analysis on two groups of variables separately : strategic management variables and the infrastructure variables. The sample size met certain criteria for factor analysis [26]. The rule of “eigen value greater than 1” was applied to determine the number of factors to be extracted. The factor score derived from this analysis were then used together with firm-specific variables in the discriminate analysis. Step 2 : Discriminan t analysis. The experience of firms investing in AMT has not been uniformly positive. Some firms achieved the intended benefits from AMT, while others have been slow to benefit from it. In justifying the implementation of AMT, a firm typically cite one or more of the “AMT benefits” listed in Section B of the survey questionnaire. In our analysis, firms with a mean score of 4 points or better on any of the nine performance (Section B of the questionnaire) variables was categorized into the “successful” group. The others were used as the contrast group, i.e., firms that are “less successful”. Discriminant analysis was used to relate the factors from step 1 to the two groups. We decided not to use the average score of all nine benefit variables in classifying the respondents because many of these benefit variables represent mutually independent goals. For example, a firm may set its goal on improving quality, and not consider the project a failure if the setup cost is not reduced. Taking the average of a score of 5 for quality and 0 for set up cost may lead to the wrong conclusion that the AMT project is a failure.
4. Results 4.1. Response
rate
Table 1 summarizes the response vey. One thousand questionnaires of which were found to have a activities, and are excluded in our
rate of the surwere sent, 197 manufacturing study. Of the
H. Zhao. H.C. Co./Int.
12 Table 1 Response
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48 (1997)
Table 2 Profile of respondents
rate of survey
Number of questionnaires Firms no longer exist Distributors and traders Manufacturing firms No AMT in the last 5 yr AMT in the last 5 yr Usable questionaries Declined to participate
Economics
mailed
N
Percentage
1000 65 132 803 313 490 110 380
100 6.5 13.2 80.3 31.3 49.0 11.0 38.0
7-19
(N= 110)
Employees (SIZE) < 1000 Fixed asset (ASSET) < S$8 1000 Engineers (ENGR) < 100 Annual sales (SALES) < S$15 Million
remaining 803 manufacturing firms surveyed, 313 firms have not implemented AMT in the last 5 yr. Among the remaining 490 firms, 380 declined to participate in our survey. This left us with 110 usable responses. Hence, the actual usable response constitute 22.5% of the firms relevant to our study. 4.2. Projile of responding jirms Previous studies suggested that firm-specific variables such as size of firm, annual sales, etc. have bearings on the introduction of new technology [27]. We included seven demographic variables in Section C of the questionnaire. The first six are used to explain the difference between the successful and the not-so-successful groups of firms. The last variable is included to ensure that the respondents are indeed from the middle or top management. These seven variables are listed in Appendix C. The variable SECTOR identifies the industrial
Metal
- li Shipbuilding Material Plastic
Electrical
Automation
Mach in. -
Fig. 1. Industry
Petroleum
classifications.
- 1%
Handling Product
- 3% - 4%
Equip. - 4%
sumer Products
. Other - g%
Percentage
98 54 99 44
89 49 90 40
groups of the respondent. Fig. 1 shows the breakdown by industrial classification. Firms engaged in electronic products and electrical machinery represented 49*X, while firms in fabricated metal products ranked second. accounting for 17’s of responding firms. This is consistent with the actual distribution of manufacturing firms in Singapore. Table 2 summarizes the demographic profile of the surveyed firms. The variable SIZE measures the number of employees. The respondent firms are relatively small firms, in terms of the number of employees. More than 89% of these firms have less than 1000 employees. The variable ENGR measures the number of engineers and technicians employed by the firms. It is interesting to note that 40 (36.4%) of the firms surveyed has less than 10 engineers and technicians. Only 11 (10.0”Y0) firms have more than 100 engineers and technicians, while the rest of the 59 (53.6%) firms have between 10 to 100 of these employees. Consistent with the size of the firms (measured by the total number of employees), the following shows that the surveyed firms are also relatively small in terms of their fixed assets (ASSET). About half of the firms surveyed have fixed assets of less than S$8 million.
Eiectronlcs - 38%
Fabricated
N
- 5%
8 Chemical - 8%
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The variable R&D measures the annual R&D expenditures of the firms. Seventy-five percent of the surveyed firms did not response to this question. One possible explanation for the lack of response is that R&D expenditure is considered by many to be highly sensitive and confidential inforForty percent of the surveyed firms mation. reported annual sales turnover (SALES) of less than S$15 million. This is again consistent with the fact that most of the surveyed firms are small manufacturing firms. The respondents of this survey (TITLE) are mainly in middle or top management. This affirms the reliability and validity of the data obtained. Table 3 summarizes the respondents’ evaluation of the success factors relevant to AMT adoption.
Table 3 Mean and rank of critical Critical
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As shown, not all success factors suggested in the literature were viewed important by the respondents. The factors that are ranked in the top 7 have mean scores above 4.30. These are variables pertinent to strategic management. Variables associated with organizational design were ranked low by the respondents. For instance, the organization and composition of the project team was ranked 22, while the need to reorganized ranked 25. The rankings shown in Table 3 are consistent with the results in [17]. Note that the factor “need for external consultants” ranked last. This agrees with Huang and Sakurai’s findings about Japanese companies not relying on external consultants
[171.
success factors
success factor
Degree of financial support Degree of alignment of the core organizational systems with the corporate strategy Understanding the potential contribution of AMT to current operations Degree of management commitment and support Well-defined objectives of AMT adoption Degree of effective alignment of employee attitudes with corporate objectives Degree of willingness of top management to take short-term risks for long-term improvement Pace of implementation Selecting the appropriate technology supplier(s) Position of the AMT champion in the organization Existence of an AMT champion Degree of top-down planning and bottom-up implementation Nature of the relationship between the technology supplier(s) and the user firm Degree of turnover of the project team members Degree of availability of hands-on training program to employees after implementation Active participation by in-house engineers Degree of specialized technical training is very important Need for long-term automation objectives Training programs must be maintained throughout the process of implementation Do not disband the project team until the new technology is absorbed by the organization Need for team members to be familiar with the new technologies Organization and composition of the project team Existence of an employee education program prior to AMT implementation Degree to which organizations obtained experience with a pilot project prior to implementation Need to reorganize Need to revise policies and procedures Need for external consultants
Mean
Std. dev.
Rank
4.55 4.55
0.52 0.55
1 2
4.53 4.46 4.35 4.35 4.32
0.57 0.54 0.60 0.55 0.69
3 4 5 6 I
4.30 4.29 4.23 4.22 4.16 4.15 4.14 4.13
0.63 0.65 0.59 0.77 0.78 0.70 0.12 0.58
8 9 10 11 12 13 14 15
4.13 4.11 4.11 4.08 4.07
0.58 0.64 0.72 0.56 0.70
16 17 18 19 20
4.02 3.97 3.97 3.88
0.68 0.58 0.70 0.8 1
21 22 23 24
3.77 3.71 2.99
0.79 0.81 0.74
25 26 27
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4.3. Results of factor analysis
pherable pattern (see Appendices D and E). In order to facilitate our understanding and interpretation of these variables, factor analysis, based on varimax rotation, was employed. The objective was to obtain a fewer dimensions that reflect succinctly the relationships among sets of many of these interrelated variables. Tables 4 and 5 summarize the results of the factor analysis. A pattern of success factors emerged
The twenty-seven variables reported in this paper and studied in past literature demonstrate a complex phenomena involving almost every aspects of the management of AMT. Neither the results in Table 3 nor the intercorrelation coefficients of both strategic management variables and the infrastructure variables indicated any deciTable 4 Varimax-rotated
matrix
of strategic
management
Variables support
Manufacturing strategy TM designated key people Financial support by TM TM’s willingness for short-term risk TM support for implementation Well trained team Team maintained throughout project Trunover of team minimized Long-term objective Top-down planning AMT champion Interdisciplinary approach Management knowledge of AMT Well-defined AMT Properly placed implementation Pilot project Eigenvalue Percent of cumulative variance
Table 5 Varimax-rotated
matrix
of infrastructure
Variables
Eigenvalue Percent of cumulative
variables Strategic AMT team
Integrety & Champion
Planning knowledge
Magt. Project
Pilot
(11
(21
(31
(4)
(51
0.76365 0.72761 0.59193 0.52159 0.39205 0.71154 0.67649 0.58612 0.68878 0.63690 0.58563 0.76102 0.64911 0.54282 3.47 21.7
variance
1.74 32.5
1.51 42.0
0.782 1.17 57.2
1.27 49.9
variables Instit. support
Adjusted organizational structure Revised policies and procedures Participation of in-house engineer Seeking consultation Close relationship with vendors Selection criteria Attitude towards AMT General knowledge of employees Continued knowledge updating All level training prior implementation All level training post implementation
7-19
Vendor
selection
Technical
knowedge
All-level training
0.78931 0.76850 0.70449 0.51282 0.86509 0.82220 0.50669 0.791 0.676 0.889 0.538 2.69 24.5
1.66 39.7
1.31 51.6
1.05 61.1
H.Zhao. H. C. Co./Int. J. Production Economics 48 (1997)
from the factor analysis of 27 variables. The pattern indicated nine dimensions of managing AMT project. Sixteen (16) strategic variables reflected the multifaceted nature of the strategic construct of AMT adoption, and a set of five underlying dimensions of AMT adoption was identified from the 11 infrastructure variables. The first factor, “strategic support”, is highly correlated (in terms of factor loading) with the first 5 variables, and all indicate the necessity of commitment of top management. The second factor, “integrity of the AMT project team”, consists of three variables with factor loading above 0.55, reflecting the consistency and stability of the project team member. The third factor, labeled “championship and planning”, loaded highly on four variables that mirror the push-effect of long-term planning and project championship. The fourth factor, “management knowledge”, comprises of three variables with factor loading greater than 0.50. Note that the last factor consists of only one variable claiming the necessity of pilot project prior implementation of AMT. The five factors accounted for 57.2%, of the total variance. The first of the four factors derived from infrastructure variables is labeled “institutional support”, with four variables highly loaded. The second factor reflects “vendor selection and the general attitudes of employees towards AMT”. “Technical knowledge of employees” composed of two variables with high factor loading greater than 0.65. “All-level of training at firm level” reflect the constant infusion of new knowledge and new ideas related to AMT. These four factors accounted for 61.1% of total variance. Table 6 Standardized
canonical
discriminant
function
coefficients”
Factors
Coefficients
Wilk’s lamda
Sig.
Team integrety Planning & champion Technical knowledge All-level training SIZE SALE
0.44407 0.55088 0.53777 -0.34465 -0.37691 0.87736
0.92575 0.90024 0.87251 0.84583 0.82583 0.81674
0.0058 0.0058 0.0040 0.0027 0.0024 0.0035
Correctly
classified
a All these factors
65.35%.
Eigen value
are significant
= 0.225
at 0.01 ‘%Ilevel
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15
4.4. Results of discriminant analysis The discriminant analysis offers some insights in the identified factors critical to successful adaptation of AMT. Table 6 shows that “project team integrity”, “strategic planning and project “technical knowledge” were championship”, significantly to the successful use of AMT. AMT brings about significant changes to every aspect of the business operation. Thus, strategic management and project leadership are crucial to the success of AMT adoption. The findings suggest that firms that adhered to strategic planning and had a committed project champion were more likely to achieve the expected results from AMT. The results show that a firm with a well-trained project team, and low turnover of team membership, are essential to AMT adoption and implementation. Project team with low attrition rate could insure the stability of the project, and attests to the smooth implementation of the project. As expected, the factor “general technical knowledge of employees” is also significantly associated with successful AMT implementation. This result indicates that the success of AMT not only depends on the personnel who are directly involved with the project, but also on firm-wide recognition and support of all employees. However, “all-level training” turned out to be negative in achieving the expected performance of AMT. This result is counterintuitive since we expect training at all level to be conducive to the AMT adoption and implementation. One explanation of this unexpected result may be the high intercorrelations between “all-level training” and “technical knowledge”, as indicated in Table 3 of the Appendix (variables 2-5). With regards to firm-specific variables, firm size and financial ability are significant factors. It is expected that firms that have a large pool of resources can generate sufficient revenue to afford adopting AMT, and thereby achieve the expected performance. The negative relationship between the firm’s size and the performance of AMT is expected, since AMT is technology- and information-intensive, rather than labor intensive. It is also shown in Table 6 that the model predicted correctly in 33 out of 51 cases in the “less successful” group (64.7%) and 33 out of 50 cases
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in the “successful firms” group (66%). The overall percentage of correctly classified firms was 66.34%. To examine further the effectiveness of the model, discriminant scores derived from the discriminant function was also used in the analysis of variance. The variability between successful and less successful firms is significantly large (F==2.937; P < 0.01)
5. Conclusion Firms in industrially advanced countries, particularly the United States and Japan, led the world in developing and utilizing advanced manufacturing technology. Industries in the NICs are gradually recognizing the strategic importance of the technologies. Albeit extensive research in the US and Japan on the success factors in adopting and implementing AMT, less is understood whether and how these factors related to the objectives of AMT. This survey of manufacturing firms in Singapore provided further evidence for the critical success factors in AMT adoption and implementation. Our empirical analysis confirmed that the critical success factors, identified in the context of developed countries, are also relevant in Singapore. Moreover, consistent with Huang and Sakurai’s findings [17], the survey showed that as in Japan, firms in Singapore do not find external consultants as critical to the success of AMT. This may be due to the cultural proximity of the two
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countries. The discriminant analysis suggested that project team integrity, strategic planning and project championship, and technical knowledge are critical to achieving the expected performances. The findings suggested that employee training at all levels was not contributing to the success of AMT implementation. However, this unexpected result deserves further investigation. Our study also found that firm-specific variables such as size of firm, annual sales, etc. have significant bearings on the introduction of new technology. One motivation for this study is the suspicion that the firm size in the NICs are generally small, and therefore factors critical in developed countries may not apply in the NICs. The results show that the firm-size factor (measured in terms of the number of employees) and the financial-availability factor (measured in terms of sales) differentiate the successful from the less successful firms in AMT adoption and implementation. Large firms have not been as successful as firms with less than 100 employees. However, firms with large financial resources were found to be more successful. This may appear to be a contradiction since “large” firms are expected to have more financial resources than “small” firms. However, manufacturing firms with large financial resources in Singapore do not necessarily employ a large labor force. Faced with rising labor cost, and competition from neighboring countries, many labor-intensive operations in Singapore have migrated steadily to neighboring countries such as Malaysia, Indonesia and China.
Appendix A. Section A of the questionnaire (critical success factors) Al. A2. A3. A4. A5. A6. A7. AZ. A9. AlO.
degree of alignment of the core organizational systems with the corporate strategy degree of financial support degree of management commitment and support understanding the potential contribution of AMT to current operations and what new technologies can achieve existence of well-defined objectives of AMT adoption pace of implementation position of the AMT champion in the organization need for team members to be familiar with the new technologies degree of willingness of top management to take short-term risks for long-term improvements degree of turnover of the project team members
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degree of top-down planning and bottom-up implementation the project team should not be disbanded until the new technology is absorbed by the organization objectives A13. need for long-term automation A14. existence of an AMT champion obtained experience with a pilot project prior to A15. degree to which organizations implementation and composition of the project team A16. organization A17. degree of effective alignment of employee attitudes with corporate objectives of hands-on training program to employees after implementation A18. degree of availability vendor(s) A19. selecting the appropriate throughout the process of implementation A2Q. training programs must be maintained from in-house engineers in system design A21. need active participation A22. existence of an employee education program prior to AMT implementation between the technology supplier and the user firm A23. nature of the relationship A24. degree of specialized technical training is very important A25. need to reorganize A26. need to revise policies and procedures A27. need for external consultants
All. A12.
Appendix B. Section B of the questionnaire Bl. B2. B3. B4. B5. B6. B7. B8. B9.
(benefits of AMT)
reduction in labor cost improvement of product quality enhancement of product/process flexibility reduction of manufacturing lead-time reduction in work-in-process inventory reduction of setup time improvement in factory utilization improvement in productivity provide for competitive advantage in marketing
Appendix C. Section C of the questionnaire SECTOR SIZE ENGR ASSET R&D SALES TITLE
(firm profile)
industry grouping total number of employees total number of engineers and technicians fixed assets annual R & D expenditure in Singapore dollars (S$) annual sales turnover for last fiscal year job title of person answering the survey questionnaire
Appendix D Means, standard deviations,
Manufacturing strategy Long-term objective Top-down planning Management knowledge Well-defined AMT
Variables I 2. 3. 4. 5.
of strategic management 9
10
I1
0.2567 0.1382 0.3888” 0.1625 0.1677 0.3518** 0.0099 0.2834* 0.3684** 0.5554*
12
variables 8
0.2777* 0.2798’ 0.1617 0.0163 0.0448
7
0.2287* 0.1602 0.0475
8
0.2759* 0.0885
9
0.5810**
10
15
I
0.3141** 0.2282* 0.2503* 0.1009 0.0483 0.0946
6
0 3764** 0:3226** 0.1753 0.0793
14
6
0.3403** 0.1152 0.1425 0.2521* 0.0780 0.24X1* 0.2078
variables
0.5505** 0.4233** 0.2028 0.1630 0.0447
13
5
0.3462** 0.2198 0.2545’ 0.0716 0.2916: 0.3255** 0.2038 0.1456
4
0.0840 0.1896 0.1699 0.0638 0.1714 0.0583 0.1105 0.3537 0.1727
of infrastructure
0.70 0.72 0.59 0.52 0.69 0.54
3
0.2190 0.0333 0.1608 0.0784 0.0827 0.0986 0.1643 0.1708 0.0459 0.1485
5
2
0.395X** 0.1844 0.1783 0.1296 0.1416 0.0799 0.0466 0.3014** 0.2506* 0.2403* 0.3X21**
4
1
3
0.2578* 0.1264 0.1921 0.1343 0.1257 0.2224 0.1020 0.1624 PO.1035 0.1401 0.0470 0.2218 0.1709
s.d.
2
0.2954** 0.1043 0.2576* 0.0967 0.0095 0.1446 0.1252 0.1053
Means
1
0.1586 0.2901* 0.3232** 0.0782 0.1127 0.1964 0.0193 0.1502 0.1756
0.64
s.d.
0.1820 0.2289* 0.2209 0.1814 0.0414 0.0912 0.1137 0.0620 0.1901 0.3725**
0.55 0.72 0.78 0.57 0.59 0.63 0.89 0.77 0.85
and intercorrelations
of AMT
6. Properly placed implementation Pilot project AMT champion Interdisciplinary approach Team trained with technology Team retained throughout project Turnover of team minimized TM designated key people Financial support by TM
7. 8. 9. 10. Il. 12. 13. 14.
Means
0.55 0.57 0.70 0.68 0.56 0.79 0.80 0.67 0.73 0.70 0.65
0.2480* 0.0905 0.1581 0.1959 0.0383 -0.0529 0.3293** 0.0118 0.1092 0.2279* 0.1712 -0.0205 -0.0717 0.2X57* 0.2563: 0.1473 0.1412 0.0358 0.3248’ ‘* 0.1246 0.1200 0.1876 0.1363 0.1018 0.2346* 0.1932 0.0101 0.2070 0.1426 0.0580 0.0276 -0.0493 -0.0178 0.1236 0.1471 -0.1314 0.0973 0.1937 0.1789 0.0863 0.1863 0.0368 0.2483* 0.0341 0.0202 0. I429 0.2413* 0.0929 0.1916 0.1292 0.2851: 0.2160 0.089 I 0.1078
4.34 4.12 3.91 4.01 4.01 3.71 3.70 4.12 2.99 4.14 4.29
4.56 4.11 4.16 4.52 4.34 4.30 3.87 4.22 3.67 4.1 I 4.07 4.13 4.22 455 4.32 4.46
and intercorrelations
15. TM willingness for short-term risk 16. TM support for implementation
deviations.
Signif: *=O.Ol. ** =O.OOl
Appendix E Means, standard
Attitudes towards AMT General knowlege of employees Training prior implementation Continued knowledge updating Training post implementation Adjusted organizational structure Revised policies and procedures Participation of in-house engineer Seeking consultation Close relationship with vendors Setting up vendor selection criteria
Variables 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. Sigmf: *=O.Ol, ** =O.OOl.
H.Zhao,
H. C. Co. JInt. J. Production
References HI Maddox,
M., 1991. Automating future growth. Singapore Bus., lS(3): 2638. and some PI Sin, G.T.T., 1992. Development of automation broad-base workforce implications: the Singapore perspective. Paper presented at the Conf. Organizational and Workforce Management Issues in Automation: CrossCultural Perspectives, Singapore, 25-27 August 1992. M. and Get-win, D., 1982. Coping with i31 Blumberg, advanced manufacturing technology. Proc. 8th Annual Conf., European International Business Association, Fontainebleau, France, December 1982. [41 Meredith, J., Hyer, N.L., Gerwin, D., Rosenthal, S.R. and Wemmerlov, U., 1986. Research needs in managing factory automation. J. Oper. Mgmt., 6(2): 203-218. [51 Stalk, G., Jr. and Hout, T.M., 1990. Competing Against Time. The Free Press, New York. WI Co, H.C., 1992. Streamlining the material flow in flexible manufacturing systems: a lesson in simplicity. Int. J. Prod. Res., 30(7): 1483-1499 [71 Udoka, S.J., and Nazemetz, J.W., 1990. An empirically based analysis of the requirements for successful implementation of advanced manufacturing technology (AMT). Comput. Ind. Eng., 19(14): 13lll35. 181 Gupta, Y.P. and Somers, T.M., 1991. Factory automation and integration of business functions. J. Manuf. Systems, 12(l): 15-23. 191 Ferraro, R.A., Hunley, T.E. and Shackney, O.Y., 1988. Banishing management barriers to automation. Manuf. Eng., January: 4448. PO1 Mize, J.H., 1987. Success factors for advanced manufacturing systems, in: K. M. Blache (Ed.), Success Factors for Implementing Change: A Manufacturing Viewpoint. Society of Manufacturing Engineers, Dearborn, Ml. the automated factory. [Ill Meredith, J., 1987. Implementing J. Manuf. Systems, 6(l): l-13. H., 1991. Critical success factors in factory WI Takanaka, automation. Long Range Planning, 24(4): 29-35. v31 Snyder, K.R. and Elliott, C.S., 1988. Barriers to factory automation: what are they, and how can they be surmounted? Ind. Eng., 4451.
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[I41 Siebeneicher,
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P.R., 1987. Educated, Trained employees are key to success for today’s businesses. Ind. Eng., March. I151 Beatty, C.A. and Gordon, J.R.M., 1988. Barriers to the implementation of CAD/CAM systems. Sloan Mgmt. Rev.. Summer: 25-33. [I61 Chang, C.H., 1989. A new perspective on realization of computer-integrated manufacturing. Manuf. Rev., 2(2): 82-9 1. [I71 Huang, P.Y. and Sakurai, M., 1989. An assessment of factory automation in Japan: a general mail survey. Manuf. Rev., 2(3): 162-168. for [I81 Hayes, R.H. and Jaikumar, R., 1991. Requirements successful implementation of new manufacturing technologies. J. Eng. Technol. Mgmt., 7: 169-175. factory: justification 1191 Attaran, M., 1989. The automated and implementation. Bus. Horizon, May-June: 80-86. Mirror, [201 Poo, A.N., 1990. A case for Further automation. January: 10-12. Pll Willis, R.G. and Sullivan, K.H., 1984. CIMS in perspective: costs, benefits, timing, payback periods are outlined. Ind. Eng., February: 28-35. P21 Co, H. and Flowers, A.D., 1990. A case-study on computer integrated manufacturing. Paper presented at February 1990 Automation Forum sponsored by NEMA in Cleveland, OH, 1990. 1231 Somers, T. and Gupta, Y.P., 1991. Factory automation: U.S. versus Japanese experiences. Manuf. Rev., 3, 4: 157-166. for FMS ~241 Badiru, A.B., 1990. Analysis of data requirements implementation is critical to success. Ind. Eng., October: 29-32. ~251 Vollmann, T. E., Berry, W. L. and Whybark, D. C., 1993. Manufacturing Planning and Control Systems, 3rd ed. Irwin, Homewood, p. 3. J.F., Anderson, R.E., Tatham, R.L. and [261 Hair, Grablowsky, B.J., 1979. Multivariate Data Analysis, Petroleum, Oklahoma. commitment ~271 Munro, H. and Norri, H., 1988. Measuring to new manufacturing technology: integrating technological push and marketing pull concepts. IEEE Trans. Eng. Mgmt., 35(2): 63-70.
production economics ELSEVIER
Int. J. Production
Adoption
Economics
48 (1997) 7-19
and implementation of advanced manufacturing technology in Singapore Hongxin
Zhao,
Henry C. Co*
Broyhili School ofManagement, Gardher- Webb University. Boiling Springs, NC 28017. USA Received
1 February
1995; accepted
5 January
1996
Abstract This paper reports a survey of 1000 firms in Singapore about their adoption and impiementation of advanced manufacturing technology (AMT). Statistical analysis such as factor analysis and discriminant analysis were used to identify those “Successful factors” that contribute positively to adoption and implementation of advanced manufacturing technology. From the 27 “successful factors” studied, we showed that project team integrity, strategic planning and project championship, and technical knowledge are significant, and training at all levels is instrumental in reducing uncertainties in AMT implementation. The results also indicated that firm size and financial availability differentiate successful from unsuccessful firms in AMT adoption and implementation. Although firms with large financial resources are likely to be more successful, large firms, in terms of the number of employees, are not necessarily beneficial to AMT and implementation. Keywords: Advanced Technical knowledge.
manufacturing
technology;
Project team integrity;
1. Introduction
Manufacturing has always played a pivotal role in Singapore’s economic development. Today, the manufacturing sector still contributes more than a quarter to Singapore’s gross domestic product. Faced with rising labor cost, and competition from neighboring countries, industries in Singapore have been turning to advanced manufacturing technology (AMT). For example, between 1980 and 1987, the average annual growth rate of industrial robot in Singapore was a remarkable 70%. By
* Corresponding
author.
0925-5273/97/$17.00 Copyright SSDI 0925-5273(96)00042-4
0
Strategic
planning
and project championship;
1992, there were a total of 1600 robots in use. Today, Singapore has the second highest density of industrial robots (number of robots per direct worker) in the world [l, 21. Increasingly, industries have recognized that the timely positioning of advanced manufacturing technologies and improvements in the management of human resources are the key elements in competing favorably in the world market. However, too much attention has been paid to technical development and not enough to the adjustments needed in organizations to accommodate the technology (see, for instance, [3]). Although there is no shortage of qualitative analysis of the critical success factors in the adoption and implementation of AMT (see Section 2)
1997 Elsevier Science B.V. All rights
reserved
8
H. Zhuo. H.C. Co./Ini.
J. Production
empirical studies showing any pattern of commonality of factors for successful implementation is still lacking. 1.1. Objectives of this study This research has been motivated by the works of Meredith et al. [4], which accentuated the need for further research in managing advanced manufacturing technology. A large number of factors have been documented in the literature as either facilitating or inhibiting the adoption of AMT. This paper examines these factors in the context of a newly industrialized country (NIC). There are two specific objectives : 1. to test empirically whether or not the critical success factors, identified in the context of developed countries, are relevant in the NICs, and 2. to identify and develop a taxonomy of the critical factors that best distinguish firms who were successful in adopting AMT from those who were less successful, 1.2. Motivation Jbr the study The literature on the implementation of advanced manufacturing technologies have been written in the context of developed countries, primarily the United States and Japan. There are, however, some compelling reasons to suspect that the factors affecting AMT adoption in industrialized countries may be different from those applicable to NICs. The reasons include: (a) Barriers in the transfer oj’ technology. Advanced manufacturing technologies in the NICs come primarily from developed countries. These technologies have been transferred mainly through the multinationals and through technical licensing agreements. The barriers inherent in the process of technology transfer may also hinder the adoption of AMT in the NICs. (b) Lower wage rate. One key benefit of AMT is the reduction of labor requirement. For years the comparative advantage among Asia’s “four little dragons” have been their relatively low cost but highly motivated workforce, and generous supply of raw materials. The low labor cost in these NICs
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48 (1997)
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often makes economic justification of automation projects difficult. (c) Size of$rms. In developed countries, manufacturing firms active in AMT adoption are typically large companies. The industrial structure in Singapore is very different from the developed countries. The industry is driven by a network of independently owned small manufacturing firms serving as subcontractors for component parts for a few large companies. These small companies are typically family-owned business with conservative views about investment. Large manufacturing firms are relatively rare. In our survey, for example, less than 11 O/oof the firms have 1000 or more employees. Small companies are generally constrained by limited financial resources to undertake ambitious AMT projects. (d) Paradigm of competition. The modern paradigms of competition have shifted from cost to quality, variety, and time (see [5]). Singapore, like the other NICs, generally compete in the global market on the basis of cost. Computercontrolled production systems offer a broader range of competitive advantages than mere cost reduction. In fact, the manufacturing cost may even be higher using these computer-controlled production systems. For example, a US manufacturer invested on two flexible manufacturing cells (FMC) in 1988 [6]. The labor-plus-overhead costs at the FMCs turned out to be 25”/0 higher! However, the FMCs allow the manufacturer to produce in small lots, following the just-in-time system (JIT). A business strategy based on the cost paradigm may discourage many firms in the NICs from implementing advanced manufacturing technologies. The following section reviews the literature pertinent to the management aspect of implementing AMT projects. As noted earlier, these have been written in the context of developed countries, primarily the United States and Japan.
2. Survey of related literature A survey of related literature shows that most studies on AMT adoption have been confined to anecdotal studies of automation projects, case
H.Zhao,
H.C. Co./Int.
J. Production
analyses of successful implementation, and articles providing various insights on the prerequisites and benefits of successful AMT adoption. Our literature review covers two areas. First, we survey factors commonly documented in the literature as attributable to the successful adoption of AMT. From this survey, we identified twenty-seven “critical success factors” variables (see Appendix A). Because of space constraint, not all factors will be discussed in detail in the literature review. The second part of this literature survey focuses on the benefits of AMT. This survey provides us a list of nine “benefits” variables in our survey questionnaire (see Appendix B). 2.1. Success fuctors
of AMT
Based on a mail survey, Udoka and Nazemetz used cluster analysis to classify 43 AMT projects as successful or failure [7]. The authors used the established groupings to test the effects of 19 success factors on these projects. Out of the 19 success factors, 7 were found to be significant in differentiating the successful projects from the failures. These are: alignment of the core organizational systems with the corporate strategy, strategy formulation, existence of an education program, top-down planning and bottom-up implementation, pace of implementation, relevance of technology to particular application, and the alignment of strategy with the organizational culture. Most of 19 factors have been incorporated in Section A of our survey questionnaire. In a survey of 279 US firms in 1989, Gupta and Somers [8] found that the degree by which the 27 aggregated benefits from factor automation and the level of integration of the firm are significantly correlated Ferraro et al. [9] stressed that an increasing degree of integration in the use of factor information means that greater demands are being placed on the various functional elements in an organization to operate in an integrated manner [9]. Many managers show great foresight in making changes in manufacturing processes, but continue to think of them in terms of traditional organizational arrangements. Ferraro et al. also highlighted that mismatches often occur between the various levels of the organization. For exam-
Economics
48 (1997)
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9
ple, manufacturing managers with expertise in operations often do not have adequate understanding of strategic issues. And conversely, top management do not have a full understanding of operational details. This often results in frustration as operation engineers are expected to meet unrealistic demands of top management. Ferraro et al. suggested that the project team should include members from various functional areas. Successful adoption of AMT requires that system planners are designers fully understand the corporate strategic goals and objectives. The system planners must direct factory automation projects to support these goals and objectives [lo]. Meredith [l l] found that the presence of a project champion is critical at the planning and implementing stages of the AMT project. If the leader is established politically in the company’s management structure, and understands the company’s business, then it is easier for the team to obtain the needed resources to ensure the success of the AMT project. A major problem hindering the success of factory automation is the shortage of suitable manpower. According to a mail questionnaire survey conducted by Nihon Keizai Shinbun, Inc. on 93 major manufacturing companies in Japan as report by Takanaka, 78% of the companies reported a shortage of staff capable to make system designs and plans at the corporate level and 69% reported a shortage of personnel for software development [12]. Snyder and Elliott [13] noted that the typical organizational structure of a company does not encourage long-term technical careers. To get the best talent to go into manufacturing related fields, corporations needed to place a new emphasis on manufacturing and put in place a career path that recognizes and rewards the technically minded individual. Technology alone will not improve a firm’s efficiency, it starts with management and people [14]. Education and training are crucial to successful implementation of AMT. Mize [IO] noted that management must recognize the critical nature of proper training and education, as experience has shown that between 25% to 40% of the total cost of an extensive automation project will be spent on education and training.
10
H. Zhao, H. C. Co. JInt. J. Production
Many manufacturing firms experience resistance whenever a new technology is introduced. Continuing education and training help to ease the resistance to AMT adoption [15]. Chang [16] also noted that an organization can never realize such a change by simply hiring engineers and technicians with new technical expertise from outside. A long-term educational and training program should be designed and implemented to train the employees so that reallocation of the human resource for jobs requiring advanced technical expertise can be made possible. A common practice among manufacturing firms in the US is to hire external technical consultants to help design, evaluate, select and implement factory automation projects. A study by Huang and Sakurai [17] showed that 85.4% of Japanese companies surveyed do not rely on external consultants. Because of the cultural proximity of Japan and the NICs in Asia, conventional wisdom suggests that these NlCs may not find external consultants critical to the success of AMT. 2.2. Benejits
of’ AMT
Advanced manufacturing technology brings about many benefits. These include reduced labor [18], improved product quality 119, 201, increased product /process flexibility [ 19, 2 11, enhanced time efficiency [ 111, and shortened time-to-market [22]. A study of 20 flexible manufacturing systems (FMS) in the US showed that FMS can reduce the labor requirement by as much as 88% and the product cost by 25-75% [18]. Another study of 573 Japanese manufacturing firms by Huang and Sakurai provided a ranking of benefits realized in implementing factor automation [17]. Labor cost reduction tops the list, followed by quality improvement. Other benefits include flexibility, setup time reduction, utilization, productivity, inventory reduction, lead-time reduction, and marketing advantage. In 1991, Somers and Gupta [23] surveyed 268 US manufacturing firms and compared their results with the finding of Huang and Sakurai [ 171. Labor cost reduction is third on the list, preceded by quality improvement and leadtime reduction.
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48 (1997)
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Flexible automation enables the manufacturer to offer a far broader range of products by stimulating new product design, simplifying style changes, and making small production runs economical [ 191. A survey of 5 FMS installations indicated a reduction in lead time by 25% [l 11. Adjusting the production rate to accommodate seasonal demand is easier than adjusting the production rate of workers in a less automated, more labor-intensive manufacturing firm [21]. Moreover, AMT also improves product quality by minimizing human error, lightening process control, simplifying problem diagnostics, and automating the quality assurance procedures [24]. Contemporary engineering methods and practices can reduce setup time by as much as 90% or more. For example, at General Motors, automation reduced the time required to change a die in a large punch press from 6 h to 18 min [19]. Reducing setup time increases available capacity and flexibility to meet schedule changes, and lowers the economic order quantity. Computer-aided design (CAD) enhances process accuracy and repeatability, lowers defect rate, and improves product quality [19]. In computer-controlled manufacturing processes, valuable process data can be collected on-line for immediate analysis and for subsequent rectification [20]. Some companies have realized considerable payoffs from investing in advanced manufacturing planning and control (MPC) techniques such as manujhuring resources planning (MRP II). For example, Tennant company, in a two-layer period with its MPC system in place, reduced purchased inventory by 42”/0, increased production rate by 66X, and increased delivery promises met from 60% to 90% [25]. “Time to market” is one of the most critical factors in today’s business. Computer-integrated manufacturing (CIM) shortens the product life cycle by reducing the time required for firms to respond to changes in market demand, and accelerating the customers’ demand for quality to be incorporated into the product. The Allen-Bradley Company invested US $3.5 million on a pilot CIM cell in Twinsburg, OH, in 1986. The adoption of the CIM cell to assemble printed circuit boards (PCBs) for four Geographically remote engineer-
H.Zhao,
H. C. Co.lInt.
ing departments reduced the engineering from 52 weeks to 26 weeks [22].
3. Methodology
J. Production
cycle time
and analysis
From the literature survey, we identified 27 critical success factors. While the list does not purport to capture all factors that affect successful implementation, it is nevertheless sufficiently comprehensive to provide a greater understanding and a framework within which to develop and empirically test the proposition listed above. 3.1. Survey
instrument
We used mail survey to collect data from companies selected from the directories of the Singapore Manufacturers’ Association (SMA) and the Automation Applications Center (AAC) in Singapore. The questionnaire has three parts. Section A consists of 27 questions covering various critical success factors (See Appendix A. The management variables). In Section B, the respondents were asked to assess the degree by which they have benefited from the implementation of AMT (See Appendix B. The benefits of AMT). Section C serves to profile the respondents, such as number of employees, fixed assets, number of R&D personnel, and annual sales, etc. (See Appendix C). For each item in the questionnaire, subjects responded to a five-point Likert-type scale where 1 = strongly disagree and 5 = strongly agree. The 5point scale provides sufficient alternatives along the continuum for respondents to express their opinion. A reliability analysis was employed to assess the reliability of the scales and to screen the data for clerical errors or misinterpretations. To identify succintly generalizable pattern of factors accountable for differentiating between successful and unsuccessful AMT adoption, the following two-step statistical analysis procedure was employed : Step 1: Factor analysis. Because a fairly large number of variables (There 27 variables listed in Section A of the questionnaire) were collected from the survey, significant intercorrelations among some variables were expected. While these indi-
Economics
48 (1997)
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11
vidual variables were useful for comprehending the views shared by the respondents, it would be cumbersome to interpret all 27 variables simultaneously. In order to identify a set of underlying dimensions of the factors, and to increase interpretability, we applied factor analysis on two groups of variables separately : strategic management variables and the infrastructure variables. The sample size met certain criteria for factor analysis [26]. The rule of “eigen value greater than 1” was applied to determine the number of factors to be extracted. The factor score derived from this analysis were then used together with firm-specific variables in the discriminate analysis. Step 2 : Discriminan t analysis. The experience of firms investing in AMT has not been uniformly positive. Some firms achieved the intended benefits from AMT, while others have been slow to benefit from it. In justifying the implementation of AMT, a firm typically cite one or more of the “AMT benefits” listed in Section B of the survey questionnaire. In our analysis, firms with a mean score of 4 points or better on any of the nine performance (Section B of the questionnaire) variables was categorized into the “successful” group. The others were used as the contrast group, i.e., firms that are “less successful”. Discriminant analysis was used to relate the factors from step 1 to the two groups. We decided not to use the average score of all nine benefit variables in classifying the respondents because many of these benefit variables represent mutually independent goals. For example, a firm may set its goal on improving quality, and not consider the project a failure if the setup cost is not reduced. Taking the average of a score of 5 for quality and 0 for set up cost may lead to the wrong conclusion that the AMT project is a failure.
4. Results 4.1. Response
rate
Table 1 summarizes the response vey. One thousand questionnaires of which were found to have a activities, and are excluded in our
rate of the surwere sent, 197 manufacturing study. Of the
H. Zhao. H.C. Co./Int.
12 Table 1 Response
J. Production
48 (1997)
Table 2 Profile of respondents
rate of survey
Number of questionnaires Firms no longer exist Distributors and traders Manufacturing firms No AMT in the last 5 yr AMT in the last 5 yr Usable questionaries Declined to participate
Economics
mailed
N
Percentage
1000 65 132 803 313 490 110 380
100 6.5 13.2 80.3 31.3 49.0 11.0 38.0
7-19
(N= 110)
Employees (SIZE) < 1000 Fixed asset (ASSET) < S$8 1000 Engineers (ENGR) < 100 Annual sales (SALES) < S$15 Million
remaining 803 manufacturing firms surveyed, 313 firms have not implemented AMT in the last 5 yr. Among the remaining 490 firms, 380 declined to participate in our survey. This left us with 110 usable responses. Hence, the actual usable response constitute 22.5% of the firms relevant to our study. 4.2. Projile of responding jirms Previous studies suggested that firm-specific variables such as size of firm, annual sales, etc. have bearings on the introduction of new technology [27]. We included seven demographic variables in Section C of the questionnaire. The first six are used to explain the difference between the successful and the not-so-successful groups of firms. The last variable is included to ensure that the respondents are indeed from the middle or top management. These seven variables are listed in Appendix C. The variable SECTOR identifies the industrial
Metal
- li Shipbuilding Material Plastic
Electrical
Automation
Mach in. -
Fig. 1. Industry
Petroleum
classifications.
- 1%
Handling Product
- 3% - 4%
Equip. - 4%
sumer Products
. Other - g%
Percentage
98 54 99 44
89 49 90 40
groups of the respondent. Fig. 1 shows the breakdown by industrial classification. Firms engaged in electronic products and electrical machinery represented 49*X, while firms in fabricated metal products ranked second. accounting for 17’s of responding firms. This is consistent with the actual distribution of manufacturing firms in Singapore. Table 2 summarizes the demographic profile of the surveyed firms. The variable SIZE measures the number of employees. The respondent firms are relatively small firms, in terms of the number of employees. More than 89% of these firms have less than 1000 employees. The variable ENGR measures the number of engineers and technicians employed by the firms. It is interesting to note that 40 (36.4%) of the firms surveyed has less than 10 engineers and technicians. Only 11 (10.0”Y0) firms have more than 100 engineers and technicians, while the rest of the 59 (53.6%) firms have between 10 to 100 of these employees. Consistent with the size of the firms (measured by the total number of employees), the following shows that the surveyed firms are also relatively small in terms of their fixed assets (ASSET). About half of the firms surveyed have fixed assets of less than S$8 million.
Eiectronlcs - 38%
Fabricated
N
- 5%
8 Chemical - 8%
H.Zhao.
H.C.
Co./Int.
J. Production
The variable R&D measures the annual R&D expenditures of the firms. Seventy-five percent of the surveyed firms did not response to this question. One possible explanation for the lack of response is that R&D expenditure is considered by many to be highly sensitive and confidential inforForty percent of the surveyed firms mation. reported annual sales turnover (SALES) of less than S$15 million. This is again consistent with the fact that most of the surveyed firms are small manufacturing firms. The respondents of this survey (TITLE) are mainly in middle or top management. This affirms the reliability and validity of the data obtained. Table 3 summarizes the respondents’ evaluation of the success factors relevant to AMT adoption.
Table 3 Mean and rank of critical Critical
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48 (1997)
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13
As shown, not all success factors suggested in the literature were viewed important by the respondents. The factors that are ranked in the top 7 have mean scores above 4.30. These are variables pertinent to strategic management. Variables associated with organizational design were ranked low by the respondents. For instance, the organization and composition of the project team was ranked 22, while the need to reorganized ranked 25. The rankings shown in Table 3 are consistent with the results in [17]. Note that the factor “need for external consultants” ranked last. This agrees with Huang and Sakurai’s findings about Japanese companies not relying on external consultants
[171.
success factors
success factor
Degree of financial support Degree of alignment of the core organizational systems with the corporate strategy Understanding the potential contribution of AMT to current operations Degree of management commitment and support Well-defined objectives of AMT adoption Degree of effective alignment of employee attitudes with corporate objectives Degree of willingness of top management to take short-term risks for long-term improvement Pace of implementation Selecting the appropriate technology supplier(s) Position of the AMT champion in the organization Existence of an AMT champion Degree of top-down planning and bottom-up implementation Nature of the relationship between the technology supplier(s) and the user firm Degree of turnover of the project team members Degree of availability of hands-on training program to employees after implementation Active participation by in-house engineers Degree of specialized technical training is very important Need for long-term automation objectives Training programs must be maintained throughout the process of implementation Do not disband the project team until the new technology is absorbed by the organization Need for team members to be familiar with the new technologies Organization and composition of the project team Existence of an employee education program prior to AMT implementation Degree to which organizations obtained experience with a pilot project prior to implementation Need to reorganize Need to revise policies and procedures Need for external consultants
Mean
Std. dev.
Rank
4.55 4.55
0.52 0.55
1 2
4.53 4.46 4.35 4.35 4.32
0.57 0.54 0.60 0.55 0.69
3 4 5 6 I
4.30 4.29 4.23 4.22 4.16 4.15 4.14 4.13
0.63 0.65 0.59 0.77 0.78 0.70 0.12 0.58
8 9 10 11 12 13 14 15
4.13 4.11 4.11 4.08 4.07
0.58 0.64 0.72 0.56 0.70
16 17 18 19 20
4.02 3.97 3.97 3.88
0.68 0.58 0.70 0.8 1
21 22 23 24
3.77 3.71 2.99
0.79 0.81 0.74
25 26 27
H. Zhao, H.C. Co.jInt. J. Production Economics 48 (1997)
14
4.3. Results of factor analysis
pherable pattern (see Appendices D and E). In order to facilitate our understanding and interpretation of these variables, factor analysis, based on varimax rotation, was employed. The objective was to obtain a fewer dimensions that reflect succinctly the relationships among sets of many of these interrelated variables. Tables 4 and 5 summarize the results of the factor analysis. A pattern of success factors emerged
The twenty-seven variables reported in this paper and studied in past literature demonstrate a complex phenomena involving almost every aspects of the management of AMT. Neither the results in Table 3 nor the intercorrelation coefficients of both strategic management variables and the infrastructure variables indicated any deciTable 4 Varimax-rotated
matrix
of strategic
management
Variables support
Manufacturing strategy TM designated key people Financial support by TM TM’s willingness for short-term risk TM support for implementation Well trained team Team maintained throughout project Trunover of team minimized Long-term objective Top-down planning AMT champion Interdisciplinary approach Management knowledge of AMT Well-defined AMT Properly placed implementation Pilot project Eigenvalue Percent of cumulative variance
Table 5 Varimax-rotated
matrix
of infrastructure
Variables
Eigenvalue Percent of cumulative
variables Strategic AMT team
Integrety & Champion
Planning knowledge
Magt. Project
Pilot
(11
(21
(31
(4)
(51
0.76365 0.72761 0.59193 0.52159 0.39205 0.71154 0.67649 0.58612 0.68878 0.63690 0.58563 0.76102 0.64911 0.54282 3.47 21.7
variance
1.74 32.5
1.51 42.0
0.782 1.17 57.2
1.27 49.9
variables Instit. support
Adjusted organizational structure Revised policies and procedures Participation of in-house engineer Seeking consultation Close relationship with vendors Selection criteria Attitude towards AMT General knowledge of employees Continued knowledge updating All level training prior implementation All level training post implementation
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Vendor
selection
Technical
knowedge
All-level training
0.78931 0.76850 0.70449 0.51282 0.86509 0.82220 0.50669 0.791 0.676 0.889 0.538 2.69 24.5
1.66 39.7
1.31 51.6
1.05 61.1
H.Zhao. H. C. Co./Int. J. Production Economics 48 (1997)
from the factor analysis of 27 variables. The pattern indicated nine dimensions of managing AMT project. Sixteen (16) strategic variables reflected the multifaceted nature of the strategic construct of AMT adoption, and a set of five underlying dimensions of AMT adoption was identified from the 11 infrastructure variables. The first factor, “strategic support”, is highly correlated (in terms of factor loading) with the first 5 variables, and all indicate the necessity of commitment of top management. The second factor, “integrity of the AMT project team”, consists of three variables with factor loading above 0.55, reflecting the consistency and stability of the project team member. The third factor, labeled “championship and planning”, loaded highly on four variables that mirror the push-effect of long-term planning and project championship. The fourth factor, “management knowledge”, comprises of three variables with factor loading greater than 0.50. Note that the last factor consists of only one variable claiming the necessity of pilot project prior implementation of AMT. The five factors accounted for 57.2%, of the total variance. The first of the four factors derived from infrastructure variables is labeled “institutional support”, with four variables highly loaded. The second factor reflects “vendor selection and the general attitudes of employees towards AMT”. “Technical knowledge of employees” composed of two variables with high factor loading greater than 0.65. “All-level of training at firm level” reflect the constant infusion of new knowledge and new ideas related to AMT. These four factors accounted for 61.1% of total variance. Table 6 Standardized
canonical
discriminant
function
coefficients”
Factors
Coefficients
Wilk’s lamda
Sig.
Team integrety Planning & champion Technical knowledge All-level training SIZE SALE
0.44407 0.55088 0.53777 -0.34465 -0.37691 0.87736
0.92575 0.90024 0.87251 0.84583 0.82583 0.81674
0.0058 0.0058 0.0040 0.0027 0.0024 0.0035
Correctly
classified
a All these factors
65.35%.
Eigen value
are significant
= 0.225
at 0.01 ‘%Ilevel
7-19
15
4.4. Results of discriminant analysis The discriminant analysis offers some insights in the identified factors critical to successful adaptation of AMT. Table 6 shows that “project team integrity”, “strategic planning and project “technical knowledge” were championship”, significantly to the successful use of AMT. AMT brings about significant changes to every aspect of the business operation. Thus, strategic management and project leadership are crucial to the success of AMT adoption. The findings suggest that firms that adhered to strategic planning and had a committed project champion were more likely to achieve the expected results from AMT. The results show that a firm with a well-trained project team, and low turnover of team membership, are essential to AMT adoption and implementation. Project team with low attrition rate could insure the stability of the project, and attests to the smooth implementation of the project. As expected, the factor “general technical knowledge of employees” is also significantly associated with successful AMT implementation. This result indicates that the success of AMT not only depends on the personnel who are directly involved with the project, but also on firm-wide recognition and support of all employees. However, “all-level training” turned out to be negative in achieving the expected performance of AMT. This result is counterintuitive since we expect training at all level to be conducive to the AMT adoption and implementation. One explanation of this unexpected result may be the high intercorrelations between “all-level training” and “technical knowledge”, as indicated in Table 3 of the Appendix (variables 2-5). With regards to firm-specific variables, firm size and financial ability are significant factors. It is expected that firms that have a large pool of resources can generate sufficient revenue to afford adopting AMT, and thereby achieve the expected performance. The negative relationship between the firm’s size and the performance of AMT is expected, since AMT is technology- and information-intensive, rather than labor intensive. It is also shown in Table 6 that the model predicted correctly in 33 out of 51 cases in the “less successful” group (64.7%) and 33 out of 50 cases
H. Zhao. H.C. Co./Int.
16
J. Production
in the “successful firms” group (66%). The overall percentage of correctly classified firms was 66.34%. To examine further the effectiveness of the model, discriminant scores derived from the discriminant function was also used in the analysis of variance. The variability between successful and less successful firms is significantly large (F==2.937; P < 0.01)
5. Conclusion Firms in industrially advanced countries, particularly the United States and Japan, led the world in developing and utilizing advanced manufacturing technology. Industries in the NICs are gradually recognizing the strategic importance of the technologies. Albeit extensive research in the US and Japan on the success factors in adopting and implementing AMT, less is understood whether and how these factors related to the objectives of AMT. This survey of manufacturing firms in Singapore provided further evidence for the critical success factors in AMT adoption and implementation. Our empirical analysis confirmed that the critical success factors, identified in the context of developed countries, are also relevant in Singapore. Moreover, consistent with Huang and Sakurai’s findings [17], the survey showed that as in Japan, firms in Singapore do not find external consultants as critical to the success of AMT. This may be due to the cultural proximity of the two
Economics
48 (1997)
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countries. The discriminant analysis suggested that project team integrity, strategic planning and project championship, and technical knowledge are critical to achieving the expected performances. The findings suggested that employee training at all levels was not contributing to the success of AMT implementation. However, this unexpected result deserves further investigation. Our study also found that firm-specific variables such as size of firm, annual sales, etc. have significant bearings on the introduction of new technology. One motivation for this study is the suspicion that the firm size in the NICs are generally small, and therefore factors critical in developed countries may not apply in the NICs. The results show that the firm-size factor (measured in terms of the number of employees) and the financial-availability factor (measured in terms of sales) differentiate the successful from the less successful firms in AMT adoption and implementation. Large firms have not been as successful as firms with less than 100 employees. However, firms with large financial resources were found to be more successful. This may appear to be a contradiction since “large” firms are expected to have more financial resources than “small” firms. However, manufacturing firms with large financial resources in Singapore do not necessarily employ a large labor force. Faced with rising labor cost, and competition from neighboring countries, many labor-intensive operations in Singapore have migrated steadily to neighboring countries such as Malaysia, Indonesia and China.
Appendix A. Section A of the questionnaire (critical success factors) Al. A2. A3. A4. A5. A6. A7. AZ. A9. AlO.
degree of alignment of the core organizational systems with the corporate strategy degree of financial support degree of management commitment and support understanding the potential contribution of AMT to current operations and what new technologies can achieve existence of well-defined objectives of AMT adoption pace of implementation position of the AMT champion in the organization need for team members to be familiar with the new technologies degree of willingness of top management to take short-term risks for long-term improvements degree of turnover of the project team members
H.Zhao,
H.C. Co.lInt.
J. Production
Economics
48 (1997J
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degree of top-down planning and bottom-up implementation the project team should not be disbanded until the new technology is absorbed by the organization objectives A13. need for long-term automation A14. existence of an AMT champion obtained experience with a pilot project prior to A15. degree to which organizations implementation and composition of the project team A16. organization A17. degree of effective alignment of employee attitudes with corporate objectives of hands-on training program to employees after implementation A18. degree of availability vendor(s) A19. selecting the appropriate throughout the process of implementation A2Q. training programs must be maintained from in-house engineers in system design A21. need active participation A22. existence of an employee education program prior to AMT implementation between the technology supplier and the user firm A23. nature of the relationship A24. degree of specialized technical training is very important A25. need to reorganize A26. need to revise policies and procedures A27. need for external consultants
All. A12.
Appendix B. Section B of the questionnaire Bl. B2. B3. B4. B5. B6. B7. B8. B9.
(benefits of AMT)
reduction in labor cost improvement of product quality enhancement of product/process flexibility reduction of manufacturing lead-time reduction in work-in-process inventory reduction of setup time improvement in factory utilization improvement in productivity provide for competitive advantage in marketing
Appendix C. Section C of the questionnaire SECTOR SIZE ENGR ASSET R&D SALES TITLE
(firm profile)
industry grouping total number of employees total number of engineers and technicians fixed assets annual R & D expenditure in Singapore dollars (S$) annual sales turnover for last fiscal year job title of person answering the survey questionnaire
Appendix D Means, standard deviations,
Manufacturing strategy Long-term objective Top-down planning Management knowledge Well-defined AMT
Variables I 2. 3. 4. 5.
of strategic management 9
10
I1
0.2567 0.1382 0.3888” 0.1625 0.1677 0.3518** 0.0099 0.2834* 0.3684** 0.5554*
12
variables 8
0.2777* 0.2798’ 0.1617 0.0163 0.0448
7
0.2287* 0.1602 0.0475
8
0.2759* 0.0885
9
0.5810**
10
15
I
0.3141** 0.2282* 0.2503* 0.1009 0.0483 0.0946
6
0 3764** 0:3226** 0.1753 0.0793
14
6
0.3403** 0.1152 0.1425 0.2521* 0.0780 0.24X1* 0.2078
variables
0.5505** 0.4233** 0.2028 0.1630 0.0447
13
5
0.3462** 0.2198 0.2545’ 0.0716 0.2916: 0.3255** 0.2038 0.1456
4
0.0840 0.1896 0.1699 0.0638 0.1714 0.0583 0.1105 0.3537 0.1727
of infrastructure
0.70 0.72 0.59 0.52 0.69 0.54
3
0.2190 0.0333 0.1608 0.0784 0.0827 0.0986 0.1643 0.1708 0.0459 0.1485
5
2
0.395X** 0.1844 0.1783 0.1296 0.1416 0.0799 0.0466 0.3014** 0.2506* 0.2403* 0.3X21**
4
1
3
0.2578* 0.1264 0.1921 0.1343 0.1257 0.2224 0.1020 0.1624 PO.1035 0.1401 0.0470 0.2218 0.1709
s.d.
2
0.2954** 0.1043 0.2576* 0.0967 0.0095 0.1446 0.1252 0.1053
Means
1
0.1586 0.2901* 0.3232** 0.0782 0.1127 0.1964 0.0193 0.1502 0.1756
0.64
s.d.
0.1820 0.2289* 0.2209 0.1814 0.0414 0.0912 0.1137 0.0620 0.1901 0.3725**
0.55 0.72 0.78 0.57 0.59 0.63 0.89 0.77 0.85
and intercorrelations
of AMT
6. Properly placed implementation Pilot project AMT champion Interdisciplinary approach Team trained with technology Team retained throughout project Turnover of team minimized TM designated key people Financial support by TM
7. 8. 9. 10. Il. 12. 13. 14.
Means
0.55 0.57 0.70 0.68 0.56 0.79 0.80 0.67 0.73 0.70 0.65
0.2480* 0.0905 0.1581 0.1959 0.0383 -0.0529 0.3293** 0.0118 0.1092 0.2279* 0.1712 -0.0205 -0.0717 0.2X57* 0.2563: 0.1473 0.1412 0.0358 0.3248’ ‘* 0.1246 0.1200 0.1876 0.1363 0.1018 0.2346* 0.1932 0.0101 0.2070 0.1426 0.0580 0.0276 -0.0493 -0.0178 0.1236 0.1471 -0.1314 0.0973 0.1937 0.1789 0.0863 0.1863 0.0368 0.2483* 0.0341 0.0202 0. I429 0.2413* 0.0929 0.1916 0.1292 0.2851: 0.2160 0.089 I 0.1078
4.34 4.12 3.91 4.01 4.01 3.71 3.70 4.12 2.99 4.14 4.29
4.56 4.11 4.16 4.52 4.34 4.30 3.87 4.22 3.67 4.1 I 4.07 4.13 4.22 455 4.32 4.46
and intercorrelations
15. TM willingness for short-term risk 16. TM support for implementation
deviations.
Signif: *=O.Ol. ** =O.OOl
Appendix E Means, standard
Attitudes towards AMT General knowlege of employees Training prior implementation Continued knowledge updating Training post implementation Adjusted organizational structure Revised policies and procedures Participation of in-house engineer Seeking consultation Close relationship with vendors Setting up vendor selection criteria
Variables 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. Sigmf: *=O.Ol, ** =O.OOl.
H.Zhao,
H. C. Co. JInt. J. Production
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