An Analysis of Intelligent Automation Demands in Taiwanese Firms

An Analysis of Intelligent Automation Demands in Taiwanese Firms

Ying-Mei Tai*

Industrial Economics and Knowledge Center (IEK), Industrial Technology Research Institute (ITRI), Taiwan

(Received 7 February 2016; Published on line 1 March 2016)
*Corresponding author: mandylo@itri.org.tw
DOI: 10.5875/ausmt.v6i1.1109

Abstract: To accurately elucidate the production deployment, process intelligent automation (IA), and production bottlenecks of Taiwanese companies, as well as the IA application status, this research conducted a structured questionnaire survey on the participants of the IA promotion activities arranged by the Industrial Development Bureau, Ministry of Economic Affairs. A total of 35 valid questionnaires were recovered. Research findings indicated that the majority of participants were large-scale enterprises. These enterprises anticipated adding production bases in Taiwan and China to transit and upgrade their operations or strengthen influence in the domestic market. The degrees of various process IA and production bottlenecks were relatively low, which was associated with the tendency to small amount of diversified products. The majority of sub-categories of hardware equipment and simulation technologies have reached maturity, and the effective application of these technologies can enhance production efficiency. Technologies of intelligent software remain immature and need further development and application. More importantly, they can meet customer values and create new business models, so as to satisfy the purpose of sustainable development.

Keywords: Intelligent automation, Taiwanese firm, demand analysis

Introduction

In response to the change in China’s role as the global factory, various industrial countries have introduced plans to actively transit or upgrade their manufacturing industries, such as Germany’s “Industry 4.0,” the United States’ “Advanced Manufacturing Partnership (AMP),” South Korea’s “Manufacturing Innovation 3.0,” Japan’s “Industry 4.1J,” and China’s “Made in China 2025.” These plans aim to promote the sustainable development of the manufacturing industries in various countries.

Taiwan also introduced its “Productivity 4.0” plan, selecting the electronic and information, metal and transportation, mechanical equipment, food, and textile industries as the key promotion targets. Technologies relevant to “Productivity 4.0,” such as the integration of Cyber Physical System (CPS) with smart manufacturing and service techniques, high-value additive manufacturing techniques, and common infrastructure, were also targeted to improve the international competitiveness of Taiwanese companies.

Methodology

This research examined the participants of the intelligent automation (IA) promotion activities (incl., business community, demonstration events, and industrial park’s demand matchmaking events) arranged by the Industrial Development Bureau, Ministry of Economic Affairs. A structured questionnaire was administered to participants that were interested in participating in these events. A total of 35 questionnaires were returned.

Based on the demographics collected from the questionnaires, participants were largely from the 3K processing industry (34.4%), followed by the 3C industry (25.7%). Among the samples, participants in industries with relatively poor working environments or find difficulty in recruiting staff, and those from enterprises with a capital exceeding NT $80 million comprised 71.4%. Statistics indicate that participant’s ability to invest in IA is correlated to their economy of scale.

Findings

Investment Deployment in “Production Bases”

This study categorized the participants’ upcoming investment regions in production bases into Taiwan, China, Southeast Asia, Central and Southern America, the United States and Canada, Europe, and Others. These categories were used to calculate the proportion of each investment location.

Findings indicated that Taiwan was the upcoming investment region in a production base by the majority of participants (45.7%), with the majority of investments directed at the transition and development of new products or techniques. China comprised the second largest number of participants (34.3%), where investments were largely for satisfying the growth of the domestic market. Southeast Asia comprised the third largest number of participants (14.3%), where investments were primarily in response to the changing environment in China, which in turn encouraged the Taiwanese firms to invest more in Southeast Asia. The remaining categories all received less than 5% of the participants, as shown in Fig. 1.

“Process” IA and Production Bottleneck

This study defined processes into eight categories, namely, product design and analysis, material loading/unloading, processing, assembly (incl., securing), defect detection, function testing, packaging/transport/storage, production information management. The degree of IA and production bottleneck is measured on a five-point scale, with a score of 1 to 5 representing “very low” to “very high,” respectively. The scores were collected to obtain an average value for each process category.

Research findings indicated that the average values for all processes were lower than “normal” (score of 3), suggesting that the degree of IA of Taiwanese companies is relatively low and they didn’t experience severe production bottlenecks. This is primary because Taiwanese companies have a tendency to small amount of diversified products and prefer manual operations that are more flexible. Two processes exhibited a lower degree of “IA” than “production bottlenecks,” namely, defect detection and function testing. These processes were the more urgent IA issues that affected product quality and labor allocation. The return of investments in these processes can be expedited with effective IA, as shown in Fig. 2.

“Intelligent” Application Status

This study defined intelligent technologies into three categories, namely, hardware equipment, software, and simulation application. Among these categories, hardware equipment was further sub-categorized into robotics, automatic Guided Vehicle (AGV), and multi-axis motion platform; software was sub-categorized into machine vision, force sensor, remote predictive diagnostics, cloud technology application, Internet of Things (IoT) application, and big data analysis; and simulation application was sub-categorized into design simulation and production simulation. These sub-categories were examined to determine the “implemented”/“unimplemented” ratio of the manufacturers.

Research findings indicated that the sub-categories with a higher “implemented” ratio than “unimplemented” comprised (1) robotics (62.9%), (2) machine vision (52.9%), (3) force sensor (52.9%), (4) big data analysis (54.5%), (5) design simulation (67.6), and (6) production simulation (55.9%). Technologies (1) to (3) exhibited maturity, and presented the advantages of increased production efficiency and reduced cost. Technologies (4) to (6) are key issues in the promotion of Productivity 4.0, and the effective application of these technologies can enhance competitiveness.

The sub-categories with a higher “unimplemented” ratio than “implemented” comprised (1) AGV (64.7%), (2) multi-axis motion platform (52.9%), (3) remote predictive diagnostics (57.6%), (4) cloud technology application (57.6%), and (5) IoT application (63.6%). Technologies (1) and (2) exhibited relative maturity. However, consideration should be put into process space and supporting systems to fully utilize these technologies. Technologies (3) also exhibited maturity. However, the use of this technology runs the risk of process disclosure. The remaining two technologies are the key issues in the promotion of Productivity 4.0. Rather, they are the technologies currently lacking professionals, as shown in Fig. 3.

Conclusion

China is a key location of investment for Taiwanese companies. In response to the change in China’s role as the global factory, Taiwanese manufacturers seek to transit or upgrade their operations, where process IA and intelligent applications are key promotion aspects.

Research findings indicated that Taiwan and China are the primarily locations Taiwanese companies aim to invest in production bases in their attempt to transit and upgrade their Taiwan operations or strengthen influence into the China market. The various process IA and production bottlenecks were relatively low, which was associated with the tendency to small amount of diversified products. Defect detection and function testing are the more urgent IA issues that affected product quality and labor allocation. Therefore, actively investing in these technologies is worthwhile. In terms of intelligent technologies, numerous sub-categories of technological hardware equipment and simulation application have reached maturity, and the effective application of these technologies can enhance production efficiency. Software is key aspect in intelligent factories. However, these software technologies remain immature, such as cloud technology application, IoT application, and big data analysis, and further development and application are required.

Increased attention should be placed on high-value additive manufacturing techniques and common infrastructure, and more importantly, customer value, such as high-volume customization, and new business models, such as the servitization of manufacturing industries, must be created, thereby satisfying the core values of sustainable management.

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