Comparative Study of Crossing the Chasm in Applying Smart Factory System for SMEs
Young-Hwan Choi1, Sang-Hyun Choi2
1Young-Hwan Choi, MIS, Chungbuk National University, Chung-Ju City, South Korea, East Asian.
2Sang-Hyun Choi, MIS, Chungbuk National University, Chung-Ju City, South Korea, East Asian.
Manuscript received on 10 June 2019 | Revised Manuscript received on 17 June 2019 | Manuscript Published on 22 June 2019 | PP: 1017-1024 | Volume-8 Issue-8S2 June 2019 | Retrieval Number: H11740688S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper describes the practical methodology which encourages manufacturing SMEs in adopting smart factory system utilizing rapidly changing innovative technology. The focus is supporting manufacturing SMEs to cross the chasm successfully between the basic and middle level of smart factory environment. Based on 140 manufacturing SMEs who are between 10 and 300 employees and less than 100 billion Korean won revenue in 2014, survey was taken with 25 questionnaires. The objectives of this survey are to identify chasm situation, which SMEs with initially implemented smart factory might face in advancing to next maturity level for higher productivity. This study analyzed the status of SMEs in terms of current satisfaction level, equipment I/F rate, target level of smart factory in 5 years, type of Information system implemented and government support to find what factors are influential or correlated with the advancement from the 2nd basic level to the 3rd Mid-1 level of smart factory. Findings: This study explains that 140 SMEs who responded to the survey are satisfied relatively with their smart factory implementation. However they have a funding problem even if they want to go further for the advancement to the 3rd level of smart factory, which bottom lines are to have all machines interfaced with MES (Manufacturing Execution System) and to collect data from shop floor in a real time manner. The survey describes that 102 out of 140 SMEs explains the insufficient budget as the 1st issue for continuing improvement of smart factory with higher satisfaction score, 16 SMEs with unclear performance as the 2nd, 13 SMEs with insufficient experts as the 3rd, and 9 SMEs with low level of innovative passion as the 4th. In general, SMEs with higher equipment interface rate expect high about 1 more advanced Mid-1 level of smart factory system. And the more advanced level of smart factory SMEs have, the better quality SMEs have. SMEs implemented with MES system are more achieving the quality improvement than other information systems such as, ERP, PLM, SCM, and EMS etc. This research explains that SMEs with their 1st smart factory implementation which some manual operations are switched to automation will face the chasm in advancing to next level of smart factory. Therefore, It suggests government’ efficient strategy, sharing economy and stable system operation with security to overcome the chasm.
Keywords: Chasm, Industry 4.0, Big Data, Smart Factory, Cyber Physical Systems.
Scope of the Article: Big Data Analytics for Social Networking using IoT