Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science

A SURVEY ON THE SAFETY SYSTEM MATURITY LEVELS OF ELECTRONICS MANUFACTURERS IN SOUTH KOREA


DOI: 10.5937/jaes0-30973 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Volume 19 article 837 pages: 642-648

Joo Yong Shim*
Seoul National University Of Science And Technology, Department of Safety Engineering, Seoul, South Korea

Jeong Hwa Park
Seoul National University Of Science And Technology, Department of Safety Engineering, Seoul, South Korea

Jung Mo Lee
ChonnNam National University, Mechanical Design Engineering, Seoul, South Korea

Dal Jae Park
Seoul National University Of Science And Technology, Department of Safety Engineering, Seoul, South Korea

Jae-Yong Lim
Seoul National University Of Science And Technology, Department of Safety Engineering, Seoul, South Korea

The main objective is to identify the level of advancement of safety systems in various levels of smart factories. Smart level verification systems are being implemented in Korea, but safety systems are not paying much attention to smart factory level checks. Using a checklist, nine Korean electronics manufacturing enterprises checked their level of safety system. The checklist consists of 142 items, which were divided into four dimensions (laws and certifications, safety designs and configurations at the facilities, safety devices and guards, and maintenance and training). As a result, a high-ranked enterprise in smart factory level showed excellence in the safety system maturity level as well. Compared to the level of the company's smart factory, the level of advancement of safety systems has been con- firmed to be lower.

View article

This study was supported by the Korea Occupational Safety and Health Agency.

1. Rossmann M, Khadikar A, Le Franc P, Perea L, Schneider-Maul R, Buvat J, Ghosh A. (2017). Smart Factories: How can manufacturers realize the potential of digital industrial revolution. Capgemini. com. https://www.capgemini.com/wp-content/ uploads/2017/05/dti-smart-factories-full-report-re-branded-web-version_16032018.pdf (accessed on 2021-02-09).

2. Mičieta, B., Herčko, J., Botka, M., & Zrnić, N. (2016). Concept of intelligent logistic for automotive industry. Journal of Applied Engineering Science, vol. 14, br. 2, str. 233-238. DOI:10.5937/jaes14-10907

3. Won, J. Y. and Park, M. J. (2020). Smart factory adoption in small and medium-sized enterprises: Empirical evidence of manufacturing industry in Korea. Technological Forecasting and Social Change, vol. 157,120117, DOI: https://doi.org/10.1016/j.tech-fore.2020.120117

4. Schumacher, A., Erol, S. and Sihn, W. (2016). A maturity model for assessing Industry 4.0 readiness and maturity of manufacturing enterprises. Procedia Cirp, vol. 52, 161-166, DOI: https://doi.org/10.1016/j. procir.2016.07.040

5. Karl L., Volker S., Roman B., Matthias B., Martin B., Agnes M., Katharina S., Edgar S., Moritz S. (2015). IMPULS - Industrie 4.0-Readiness. VDMA, Ger- many(Frankfurt):Impuls-Stiftung. https://industrie40. vdma.org/documents/4214230/26342484/Indus- trie_40_Readiness_Study_1529498007918.pdf (ac- cessed on 2021-02-09).

6. Rockwell Automation, The Connected Enterprise Maturity Model, from https://literature.rockwellautomation.com/idc/groups/literature/documents/wp/cie- wp002_-en-p.pdf (accessed on 2021-02-09).

7. Schuh, G., Anderl, R., Gausemeier, J., ten Hom- pel, M., Wahlster, W. (2017). Industrie 4.0 maturity index. Managing the digital transformation of com- panies. Munich: Herbert Utz. https://en.acatech. de/wp-content/uploads/sites/6/2020/04/aca_STU_MatInd_2020_en_Web-1.pdf (accessed on 2021- 02-09).

8. Lee, J., Jun S., Chang T.-W. and Park J. (2017). A smartness assessment framework for smart facto- ries using analytic network process. Sustainability, vol. 9, no. 5, 1-15, DOI: https://doi.org/10.3390/ su9050794

9. Lee, J., Cameron, I. and Hassall, M. (2019). Im- proving process safety: What roles for Digitalization and Industry 4.0?. Process safety and environmental protection, vol. 132, 325-339, DOI: https://doi. org/10.1016/j.psep.2019.10.021

10. Dumitraşcu-Băldău, I. and Dumitraşcu, D. D. (2017). Occupational emerging risks affecting internation- al virtual project Team Results. In MATEC Web of Conferences. EDP Sciences, vol. 121, 07003, DOI: https://doi.org/10.1051/matecconf/201712107003

11. Brocal, F., Sebastián, M. A., & González, C. (2017) Theoretical framework for the new and emerg- ing occupational risk modeling and its monitoring through technology lifecycle of industrial processes. Safety Science, vol. 99, 178-186, DOI: https://doi.org/10.1016/j.ssci.2016.10.016

12. Komadinić, V., & Ilić, D. (2013). Risk assessment in small and medium-sized enterprises, specifics and differences in approach. Journal of applied engineer- ing science, vol. 11, br. 3, str. 123-126. DOI:10.5937/ jaes11-3665Joo Yong Shim, et. al. - A survey on the safety system maturity levels of electronics manufacturers in South Korea

13. Cho, J. H., & Shin, W. S. (2019). Developing a Framework for Assessing Smart Factory Readiness of SMEs and Case Study. J Korean Soc Qual Manag, vol. 47, no. 1,1-15, DOI: https://doi.org/10.7469/ JKSQM.2019.47.1.1

14. Maasouman, M. A., & Demirli, K. (2015). Assessment of Lean Maturity Level in Manufacturing Cells. IFAC-PapersOnLine, vol. 48, no. 3, 1876–1881, DOI: https://doi.org/10.1016/j.ifacol.2015.06.360

15. Tupa J, Simota J. and Steiner F. (2017). Aspects of risk management implementation for Industry 4.0. Procedia Manufacturing, vol. 11, no. 1, 223-1230, DOI: https://doi.org/10.1016/j.promfg.2017.07.248

16. Niesen, T., Houy, C., Fettke, P., & Loos, P. (2016, January). Towards an integrative big data analysis framework for data-driven risk management in industry 4.0. In 2016 49th Hawaii International Con- ference on System Sciences (HICSS), 5065-5074, DOI: 10.1109/HICSS.2016.627

17. KMR CERTIFICATION, Smart Factory Level Verification System, from http://www.ikmr.co.kr/sub/ sub4_26.asp(accessed on 2021-02-09).

18. Mourtzis, D., Gargallis, A., & Zogopoulos, V. (2019). Modelling of Customer Oriented Applications in Prod- uct Lifecycle using RAMI 4.0. Procedia Manufacturing, vol. 28, 31-36, DOI: https://doi.org/10.1016/j. promfg.2018.12.006

19. Jens Popper, Marius Blügel, Hagen Burchardt, Stef- fen Horn, Joachim Merx, Detlev Richter, Werner Varro, Michael Pfeifer, Pascal Staub-Lang. (2018). Safety an modularen Maschinen. Technology Initiative SmartFactory KL e.V., Report No.: Whitepaper SF-3.1. from https://www.phoenixcontact.com/as- sets/downloads_ed/global/web_dwl_specialist_es- say/SF_WP_Safety_2018_EN.pdf (accessed on 2021-02-09).

20. Baek J. B., Lee K. B., Im J. G, Kim T. Y., Park J. M., Lim Y. M., Woo J. J., Joo O.G., Jeon S. Y., Shim J. H., Choi D. S., Yang S. B. (2018) Securing Safety of Smart Factory model development. Korea Occupa- tional Safety and Health Agency, KOSHA. [in Kore- an]

21. Lee K. O. and Yeo H. O. (2017) Technical guidelines for safety concerning the use of industrial robots, etc. Korea Occupational Safety and Health Agency, KOSHA. Reprt No.: M-61-2017. from https://www. kosha.or.kr/kosha/info/searchTechnicalGuidelines. do (accessed on 2021-02-09).

22. Hiroo Kanamaru. and Taro Harima. (2008). Safety field network technology and its implementation. SICE Annual Conference, Tokyo, 1487-1490, DOI: 10.1109/SICE.2008.4654894.