4th generation industry; Develop a professional competency model for quality managers
Subject Areas :
1 - - Faculty of Humanities, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.
Keywords: Industry 4, professional Competencies, Quality, human resources, Content analysis.,
Abstract :
The purpose of this study is to identify the competencies required by quality management professionals to comply with the requirements of industry 4. The researcher has tried to examine the expected changes in industry 4 from four aspects; Identify the factory (people and process), business, product and customers, technical, methodological, social and personal competencies of quality specialists to enter the industry. This is a qualitative study and with the method of content analysis, semi-structured interviews conducted with sixteen quality managers and human resource managers of companies receiving different levels of excellence in manufacturing in 1400, analysis and basic themes. Organizing themes and themes were identified. The findings show that quality professionals need technical competence to interpret big data related to processes to make strategic decisions, use digital technologies, and be aware of data security risk. Methodological competencies will be required to use the data to identify the source of problems, access to reliable learning resources, and the ability to use new tools to effectively solve complex problems. Social competencies in inter-organizational communication, communication with suppliers and customers on new shared virtual platforms, along with the ability to maintain tacit and explicit knowledge in a decentralized environment that requires leadership ability to make decisions, will be essential. . Ability to perform job duties in flexible workplaces at flexible times, as well as adaptation to frequent work-related changes are among the personal competencies required..
1- Dirican, C. (2015), “The impacts of robotics, artificial intelligence on business and economics”, Procedia - Social and Behavioral Sciences, Vol. 195, pp. 564-573.
2- Lyle, M. (2017), “From paper and pencil to industry 4.0: revealing the value of data through quality intelligence”, Quality, Vol. 10, pp. 25-29, available at: http://eds.b.ebscohost.com/eds/detail/detail?
3- Kasriel, S. (2017), “4 predictions for the future of work”, World Economic Forum Website, available at:https://www.weforum.org/agenda/2017/12/predictions-for-freelance-work-education/.
4- Cimini, C., Pinto, R. and Cavalieri, S. (2017), “The business transformation towards smart manufacturing: a literature overview about reference models and research agenda”, IFACPapers OnLine, Vol. 50 No. 1, pp. 14952-14957.
5- Lu, Y. (2017), “Industry 4.0: a survey on technologies, applications and open research issues”, Journal Of Industrial Information Integration, Vol. 6, pp. 1-10, doi: 10.1016/j.jii.2017.04.005.
6- Elg, M., Gremyr, I., Hellstreom, A. and Witell, L. (2011), “The role of quality managers in contemporary organisations”, Total Quality Management and Business Excellence, Vol. 22 No. 8, pp. 795-806, doi: 10.1080/14783363.2011.593899.
7- Goetsch, D. and Davis, S. (2016), Quality Management for Organizational Excellence: Introduction to Total Quality, 8th ed., Pearson, Boston.
8- Garad, A. (2007), “The effective quality manager”, in Hoque, M. and Fernandes, C. (Eds), Proceedings of the Fifth International Business Research Conference, Vol. 5, pp. 1-19, available at: http://ro.uow.edu.au/commpapers/1129/. Singh, R. (2018), 50,000 Malaysians Expected to Be Laid off This Year, January 4, The Sun daily, available at: http://www.thesundaily.my/node/516338.
9- Benesova, A. and Tupa, J. (2017), “Requirements for education and qualification of people in industry 4.0”, Procedia Manufacturing, Vol. 11, pp. 2195-2202, doi: 10.1016/j.promfg.2017.07.366. Boulanger, M., Chang, W., Johnson, M. and Kubiak, T.M. (2017), “The deal with big data”, ASQ Quality Progress, Vol. 50 No. 9, pp. 26-33.
10- Gorecky, D., Schmitt, M., Loskyll, M. and Zuhlke, D. (2014), “Human-machine-interaction in the industry 4.0 era”, in 12th IEEE International Conference on Industrial Informatics (INDIN), pp. 289-294, doi: 10.1109/INDIN.2014.6945523.
11- Dal Porto, L. (2018), “The state of manufacturing”, January, ASQ Quality Progress, Vol. 51 No. 1.
12- Gaskill, T. (2017), “Facing new reality”, February, ASQ Quality Progress, Vol. 50 No. 2, pp. 10-12.
13- Evans, J.R. (2015), “Modern analytics and the future of quality and performance excellence”, Quality Management Journal, Vol. 22 No. 4, pp. 6-17, doi: 10.1080/10686967.2015.11918447.
14- Roblek, V., Me_sko, M. and Krape_z, A. (2016), “A complex view of industry 4.0”, SAGE Open, Vol. 6 No. 2, pp. 1-11, doi: 10.1177/2158244016653987.
15- Keim, L. and La Londe, P. (2017), “Changing competencies for quality professionals report”, pp. 1-23, available at: https://asq.org/quality-resources/research.
16- Longo, F., Nicoletti, L. and Padovano, A. (2017), “Smart operators in industry 4.0: a human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context”, Computers and Industrial Engineering, Vol. 113, pp. 144-159, doi: 10.1016/j.cie.2017.09.016.
17- Rojko, A. (2017), “Industry 4.0 concept: background and overview”, International Journal of Interactive Mobile Technologies, Vol. 11 No. 5, pp. 77-90, doi: 10.3991/ijim.v11i5.7072.
18- Stancioiu, A. (2017), “The fourth industrial revolution, Industry 4.0”, Fiability and Durability/Fiabilitate Si Durabilitate, Vol. 1, pp. 74-78, available at: http://eds.a.ebscohost.com/eds/detail/detail?
19- Lindborg, H.J. (2017), “Preparing for the revolution”, August, ASQ Quality Progress, Vol. 50 No. 8, pp. 10-12.
20- Oliff, H. and Liu, Y. (2017), “Towards industry 4.0 utilizing data-mining techniques: a case study on quality improvement”, in Procedia CIRP, 63(Manufacturing Systems 4.0 - Proceedings of the 50th CIRP Conference on Manufacturing Systems), pp. 167-172, doi: 10.1016/j.procir.2017.03.311.
21- Trappey, A.J.C., Trappey, C.V., Govindarajan, U.H., Chuang, A.C. and Sun, J.J. (2017), “Review article: a review of essential standards and patent landscapes for the Internet of Things: a key enabler for Industry 4.0”, Advanced Engineering Informatics, Vol. 33, pp. 208-229, doi: 10.1016/j.aei.2016. 11.007.
22- Wagner, T., Herrmann, C. and Thiede, S. (2017), “Industry 4.0 impacts on lean production systems”, Procedia CIRP, Vol. 63, pp. 125-131, doi: 10.1016/j.procir.2017.02.041.
23- Hecklau, F., Galeitzke, M., Flachs, S. and Kohl, H. (2016), “Holistic approach for human resource management in industry 4.0”, Procedia CIRP, Vol. 54, pp. 1-6.
24- Schotz, S., Butzer, S., Molenda, P., Drews, T. and Steinhilper, R. (2017), “An approach towards an adaptive quality assurance”, Procedia CIRP, Vol. 63, pp. 189-194, doi: 10.1016/j.procir.2017. 03.096.
25- Goh, T.N. (2015), “Emerging megatrends in quality engineering and the “new 5S” response”, Quality Engineering, Vol. 27 No. 4, pp. 450-460, doi: 10.1080/08982112.2015.1036294.
26- Prifti, L., Knigge, M., Kienegger, H. and Krcmar, H. (2017), “A competency model for “industrie 4.0” employees”, in Leimeister, J.M. and Brenner, W. (Eds), Proceedings der 13. Internationalen Tagung Wirtschaftsinformatik (WI 2017), Hrsg, St. Gallen, pp. 46-60.
27- Hsieh, H.-F., & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis. Qualitative Health Research, 15(9), 1277–1288. https://doi.org/10.1177/1049732305276687.
28- Saedi, Abdullah., Sepahvand, Reza., Mousavi, Seyed Najmuddin., Hakak, Mohammad. (2019). Designing and explaining the architectural model of human resource knowledge in knowledge-based organizations. Journal of Human Resources Research Management (Imam Hossein University), 11 (3), 37-68.
29- Golshahi, Behnam., Rastegar, Abbas Ali., Feyz, Davood., Zarei, Azimullah. (2018). Architecture of the process of guiding and employing scientific talents in Iran. Journal of Human Resource Research Management (Imam Hossein University), 10 (3), 1-23.
30- Iman, Mohammad Taqi; Noshadi, Mahmoud Reza. (2011). Quality of Research in Humanities Fall and Winter 2011 - Number 6 (30 ), pages: 15 to 44.
31- Lawshe, C.H. (1975), “A quantitative approach to content validity”, Personnel Psychology, 28, 563-575.