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Conceptual Key Competency Model for Smart Factories in Production Processes
Organizacija ( IF 1.5 ) Pub Date : 2020-02-01 , DOI: 10.2478/orga-2020-0005
Andrej Jerman 1 , Andrej Bertoncelj 1 , Gandolfo Dominici 2 , Mirjana Pejić Bach 3 , Anita Trnavčević 1
Affiliation  

Abstract Background and Purpose: The aim of the study is to develop a conceptual key competency model for smart factories in production processes, focused on the automotive industry, as innovation and continuous development in this industry are at the forefront and represent the key to its long-term success. Methodology: For the purpose of the research, we used a semi-structured interview as a method of data collection. Participants were segmented into three homogeneous groups, which are industry experts, university professors and secondary education teachers, and government experts. In order to analyse the qualitative data, we used the method of content analysis. Results: Based on the analysis of the data collected by structured interviews, we identified the key competencies that workers in smart factories in the automotive industry will need. The key competencies are technical skills, ICT skills, innovation and creativity, openness to learning, ability to accept and adapt to change, and various soft skills. Conclusion: Our research provides insights for managers working in organisations that are transformed by Industry 4.0. For instance, human resource managers can use our results to study what competencies potential candidates need to perform well on the job, particularly in regards to planning future job profiles in regards related to production processes. Moreover, they can design competency models in a way that is coherent with the trends of Industry 4.0. Educational policy makers should design curricula that develop mentioned competencies. In the future, the results presented here can be compared and contrasted with findings obtained by applying other empirical methods.

中文翻译:

生产过程中智能工厂的概念关键能力模型

摘要背景和目的:研究的目的是为智能工厂的生产过程开发概念性关键能力模型,重点是汽车行业,因为该行业的创新和持续发展是其长期发展的关键,并代表了其长期发展的关键。长期的成功。方法:出于研究目的,我们使用半结构化访谈作为数据收集的方法。参加者分为三类,分别是行业专家,大学教授和中学教育老师以及政府专家。为了分析定性数据,我们采用了内容分析的方法。结果:基于对结构化访谈收集的数据的分析,我们确定了汽车行业智能工厂工人所需的关键能力。关键能力是技术技能,信息通信技术技能,创新和创造力,学习开放性,接受和适应变化的能力以及各种软技能。结论:我们的研究为在工业4.0转型的组织中工作的经理提供了见识。例如,人力资源经理可以使用我们的结果来研究潜在候选人在工作中需要表现出什么才能,尤其是在计划与生产过程相关的未来工作概况方面。而且,他们可以以与工业4.0趋势一致的方式设计能力模型。教育政策制定者应设计能够提高上述能力的课程。将来,此处介绍的结果可以与通过应用其他经验方法获得的发现进行比较和对比。
更新日期:2020-02-01
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