Abstract

The fourth industrial revolution known as Industry 4.0 is reshaping and evolving the way industries produce products and individuals live and work therefore, gaining massive attraction from academia, business, and politics. The manufacturing industries are optimistic regarding the opportunities that Industry 4.0 may offer such as improved efficiency, productivity and customization. The present research contributes to the Industry 4.0 literature by identifying, modeling, analyzing, and prioritizing the challenges in implementing Industry 4.0 in manufacturing industries. In doing so, the article first introduces the interpretive structural modeling (ISM) to develop the hierarchical relationships among the challenges and analyzes their mutual interactions. Further, “Matrice d’Impacts Croises Multiplication Appliquee aun Classement” (MICMAC) analysis is used to categorize the challenges into four categories, namely autonomous, driver, dependent, and linkage based on their driving power and dependence power. Moreover, fuzzy analytic hierarchy process (F-AHP) methodology is used to prioritize the challenges based on three criteria: driving power, dependence power, and change management. The hierarchical model developed through ISM methodology shows that “lack of vision and leadership from top management (C12), lack of skills training program and education (C2), and uncertainty of return on investment (C9)” are the major challenges in implementing Industry 4.0 in manufacturing industries. The findings of F-AHP analysis suggest that “lack of vision and leadership from top management (C12), lack of skilled workforce (C3), lack of skills training program and education (C2), and uncertainty of return on investment (C9)” are some of the major challenges of implementing Industry 4.0. Finally, the obtained results show how challenges affect other so that to uncover the root cause triggering the other challenges. The industrial practitioners and managers can then take advantage of these analyses to know which challenge acts as the main barrier in implementing Industry 4.0 and to be focused first in order to reach a solution.

摘要

第四次工业革命被称为“工业4.0”，它正在重塑和发展工业生产产品以及个人生活和工作方式的方式，因此受到了学术界，商业界和政治界的广泛关注。制造业对工业4.0可能提供的机会持乐观态度，例如提高效率，生产率和定制化。本研究通过识别，建模，分析和优先考虑在制造业中实施工业4.0的挑战，为工业4.0文献做出了贡献。为此，本文首先介绍了解释性结构建模（ISM），以开发挑战之间的层次关系并分析它们之间的相互影响。进一步，运用“影响矩阵模型”（MICMAC）分析将挑战分为四个类别，即自治，驾驶员，从属和联系，基于其驱动力和依赖性。此外，模糊分析层次过程（F-AHP）方法用于基于三个标准对挑战进行优先级排序：驱动力，依赖力和变更管理。通过ISM方法开发的分层模型表明，“缺乏高层管理者的远见和领导才能（C12），缺乏技能培训计划和教育（C2）以及投资回报率的不确定性（C9）”是实施行业的主要挑战制造业4.0。F-AHP分析的结果表明，“高层管理人员缺乏远见和领导才能（C12），缺乏熟练的劳动力（C3），缺乏技能培训计划和教育（C2）以及投资回报率的不确定性（C9）”是实施工业4.0的主要挑战。最后，获得的结果表明挑战如何影响其他挑战，从而找出触发其他挑战的根本原因。然后，行业从业人员和管理人员可以利用这些分析来了解哪些挑战是实施Industry 4.0的主要障碍，并且需要首先进行重点关注以寻求解决方案。