Development of an Assessment Model for Industry 4.0: Industry 4.0-MM


Gokalp E. , ŞENER U. , EREN P. E.

17th International Conference on Software Process Improvement and Capability Determination (SPICE), Palma de Mallorca, İspanya, 4 - 05 Ekim 2017, cilt.770, ss.128-142 identifier identifier

  • Cilt numarası: 770
  • Doi Numarası: 10.1007/978-3-319-67383-7_10
  • Basıldığı Şehir: Palma de Mallorca
  • Basıldığı Ülke: İspanya
  • Sayfa Sayıları: ss.128-142

Özet

The application of new technologies in the manufacturing environment is ushering a new era referred to as the 4th industrial revolution, and this digital transformation appeals to companies due to various competitive advantages it provides. Accordingly, there is a fundamental need for assisting companies in the transition to Industry 4.0 technologies/practices, and guiding them for improving their capabilities in a standardized, objective, and repeatable way. Maturity Models (MMs) aim to assist organizations by providing comprehensive guidance. Therefore, the literature is reviewed systematically with the aim of identifying existing studies related to MMs proposed in the context of Industry 4.0. Seven identified MMs are analyzed by comparing their characteristics of scope, purpose, completeness, clearness, and objectivity. It is concluded that none of them satisfies all expected criteria. In order to satisfy the need for a structured Industry 4.0 assessment/maturity model, SPICE-based Industry 4.0-MM is proposed in this study. Industry 4.0-MM has a holistic approach consisting of the assessment of process transformation, application management, data governance, asset management, and organizational alignment areas. The aim is to create a common base for performing an assessment of the establishment of Industry 4.0 technologies, and to guide companies towards achieving a higher maturity stage in order to maximize the economic benefits of Industry 4.0. Hence, Industry 4.0-MM provides standardization in continuous benchmarking and improvement of businesses in the manufacturing industry.