An approach to support Industry 4.0 adoption in SMEs using a core-metamodel

Abstract Despite the recent growing interest in the “factory smartness”, still there are only few small and medium enterprises (SMEs) that adopt effective Industry 4.0 (I4.0) solutions. The main reasons can be related to the lack of formalized processes, lack of ICT knowledgeas well as low-cost commercial systems.To cope with these issues, this work focuses on the development and the application of an approach to provide SMEs with a multi-purpose, modular, knowledge-based system: the main aim is to provide a modular and extensible system that can be incrementally implemented without requiring huge initial investments.This system is based on a core design-knowledge meta-model. From this core meta-model, multi-purposes modules can be built: in this paper, we present modules for the traceability support, the AR-powered assembly support, the machine-to-machine control and the data analysis support.

[1]  Irlán Grangel-González,et al.  Towards a Semantic Administrative Shell for Industry 4.0 Components , 2016, 2016 IEEE Tenth International Conference on Semantic Computing (ICSC).

[2]  Klaus-Dieter Thoben,et al.  "Industrie 4.0" and Smart Manufacturing - A Review of Research Issues and Application Examples , 2017, Int. J. Autom. Technol..

[3]  Fei Tao,et al.  Cloud manufacturing: a computing and service-oriented manufacturing model , 2011 .

[4]  Malte Brettel,et al.  How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective , 2014 .

[5]  Kagermann Henning Recommendations for implementing the strategic initiative INDUSTRIE 4.0 , 2013 .

[6]  Michele Dassisti,et al.  An approach to support I4.0 adoption in SMEs: a core-metamodel and applications , 2018 .

[7]  Tim Berners-Lee,et al.  A Demonstration of the Solid Platform for Social Web Applications , 2016, WWW.

[8]  Michele Dassisti,et al.  Enterprise Integration and Economical Crisis for Mass Craftsmanship: A Case Study of an Italian Furniture Company , 2012, OTM Workshops.

[9]  Marco Santochi,et al.  Automated Sequencing and Subassembly Detection in Assembly Planning , 1992 .

[10]  Jürgen Beyerer,et al.  Plug & produce by modelling skills and service-oriented orchestration of reconfigurable manufacturing systems , 2015, Autom..

[11]  Michele Dassisti,et al.  Hybrid Production-System Control-Architecture for Smart Manufacturing , 2017, OTM Workshops.

[12]  Michele Dassisti,et al.  Anti-logicist framework for design-knowledge representation , 2015, Annu. Rev. Control..

[13]  Tino Langer,et al.  Developing and Harnessing the Potential of SMEs for Eco-efficient Flexible Production , 2017 .

[14]  Thomas Bauernhansl,et al.  Mobilizing SMEs Towards Industrie 4.0-enabled Smart Products , 2017 .

[15]  Biqing Huang,et al.  Cloud manufacturing service platform for small- and medium-sized enterprises , 2012, The International Journal of Advanced Manufacturing Technology.

[16]  Jay Lee,et al.  A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems , 2015 .

[17]  Thomas Greiner,et al.  Two-Stage Orchestration Approach for Plug and Produce Based on Semantic Behavior Models , 2016, 2016 IEEE Tenth International Conference on Semantic Computing (ICSC).

[18]  Zahir Tari,et al.  On the Move to Meaningful Internet Systems. OTM 2018 Conferences , 2018, Lecture Notes in Computer Science.