Journal of Software Engineering and Applications

Volume 10, Issue 8 (July 2017)

ISSN Print: 1945-3116   ISSN Online: 1945-3124

Google-based Impact Factor: 1.22  Citations  h5-index & Ranking

From Mechatronic Components to Industrial Automation Things: An IoT Model for Cyber-Physical Manufacturing Systems

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DOI: 10.4236/jsea.2017.108040    2,305 Downloads   4,599 Views  Citations

ABSTRACT

IoT is considered as one of the key enabling technologies for the fourth industrial revolution that is known as Industry 4.0. In this paper, we consider the mechatronic component as the lowest level in the system composition hierarchy that tightly integrates mechanics with the electronics and software required to convert the mechanics to intelligent (smart) object offering well defined services to its environment. For this mechatronic component to be integrated in the IoT-based industrial automation environment, a software layer is required on top of it to convert its conventional interface to an IoT compliant one. This layer, which we call IoT wrapper, transforms the conventional mechatronic component to an Industrial Automation Thing (IAT). The IAT is the key element of an IoT model specifically developed in the context of this work for the manufacturing domain. The model is compared to existing IoT models and its main differences are discussed. A model-to-model transformer is presented to automatically transform the legacy mechatronic component to an IAT ready to be integrated in the IoT-based industrial automation environment. The UML4IoT profile is used in the form of a Domain Specific Modelling Language to automate this transformation. A prototype implementation of an Industrial Automation Thing using C and the Contiki operating system demonstrates the effectiveness of the proposed approach.

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Foradis, T. and Thramboulidis, K. (2017) From Mechatronic Components to Industrial Automation Things: An IoT Model for Cyber-Physical Manufacturing Systems. Journal of Software Engineering and Applications, 10, 734-753. doi: 10.4236/jsea.2017.108040.

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