Electric drives as fog nodes in a fog computing‐based industrial use case

Abstract

Electric drives, which are a main component in industrial applications, control electric motors and record vital information about their respective industrial processes. The development of electric drives as Fog nodes within a fog computing platform (FCP) leads to new abilities such as programmability, analytics, and connectivity, increasing their value. In this study, the FORA FCP reference architecture is used to implement electric drives as Fog nodes, which is called "fogification". The fogified drive architecture and its components are designed using Architecture Analysis and Design Language (AADL). The design process was driven by the high-level requirements that the authors elicited. Both the fogified drive architecture and the current drive architecture are used to implement a self baggage drop system in which electric drives are the key components. The fog-based design was then evaluated using several key performance indicators (KPIs), which reveal its advantages over the current drive architecture. The evaluation results show that safety-related isolation is enabled with only 9% overhead on the total Fog node utilization, control applications are virtualized with zero input-output jitter, the hardware cost is reduced by 44%, and machine learning at the edge is performed without interrupting the main drive functionalities and with an average 85% accuracy. The conclusion is that the fog-based design can successfully implement the required electric drive functionalities and can also enable innovative uses needed for realizing the vision of Industry 4.0. INTRODUCTIONIndustry 4.0 is an industrial revolution via digitalization that affects all industries and sectors. Digitization increases productivity, flexibility, and product quality. Moreover, it reduces time-to-market and supports mass-customization [1]. When machines become connected with each other, sensors, and actuators, they form the Industrial IoT (IIoT), which is expected to increase the global gross domestic product (GDP) value to USD 15 trillion by 2030 [2]. The convergence of Operational Technology (OT) and Information Technology (IT) drives this digital transformation [3]. However, OT and IT use different computation and communication technologies [3]. OT employs dedicated hardware and software to implement real-time and safety-critical applications that have stringent timing and dependabilityThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.