Abstract

The Industrial Internet of Things (IIoT) is becoming a reality thanks to Industry 4.0, which requires the Internet connection of as many industrial devices as possible. The sharing and storing of a huge amount of data in the Cloud allows the implementation of new analysis algorithms and the delivery of new “services” with added value. From an economical point of view, several factors can decide the success of Industry 4.0 new services but, among others, the “short latency” can be one of the most interesting, especially in the industrial market that is used to the “real-time” concept. For these reasons, this work proposes an experimental methodology to investigate the impact of quality of service parameters on the communication delay from the production line to the Cloud and vice versa, when gateways with OPC UA (Open Platform Communications Unified Architecture) are used for accessing data directly in the production line. In this work, the feasibility of the proposed test methodology has been demonstrated by means of a use case with a Siemens S7 1500 controller exchanging data with the IBM Bluemix platform. The experimental results show that, thanks to the proposed method, the solutions based on OPC UA for the implementation of industrial IoT gateways can be easily evaluated, compared and optimized. For instance, during the 14-day observation period of the considered use case, the great impact on performance of the Quality of Service parameters emerged. Indeed, the average communication delay from the production line to the Cloud may vary from less than 90 ms to about 300 ms.

Highlights

  • Nowadays, the industrial world is using many technologies created for the consumer market and Internet: low-cost sensors, advanced computing and analytics [1]

  • The impact of Node.js can be estimated around 10% of the processing power of the gateway used in the demonstration use case

  • This paper deals with a methodology to measure time delay metrics in OPC UA systems in order to study the impact that quality of service parameters have on the communication delay from the production line to the Cloud and vice versa

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Summary

Introduction

The industrial world is using many technologies created for the consumer market and Internet: low-cost sensors, advanced computing and analytics [1]. The surprising level of connectivity supports the so called fourth industrial revolution, promising greater speed and increased efficiency. New embedded sensors/instruments with connectivity features move data from the production site (i.e., the machines) to the Cloud. The collection of data takes place from every production site in the world and, the giant quantity of gathered data is analysed. In this way, new services, derived from the analysis of the data, are offered with the intention of improving both the general system and the single machine performance [2].

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