How edge computing is affecting remote services in the process industry?: Risks, opportunities, and required capabilities

Abstract

The process industry has moved towards digital servitization and data-driven services to provide value for the end customer. A common way has been to do remote monitoring in the cloud and perform remote services with cloud-based IoT applications and other analytical capabilities. Since the amount of data is increasing and the requirements for remote services are changing, the cloud can not answer all demands anymore. The huge amount of data has caused latency and increased data processing costs in the cloud. Hence a new solution edge has been proposed to answer the real-time requirements and to reduce the burden of the cloud for a better user experience and minimized latency and costs. The edge solution is still a new solution, which is why there is yet no clear definition of how it should be utilized in the process industry and what are its roles compared to the cloud. This research was done as a case study. The case company wanted to understand how an edge solution will change the traditional way of performing remote services in the cloud and what kind of capabilities are needed to keep performing remote services at the edge. Hence, this research aims to understand how edge solution will change how remote services are performed, and what needs to be taken into account when developing edge solution for enabling remote services at the edge. The base understanding and base theory of the topic were collected from the case company and with a literature review. The defined theory was then tested with a case study in the case company consisting of a pre-questionnaire and interviews with research participants to collect both qualitative and quantitative data. As a result, findings from the literature review and case study were combined to answer the research problem and seven sub-research questions. It was found that the edge cloud can not fully replace the cloud since the cloud has still some strengths and opportunities that the edge can not meet like fleet monitoring and training more advanced analytical models. Edge solution can broaden the service and product portfolio by enabling local solutions of the offering for customers who do not want to transfer their data to the cloud. Edge can also act as an extension of the cloud to answer real-time requirements and lower the burden of cloud computing and possibly minimize costs. This model is a hybrid model where the strengths of both cloud and edge are utilized to achieve the best outcome. In the hybrid model, the edge can handle pre-processing data that can then be transferred to the cloud for post-processing. Cloud can handle training more advanced analytical models which edge does not have enough capacity for and the trained model attributes can be transferred to edge for local implementation. To enable performing remote services at the edge, there needs to be remote access which enables easy access to the solution. Additionally, the roles of edge and cloud need to be clearly defined in a hybrid model. This research guides companies working in the process industry and providing remote services about how edge solution should be utilized and what needs to be considered when developing the solution. Additionally, the research creates a base for further studies. The topic is wide which is why there are a lot of possibilities for future work. For literature, this research fills the identified gap and provides a further understanding of the edge in the context of process industry and remote services.