IDC Interview with Schneider Electric

IDC EUROPEAN FUTURE OF OPERATIONS DIGITAL SUMMIT 2021

We had the great pleasure to exchange views on the topic with the Keynote Speakers and Breakout Session Leaders of the IDC European Future of Operations Digital Summit 2021. The following interview was conducted by Jan Burian, Senior Research Director, Manufacturing Insights, IDC EMEA and Hervé Hellez, Director of Commercial and Industrial Business, Schneider Electric, Secure Power Division, Europe

Jan Burian: The COVID-19 pandemic has accelerated a digital transformation across industries. To what extend the industrial edge is being a part of this transformation?

Hervé Hellez: There is little doubt that the pandemic has helped to accelerate digital transformation within many areas of business, as a new survey from IDC confirms, with over 40% of all respondents agreeing that hybrid working models will become an embedded part of accepted working practices; many of which being supported by digital transformation and IoT projects

Covid has helped to accelerate digital transformation in the industrial space due to the requirement to have fewer people on the factory floor for safety and social distancing. Running existing processes with fewer people is also a natural progression enabled via digital transformation, however, Covid has certainly sped up adoption of new technologies that enable such processes.In the case of Industry 4.0, the nature of the manufacturing sector means that IT needs to be deployed close to the point of operation. In fact, avoiding downtime is critical, especially in the case of businesses with perishable raw materials such as the food or pharmaceutical sectors, and the costs of lost production in some sectors such as automotive can reach a million euros per hour.

To ensure high levels of availability, resilience and reliability, computing resources have to be located right at the point of use, in other words at the edge. Industry 4.0 technologies such as advan-ced robotics, HD video processing and predictive maintenance all require low levels of latency, meaning it’s a necessity to have a hybrid IT approach. Here edge computing becomes a key component for mission-critical industrial applications requiring ultra-fast connectivity and data transmission.

Burian: Have you recognized some new (maybe even disrupting) edge computing use cases recently?

Hellez: IT has been part of the industrial environment for a long time, with process automation and software supervision as leading drivers. Of late, the sheer volume of data that is now available to industrial operators, thanks to the ubiquity of IoT sensors and high-definition video cameras, is creating new levels of operational insight and intelligent decision-making.

Digital Twins, for example, enable operators to accurately model and test their environment, driving predictive capabilities while offering data-driven insights. AI is also helping develop new and more accurate algorithms for predictive maintenance, allowing plant managers to plan their maintenance and asset replacement programs with greater ac-curacy, at lower cost, and with far less downtime.

Other examples include the use of real-time video in what were previously manual and labour-intensive quality assurance processes. This may be within the inspection of bottled products to ensure that corking, labelling, and filling are within tolerances. Warehousing processes are also being transformed by the use of autonomous robotics and artificial intelligence (AI), and are in most cases enabled by industrial edge computing deployments.

Smart warehouse technologies require significant on-site compu-ting power, to drive efficiency and automation. This includes managing the carts, their recharging schedules, and collecting or repositioning stock when it is needed.

Burian: How would you explain the line between industrial edge computing and cloud computing? Are these two technologies com-peting or complementing each other?

Hellez: The edge and the cloud are completely complementary and symbiotic; they both bring strengths that complement each other, especially within the industrial environment.

Although the cloud offers the potential of almost infinite computing resource, the issues of latency, application or production line resilience, and data sovereignty require that some computing infrastructure must be situated on site.

In simple terms, the cloud is the best place in which to develop the learning algorithms and processing, made possible by the volume of data collected at the edge. Aggregating and assembling data from multiple sites and multiple systems to deliver deep insights into the production process and the operating equipment clearly offers significant business benefits.

Given the volume of data and the resource required, it is essential that this work is performed within intensive data processing sites at the centre of the network. However, deployment of such learnings or turning them into actionable processes is best performed at the edge, ensuring maximum uptime, speed of response, and resilience.

Burian: What are the typical industrial edge computing deployment barriers? Could you share your recommendation on how to overcome them?

Hellez: We see four main challenges to be overcome when deploying industrial edge computing systems.

First, there is the combined challenge posed by security and environmental concerns. Locating compute close to an industrial production line, or in a hazardous area such as excavation or mining, forces one to contend with issues such as vibration, dust ingress, poor air quality, or excessive temperature.

These challenges can be met with preintegrated, ruggedized enclosures and air-conditioning systems, at the expense of additional capital cost. Security is also crucial and the task of preventing un-authorised access, both in terms of physical and cyber intrusion, requires adequate security measures to be put in place.

Secondly, maintaining IT equipment in locations without adequate on-site technical personnel is a key challenge for operators. This can be resolved through cloud-based management software, remote monitoring, and external maintenance partners equipped with appropriate access devices.

Perhaps the major issue, however, is the IT/OT competency gap. Typically, industrial operators have built up great expertise in how their processes work or can be improved without having the knowledge of how IT capabilities can support their objectives or specific considerations to be taken for their deployment. Likewise, IT professionals may understand their own systems, but may be less knowledgeable about how they can best be deployed in support of an industrial organisation’s strategy.

Here bridging the gap via collaboration is essential and we see companies implementing multi-functional digitization teams or rely on external expertise.

Finally, a related challenge is the issue of standardised IT systems. This is a particular issue for large organisations with multiple sites, all of whom may have grown organically with their own IT systems, or by acquisition of companies with incompatible systems.

Frequently, the task of reconfiguring one site’s data so that it is interoperable with that of another’s can consume most of a data scientists time, resulting in prolonged “Pilot Purgatory” and delaying the implementation of more productive IT systems. Here the development of standards or ontology for interoperability is key.

Burian: How can the organization leverage industrial edge computing in the most effective way?

Hellez: The main benefits of industrial edge computing systems are that production processes will become more reliable and efficient, new technologies can be deployed to drive greater productivity, efficiency, and profitability, and that business processes can be transformed to satisfy changing customer demands. Edge computing also helps industrial operators become more resilient and agile across their entire supply chain, enabling them not only to meet changing customer demands but manage their operations reliably during macro-economic disruptions, for example, CO-VID-19, or other challenging conditions.

A key competency is the ability to define a clear use case before deployment. This will help to clarify exactly what IT resources are needed and avoid expensive overruns caused by “digitising for digitising’s sake”. Once the pilot is proven, then standardization is another key consideration to speed up deployment across multiple sites.

The challenge of bridging the IT/OT competency gap can best be achieved by the strategic deployment of digitisation teams, tasked specifically with extracting the maximum benefit from IT in industrial processes. Led by a CDO (Chief Digitisation Officer) and staffed with personnel whose expertise spans both IT and OT disciplines, such teams can smooth the transition and produce more streamlined and efficient outcomes.

Using external consultancies or partners, many of whom have developed their own expertise in the area of collaboration and compatibility, can also speed up the deployment of industrial applications delivered at the edge.

Finally, the benefits of standardisation will lead to faster deployment of mission-critical IT and offer the ability to scale across multiple sites. Prefabricated and pre-tested, ruggedized micro data centres offer operational reliability in the harshest environments and can be designed to fit in the most space-constricted locations. This enables all the benefits of ultra-secure, on-site, edge computing, and the processing scale of the cloud, to be exploited by industrial organisations.

Burian: Thank you for the interview, Hervé.