One of the discussion points from ARC’s latest DCS market research “Distributed Control Systems Worldwide Market Outlook”, concerned cloud computing adoption as related to process automation systems.
Confusion Over Implementation Practices is Limiting Adoption
Most process automation end users are convinced of the benefits of cloud computing technologies and many of them are ready to begin embracing them. However, there is still a great deal of confusion regarding how to begin adopting cloud and which applications are best suited to the cloud. This confusion is preventing many end users from investing in cloud, or worse, causing them to invest in areas that will not improve their operations. In many cases, end users are forced into making their initial investments with unclear benefits or returns.
Knowing Where, And How, to Implement Cloud Computing is Critical
When wisely deployed, cloud can greatly improve operations and flexibility. However, end users should carefully consider where and how to implement before rushing into a project. From an application perspective, consider the criticality of the application, its required speed of response, and its location, when determining the applicability of cloud. Predictive maintenance applications designed to reduce asset downtime and maximize asset performance are typically the best fit for the cloud because many of these applications are less critical and do not require real-time response. In fact, many end users are not actively monitoring many of their assets at all today, so embracing cloud to monitor them opens the door to new monitoring applications.
The location of the assets is another important factor. As processes become ever more remote, and operations more extensive, it becomes expensive and hazardous for end users to monitor their remote assets in the traditional fashion. End users with such operations should consider cloud technologies for remote operations monitoring and management. In many cases, embracing cloud technologies that allow remote operations management to enable related improvements in HMI flexibility, alarm management, and presentation, location independence and scalability.
End users should consider edge computing as a first step toward cloud. Edge computing devices are particularly useful due to the tidal wave of data generated by industrial devices and smart sensors. End users need to filter and massage this data to prevent overloading of low-capacity networks and prevent higher-level platforms from being flooded. Too much data, without any actionable advice to go along with it, is a common problem among end users who have not properly thought through their initial deployment. Edge computing, fog computing, and similar strategies to both prevent this data deluge and can deliver feedback locally for low-latency applications.
Consider Partnering with a DCS Supplier
In many cases, it may make sense for end users to begin their adoption of cloud technologies by entering into a partnership with their DCS supplier, who often can provide remote monitoring and diagnostics “as a service.” However, to benefit fully from this type of diagnostic service, operations/maintenance/engineering teams need to begin working together with IT to identify and resolve any existing roadblocks, and allow analytics suppliers access to a well-defined set of process-related data.