Automation Strategies: Rethinking automation: A stepwise approach to the IIoT
Energy producers are under tremendous pressure to reduce operational costs and maximize efficiency throughout the value chain. This is easier said than done.
Energy producers are under tremendous pressure to reduce operational costs and maximize efficiency throughout the value chain. This is easier said than done. The efforts of many hydrocarbon producers are hampered by the very operational technology (OT) infrastructure they rely on for critical operations—from supervisory control and data acquisition (SCADA) systems and historians, to automation control systems at satellite facilities and remote pumping stations.
Many of these automation and control systems were installed decades ago and run outdated hardware and software that is nearing or beyond the end of life. While these systems gather potentially valuable data, that data is not easily extractable for higher-level analysis. These legacy systems persist, however, thanks to the philosophy of, “If it ain’t broke, don’t fix it.”
Meanwhile, information technology (IT) has progressed significantly since many of those OT systems were installed. In corporate data centers, IT has advanced to take advantage of new developments in virtualization, connectivity and data analytics. However, as long as OT infrastructure remains behind the times (and behind the wall that separates IT and OT), energy producers will be unable to leverage the enormous potential of Industrial Internet of Things (IIoT) technologies that are transforming process and manufacturing industries worldwide. Connecting machines, equipment and sensors throughout the processing value chain, and linking them with advanced control systems and analytics, is vital to achieving tremendous efficiency gains and unlocking new business insights to drive growth.
What impact can a “connected, intelligent enterprise” achieve? Consider the example of Columbia Pipeline Group (CPG), which needed to improve the reliability, efficiency and uptime of its natural gas transmission infrastructure across nearly 15,000 mi of pipelines in 16 states, stretching from New York to the Gulf of Mexico. The home-grown control systems were outdated and difficult to maintain and repair, requiring a technician to venture to remote pumping stations whenever a system outage occurred—a costly and time-consuming situation.
CPG upgraded its operational environment with state-of-the-art, fault-tolerant, distributed SCADA systems that significantly improved reliability. Even more valuable, however, is the stream of new operational data that is now fed back to the central supervisory control systems, enabling CPG engineers to proactively analyze and optimize operations at a granular level for maximum efficiency. This data can now be integrated with corporate data warehouses for a variety of business analytics. In the first year since the major upgrade, CPG saved approximately $2.3 MM in maintenance costs and reductions in unplanned downtime. CPG is now positioned to run at 100% capacity with near-100% reliability.
Of course, not every enterprise is in a position to make such an extensive—and expensive—upgrade to its OT infrastructure. How can energy companies take meaningful steps toward becoming the intelligent, connected, IIoT-enabled enterprises they want to become, within the realities of their budgetary and technological constraints? A stepwise approach could be the answer.
Step 1: Begin at the center
A realistic strategy is to start by upgrading the central control environment. This enables the improvement of uptime performance and efficiency in the short term, while creating a foundation for incrementally upgrading distributed control systems throughout the plant and at remote locations.
This begins with Level 2 supervisory control and Layer 3 operational and control infrastructure, including supervisory control and asset management systems, the historian, and manufacturing execution and process history systems. While data from Level 1 process controllers and sensors remains unchanged, upgrading the central control environment enables greater use of that data, including advanced analytics to optimize both operational and business planning.
The fact is, many organizations do not effectively use data that they already possess. By enabling advanced analytics, the value of that data increases. For example, data fed from instrumented equipment can be analyzed to help predict when the equipment is at risk of failure. This predictive maintenance capability helps avoid unplanned downtime and assists scheduled maintenance plans, generating significant savings and maximizing uptime.
Step 2: Expand outward
As organizations begin to reap the rewards of an upgraded central control environment and advanced analytics, one thing becomes clear: The more data that is gathered, the greater the value and accuracy of the analytics, which is a key component of the IIoT value proposition. Extending an intelligent, connected enterprise to individual machines throughout an operational infrastructure—down to individual sensors, actuators and control valves—takes automation and predictive management to an entirely new level.
Progressing through the value chain with state-of-the-art intelligent control technology can be a major investment, depending on the extent of operations, but the CPG case is evidence that the rewards can be significant.
Future upgrades to the Level 1 basic control environment, including process controllers, sequence/batch controllers, programmable automation controllers, and the Level 0 infrastructure of sensors, control valves and actuators, can unlock tremendous value. Rather than collecting data every few seconds, data can be collected almost continuously from hundreds of sensors. Feeding this data back to analytics engines enables near-real-time management to optimize performance and uptime.
Given budgetary realities, this may be an aspirational vision for many in the hydrocarbon industry, but the return on investment is there, measured in terms of increased productivity and efficiency, and reduced unplanned downtime.
Focus on availability
Regardless of the extent of infrastructure upgrade plans, having a solid availability strategy is a key factor in reaping the full benefits of system modernization. Replacing outdated PCs with state-of-the-art, standards-based virtual servers offers many benefits: significant footprint reduction, simplified diagnosis and repair, simplified provisioning of new applications, and reduced systems management workload, among others.
Virtualization does present challenges: Consolidating multiple control applications on a single physical machine replaces many points of potential failure with a single point, which can increase exposure to unplanned downtime. As the move is made toward a true IIoT infrastructure, the volume and value of data increases significantly. Ensuring an uninterrupted stream of data is crucial. While traditional failure recovery technologies are designed to bring systems back up quickly, they do not prevent failure, and that can mean that “in flight” data is lost.
Focusing on fault-tolerant solutions that provide an “always on” virtualized processing environment is a critical factor in IIoT migration success.
Reducing the risk of modernization
For OT professionals, change introduces risk potential, yet it is essential to keep pace with ever-growing demands on the hydrocarbon industry to maximize efficiency and reduce costs. By taking a thoughtful, incremental approach to upgrading automation and control infrastructure, it is possible to reap the advantages of modernization while minimizing risk.
Beginning with the central supervisory control infrastructure and moving upstream as the business permits allows the utilization of IIoT technologies that are redefining the oil and gas industry. The sooner the first step is taken, the sooner the financial and competitive advantages offered by the IIoT can be enjoyed. HP
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