- By Sean Sims
- Executive Corner
Summary
In the past few years, discussion around the Industrial Internet of Things (IIoT), Industry 4.0, cloud, edge, and enterprise connectivity has been pervasive. It is exciting to think about the potential of IIoT, digital transformation, and autonomous operations, but what is often overlooked is that many organizations are operating below capacity, producing off-spec product, and dealing with unplanned production upsets. All of these and other issues can be addressed by optimizing the process control system in place today.
By considering how the control system functions as the core of a successful digital strategy—whether the vision revolves around IIoT, digital transformation, or autonomous operations—organizations can achieve performance gains from their existing automation investments.
Maintaining a robust, well-configured control system is a key element of any digital transformation strategy. Applying new solutions without first leveraging existing automation within the control system means opportunities are missed to increase the value of an organization’s entire digital infrastructure.
Two of the most common areas where organizations underutilize the control system, and as a result leave value on the table, are optimizing control loop performance and implementing state-based control. A predictive modeling infrastructure can help improve production performance, quality, and repeatability. However, if that infrastructure is built on a suboptimal automation foundation and operators do not have the best decision support tools available, existing operational inefficiencies can prevent production and profitability gains when a new production plan is pushed down to the plant.
Control loop performance improvements ensure optimal control capabilities per control loop, which aggregate to significant gains, while state-based control manages normal and abnormal process situations and gives operators the bandwidth to drive peak performance. These proven programs, which are the basis for autonomous operations, have reduced operator interventions by more than 80 percent and increased annual capacity by 1.5 percent, which equates to a fast and long-standing return on investment (ROI). The underlying architecture to support both is likely already part of the plant’s control system and readily available for deployment.
Capturing unrealized value in the control system must also include empowering personnel. An effective alarm management strategy—which in Emerson implementations has achieved as much as a 90 percent reduction in alarms—makes it easier for operators to focus on proactively avoiding abnormal production situations and increasing their span of enhanced control. Many modern control systems also have the ability to configure in-place analytics that provide situational awareness and decision support for operators at a glance, creating the right environment for operators to perform at their best.
One critical strategy for building a strong automation foundation is to optimize control systems immediately after they are deployed, and to make a commitment for continued optimization across the life cycle of the equipment. Organizations that prioritize this strategy early unlock the highest long-term ROI from their systems. It does not take long for a new operation to become the status quo. By making continual optimization part of that status quo, plants maintain a far higher baseline of performance.
At the same time, many plants are staffed to run, not optimize. Increasingly, companies are looking to automation partners for expertise to help them stay on top of the updates, upgrades, adjustments, tools, and process changes that can help keep control infrastructure operating at its best. These providers’ automation expertise and institutional knowledge about their customers’ operations helps optimize the operational foundation today, while preparing them to take the next step toward digital transformation initiatives that deliver the highest value.
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