Digital Twin as Transformational Technology
Let’s examine these characteristics in context with some common technology dilemmas process companies face right now. One example at the plant level is digital twins for predictive and prescriptive analytics. What would or should a plant do differently if it knew with high confidence that a piece of critical equipment was going to fail in 60 days? If the planning, scheduling maintenance, and operations processes don't change when it knows the impact, then what's the point of using digital twin technology? The opportunity for improvement is lost.
Let's consider a different scenario, this time at the corporate level. In this example, the operating company has two plants, each manufacturing the same specialty chemical using the same process. One plant meets and often exceeds volume targets but has trouble with quality, while the other produces consistently high-quality product but struggles with downtime. Both plants supply product to the same set of customers in multiple locations. How can the operating company get a handle on the disparities, and what should it do differently?
Each plant will undoubtedly understand its unique situation, but does corporate understand the details? How can the company compare and analyze differences without the right visibility and tools? Further, how can corporate evaluate the impact on customer satisfaction? What’s required so they two plants can share experiences and help solve each other's problems?