9DECEMBER 2023Normalized metrics attempt to present figures somewhat independent of variations in production output to enReporting and Learning Sable performance comparisons between lines/plants over time. However, they cannot provide any real indication of the opportunity for improvement (i.e., `waste' identification and Quality and Performance Iquantification). Whereas the purpose of the NPC metric is to directly measure the actual waste (opportunity for improvement).In a simplified example in the context of a manufacturing plant in the food & beverage industry, the NPC could span three aspects of production and could include:1. Packaging Materials: The portion of packaging materials that don't make it to a finished saleable product (including finished but non-saleable products)2. Product: This includes the loss of both not-yet-packaged products during the production process, as well as within finished non-saleable packaged product3. Energy & Utilitieso Idle runs (periods in between actual production runs where the production line is on/powered up, temperatures are maintained, and Physical Security compressed air systems are at pressure)o Efficiency gap (loss): The energy consumption of a proData Managementduction run as compared to past best performance for a similar volume of the same product on the same production lineThese aspects are not trivial to incorporate into an automated, sustainable NPC metric (especially the efficiency gap). They require integrating accurate plant floor data (segregated by production run or batch) with higher-level database content on material and products.There is no real way to objectively measure the upper limit for `maximum efficiency' as it will change over time as the inherent efficiency of new equipment improves. One of the strengths of the efficiency gap component of the NPC metric is that it provides a relative comparison against the Cybersecuritybest performance that has been achieved on the same plant/line for the same product. Hence, by definition, it is a real achievable target. Another advantage of this metric type is that it is inherently adaptive, as the target will change over time as the line becomes more efficient.While Industry 4.0 infrastructure could be sufficient for monitoring NPC, digital twins have the potential to provide a greater opportunity to improve NPC. In addition to providing the infrastructure required for high-fidelity measurement and identification of NPC, digital twins enable simulation-based scenario analysis of the impact that changes to equipment and processes could have on NPC. Some more specific examples could include such things as:· Simulate the impact of energy-aware scheduling on product sequence, idle runs, and, ultimately, NPC· Simulate the impact of product sequence (change-over and run-out) on packaging yield· Compare the NPC for production of Incident Response Plansthe same SKU across different lines (and plants)· Provide quantified evidence-based input into the determination of minimum viable run-length (map the NPC by production run-length)· Compare NPC variation (for the same line and Regular Audits and Assessments3.SKU) by shift/operator-crewIt Is Not the Tool (Digital Twin) That Will Bring You Success, It Is What You Do With ItWhile digital twin platforms promise a wealth of different opportunities for business impact, they are typically a significant investment. A strong business case can help to garner the support to acquire one and, importantly, to increase the li4.kelihood of realizing the aspired return on investment.Waste reduction is an ever-appealing direction as it can be very profitable while also reducing the environmental impact of the business (and consequentially of its upstream supply chain). It can sometimes also result in an effective capacity increase of the plant. Waste reduction opportunities become progressively more difficult to find in plants that are 5.not new to this journey and are already somewhat efficient.Having a specific pathway to focus on (such as NPC) can support and strengthen a business case as well as improve the realized return on investment. Importantly, a focus on NPC can provide a pragmatic and structured pathway to quantify and predict a realistic and achievable target. The digital twin paradigm provides the required informatics infrastructure and scenario analysis opportunity to enable NPC to be both monitored and improved.No one wins if end users do not realize a return on their digitization investment. No one wins if end users do not realize a return on their digitization investment
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