Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories

Manufacturing systems are dynamic and exhibit increasing complexity and uncertainty. Smart manufacturing uses Data Analytics methods to optimize manufacturing processes, systems and products. One approach to structure use cases in production management in smart manufacturing is the Product-Process-Resource (PPR) model, where the resource executes a process on a given product. The PPR model needs to be extended for smart manufacturing, to meet the requirements of prescriptive analytics (but not exclusively). Our contributions are an extended PPR model for prescriptive analytics (P2PR) that involves environmental effects, expert knowledge and adds a process sub-model distinguishing between manufacturing and supervisory processes. We develop prescriptive analytics decision-making categories based on the area of validity and the degree of interconnectivity. The combination results in a systematization scheme for prescriptive analytics use cases in a smart factory environment. It assists entities to find shared characteristics in different prescriptive smart factory use cases within one production ecosystem. A mapping of prescriptive algorithms (as part of a use case) to a category and domain is enabled for future case studies.