Predictive Production Planning Considering the Operative Risk in a Manufacturing System

Abstract

Customers’ ever more stringent quality requirements, continually shrinking product-life-cycle durations, and a rising number of variants confront manufacturing companies with new challenges. Reliable production is fundamentally important for any industrial company attempting to address these challenges. An effective risk management system helps to ensure such production. The ongoing digitization of production systems also yields new possibilities for evaluating production risks such as machine failures or delivery delays. Especially the growing number of sensors in production systems increases the availability of data for a manufacturing system. This data can be employed to more precisely recognize process related, operative risks during the production process. This offers the opportunity to act on possible risks during production planning and control (PPC). PPC-like sequencing or machine scheduling can hence be applied to reduce risks in a manufacturing system. We therefore present a new approach for a production planning system taking a production system's actual risk level into account. Risk identification in and modeling of a production system is therefore proposed. The evaluated risk then has to be integrated into the planning procedures to reduce the risk level in a manufacturing system. A prototypical application scenario is subsequently presented to demonstrate the approach's feasibility.