Process Transparency: Effects of a Structured Read Point Selection

Modern supply chains, especially in the automotive industry, are prone to events that endanger their ability to deliver products on time. Comprehensive real-time tracking and tracing systems (e.g. RFID-based) can help in making them more robust by identifying events and enabling early responses that are capable of mitigating adverse effects. However, these systems are rarely realized and read points only placed in a few default locations (e.g. receiving and shipping) without further considerations. In this contribution weighted linear optimization models are used to assess the effect of including process characteristics such as variability and cycle times in this decision problem. Using an intuitive simulation setup in which the degree of transparency and system sensitivity are varied, the results indicate that locating read points in sensible places along a process rather than by chance can reduce false alarms by 31% while raising successful identifications by 2%.