Achieving Higher Scheduling Accuracy in Production Control by Implementing Integrity Rules for Production Feedback Data

Excellent production planning and control (PPC) processes are a prerequisite for accomplishing a high adherence to promised delivery dates. Despite enormous efforts which are put into achieving high scheduling accuracy, manufacturing companies still regularly struggle in meeting their logistic targets. In consequence, these companies deal with high stocks, long lead times and ultimately only achieve a bad adherence to promised delivery dates. An important reason for this discrepancy are data inconsistencies, which occur in data collected on the shop floor, because these data are used to update the near- and middle-term scheduling of current production jobs. In this paper, the impact of several data inconsistencies in real-world production feedback data sets are investigated. Integrity rules for selected data inconsistencies are proposed and tested for their effects on a number of logistic targets in a simulation study.