Disruption attributes for low-volume, complex product assembly
The assembly process of most low-volume, complex products (LVCP) suffers from disruptions. Disruptions are deviations from the planned assembly schedule, which harm the economic performance of LVCP manufacturers. This research investigates how the quality of data on disruption events influences an effective disruption management. For this purpose, we combine a literature review and a single case study at a LVCP manufacturer. The results reveal three areas of action around data completeness to improve data quality and increase the efficiency of disruption management: Increasing population completeness, ensuring column completeness, and designing proper schema completeness.