Investigation into the efficiency of a PLM system

Abstract

This thesis explores time-related data recorded within a Product lifecyle management (PLM) system, with a focus on Engineering Change Requests (ECRs). A total of 166 ECRs were collected, categorized into four distinct cases, and analyzed to understand process times, task distribution, outlier occurrences, and iterative work. Data was manually gathered and visualized using box plots. The analysis showed that cases handling Product Change Requests (PCRs) had significantly longer and more variable processing times, often due to inactive time being recorded as active work in the data. Furthermore, a noticeable proportion of outliers and iterative work were found in certain data sets generally belived to be caused by the requirement of PCRs. Limitations in the data included lack of clear project identifiers, inconsistencies in how time was recorded, and the inability to differentiate between rework and multi-article tasks. Despite these constraints, inefficiencies were identified such as idle time, undocumented steps, and inconsistent timestamping. The thesis finds that the PLM data is not fully representative of actual work, but inefficacies are and were still possible to be identified from the data. Recommendations for improving data quality include automation of data collection, better categorization of ECRs, and improving data tracking. These measures would support better process understanding and lead to potential efficiency increase in the product change workflows