Revising standard operating procedures to improve Time Data Management A case study at SKF

Abstract

This thesis investigates how standard operating procedures (SOPs) at SKF can be designed to support reliable Time Data Management (TDM). Reliable time data and efficiency measures are essential for production planning, cost calculation, and strategic decision- making. However, manufacturing companies often experience mismatches between actual shop-floor operation times and the time standards stored in databases and systems. At SKF, the implementation of a new manufacturing intelligence system (MIS) has created new opportunities to improve the quality and traceability of production data. However, reliable TDM depends not only on technological capabilities, but also on clearly defined organizational procedures and responsibilities. The study was conducted as a mixed-method case study at SKF’s roller bearing production facilities in Gothenburg. Empirical data were collected through internal documentation, semi- structured interviews, workplace discussions, observations, and production related data. The collected data was analyzed to identify recurring issues, patterns, and organizational challenges connected to the management of time data and efficiency measures. In addition, several identified issues were further examined through quantitative analysis. The findings revealed challenges related to both the design of the existing SOPs, and the adherence to them in practice. Weaknesses were identified regarding unclear responsibilities, inconsistent definitions, insufficient alignment between systems, infrequent updates of time data and efficiency measures, and reliance on comparison and estimation-based time determination methods. Together, these challenges contribute to reduced reliability of data used in production planning and standard cost calculations. Based on the findings, an updated SOP is proposed to support more reliable TDM. The proposed approach establishes clearer ownership of tasks, consistent definitions, improved alignment between systems, and a standardized revision procedure supported by data enabled by the MIS, thereby improving the reliability of data used in production planning and cost calculations.