Facilitating Engineering Process Alignment, Quality, and Productivity through Cross- Functional Standardization

Abstract

Ensuring consistency, traceability, and comparability in complex engineering activities remains a key challenge in global organizations, particularly when practices evolve locally across multiple sites. This thesis investigates these challenges within the context of bearing life testing, where variations in workflows, documentation, and data management limit the effective reuse and interpretation of test results over time. The study was conducted as a single case study at SKF, combining document analysis, expert interviews, and iterative concept development based on a Six Sigma-inspired methodology. The objective was to develop a structured framework that improves transparency, supports evaluation, and enables systematic reuse of life testing knowledge while maintaining flexibility for practical engineering. The result of this work is a multi-layered framework consisting of three core elements: a modular structure describing the life testing process, a maturity perspective enabling evaluation of test completeness and quality, and a data management perspective supporting structured data management and long-term knowledge retention. Across three iterative concepts, the framework evolves from a descriptive reference model into an applied and decision-support-oriented system, incorporating deliverable-based gating, maturity evaluation, and data integration. The findings demonstrate that the primary limitation in engineering testing is not technical capability, but the lack of a shared structure for describing, evaluating, and reusing knowledge from activities. By introducing a standardized yet flexible framework, the study shows how transparency, consistency, and comparability can be improved across sites. The proposed approach supports both operational decision-making and long-term organizational learning by making implicit practices explicit and enabling systematic continuous improvement by tracking performance over time.