Background and purpose

Process Failure Mode and Effects Analysis (PFMEA) is an important risk-assessment tool in the automotive industry, however, several shortcomings limit its ability to accurately and proactively predict failure causes in complex production environments such as assembly, where human work activity is central. Traditional PFMEA tends to focus on technical or procedural deviations often overlooking sociotechnical interactions among human, technological, and organizational factors that shape process outcomes. As a result, PFMEA documentation struggles to reflect the actual failure causes observed in daily operations. This degree project investigates the gap between potential failure causes documented in PFMEA and the actual causes identified during assembly operations. The purpose is to conceptually extend PFMEA by integrating human, technological, and organizational factors to support comprehensive failure cause identification of complex work activity.

Methodology

This study adopts a qualitative single-case research design focusing on the assembly operations of a top-tier supplier within the automotive industry. Empirical findings are derived from semi-structured interviews with practitioners and analysis of company documentation, including PFMEA records and 8D reports. The results show that PFMEA’s difficulty in reflecting actual failure causes stems from several interconnected issues: subjective and inconsistent risk evaluations, outdated and reactive documentation practices, fragmented information flows. Findings also illustrated the limitations of traditional PFMEA representing human, technological, and organizational factors, both individually and in terms of their interactions. Many sociotechnical contributors, such as signal visibility issues, tool communication instability, layout-driven constraints, and unclear instructions, were found to be absent from PFMEA despite their clear influence on failure development.

Contributions

Drawing on sociotechnical systems theory and the Human–Technology–Organization (HTO) perspective, this degree project proposes a conceptual HTO-PFMEA framework that structures failure-cause identification across human, technological, and organizational dimensions. This framework enhances PFMEA’s analytical depth and supports more comprehensive identification of potential failure causes. The study contributes to academic discussions on sociotechnical risk assessment and to practical efforts to integrate systems thinking into risk identification and quality management in automotive assembly.