A Quasi-Experimental Evaluation of Risk Reduction Methodologies in Nigerian Manufacturing Systems

{ "background": "Manufacturing systems in Nigeria face significant operational risks, yet there is a paucity of rigorous, field-based evaluations comparing the efficacy of different risk reduction methodologies within this context.", "purpose and objectives": "This study aimed to conduct a quasi-experimental comparison of two prominent risk reduction methodologies—Failure Mode and Effects Analysis (FMEA) and a tailored Hazard and Operability Study (HAZOP) variant—to determine their relative effectiveness in mitigating identified risks.", "methodology": "A quasi-experimental design was implemented across four comparable manufacturing plants. Two plants were assigned to each methodology. Pre- and post-intervention risk scores were collected over an operational period. The core treatment effect was estimated using a difference-in-differences model: Yit = \β0 + \β1 + \β2 + \β3 ( \× ) + \εit, where robust standard errors were clustered at the plant level.", "findings": "The tailored HAZOP variant yielded a significantly greater reduction in mean risk priority numbers. The estimated coefficient \β₃ was -18.7 (95% CI: -22.3, -15.1), indicating a substantially stronger treatment effect compared to the FMEA approach. Thematic analysis revealed that HAZOP's structured guideword protocol was more effective in uncovering procedural and interaction-based hazards.", "conclusion": "The quasi-experimental evidence demonstrates that a contextually adapted HAZOP methodology outperformed a conventional FMEA approach in this manufacturing setting, providing a robust basis for methodological selection.", "recommendations": "Manufacturing system engineers should prioritise the adaptation and application of structured, guideword-based hazard identification techniques over purely inductive methods for complex operational risks. Further research should investigate the longitudinal sustainability of these risk reductions.", "key words": "quasi-experimental design,