Job Risk Analysis in the Implementation of Industrial Automation in the Electronics Sector

Abstract

The accelerating adoption of industrial automation technologies—including collaborative robots (cobots), automated optical inspection (AOI) systems, and programmable logic controllers (PLCs)—in electronics manufacturing introduces complex and evolving occupational risk profiles that existing safety frameworks are often inadequate to address. Purpose: This research aims to identify and evaluate occupational safety risks arising from the implementation of industrial automation in the electronic manufacturing sector, as well as to assess the effectiveness of Hierarchy of Controls-based interventions in reducing incident rates and strengthening the occupational safety culture. Methods: The research uses a mixed methods approach with a pre-post intervention study design without a control group. Hazard identification was conducted through task-based observations, semi-structured interviews with 186 workers, and analysis of historical incident data. Results: A total reduction in work incidents by 60.5% after the intervention. The highest risk comes from exposure to toxic smoke (RPN = 16). Elimination-based and engineering controls have the highest effectiveness (scores up to 9.4). Near-miss reporting increased by 187.3%, while the safety climate score significantly improved from 3.12 to 4.31 (p < 0.001) with a large effect size (d = 2.43). Implications: These findings indicate that a systematic intervention approach based on HIRA and the Hierarchy of Controls is effective in comprehensively improving safety performance, from both technical and organizational behavior aspects. Conclusion: This study confirms that structured risk analysis-based interventions are capable of significantly reducing work incidents and promoting a transformation of safety culture in the electronic automation industry environment.