Assessing ergonomic risk factors using combined data envelopment analysis and conventional methods for an auto parts manufacturer

Abstract

BACKGROUND: Occupational injuries are currently a major contributor to job loss around the world and are also costly for businesses. The absence of rational analysis is felt in this area, so mathematical analysis is needed to obtain the logical results of these injuries in order to find gaps or loss points of the industry. OBJECTIVE: This paper assesses the effects of five demographic factors on ergonomic risk and occupational injuries using an integrated mathematical programming approach. The obtained results will help managers to carry out any required corrective actions or establish benchmarks. METHODS: Two typical ergonomic risk assessment methods, the Quick Exposure Check (QEC) and Rapid Entire Body Assessment (REBA), are applied to assess musculoskeletal disorders in workers. Then, considering the five demographic factors as input variables and risks computed by the QEC and REBA methods as outputs, final risk rates for each decision-making unit (DMU) are calculated using data envelopment analysis (DEA). The importance and weight of each risk factor is analyzed using statistical techniques and analysis of variance (ANOVA). To demonstrate the applicability of the methodology, it is applied to a large auto parts manufacturer. RESULTS: The results revealed that the information obtained by DEA is consistent with those for REBA and QEC, which shows that education, experience and weight are factors that could help reduce ergonomic risks. CONCLUSION: It is shown that demographic variables such as age, height, weight, education and work experience play an important and effective role in the explanation of ergonomic risk factors.