Affiliations: [a] Department of Mechanical Engineering, Dayalbagh Educational Institute, Agra, India | [b] Department of Mathematics, Dayalbagh Educational Institute, Agra, India
Correspondence:
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Corresponding author: Sanjay Srivastava, Department of Mechanical Engineering, Dayalbagh Educational Institute, Agra 282110, India. Tel.: +91 9412509324; Fax: +91 562 2121226; E-mail:ssrivastava@dei.ac.in
Abstract:
BACKGROUND: In labor-intensive manufacturing units, workers in
general subject themselves to extreme work conditions due to economic
reasons and are exposed to high risk of occupational health hazard (RoOHH). OBJECTIVE: We design and implement a methodology for assessment and
minimization of RoOHH while maintaining workers' earnings. METHODS: Proposed method, consisting of two phases, employs a
job-combination strategy (JCS) wherein workers doing a high risk job (HRJ)
also perform a low risk job (LRJ) having undergone sufficient training on it
within their scheduled work day thereby reducing their exposure to HRJ.
Phase 1, called `composite discomfort score with factor rating' (CDSwFR),
assesses RoOHH for different job-combination schedules while phase 2, called
evolutionary multiobjective optimization with JCS (EMOwJCS), finds out
schedules which simultaneously optimizes CDS and earnings of HRJ workers
doing a LRJ as well. Method is demonstrated with a case study in a brick
manufacturing unit. RESULTS: Risk assessment method is verified using real life data.
Results of minimization of RoOHH provide a huge flexibility to supervisors
to choose a suitable schedule considering CDS and earnings of workers, while
meeting production targets. CONCLUSION: A unifying method amalgamating CDSwFR and EMOwJCS in a
unique way turns out to be a powerful scheme without losing its simplicity.
