An Ann Approach for Ergonomic Evaluation of Peddle Driven Sewing Machine Operators for Study of Process Time

Abstract

Present study is conducted in Nagpur city where sewing machine work  is one of the busy working operation  in culturally background country like India. The study aims  to execute the analysis of ergonomic tools and ANN approach for process time in connection with  the musculoskeletal disorders (MSD) of  operators. These operators are  using seating stools which are not ergonomically designed. The investigation is led on 30 male sewing machine operators working on peddle  driven sewing machine with experience of  10 to 12 years. This activity is portrayed by a static sitting  stance , with forward angular tendency of head and trunk. The operators are using  stools without back support. Ankle and knee are positioned in awkward angles, the eyes are required to continuously observe the work of sewing , while the hands are constantly coordinating the sewing material with the assimilation of vibrations on working surface of sewing table,to catch up the time constraint given to clients. The legs and feets are continuously working for steady and speedy control of work. The study has demonstrated the application of  ergonomic tools  for analysis of musculoskeletal loads. The operator’s score with the help of RULA and REBA ergonomic tools for elbow to wrist position, neck to shoulder position and lumber region was found above limits of risk  .  The need of immediate change in the working postures and creation of  ergonomic awareness  in standalone sewing machine operators is felt.  Help of Artificial Neural Network approach is taken to reduce the risk of msd on body postures. ANN simulation is established for 1 dependant Pi term  Z1 (process time),  and 5 independent Pi terms . The  final model established with the help of ANN shows the clear nearness with the mathematical model established  by regression analysis method .