Development of Mathematical Model for Reduction of Process Time for Peddle-Driven Sewing Machine

By using response surface curve (RSM) method of regression, a model is developed. In the present investigation, a fairly large data of workstations is collected. Based on collected data in terms of independent parameters and dependant parameters, the mathematical co-relationships of effects as function of causes are established. Since the data based on which these relationships are established is a field data, the deduced models are conceptualized as field data-based models. Pedal sewing operation is a man–machine system, comprising of (1) an operator, (2) pedal sewing machine, (3) workstation, and (4) environmental conditions. This operation takes place at a workstation usually known as single person owned premises meant for stitching clothes of the clients of the shop owner. The field study indicated that there is a considerable musculo-skeletal disorder on the part of the operator. Hence, it was decided to execute an assignment in which substantially large field data of this operation is collected. Based on this data, mathematical co-relationships are established between various causes and effects of this activity. The paper reports on: (1) Planning of collection of data. (2) Execution toward collection of data. (3) Presentation of collected data. (4) Processing of the data for formulation of cause–effect relationships. Upon formulation of model, the reliability of model and its optimization is executed. The data collected comprises of 30 sewing machine operators working on stand-alone pedal-driven sewing machines. The collection of data was done on 36 causes/input parameters/independent variables and 1 effects/output parameters/dependant variables. The causes are clubbed and converted into 5 independent dimensionless terms known as Pi terms such as Π1, Π2, Π3, Π4, and Π5. The effects/output/dependant parameter is nomenclated as Z1.