Formulation of Field Data Based Model for Productivity Improvement of an Enterprise Manufacturing Tractor Axle Assembly: an Ergonomic Approach

摘要

The paper describes an approach for formulation of generalized field data based model for the process of tractor axle assembly of an enterprise. The theory of experimentation as suggested by Hilbert Schenck Jr. is applied. It suggests an approach of representing the response of any phenomenon in terms of proper interaction of various inputs of the phenomenon. The Tractor axle assembly process is considered for study which is a complex phenomenon. The aim of field data based modeling for axle assembly process is to improve the performance of system by correcting or modifying the inputs for improving output. The reduction of human energy expenditure while performing axle assembly is main objective behind study. Reduced human energy consumption will increase overall productivity of assembly process. The work identifies major ergonomics parameters and other workstation related parameters which will affect the productivity of axle assembly process. The identified parameters are raw material dimensions, workstation dimensions, energy expenditure of workers, anthropometric data of the workers and working conditions. Working conditions include humidity of air, atmospheric temperature, noise level, intensity of light etc. at workstation which influence the productivity of assembly operation. Out of all the variables identified, dependant and independent variables of the axle manufacturing system are identified. The no of variables involved were large so they are reduced using dimensional analysis into few dimensionless pi terms. Buckingham pi theorem is used to establish dimensional equations to exhibit relationships between dependent terms and independent terms. A mathematical relationship is established between output parameters and input. The mathematical relationship exhibit that which input variables is to be maximized or minimized to optimize output variables. Once model is formulated it can be optimized using the optimization technique. Sensitivity analysis is a tool which can be used to find out the effect of input variables on output variables. Simultaneously it would be interesting to know influence of one parameter over the other. The model will be useful for an entrepreneur of an industry to select optimized inputs so as to get targeted responses.