corrugated box production process optimization using dimensional analysis and response surface method

The paper focuses on optimization of the manufacturing process of the corrugated sheet box using Dimensional Analysis (DA) and Response Surface Method (RSM). A mathematical model for five different box sizes in terms of Pi terms using Buckingham’s Pi theorem and polynomial equation between independent and response parameters are obtained. RSM is the statistical method useful in the modeling and analysis of problems in which the response variable receives the influence of several independent variables, in order to determine which are the conditions under which should operate these variables to optimize a corrugated box production process. The objective of this study is to minimize the root mean square error (RMS) between the experimental values and computed values of cycle time obtained from mathematical model using RSM. Studies carried out for corrugated sheet box manufacturing industries having man machine system revealed the contribution of many independent parameters like anthropometric data of workers, personal data, machine specification, workplace parameters, product specification, environmental conditions and mechanical properties of corrugated sheet on cycle time. Their effect on response parameter cycle time is totally unknown. The developed model was simulated and optimized with the aid of MATLAB R2011a data cursor tool. The results obtained showed that the correlation R towards linearity, adjusted R2 upto 95% and RMS error less than 10% were valid

Keywords:

Dimensional Analysis (DA) , ResponseSurfaceMethod(RSM) , Independent Variables , Response Variable , Correlation (R) , Root Mean Square Error (RMS)