Design of Experiment (DoE): Implementation in Determining Optimum Design Parameters of Portable Workstation

Abstract

In the modern era of manufacturing, it is important to optimize every design parameter in product development stage to reduce cost, material usage and to achieve the desired efficacy level. There are various models which serve those purposes, for instance, Design of Experiment (DoE) is used to check the parameters after adopting optimization tactics which results in reduced cost or saving operating time. In this regard, this research aims to construct a DoE model on a portable workstation to optimize its design parameters. The methodology of DOE would be a 2 level 3 factors full factorial DOE which is conducted to determine the optimal value for three design parameters (factors) which are material density, the length of the table and the length of the table stand in terms of the response which is the required time of fold ability function of the portable workstation. Based upon the evaluated interactions between the parameters, the optimized parameters are chosen for responses. Here, the resultant design parameters are at their lowest level, so the goal of time efficiency in fold ability function is achieved. This similar sort of DoE can be implemented in the furniture and other manufacturing industries who wish to optimize their material usage as well as increase efficiency and reduce cycle time.

Exploring Bayesian Optimization for Photocatalytic Reduction of CO2

“…However, as a local optimization algorithm, DOE cannot locate the global optimal solution in the dynamic photocatalytic reduction reaction. In the case of a given range of parameters, DOE has design limitations that involve only three levels [14] and three factors [55]. When there are multi-factor variables or even mixed-parameter spaces containing categorical variables, DOE must carry out factor screening [56], thus increasing the experimental budget.…”

“…Lee et al [13] explained the application of the central composite design (CCD) DOE method in environmental chemistry. Anika et al [14] successfully implemented the full factorial design (FFD) DOE method in furniture and other manufacturing industries. DOE seeks key factors and control-related factors through quantitative analysis of process parameters.…”

Design of experiments optimization application in physics: a case study of the damped driven pendulum experiment

“…Grine and Benhamza have modelled nanofluids' effective thermal conductivity using full-factorial design analysis [29]. Anika et al have made an application using DoE to determine the optimum design parameters of the portable workstation [30].…”