Design of Experiments (DOE)—A Valuable Multi-Purpose Methodology


The DOE methodology is an effective tool for upgrading the level of measurement and assessment. In any design, planning or control problem the designer is faced with many alternatives. He/she is challenged to develop design approaches that can meet both quality and cost criteria. The way experiments are designed greatly affects the effective use of the experimental resources and the easiness with which the measured results can be analyzed. This paper does not present new evidence based on designed experiments. Its objective is solely to show how useful application of multifactor experiments is in a variety of circumstances and decision making scenarios. The paper reviews three published examples where this method was used in different contexts: quality control, flexible manufacturing systems (FMS) and logistics systems. The physical experiment has been carried out to improve the quality of a special type of batteries. The simulation experiment has been carried out to investigate the impact of several flexibility factors in a flexible manufacturing system. The numerical value of a complex analytical expression representing a customer oriented logistics performance measure has been calculated for different values of its parameters, i.e. the given numerical values of the investigated factors. It enabled a methodical examination of all factor effects and especially their interactions, thus shedding light on complex aspects of the logistics decision problem. In these examples, cases from different contexts were presented, enabling to view design of experiments as a powerful ingredient for improving decision making in a variety of circumstances.

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Barad, M. (2014) Design of Experiments (DOE)—A Valuable Multi-Purpose Methodology. Applied Mathematics, 5, 2120-2129. doi: 10.4236/am.2014.514206.

Conflicts of Interest

The authors declare no conflicts of interest.


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