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