one-factor-at-a-time-ofaat-and-design-of-experiment-doe

• Per the textbook, trying to understand factors that impact the outcomes of business process is an important aspect of improving business operations. Conventional wisdom plans experiment one-factor-at-a-time (OFAAT). Compare and contrast the main advantages and disadvantages of OFAAT and DOE and select the approach (e.g., OFAAT or DOE) that you would use in order to obtain effective business process. Provide a rationale for your response.

Please respond to peer post:

Experimental Design

One-factor-at-a-time (OFAT) an experiment has only one variable at a time with the rest kept constant as compared to the design experimentation (DOE) that has several factors varied when the study involves more than consideration (Miriam et al., 2015). Using OFAT, therefore, implies that fewer assets for data measuring is required. Moreover, the impacts of every composition of the data are accurately achieved with decreased variability in the process of analysis when using DOE. However, both the OFAAT and DOE are data analysis tools, though with varied applications.

The resources required for a designed experiment are less in terms of time, operations, and materials (Treglia, 2015). The benefit of this is the relevance in the industry where trials involved are many, expensive, and require a lot of time to conduct. Notably, when using design experiments, it is possible to estimate the interaction existing between the variables systematically. While using the OFAAT experiment, it is quite hard to determine the communications, and those who do not apply designed experiments use the hit-and-miss shots scattered over a large area. The scattershot cannot estimate the interactions.

Contrarily, the advantage of OFAAT over DOE is that it requires few resources to complete the analysis. In approximation, six runs are necessary for a double scheme design (Miriam et al., 2015). However, the long-run cost of the experimental analysis is expensive in terms of resources such as time as compared to the requirements by DOE for an equal number of experiments. In DOE, the preliminary information in a more significant factor space region can be deduced. The benefit of this is the improvement of the predictability in response since it reduces the variability of the estimates. Therefore, with DOE, the optimization of the process thus becomes efficient.

In my experimental data analysis, I would prefer DOE over OFAAT due to its preciseness. The DOE can handle many variables at a go, thus allowing convenient and dependable business data.

References

Miriam, K. R., Márcia, F. S., Alexandre, J. d., André, L. D., Adrícia, F. M., & Messias, B. S. (2015). The Design of Experiment Application (DOE) in the Beneficiation of Cashew Chestnut in Northeastern Brazi. American Journal of Theoretical and Applied Statistics., 4(1), 6-14. doi:10.11648/j.ajtas.20150401.12

Treglia, M. (2015, March 12). Understanding the Design of Experiments. Retrieved from Quality Digest Website: https://www.qualitydigest.com/inside/quality-insid…