<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The research aims to emphasise the relevance of the Design of Experiments (DOE) technique as a reliable method for ensuring efficient use of statistical methods in routine industrial processes. A case study approach with a deductive strategy was used to assess the effectiveness of different DOE methods to achieve the desired objectives. Screening, mid-resolution and high-resolution DOE methods helped identify, characterise, and optimise an experimental variable against the desired output response. A general framework for effective DOE is provided as part of DOE planning, including defining DOE objectives, selection criteria, noise reduction, and application across industries. Overall, various DOE models proved successful in identifying a complicated relationship between experimental variables and output response. However, when ideal DOE models may not be feasible, reducing test run by choosing lower resolution DOE or fewer replicates can still provide important insights into the experimental variables’ impact on output responses.</p>
</abstract>

The research aims to emphasise the relevance of the Design of Experiments (DOE) technique as a reliable method for ensuring efficient use of statistical methods in routine industrial processes. A case study approach with a deductive strategy was used to assess the effectiveness of different DOE methods to achieve the desired objectives. Screening, mid-resolution and high-resolution DOE methods helped identify, characterise, and optimise an experimental variable against the desired output response. A general framework for effective DOE is provided as part of DOE planning, including defining DOE objectives, selection criteria, noise reduction, and application across industries. Overall, various DOE models proved successful in identifying a complicated relationship between experimental variables and output response. However, when ideal DOE models may not be feasible, reducing test run by choosing lower resolution DOE or fewer replicates can still provide important insights into the experimental variables’ impact on output responses.

Critical Evaluation into the practical utility of the Design of Experiments

Engineering Management in Production and Services

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Critical Evaluation into the practical utility of the Design of Experiments"}

The research aims to emphasise the relevance of the Design of Experiments (DOE) technique as a reliable method for ensuring efficient use of statistical...

Critical Evaluation into the practical utility of the Design of Experiments

Online veröffentlicht: 30. Okt. 2021

Seitenbereich: 50 - 65

Eingereicht: 10. Feb. 2021

Akzeptiert: 01. Aug. 2021

DOI: https://doi.org/10.2478/emj-2021-0021

Schlüsselwörter
Six-Sigma, Design of Experiments, screening, Taguchi screening, full factorial

© 2021 Mithun Sharma et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Critical Evaluation into the practical utility of the Design of Experiments

Online veröffentlicht: 30. Okt. 2021

Seitenbereich: 50 - 65

Eingereicht: 10. Feb. 2021

Akzeptiert: 01. Aug. 2021

DOI: https://doi.org/10.2478/emj-2021-0021

SchlüsselwörterSix-Sigma, Design of Experiments, screening, Taguchi screening, full factorial

© 2021 Mithun Sharma et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Six-Sigma, Design of Experiments, screening, Taguchi screening, full factorial