Paul L. Goethals

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The development of multi‐response experimental designs for process parameter optimization

Paul L. Goethals, Byung Rae Cho, 2011 .

Using higher precision-based response surface designs to determine the optimal process target

Paul L. Goethals, Byung Rae Cho, 2011 .

Investigating estimation error reduction strategies in complex engineering systems

Paul L. Goethals, Byung Rae Cho, B. Cho, 2014, Int. J. Data Anal. Tech. Strateg..

The development of target-based posterior process capability indices and confidence intervals

Paul L. Goethals, Byung Rae Cho, Anintaya Khamkanya, 2017 .

Extending the desirability function to account for variability measures in univariate and multivariate response experiments

Paul L. Goethals, Byung Rae Cho, B. Cho, 2012, Comput. Ind. Eng..

The development of a robust design methodology for time‐oriented dynamic quality characteristics with a target profile

Paul L. Goethals, Byung Rae Cho, B. Cho, 2011, Qual. Reliab. Eng. Int..

A case study: applying Lean Six Sigma concepts to design a more efficient airfoil extrusion shimming process

Paul L. Goethals, Claiborne Hardeman, P. Goethals, 2011 .

The United States Military Academy Reception Day: A Process Improvement Study

Paul L. Goethals, Phoebe White, P. Goethals, 2014 .

The development of a target‐focused process capability index with multiple characteristics

Paul L. Goethals, Byung Rae Cho, B. Cho, 2011, Qual. Reliab. Eng. Int..

A review of scientific research in defensive cyberspace operation tools and technologies

Paul L. Goethals, Meghan E. Hunt, P. Goethals, 2019, Journal of Cyber Security Technology.

Higher-order response surface methods for nanomanufacturing process optimisation

Paul L. Goethals, 2013 .

Analysing the effects of variability measure selection on process and product optimisation

Paul L. Goethals, Gregory L. Boylan, 2011 .

Solving the optimal process target problem using response surface designs in heteroscedastic conditions

Paul L. Goethals, Byung Rae Cho, B. Cho, 2011 .

Reverse programming the optimal process mean problem to identify a factor space profile

Paul L. Goethals, Byung Rae Cho, 2011, Eur. J. Oper. Res..

Achieving cost robustness in processes with mixed multiple quality characteristics and dynamic variability

Paul L. Goethals, Gregory L. Boylan, 2011 .

Robust design modeling and optimization of a multi-response time series for a pharmaceutical process

Paul L. Goethals, Byung Rae Cho, Sangmun Shin, 2014 .

Integrating Customer Perception into Process Capability Measures

Paul L. Goethals, Byung Rae Cho, Anintaya Khamkanya, 2016, Qual. Reliab. Eng. Int..

The optimal process mean problem: Integrating predictability and profitability into an experimental factor space

Paul L. Goethals, Byung Rae Cho, 2012, Comput. Ind. Eng..

Designing the optimal mean for an asymmetrically distributed process

Paul L. Goethals, Byung Rae Cho, 2012 .

Eliminating the Weakest Link Approach to Army Unit Readiness

Paul L. Goethals, Natalie M. Scala, P. Goethals, 2018, Decis. Anal..

Solving multi-response optimisation problems with enhanced precision

Paul L. Goethals, Byung Rae Cho, 2012 .

Solving the optimal process target problem using computer-generated experimental designs

Paul L. Goethals, Byung Rae Cho, 2012 .

Robust parameter design in resource-constrained environments: An investigation of trade-offs between costs and precision within variable processes

Paul L. Goethals, Byung Rae Cho, Gregory L. Boylan, 2013 .

Classifying the Engineering Mathematics Student: An Investigation of Trends in Learning

Paul L. Goethals, Karoline Hood, 2018 .

Designing the optimal process mean vector for mixed multiple quality characteristics

Paul L. Goethals, Byung Rae Cho, 2012 .

A Model for and Inventory of Cybersecurity Values: Metrics and Best Practices

Paul L. Goethals, Natalie M. Scala, 2020 .

Experimental investigations of estimated response surface functions with different variability measures

Paul L. Goethals, Byung Rae Cho, B. Cho, 2009 .