Design of experiments applied to stress testing of pharmaceutical products: a case study of Albendazole

2021 ◽  
pp. 105939
Author(s):  
Jorge Armando Ardila ◽  
Benedito Roberto de Alvarenga Junior ◽  
Luis Cuadrado Durango ◽  
Frederico Luis Felipe Soares ◽  
Bruno Perlatti ◽  
...  
Keyword(s):  
Design Of Experiments ◽  
Stress Testing ◽  
Pharmaceutical Products

scholarly journals Runtime Adaptation of Applications Using Design Of Experiments: A Smartphone-Based Case Study

2014 ◽  
Vol 6 (2) ◽  
pp. 25-28
Author(s):  
Frank Maker ◽  
Rajeevan Amirtharajah ◽  
Venkatesh Akella
Keyword(s):  
Design Of Experiments ◽  
Runtime Adaptation

scholarly journals A Case Study of Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) Methodology in Garment Sector

2017 ◽  
Vol 8 (4) ◽  
pp. 1309 ◽  
Author(s):  
Abdur Rahman ◽  
Salaha Uddin Chowdhury Shaju ◽  
Sharan Kumar Sarkar ◽  
Mohammad Zahed Hashem ◽  
S. M. Kamrul Hasan ◽  
...  
Keyword(s):  
Design Of Experiments ◽  
Analysis Of Variance ◽  
Six Sigma ◽  
Empirical Application ◽  
Sigma Level ◽  
Manufacturing Organization

This paper demonstrates the empirical application of Six Sigma and Define-Measure-Analyze-Improve-Control (DMAIC) methodology to reduce product defects within a garments manufacturing organization in Bangladesh which follows the DMAIC methodology to investigate defects, root causes and provide a solution to eliminate these defects. The analysis from employing Six Sigma and DMAIC indicated that the broken stitch and open seam influenced the number of defective products. Design of experiments (DOE) and the analysis of variance (ANOVA) techniques were combined to statistically determine the correlation of the broken stitch and open seam with defects as well as to define their optimum values needed to eliminate the defects. Thus, a reduction of about 35% in the garments defect was achieved, which helped the organization studied to reduce its defects and thus improve its Sigma level from 1.7 to 3.4.

Design of experiments and response surface methodology to tune machine learning hyperparameters, with a random forest case-study

2018 ◽  
Vol 109 ◽  
pp. 195-205 ◽  
Author(s):  
Gustavo A. Lujan-Moreno ◽  
Phillip R. Howard ◽  
Omar G. Rojas ◽  
Douglas C. Montgomery
Keyword(s):  
Machine Learning ◽  
Response Surface Methodology ◽  
Random Forest ◽  
Design Of Experiments ◽  
Response Surface

scholarly journals Performing price scenario analysis and stress testing using quantile regression: A case study of the Californian electricity market

Energy ◽  
2021 ◽  
Vol 214 ◽  
pp. 118796 ◽  
Author(s):  
Sjur Westgaard ◽  
Stein-Erik Fleten ◽  
Ahlmahz Negash ◽  
Audun Botterud ◽  
Katinka Bogaard ◽  
...  
Keyword(s):  
Quantile Regression ◽  
Scenario Analysis ◽  
Electricity Market ◽  
Stress Testing

Light Consulting after Design of Experiments Training: Lessons from a Case Study

2013 ◽  
Vol 30 (3) ◽  
pp. 437-446 ◽  
Author(s):  
Lluís Marco-Almagro ◽  
Pere Grima ◽  
Xavier Tort-Martorell
Keyword(s):  
Design Of Experiments

scholarly journals Combined Use of Mathematical Optimization and Design of Experiments for the Maximization of Profit in a Four-Echelon Supply Chain

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Daniel Arturo Olivares Vera ◽  
Elias Olivares-Benitez ◽  
Eleazar Puente Rivera ◽  
Mónica López-Campos ◽  
Pablo A. Miranda
Keyword(s):  
Supply Chain ◽  
Design Of Experiments ◽  
Mathematical Optimization ◽  
Fractional Factorial ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Cost Component ◽  
Allocation Model

This paper develops a location-allocation model to optimize a four-echelon supply chain network, addressing manufacturing and distribution centers location, supplier selection and flow allocation for raw materials from suppliers to manufacturers, and finished products for end customers, while searching for system profit maximization. A fractional-factorial design of experiments is performed to analyze the effects of capacity, quality, delivery time, and interest rate on profit and system performance. The model is formulated as a mixed-integer linear programming problem and solved by using well-known commercial software. The usage of factorial experiments combined with mathematical optimization is a novel approach to address supply chain network design problems. The application of the proposed model to a case study shows that this combination of techniques yields satisfying results in terms of both its behavior and the obtained managerial insights. An ANOVA analysis is executed to quantify the effects of each factor and their interactions. In the analyzed case study, the transportation cost is the most relevant cost component, and the most relevant opportunity for profit improvement is found in the factor of quality. The proposed combination of methods can be adapted to different problems and industries.

A Methodology for Quantifying the Perceived Environmental Friendliness of Vehicle Silhouettes in Engineering Design

2009 ◽  
Author(s):  
Tahira Reid ◽  
Richard Gonzalez ◽  
Panos Papalambros
Keyword(s):  
Statistical Analysis ◽  
Design Of Experiments ◽  
Design Optimization ◽  
Engineering Design ◽  
Survey Design ◽  
Modeling Method ◽  
Modeling Framework ◽  
Environmental Friendliness ◽  
Design Attributes

Methods from psychology and engineering are used to quantify subjective, or perceptual, design attributes of artifacts. A modeling framework of perceptual attributes suitable for inclusion in design optimization is presented. The framework includes stimuli development based on design of experiments, survey design, and statistical analysis of data. The proposed modeling method is demonstrated on a subjective attribute we call ‘perceived environmental friendliness’ using vehicle silhouettes as a case study.

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