Software that is used for designing factorial experiments plays an important role in scientific experiments and represents a route to the implementation of design of experiments procedures that derive from statistical and combinatorial theory. In principle, easy-to-use design of experiments (DOE) software should be available to all experimenters to foster use of DOE.
Factorial experimental design software drastically simplifies previously laborious hand calculations needed before the use of computers.
During World War II, a more sophisticated form of DOE, called factorial design, became a big weapon for speeding up industrial development for the Allied forces. These designs can be quite compact, involving as few as two levels of each factor and only a fraction of all the combinations, and yet they are quite powerful for screening purposes. After the war, a statistician at Imperial Chemical, George Box, described how to generate response surfaces for process optimization.[1] From this point forward, DOE took hold in the chemical process industry, where factors such as time, temperature, pressure, concentration, flow rate and agitation are easily manipulated.
DOE results, when discovered accurately with DOE software, strengthen the capability to discern truths about sample populations being tested: see Sampling (statistics). Statisticians[2][3] describe stronger multifactorial DOE methods as being more “robust”: see Experimental design.
As DOE software advancements gave rise to solving complex factorial statistical equations, statisticians began in earnest to design experiments with more than one factor (multifactor) being tested at a time. Simply stated, computerized multifactor DOE began supplanting one-factor-at-a-time experiments. Computer software designed specifically for designed experiments became available from various leading software companies in the 1980s and included packages such as JMP, Minitab, Cornerstone and Design–Expert.
Notable benefits when using DOE software include avoiding laborious hand calculations when:
Identifying key factors for process or product improvements.
Exploring 2D contours with a computer mouse, setting flags along the way to identify coordinates and predict responses.
Precisely locating where all specified requirements meet using numerical optimization functions within DOE software.
Finding the most desirable factor settings for multiple responses simultaneously.
Today, factorial DOE software is a notable tool that engineers, scientists, geneticists, biologists, and virtually all other experimenters and creators, ranging from agriculturists to zoologists, rely upon. DOE software is most applicable to controlled, multifactor experiments in which the experimenter is interested in the effect of some process or intervention on objects such as crops, jet engines, demographics, marketing techniques, materials, adhesives, and so on. Design of experiments software is therefore a valuable tool with broad applications for all natural, engineering, and social sciences.
^Mark J. Anderson & Patrick J. Whitcomb (2015), DOE Simplified: Practical Tools for Effective Experimentation, 3rd Edition by ISBN1-48221-894-1
^Mark J. Anderson & Patrick J. Whitcomb (2016), RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments, 2nd Edition, Productivity Press, ISBN1-49874-598-9
External linksedit
Response Surface Methodology: Process and Product Optimization Using Designed Experiments, 4th Edition
Design and Analysis of Experiments, 9th Edition
DOE Simplified: Practical Tools for Effective Experimentation, 3rd Edition
RSM Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments, 2nd Edition
Warning Signs in Experimental Design and Interpretation
NIST Eng. Stats Section 5 Process Improvement
January 01, 1970
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This article needs additional citations for verification Please help improve this article by adding citations to reliable sources Unsourced material may be challenged and removed Find sources Multifactor design of experiments software news newspapers books scholar JSTOR July 2016 Learn how and when to remove this message Software that is used for designing factorial experiments plays an important role in scientific experiments and represents a route to the implementation of design of experiments procedures that derive from statistical and combinatorial theory In principle easy to use design of experiments DOE software should be available to all experimenters to foster use of DOE Contents 1 Background 2 Use of software 3 Notes 4 External linksBackground editMain article Design of experimentsUse of software editFactorial experimental design software drastically simplifies previously laborious hand calculations needed before the use of computers During World War II a more sophisticated form of DOE called factorial design became a big weapon for speeding up industrial development for the Allied forces These designs can be quite compact involving as few as two levels of each factor and only a fraction of all the combinations and yet they are quite powerful for screening purposes After the war a statistician at Imperial Chemical George Box described how to generate response surfaces for process optimization 1 From this point forward DOE took hold in the chemical process industry where factors such as time temperature pressure concentration flow rate and agitation are easily manipulated DOE results when discovered accurately with DOE software strengthen the capability to discern truths about sample populations being tested see Sampling statistics Statisticians 2 3 describe stronger multifactorial DOE methods as being more robust see Experimental design As DOE software advancements gave rise to solving complex factorial statistical equations statisticians began in earnest to design experiments with more than one factor multifactor being tested at a time Simply stated computerized multifactor DOE began supplanting one factor at a time experiments Computer software designed specifically for designed experiments became available from various leading software companies in the 1980s and included packages such as JMP Minitab Cornerstone and Design Expert Notable benefits when using DOE software include avoiding laborious hand calculations when Identifying key factors for process or product improvements Setting up and analyzing general factorial two level factorial fractional factorial and Plackett Burman designs Performing numerical optimizations Screening for critical factors and their interactions Analyzing process factors or mixture components Combining mixture and process variables in designs Rotating 3D plots to visualize response surfaces Exploring 2D contours with a computer mouse setting flags along the way to identify coordinates and predict responses Precisely locating where all specified requirements meet using numerical optimization functions within DOE software Finding the most desirable factor settings for multiple responses simultaneously Today factorial DOE software is a notable tool that engineers scientists geneticists biologists and virtually all other experimenters and creators ranging from agriculturists to zoologists rely upon DOE software is most applicable to controlled multifactor experiments in which the experimenter is interested in the effect of some process or intervention on objects such as crops jet engines demographics marketing techniques materials adhesives and so on Design of experiments software is therefore a valuable tool with broad applications for all natural engineering and social sciences Notes edit Box and Wilson 1951 On the Experimental Attainment of Optimum Conditions Journal of the Royal Statistical Society Series B 13 1 Mark J Anderson amp Patrick J Whitcomb 2015 DOE Simplified Practical Tools for Effective Experimentation 3rd Edition by ISBN 1 48221 894 1 Mark J Anderson amp Patrick J Whitcomb 2016 RSM Simplified Optimizing Processes Using Response Surface Methods for Design of Experiments 2nd Edition Productivity Press ISBN 1 49874 598 9External links editResponse Surface Methodology Process and Product Optimization Using Designed Experiments 4th Edition Design and Analysis of Experiments 9th Edition DOE Simplified Practical Tools for Effective Experimentation 3rd Edition RSM Simplified Optimizing Processes Using Response Surface Methods for Design of Experiments 2nd Edition Warning Signs in Experimental Design and Interpretation NIST Eng Stats Section 5 Process Improvement Retrieved from https en wikipedia org w index php title Multifactor design of experiments software amp oldid 1210358633, wikipedia, wiki, book, books, library,
