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Robustification
Robustification is a form of optimisation whereby a system is made less sensitive to the effects of random variability, or noise, that is present in that system's input variables and parameters. The process is typically associated with engineering systems, but the process can also be applied to a political policy, a business strategy or any other system that is subject to the effects of random variability. Clarification on definition Robustification as it is defined here is sometimes referred to as parameter design or robust parameter design (RPD) and is often associated with Taguchi methods. Within that context, robustification can include the process of finding the inputs that contribute most to the random variability in the output and controlling them, or tolerance design. At times the terms design for quality or Design for Six Sigma (DFFS) might also be used as synonyms Principles Robustification works by taking advantage of two different principles. Non-linearities Consi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Robustification
Robustification is a form of optimisation whereby a system is made less sensitive to the effects of random variability, or noise, that is present in that system's input variables and parameters. The process is typically associated with engineering systems, but the process can also be applied to a political policy, a business strategy or any other system that is subject to the effects of random variability. Clarification on definition Robustification as it is defined here is sometimes referred to as parameter design or robust parameter design (RPD) and is often associated with Taguchi methods. Within that context, robustification can include the process of finding the inputs that contribute most to the random variability in the output and controlling them, or tolerance design. At times the terms design for quality or Design for Six Sigma (DFFS) might also be used as synonyms Principles Robustification works by taking advantage of two different principles. Non-linearities Consi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Robust Parameter Design (RPD)
A robust parameter design, introduced by Genichi Taguchi, is an experimental design used to exploit the interaction between control and uncontrollable noise variables by robustification—finding the settings of the control factors that minimize response variation from uncontrollable factors. Control variables are variables of which the experimenter has full control. Noise variables lie on the other side of the spectrum. While these variables may be easily controlled in an experimental setting, outside of the experimental world they are very hard, if not impossible, to control. Robust parameter designs use a naming convention similar to that of FFDs. A 2''(m1+m2)-(p1-p2)'' is a 2-level design where ''m1'' is the number of control factors, ''m2'' is the number of noise factors, ''p1'' is the level of fractionation for control factors, and ''p2'' is the level of fractionation for noise factors. Consider an RPD cake-baking example from Montgomery (2005), where an experimenter wants ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Taguchi Methods
Taguchi methods ( ja, タグチメソッド) are statistical methods, sometimes called robust design methods, developed by Genichi Taguchi to improve the quality of manufactured goods, and more recently also applied to engineering, biotechnology, marketing and advertising. Professional statisticians have welcomed the goals and improvements brought about by Taguchi methods, particularly by Taguchi's development of designs for studying variation, but have criticized the inefficiency of some of Taguchi's proposals. Taguchi's work includes three principal contributions to statistics: *A specific loss function *The philosophy of ''off-line quality control''; and *Innovations in the design of experiments. Loss functions Loss functions in the statistical theory Traditionally, statistical methods have relied on mean-unbiased estimators of treatment effects: Under the conditions of the Gauss–Markov theorem, least squares estimators have minimum variance among all mean-unbiased li ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Design For Six Sigma
Design for Six Sigma (DFSS) is an Engineering design process, business process management method related to traditional Six Sigma.Chowdhury, Subir (2002) Design for Six Sigma: The revolutionary process for achieving extraordinary profits, Prentice Hall, It is used in many industries, like finance, marketing, basic engineering, process industries, waste management, and electronics. It is based on the use of statistical tools like linear regression and enables empirical research similar to that performed in other fields, such as social science. While the tools and order used in Six Sigma require a process to be in place and functioning, DFSS has the objective of determining the needs of customers and the business, and driving those needs into the product solution so created. It is used for product or process ''design'' in contrast with process ''improvement''. Measurement is the most important part of most Six Sigma or DFSS tools, but whereas in Six Sigma measurements are made fro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Optimisation
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems of sorts arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. More generally, optimization includes finding "best available" values of some objective function given a defi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sensitivity Analysis
Sensitivity analysis is the study of how the uncertainty in the output of a mathematical model or system (numerical or otherwise) can be divided and allocated to different sources of uncertainty in its inputs. A related practice is uncertainty analysis, which has a greater focus on uncertainty quantification and propagation of uncertainty; ideally, uncertainty and sensitivity analysis should be run in tandem. The process of recalculating outcomes under alternative assumptions to determine the impact of a variable under sensitivity analysis can be useful for a range of purposes, including: * Testing the robustness of the results of a model or system in the presence of uncertainty. * Increased understanding of the relationships between input and output variables in a system or model. * Uncertainty reduction, through the identification of model input that cause significant uncertainty in the output and should therefore be the focus of attention in order to increase robustness (perhap ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Monte Carlo Method
Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution. In physics-related problems, Monte Carlo methods are useful for simulating systems with many coupled degrees of freedom, such as fluids, disordered materials, strongly coupled solids, and cellular structures (see cellular Potts model, interacting particle systems, McKean–Vlasov processes, kinetic models of gases). Other examples include modeling phenomena with significant uncertainty in inputs such as the calculation of ris ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Propagation Of Error
In statistics, propagation of uncertainty (or propagation of error) is the effect of variables' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement limitations (e.g., instrument precision) which propagate due to the combination of variables in the function. The uncertainty ''u'' can be expressed in a number of ways. It may be defined by the absolute error . Uncertainties can also be defined by the relative error , which is usually written as a percentage. Most commonly, the uncertainty on a quantity is quantified in terms of the standard deviation, , which is the positive square root of the variance. The value of a quantity and its error are then expressed as an interval . If the statistical probability distribution of the variable is known or can be assumed, it is possible to derive confidence limits to describe t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Western World
The Western world, also known as the West, primarily refers to the various nations and state (polity), states in the regions of Europe, North America, and Oceania.Western Civilization Our Tradition; James Kurth; accessed 30 August 2011 The Western world is also known as the Occident (from the Latin word ''occidēns'' "setting down, sunset, west") in contrast to the Eastern world known as the Orient (from the Latin word ''oriēns'' "origin, sunrise, east"). Following the Discovery of America in 1492, the West came to be known as the "world of business" and trade; and might also mean the Northern half of the North–South divide, the countries of the ''Global North'' (often equated with capitalist Developed country, developed countries). [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Japan
Japan ( ja, 日本, or , and formally , ''Nihonkoku'') is an island country in East Asia. It is situated in the northwest Pacific Ocean, and is bordered on the west by the Sea of Japan, while extending from the Sea of Okhotsk in the north toward the East China Sea, Philippine Sea, and Taiwan in the south. Japan is a part of the Ring of Fire, and spans Japanese archipelago, an archipelago of List of islands of Japan, 6852 islands covering ; the five main islands are Hokkaido, Honshu (the "mainland"), Shikoku, Kyushu, and Okinawa Island, Okinawa. Tokyo is the Capital of Japan, nation's capital and largest city, followed by Yokohama, Osaka, Nagoya, Sapporo, Fukuoka, Kobe, and Kyoto. Japan is the List of countries and dependencies by population, eleventh most populous country in the world, as well as one of the List of countries and dependencies by population density, most densely populated and Urbanization by country, urbanized. About three-fourths of Geography of Japan, the c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
United States
The United States of America (U.S.A. or USA), commonly known as the United States (U.S. or US) or America, is a country primarily located in North America. It consists of 50 states, a federal district, five major unincorporated territories, nine Minor Outlying Islands, and 326 Indian reservations. The United States is also in free association with three Pacific Island sovereign states: the Federated States of Micronesia, the Marshall Islands, and the Republic of Palau. It is the world's third-largest country by both land and total area. It shares land borders with Canada to its north and with Mexico to its south and has maritime borders with the Bahamas, Cuba, Russia, and other nations. With a population of over 333 million, it is the most populous country in the Americas and the third most populous in the world. The national capital of the United States is Washington, D.C. and its most populous city and principal financial center is New York City. Paleo-Americ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Genichi Taguchi
was an engineer and statistician. From the 1950s onwards, Taguchi developed a methodology for applying statistics to improve the quality of manufactured goods. Taguchi methods have been controversial among some conventional Western statisticians, but others have accepted many of the concepts introduced by him as valid extensions to the body of knowledge. Biography Taguchi was born and raised in the textile town of Tokamachi, in Niigata prefecture. He initially studied textile engineering at Kiryu Technical College with the intention of entering the family kimono business. However, with the escalation of World War II in 1942, he was drafted into the Astronomical Department of the Navigation Institute of the Imperial Japanese Navy. After the war, in 1948 he joined the Ministry of Public Health and Welfare, where he came under the influence of eminent statistician Matosaburo Masuyama, who kindled his interest in the design of experiments. He also worked at the Institute of Stati ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
