- published: 30 May 2021
- views: 4111
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.
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 (DFSS) might also be used as synonyms.
Robustification works by taking advantage of two different principles.
Consider the graph below of a relationship between an input variable x and the output Y, for which it is desired that a value of 7 is taken, of a system of interest. It can be seen that there are two possible values that x can take, 5 and 30. If the tolerance for x is independent of the nominal value, then it can also be seen that when x is set equal to 30, the expected variation of Y is less than if x were set equal to 5. The reason is that the gradient at x = 30 is less than at x = 5, and the random variability in x is suppressed as it flows to Y.
Renaud Anjoran, Sofeast's CEO, is joined by Andrew Amirnovin to explore DFQ (Design For Quality). They will explain what this concept is, and why it's important when designing and developing a new product for manufacturing. When designing the product you are keeping in mind quality aspects during the design and development process, including tolerances, inspection criteria, and more. This is often planned at the same time as DFM and DFA (watch this video to learn about these design concepts: https://youtu.be/SIYrRIuhaKA) as simpler and more mature processes oftentimes lead to better quality. Summary: ► Ensuring that the designer hears the voice of the customer and considers how the product will be used in the field. ► Choosing standard parts (which may require less testing validation an...
https://www.surplex.com//en/m/kalmar-dfq-501455-d-sideloaders-566736.html You are looking for a used machine? Then you might be interested in this used machinery offer: KALMAR DFQ 501455 D Sideloaders. Find more machine tools and other used metalworking, woodworking and plastics processing machinery on www.surplex.com. Surplex is your reliable partner for the sale and purchase of used machines in Germany.
A little wisdom from Cadre Dan on how to finish the GORUCK Challenge. Sign up for a real challenge here: http://ruck.ly/1j5BDPM
Look for or Comment your FAVORITE show below and LIKE it to vote! The Show with the MOST LIKES by the end of the week will win! (To make searching easier, press: CTRL + F and type it in there.) HAPPY VOTING!!! Join us on Patreon for FULL LENGTH Reactions, Exclusive Polls and More! www.patreon.com/DFQreacts or Leave a Tip on Venmo! @DustyMacDFQ and Join us in the Discord Server for chats, info and more! https://discord.gg/XEG6V2pk8a Music: stay safe by JP is licensed under a Creative Commons License. https://creativecommons.org/licenses/... / dahjp Support by RFM - NCM: https://bit.ly/2xGHypM **FAIR USE ADVISORY** All the videos, songs, images, and graphics used in the video belong to their respective owners and I or this channel does not claim any right over them. Copyright Dis...
DFQ-A3 High Speed Slitting Rewinder Machine for Paper or Films or Aluminum Foils. It is equiped with protection cover. It is applied for slitting paper rollers, film rolls. The max speed can reach 300m/min. Please contact me for more information. ➡️Wity Machinery 👩💻Doris Lin 📮sales7@witymachine.com 📱 WhatsApp/Mobile/WeChat:+86 15067868992
Each SOT lesson has a DFQ.
GPU: GeForce GTX 1050 CPU: Intel(R) Core(TM) i5-3470 CPU @ 3.20GHz Memory: 8 GB RAM (7.97 GB RAM usable) Current resolution: 1920 x 1080, 60Hz Operating system: Microsoft Windows 7 Ultimate
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.
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 (DFSS) might also be used as synonyms.
Robustification works by taking advantage of two different principles.
Consider the graph below of a relationship between an input variable x and the output Y, for which it is desired that a value of 7 is taken, of a system of interest. It can be seen that there are two possible values that x can take, 5 and 30. If the tolerance for x is independent of the nominal value, then it can also be seen that when x is set equal to 30, the expected variation of Y is less than if x were set equal to 5. The reason is that the gradient at x = 30 is less than at x = 5, and the random variability in x is suppressed as it flows to Y.
Saranghae saranghae sesang nuguboda deo
Neo hanaman isseojumyeon naneun haengbokhae
Sesange sesange gajang bitnaneun saram
Haneuri jun ojik han saram
Bamhaneurui byeori uril bichugo
Jibeuro ganeun gireun cham aswipgimanhae
Jobeun golmokgire neowa naega immatchumhamyeon
Byeoldeuldo utgonhae
Saranghae saranghae sesang nuguboda deo
Neo hanamyeon isseojumyeon naneun haengbokhae
Sesange sesange gajang bitnaneun saram
Haneuri jun ojik han saram
Nae jumeoni soge neol neoheodugo
Bogo sipeul ttaemada kkeonaeeo bogopa
24siganeul saranghandago malhaejullae
Nal kkok anajullae
Oneuldo naeildo uri sarang idaero
Sesang modu byeonhandaedo urin an byeonhae
Neoege neoege naega yaksokhaneun mal
Neomanui banjjogi doejulge
Gaseum apeuge hal il manketjiman
Sangcheo juneun il manketjiman
Bion dwie ttangi gudeoji deut
Uri sarangdo geureol tenikka
Saranghae saranghae sesang nuguboda deo
Neo hanaman isseojumyeon naneun haengbokhae
Sesange sesange gajang bitnaneun saram