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Design-Expert | 實驗條件優(yōu)化設(shè)計、分析軟件培訓(xùn) |
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班級人數(shù)--熱線:4008699035 手機:15921673576( 微信同號) |
增加互動環(huán)節(jié),
保障培訓(xùn)效果,堅持小班授課,每個班級的人數(shù)限3到5人,超過限定人數(shù),安排到下一期進行學(xué)習(xí)。 |
授課地點及時間 |
上課地點:【上海】:同濟大學(xué)(滬西)/新城金郡商務(wù)樓(11號線白銀路站) 【深圳分部】:電影大廈(地鐵一號線大劇院站)/深圳大學(xué)成教院 【北京分部】:北京中山學(xué)院/福鑫大樓 【南京分部】:金港大廈(和燕路) 【武漢分部】:佳源大廈(高新二路) 【成都分部】:領(lǐng)館區(qū)1號(中和大道) 【廣州分部】:廣糧大廈 【西安分部】:協(xié)同大廈 【沈陽分部】:沈陽理工大學(xué)/六宅臻品 【鄭州分部】:鄭州大學(xué)/錦華大廈 【石家莊分部】:河北科技大學(xué)/瑞景大廈
開班時間(連續(xù)班/晚班/周末班):2020年3月16日 |
課時 |
◆資深工程師授課
☆注重質(zhì)量
☆邊講邊練
☆若學(xué)員成績達到合格及以上水平,將獲得免費推薦工作的機會
★查看實驗設(shè)備詳情,請點擊此處★ |
質(zhì)量以及保障 |
☆
1、如有部分內(nèi)容理解不透或消化不好,可免費在以后培訓(xùn)班中重聽;
☆ 2、在課程結(jié)束之后,授課老師會留給學(xué)員手機和E-mail,免費提供半年的課程技術(shù)支持,以便保證培訓(xùn)后的繼續(xù)消化;
☆3、合格的學(xué)員可享受免費推薦就業(yè)機會。
☆4、合格學(xué)員免費頒發(fā)相關(guān)工程師等資格證書,提升您的職業(yè)資質(zhì)。 |
☆課程大綱☆ |
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- Design Ease是實用的實驗設(shè)計軟件,可幫助您設(shè)置與分析常規(guī)析因設(shè)計、二級析因設(shè)計、部分析因設(shè)計(多達31個變量)與PlackettBurman設(shè)計(多達31個變量)。 您也可以進行數(shù)值優(yōu)化。利用這些設(shè)計,您可以快速篩選出關(guān)鍵因素及其相互作用。當(dāng)前Design Ease的新版本為V 10.
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- DesignEase is a powerful, yet easytouse program for experimental design.A must for anyone wishing to improve a process or a product, DesignEase allows you to screen for vital factors and make breakthrough process improvements.
- DesignEase is an entrylevel program for design and analysis of factorial screening experiments. It is a 'light' version of the much more comprehensive DesignExpert software from StatEase (which offers response surface methods (RSM) and mixture designs for product formulators). Use DesignEase software to detect main effects and interactions that lead to breakthrough improvements. A few of version 8's many new features include upfront power calculations for factorial designs, the option of displaying grid lines on 3D graph back planes, and MinRun Res V designs up to 50 factors.
- Features
- A Variety of Design Creation Tools to Meet All Your Experimental Needs:
- Upfront power calculation for factorial designs: This mainstreams in the designbuilder a ‘headsup’ on the percent probability of seeing the desired difference in each response—the signal—based on the underlying variability—the noise.
- “MinRun Res V” designs are now available for 6 to 50 factors: Resolve twofactor interactions (2FI's) in the least runs possible while maintaining a balance in low versus high levels.
- “MinRun Res IV” (twolevel factorial) designs for 5 to 50 factors: Screen main effects with maximum efficiency in terms of experimental runs.
- Twolevel full and fractional factorials for up to 512 runs and 21 factors, along with minimumaberration blocking choices: Build large designs.
- New “Color By” option: Colorcode points on graphs according to the level of another factor—a great way to incorporate another piece of information into a graph.
- General (multilevel) factorial designs (up to 32,766 runs) using factors with mixed levels.
- Highresolution irregular fractions, such as 4 factors in 12 runs.
- PlacketBurman designs for 11, 19, 23, 27 or 31 factors in up to 64 runs respectively.
- Taguchi orthogonal arrays.
- Ability to graph any two columns of data on the XY graph (this is a great way to view a blocked effect).
- Easytouse automatic or manual model reduction.
- Ability to easily analyze designs with botched or missing data.
- Designbuilder updates resolution of twolevel fractional factorials when the number of blocks is changed: Immediately see how segmenting a design might reduce its ability to resolve effects.
- Block names are now entered during the design build: Identify how you will break up your experiment, for example by specific shift, material lot or the like.
- “MinRun Res IV plus two” option: Ask for two extra runs to make your experiment more robust to missing data.
- Userdefined base factors for design generators: You have more flexibility to customize fractional factorial designs.
- Expanded Doptimal capabilities—impose balance penalty, force categoric balance: This feature helps users equalize the number of treatments.
- Coordinate Exchange capability for Doptimal designs: Avoid the arbitrary nature of designs constructed from candidate point sets.
- In General or Factorial Doptimal designs, categorical factors can be specified as either nominal or ordinal (orthogonal polynomial contrasts): This affects the layout of analysis of variance (ANOVA).
- Specify the same amount for low and high in a mixture design: This is handy for keeping track of fixed component levels—these do not appear in the model.
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