|
Design-Expert | 实验条件优化设计、分析软件培训 |
|
班级人数--热线:4008699035 手机:15921673576( 微信同号) |
增加互动环节,
保障培训效果,坚持小班授课,每个班级的人数限3到5人,超过限定人数,安排到下一期进行学习。 |
授课地点及时间 |
上课地点:【上海】:同济大学(沪西)/新城金郡商务楼(11号线白银路站) 【深圳分部】:电影大厦(地铁一号线大剧院站)/深圳大学成教院 【北京分部】:北京中山学院/福鑫大楼 【南京分部】:金港大厦(和燕路) 【武汉分部】:佳源大厦(高新二路) 【成都分部】:领馆区1号(中和大道) 【广州分部】:广粮大厦 【西安分部】:协同大厦 【沈阳分部】:沈阳理工大学/六宅臻品 【郑州分部】:郑州大学/锦华大厦 【石家庄分部】:河北科技大学/瑞景大厦
开班时间(连续班/晚班/周末班):即将开课,详情请咨询客服! |
课时 |
◆资深工程师授课
☆注重质量
☆边讲边练
☆若学员成绩达到合格及以上水平,将获得免费推荐工作的机会
★查看实验设备详情,请点击此处★ |
质量以及保障 |
☆
1、如有部分内容理解不透或消化不好,可免费在以后培训班中重听;
☆ 2、在课程结束之后,授课老师会留给学员手机和E-mail,免费提供半年的课程技术支持,以便保证培训后的继续消化;
☆3、合格的学员可享受免费推荐就业机会。
☆4、合格学员免费颁发相关工程师等资格证书,提升您的职业资质。 |
☆课程大纲☆ |
|
- Design Ease是实用的实验设计软件,可帮助您设置与分析常规析因设计、二级析因设计、部分析因设计(多达31个变量)与PlackettBurman设计(多达31个变量)。 您也可以进行数值优化。利用这些设计,您可以快速筛选出关键因素及其相互作用。当前Design Ease的新版本为V 10.
-
- 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.
|
|
|
|
|
|