EVOPtimizer Evolutionary Operating Method Software
First of all EVOP is much easier to apply than traditional experimental techniques such as response surfaces, factorial designs and even Taguchi methods. It is also more accurate. A second order polynomial is the best approximation to the response surface other methods can make. This assumption limits the accuracy of the final answer. Another problem with conventional methods is the complexity with the number of factors. The table below shows the minimum number of trials required for a response surface design as a function of the number of factors.
In addition, it usually takes several response surface designs (each modeling a smaller portion of the region) to obtain a satisfactory solution.
With sequential simplex optimization the number of trials in the initial simplex is k+1 where k is the number of experimental factors. Optimization is achieved by evaluating the slope of the immediate area and moving in the best direction.
Another advantage of EVOP is the effect on current production. The factor settings for the initial simplex can be set very close to current production settings. This allows the initial experimental trials to be run with either no impact or a limited impact on either scrap or downtime. Additional experimental trials improve existing production output over time. EVOP is a great way to pursue continuous improvement!
Traditional experimental techniques are difficult to use when yield is the response variable. How can conduct an experiment to reduce scrap for 1000 parts per million? At least 1000 trials are required to expect to find one defect. EVOP is perfect in this situation because the initial trials are conducted with factors setting very close to current production levels. This allows an experimental setting to be replicated for weeks if necessary because there is either an improvement in scrap or a slight degradation.
Required Operating System: Windows XP or later
EVOP 的另一個優點是對當前生產的影響。初始單純形的因子設置可以設置得非常接近當前生產設置。這允許在對廢料或停機時間沒有影響或影響有限的情況下運行初始實驗試驗。隨著時間的推移，額外的實驗性試驗提高了現有的產量。EVOP 是追求持續改進的好方法！
當產量是響應變量時，傳統的實驗技術很難使用。如何進行實驗以減少 1000 ppm 的廢料？至少需要 1000 次試驗才能找到一個缺陷。EVOP 在這種情況下是完美的，因為初始試驗是在非常接近當前生產水平的因素下進行的。這允許在必要時重複實驗設置數週，因為廢品率有所改善或略有下降。
Aabel being dynamic, interactive visualization of the data, integrated (inference and multivariate) is statistics, data investigation, the scientific graph and the up-to-date powerful application which integrates drawing in the subject figure to one package.
QI Macros 是一款經濟實惠、直觀、省時的 Excel 插件,可以繪製帕累托圖、帶有穩定性分析的控製圖（C、NP、P、U、XmR、XbarR、XbarS）、帶有Cp Cpk的柱狀圖、散點圖、盒狀圖和晶須圖等等。