【正文】 如何進(jìn)行問題陳述？分六個方面進(jìn)行問題陳述：5，描述項目的主線。我們簡單介紹以下項目是如何定義的。1確定主要商業(yè)問題：b目的a循環(huán)時間c耗費(fèi)3項目的選擇b項目的標(biāo)準(zhǔn)（評估）b1減少缺陷的70%b2第一年節(jié)省 $175Kb3項目完成周期為4個月b4最少的資金總額b5黑帶的第一個項目必須滿足培訓(xùn)目標(biāo)《6 Sigma項目運(yùn)作實(shí)例》《定義階段》我們在定義階段做什么我們在定義階段需要做什么？1，完成項目陳述。？？？6，完成目標(biāo)陳述?！? Sigma項目運(yùn)作實(shí)例》《測量階段》如何進(jìn)行項目描述如何進(jìn)行項目描述: 1，目標(biāo)陳述2，Metric 圖3，月節(jié)省額如何繪制工藝流程圖:召集小組:流程圖繪制是集體努力的結(jié)果小組包括：流程負(fù)責(zé)人：項目結(jié)果的負(fù)責(zé)人工程部門工藝，產(chǎn)品，設(shè)計及設(shè)備生產(chǎn)部門操作員，各班次主管，培訓(xùn)員，操作班長，維修技師流程圖所需信息腦力風(fēng)暴觀察/經(jīng)歷操作手冊工程標(biāo)準(zhǔn)，工作指示六大方面（人，機(jī)，方法，測量，材料，環(huán)境）文件記錄/確認(rèn):文件記錄的工藝流程首先繪制記錄下來的工藝加入并標(biāo)明隱形工廠步驟當(dāng)所有步驟展示出來后，流程圖就屬于實(shí)際工藝確認(rèn)流程圖的準(zhǔn)確性至關(guān)重要項目組必須花時間觀察工藝秘密進(jìn)行。工藝流程細(xì)圖程序：1，從流程圖中列出工藝步驟2，加入下列內(nèi)容輸出指標(biāo)輸出指標(biāo)標(biāo)準(zhǔn)，若存在輸入指標(biāo)輸入指標(biāo)標(biāo)準(zhǔn)，若存在工藝能力或量具能力指標(biāo)所用設(shè)備3，標(biāo)明隱形工廠步驟4，標(biāo)明各步驟屬于增值性（VA）或非增值性（NVA）5，標(biāo)明各步驟屬于可控性的（C）或噪音性的（N）6，確認(rèn)各設(shè)備的輸入指標(biāo)設(shè)置7，確認(rèn)流程圖準(zhǔn)確性8，必要時更改及更新流程3. 在箭頭上下寫上傳統(tǒng)因素類型名稱*或你懷疑是的類型名稱。*6mman, machine ,method, measurement, mother nature (environment)(6M:人員，機(jī)器，測量方法，原材料，環(huán)境)R檢驗過程中，檢驗員前后一致的比例定性數(shù)據(jù)定性（合格/不合格）數(shù)據(jù)，可用來做記錄和分析定性型測量系統(tǒng)把每個部件與標(biāo)準(zhǔn)進(jìn)行比較，從而決定部件是否符合標(biāo)準(zhǔn)的測量系統(tǒng)。使用定性型量具 Ramp。R試驗，核實(shí)調(diào)整后的有效性標(biāo)準(zhǔn)化分?jǐn)?shù)如果員工時常與標(biāo)準(zhǔn)不一致，則需要改變測量系統(tǒng)（或局部標(biāo)準(zhǔn)）工藝能力分析:為何測量工藝能力?使我們根據(jù)數(shù)據(jù)分配資源！ （這可不常見！）缺陷率得以量化確認(rèn)可以改進(jìn)機(jī)會分析工藝能力可使組織預(yù)測其所有產(chǎn)品和服務(wù)的真實(shí)質(zhì)量水平確認(rèn)工藝發(fā)生問題的本質(zhì)居中程度或分散度設(shè)備室溫度和在最小飽和蒸汽濃度的周期時間決定殺菌程度在整個設(shè)備室維持前后一致的溫度范圍很重要。R 模型測量系統(tǒng) μ總和=μ工藝+Δμ測量系統(tǒng)偏離度： 觀察值=實(shí)際真實(shí)值+測量偏移通過“校準(zhǔn)計劃” Δ 測量偏移來評估 真實(shí)值 測量值（準(zhǔn)確度）測量系統(tǒng) σ2 總合=σ2工藝+σ2測量系統(tǒng)偏離度： 觀察的偏差=工藝的偏差+測量的偏差通過“校準(zhǔn)計劃”來評估 真實(shí)值 測量值（準(zhǔn)確度）R）6 Sigma 首選測量量具與量具研究偏差相比其性能如何最適合進(jìn)行工藝改進(jìn)的評估使用時應(yīng)小心。R 使用方法說明:1，校準(zhǔn)量具或確認(rèn)最近校準(zhǔn)仍然有效2，收集10個代表工藝偏差全部范圍的樣本3，從每日使用這種測量方法的員工中選出檢驗員4，運(yùn)用 ClacMake Patterned Data 準(zhǔn)備量具研究數(shù)據(jù)表5，讓員工測量所有無標(biāo)識，隨機(jī)次序的樣本6，分別讓另外其他員工測量所有無標(biāo)識，隨機(jī)次序的樣本7，重復(fù)第五步及第六步循環(huán)三次。 中。Minitab 默認(rèn)計算P/SV量具Ramp。E matrix team.
May need to add a rep from quality, a supplier, reliability
When should the FMEA be constructed?
After the process map amp。 DetectionFMEA Examples
Plating ExampleAn aerospace plating pany was shipping product to itscustomers with nickel plating that was too thin. Parts were failingcorrosion testing at the customer.
Shipping ExampleThe shipping department of an electronics pany is unable toship an assembly without its clam shell protective packaging. Thiscauses occasional late shipments to the customer.
In the following examples, a single line from the FMEA is used as anillustration for each of the above examples. 圖形技術(shù)分析:Graphical MethodsProcess Variation
Noise variation from discrete inputs
Different operators, machines, setups
Different days, shifts
Different batches, mixtures, raw materials
Noise variation from continuous inputs
Ambient temperature, humidity, pressure
Wear, drift, erosion, chemical depletion) ,..., , ( 2 1 k Process x x x f y =) ,..., , ( 2 1 k Noise n n n f +Intentional Unwanted The equation just means that any output isdetermined by the intentional process settingsand the unwanted noise variation.Common Classification of Noise Variables
Positional (within part variation) Variation within a single production unit
Thickness variation across a plated part Variation across a unit containing many parts
Variation across a semiconductor wafer with many die Variation by position in a batch process
Cavitytocavity variations in an injection molding operation
Cyclical (parttopart variation) Variation between consecutive production units Batchtobatch average differences – consecutive batches
Temporal (timetotime variation) Shifttoshift, DaytoDay, Setuptosetup Variation not accounted for by Positional or Cyclical2 2 2 2Temporal Cyclical Positional Noise σ σ σ ++=Graphical Analysis – Example
Injection molding is used to make a type of socket, four pieces at a time, onepiece per slot. Measurements of the sockets consist of thickness values inexcess of millimeters. The gauges measure in hundredths of amillimeter. The specification is 11 177。 storage plan (who, what, when, etc.)6. Describe the procedure and settings used to run the process7. Assemble and train the team. Define responsibilities8. Collect the data9. Analyze the data10. Verify the results11. Draw conclusions. Report results. Make remendationsInjection Molding Example1. Clearly state the objective Determine the process capability of the injection molding process Determine the major sources of noise variation2. List the X’s and Y’s to be studied Output: Thickness Inputs: Cavity (slot), cycle, sample3. Ensure measurement system capability An MSA was conducted and the system was found capable4. Describe the sampling plan One sample from each slot, five consecutive runs, four times aday for five days.5. Describe the data collection amp。 x) – A Few ThoughtsPg 8 ?March 01, Breakthrough Management Group. Unpublished proprietary work available only under license. All rights reserved. March 16, 2001
Make sure the process settings cover the likely productionrange (but not too far).
Too great a range
points outside the normal range mayhave too great an effect on the model.
Too small a range
Error term may dominate the fit.
Take several replicates at each input setting (x).
Replicate runs help increase the model accuracy.
Randomize runs whenever practical.
Run order is often significant factor.
The output (y) at different inputs (x抯) is not alwaysindependent of previous settings.A good spread in the data is required for agood model. Consider two examples:All of the data is collected at the normalprocess settings. In this case, regression willtry to fit a linear model to a bination ofrandom process variation and randommeasurement variation. The results will be ofno value.The second c