这是黑带如何完成一个项目的实例教程(doc74)-管理培训(编辑修改稿)

这是黑带如何完成一个项目的实例教程(doc74)-管理培训(编辑修改稿)内容摘要：

tion 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 Cyclical 2 2 2 2 Temporal Cyclical Positional Noise σ σ σ ++= Graphical Analysis – Example Injection molding is used to make a type of socket, four pieces at a time, one piece per slot. Measurements of the sockets consist of thickness values in excess of millimeters. The gauges measure in hundredths of a millimeter. The specification is 11 177。 6. Four times a day the supervisor would go to the press and gather up the parts produced by five consecutive cycles of the press. Since each cycle produced four parts, he would have 20 parts to measure every two hours. The supervisor kept track of the cycle and the cavity from which each part came and wrote his twenty measurements in an array like this: The supervisor collected samples four times a day for five days (20 samples total, 20 parts per sample). Calculate the process capability and use a MultiVari chart to help determine sources of variation. A BCDE S1 18 19 20 19 21 S2 13 16 14 13 13 S3 10 11 13 10 13 S4 11 12 13 13 13 Exercise: Determine Capability Using Minitab, analyze the Thick data in for process capability  Remember, the specifications are: 11 177。 6 What is the shortterm process capability? What is the longterm process capability? Are these good or bad values? Remember, one goal of Six Sigma is to reduce variation, which will increase capability. It is always important to understand the process capability. Preparing Data for Marginal Plot by “ Slot” Marginal plots require both variables to be defined numerically  We need to convert “ Slot” to a numeric column first  Step 1: Convert “ Slot” ManipCodeText to Numeric Manip Code Text to Numeric MultiVari Analysis – Defined A graphical analysis tool Uses logical subgrouping Analyzes the effects of discrete X’ s on continuous Y’ s A capability and process analysis tool Data collected for a relatively short time  Data can estimate capability, stability, and y = f(x)’ s Major focus: study uncontrolled noise variation first Variation in noise variables produces chronic and acute mean shifts, changes in variability, and instability Noise variation must be reduced or eliminated in order to leverage the important controllable variables systematically Multivari analysis is a very useful tool for graphically identifying sources of variation, especially noise variation. Later this week, we will be studying correlation amp。 regression (an analysis of the effect of continuous X’ s on continuous Y’ s), analysis of variance (ANOVA) and the General Linear Model (GLM), both numerical analyses of variance data. Multivari analyses will help identify the variation sources with the purpose of reducing or eliminating them. A MultiVari Plan 1. Clearly state the objective 2. List the X’ s and Y’ s to be studied 3. Ensure measurement system capability 4. Describe the sampling plan 5. Describe the data collection amp。 storage plan (who, what, when, etc.) 6. Describe the procedure and settings used to run the process 7. Assemble and train the team. Define responsibilities 8. Collect the data 9. Analyze the data 10. Verify the results 11. Draw conclusions. Report results. Make remendations Injection Molding Example 1. Clearly state the objective Determine the process capability of the injection molding process Determine the major sources of noise variation 2. List the X’ s and Y’ s to be studied Output: Thickness Inputs: Cavity (slot), cycle, sample 3. Ensure measurement system capability An MSA was conducted and the system was found capable 4. Describe the sampling plan One sample from each slot, five consecutive runs, four times a day for five days. 5. Describe the data collection amp。 storage plan (who, what, when, where, etc.) The supervisor collected the data and entered it in a worksheet 6. Describe the procedure and settings used to run the process Standard, constant process settings. 7. Assemble and train the team. Define responsibilities. For a small project, the supervisor did all the work 8. Collect the data. The data are in Minitab worksheet 9. Analyze the data Analysis is on the following slides 中心限理论 : Central Limit Theorem Q: Why Are So Many Distributions Normal? Why is something this plicated so mon? Science has shown us that variables that vary randomly are distributed normally. So a normal distribution is actually a random distribution. Another reason why some distributions are normally distributed is because measurements are actually averages over time of many submeasurements. The single measurement that we think we are making is actually the average (or sum) of many measurements. The Central Limit Theorem, discussed in the following slides, provides an explanation of why averages of nonnormal data appear normal. Dice Demonstration (Integer Distribution) What does a probability distribution from a single die look like? What is the mean? What is the standard deviation? Construct a dataset in Minitab  Select Calc Random Data Integer… from the main menu Generate 1,000 rows of data in C1: Min = 1, Max = 6  Use Minitab’ s Graphical Summary routine for analysis Stat Basic Statistics Display Descriptive Statistics… Minitab Output (Typical) The probability distribution of the possible outes of the roll of a si。