【正文】 iple Responses The results of this mand are shown below: An overall desirability score less than 1 shows a trade off was necessary between the responses The Cur values are the factor level settings that achieve the optimum desirability. The y values listed give the response at the Cur settings The vertical lines slide. As you move them, you can see the effect on the desirability score 37 Recap of DOE Module A. Awareness B. Full Factorial Designs Topic Purpose Subtopics Get people thinking about what’s involved with running an experiment Demonstrate benefits of structured multifactor experiments Learn ways to reduce the number of trials needed for a designed experiment and still get all the information you need Understand the practical aspects of experimental design How we currently run an experiment ? Change one thing at a time ? Change everything we think matters all at once Do by hand Using Minitab to design and analyze experiments Random ization Replica tion , Residuals Main effects Inter actions Effects amp。 calculate the mean (proportion ) for each subgroup 17 Types of Variation ?Special Cause: something different happening at a certain time or place ?Common Cause: always present to some degree in the process 18 Process Capability Statistics Mean Standard Deviation Specification Cp amp。DMAIC Review Use this entire section to give a good review of week 1. Spend time on each slide and get the class to interact and address what they learned/remember from week 1. Let the class lead discussions. It is Monday morning and you may have to “drag” them into the discussions. The purpose is to stimulate their memories and to reinforce the week 1 concepts. They will need to recall some of this material in order to make the second week more meaningful. KEEP THEM ENGAGED!!!!!!!!! 2 INSTRUCTOR NOTES: Explain that a full size version of the Charter is available in the Worksheets Section of the training material DMAIC Define Measure Analyze Improve Control 3 DEFINE IMPROVE INSTRUCTORS NOTES: Discuss each output. 4 Project Charter G r e e n Be l t Pr o j e c t Ch a r te r Pr o j e c t Na m e Bu s i n e s s / L o c a ti o n G r e e n Be l t T e l e p h o n e Nu m b e r M a s te r Bl a c k Be l t T e l e p h o n e Nu m b e r Ch a m p i o n T e l e p h o n e Nu m b e r Star t Da te : T a r g e t En d Da te : Pr o j e c t De ta i l s Pr o j e c t De s c r i p ti o n Bu s i n e s s Ca s e Pr o b l e m State m e n t Pr o c e s s amp。 Effect Diagram (Fishbone) Affinity Diagram Tree Diagram Prioritization Matrix 12 Displaying Stratified Data When it es to displaying stratified data, the data points will usually be coded to visually separate the groups. Most often, the coding is acplished by using ? Different labels, colors or symbols ? Different plots sidebyside 1 2 3 4 5 6 Count 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Minutes 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Location A Location B Location C Time to Complete Lubes (all locations) In later modules, you’ll learn how to analyze stratified data. Here is one example: 13 Population vs. Process A Population ?Situation: You can operationally define the boundaries of an existing (whole) group so that each unit in the group can be identified and, theoretically, numbered. ?Sampling Purpose: To describe characteristics of that group. ?Example: University alumni (as of Aug 31st) are sampled to determine what percentage will send at least one child to college within the next two years. Use the sample to draw inferences about the whole group: ., Average = X, Proportion = p Sample 14 Representative Samples For conclusions to be valid, samples must be representative. ?Data should fairly represent the population or process ?No systematic differences should exist between the data you collect and the data you don’t collect 15 Sampling Approaches Random Sampling Stratified Random Sampling S a m p leP o p u la t i o nEach unit has the same chance of being selected Randomly sample a proportionate number from each group AABBBBCDDD Population Sample C A B D A A A C D D D D D B B B B B B B 16 Sampling Approaches Sample Population or Process Preserve time order Sample Process 9:00 9:30 10:30 10:00 Preserve time order Systematic Sampling Subgroup Sampling Sample every nth one (., every 3rd) Sample n units every tth time (., 3 units every hour)。 you walk Conclusion or Decision Guilty Innocent amp。 Target None required 47 After the FMEA In production processes, much of the automotive industry requires us to use the FMEA to construct a Control Plan The control plan is designed to answer the question: ?Now that we’ve identified and assessed the risks, what do we do to ensure that we mitigate the risks and protect our customer? ?Where required by our customers: ? The FMEA cannot be modified without examining the control plan for associated changes. ? Under no circumstances can a GB or BB project modify a production process without a reexamination of the FMEA. INSTRUCTOR NOTES: Introduce Control Plan Ask students if any have used in past. 48 Tasks amp