doeintroduction(ppt39)(英文)-質(zhì)量工具(文件)
【正文】 xplain how experimentation is similar to and different from hypothesis testing ? Design of Experiment 187。 Conclusions ? Appendices 187。 Input Variables 187。 Executive Summary or Abstract 187。R) ? Noise factors in the experimental setting inflates variability of measurement Randomization and sample size minimize threats 30 Further Planning Questions ? How will we determine sample sizes? ? What is our plan for randomization? ? What will it cost? ? Have we talked to internal customers about this? ? How long will it take? ? How are we going to analyze the data? ? Have we planned a pilot run? ? Where’s the proposal? 31 Performing the Experiment ? Document initial information ? Verify measurement systems ? Ensure baseline conditions are included in the experiment ? Make sure clear responsibilities are assigned for proper data collection ? Perform a pilot run to verify and improve data collection procedures ? Watch for and record any extraneous sources of variation ? Analyze data promptly and thoroughly 187。 Generally, more data must be taken over a longer period of time 187。 Experiment focused on specific subset of overall operation 187。 F. Callaway Clubs Dunlop Balls High Wind 187。 B. Callaway Clubs Dunlop Balls No Wind 187。 Grass Height 187。 Golf Balls 187。 Length of drive is not long enough. ? Establish the Objective: 187。 2) Two Types of Golf Balls: Dunlop amp。 Sequential experimentation is also used 19 The Higher You Get, The More You Will Learn ! Step 4 Selecting the Type of Experiment Design ? Response Surface Methods ? Full Factorials with Replication ? Full Factorials with Repetition ? Full Factorials without Replication or Repetition ? Screening or Fractional Designs ? OFAT (One Factor At a Time) 20 Quantitative Output Example ? Suppose you have been watching Golf on TV and are very interested in all of the advertised items which claim to help generate improved scores by increasing the distance you drive the golf ball. You are not sure why these clubs amp。 Will exaggerate variation ? Objective: To better understand factor interactions (Mathematical Relationship) 187。 For a quantitative (variables data) factor, . temperature: ? If an experiment is to be conducted at two different temperatures, then the factor temperature has two levels. 187。 Engineering Knowledge 187。 Hypothesis Testing 187。 A factor may be quantitative (variables data), ., temperature in degrees, time in seconds. 187。 What is the Baseline (Mean and Sigma)? ? Is Output under statistical control? 187。 Are you trying to establish the relationship between the input factors (X’s) and the output (responseY)? 187。 Performance: Execution relative to CTQ 187。 Definition of the measurement source to be used 187。 The focused statement relates to the problem and contains no solutions or conclusions 187。 Analyze the Data 187。 Choose the Factor Levels ? Step (4) 187。 Define the Problem 187。 Response Selection 187。DOE Introduction The purpose of an experiment is to better understand the real world, not to understand the experimental data William Diamond IBM Retired Statistician 2 At the end of this module, you will be able to ? Explain how
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