Download presentation

Published byJulien Garnsey Modified over 3 years ago

1
**Blended Lean Six Sigma Black Belt Training – ABInBev**

Normal class introduction – “Welcome to the 3 Day session of the ASQ Lean Six Sigma Black Belt Blended training. We’re planning to cover several topics and areas during our time today. The scope and intent is to review some of the session materials that you have already completed—or in process of completing, to ensure that you’re comfortable with the pace of learning, the materials, and progress you have made to date on your project. Transition to next Week One Review ©2010 ASQ. All Rights Reserved.

2
Last Time We … Defined our project Leaned our processes Learned statistical techniques Validated our measurement system Created standard work Conducted hypothesis tests Practiced coaching Green Belts Let’s do a quick review before starting the new material.

3
Define Phase Created the project charter – the critical first step in any LSS project Collected Voice of the Customer High-level process map (SIPOC)

4
**A complete lean system should have:**

Lean Defined A philosophy and set of methods where waste is identified continuously and eliminated passionately. A complete lean system should have: Techniques/Tools Management (mindset and accountability) Organizational Environment (skills, culture, and behaviors) Waste is any activity (or inactivity) that consumes resources and do not add value to the customer through the product or service.

5
Key Terms Value-adding activities transform the product in a way the customer would be willing to pay for. Value stream is a series of activities, both those that create value and those that do not, required to deliver a product or service. Value stream mapping is a tool used to document (map) all activities of a value stream to clearly see waste and variations.

6
**8 Wastes The Eight Wastes EXCESS INVENTORY EXTRA PROCESSING DEFECTS**

EXCESS TRANSPORTATION WAITING EXCESS MOTION OVERPRODUCTION UNUSED CREATIVITY

7
5 S SORT involves sorting through the contents of the workplace and removing unnecessary items. STRAIGHTEN involves putting the necessary items in their place and providing easy access. SHINE involves cleaning everything, keeping it clean daily, and using cleaning to inspect the workplace and equipment for defects. STANDARDIZE involves creating visual controls and guidelines for keeping the workplace organized, orderly, and clean. SUSTAIN involves training and discipline to ensure that everyone follows the 5S standards.

8
**Seven basic probability rules**

Basic Statistics Seven basic probability rules All events have a probability between 0 and 1. The sum of all possible probabilities of defined events is equal to 1.00. The probability of an event not occurring is equal to the probability of the event occurring subtracted from 1.0. If events are mutually exclusive, the sum of the probability of occurrence of these events is equal to 1. The probability of the joint occurrence of independent events is the product of the probability of each event. The probability of occurrence of either or both non-independent events is the sum of the probability of each independent events minus the probability of joint events. The probability of observing two dependent events is the product of the probability of the first event and the conditional probability of the second event, given that the first has occurred.

9
Your Turn 1 Assume a sample is selected from a normally distributed population with a mean of 12 oz and a standard deviation of .01 oz. What percent of the sample would be expected to have a value greater than 12.02? What percent of the sample would be expected to have a value less than 11.99? Ten percent of the sample would be expected to have X or less. What is X? Find the answers and draw graphs of the results using Minitab.

10
Your Turn 2 Assume a fair coin is flipped 100 times. What is the probability of exactly 50 heads? What is the probability of greater than 60 heads? Assume a process creates .01 defects per unit. One hundred units were sampled. What is the probability there will be: Zero defects? Two defects? Find the answers with Minitab.

11
**Measurement Systems Analysis (Gage R&R)**

Observed Variation Actual Process Variation Measured Variation Long-Term Process Variation Short-Term Process Variation Variance Due to Instrument Variance Due to Operators Repeatability Calibration Stability Linearity Reproducibility Repeatability and reproducibility are typically the primary contributors to measurement error

12
Your Turn 3 A Green Belt conducted a gage R&R on a bottling line. He had three operators measure the temperature of the product at 20 locations in the line three times each. He sent the data in Temperature Measurement.mtw. What would you recommend?

13
Error Proofing Error proofing is a systematic approach for anticipating and detecting potential defects and preventing them from reaching the customer (internal or external) Proactive identification and prevention Prevent first Do not allow defects from going further Intentionally designed, not by chance At the source—close to the origination Inexpensive first Transparent to the operator Absolutely reliable

14
**Defining Process Capability**

Principle: process capability is a ratio of process variability to design tolerance. Process width Design width It is measured in several ways.

15
**Process Capability Terms**

Cp – Short-term process capability For a limited period of time (not including shifts and drifts) Does not consider process centering Also known as process entitlement Cpk – Short-term process capability index Does consider process centering Pp – Long-term process capability For an extended period of time (including shifts and drifts) Ppk – Long-term process capability index Here are some basic definitions for capability indices. Note the difference between the short and long term indices. [Briefly review.] See formulae on next page.

16
**Cp = Capability Formulae Specification Width(s)**

Short-Term Process Width Cp = Pp = Cpk= Ppk= = Specification Width(s) Long-Term Process Width = Lesser of: or Lesser of: or

17
Your Turn 4 A Green Belt collected data on the fill volumes in cans. The specification limits are to with a target of 12. The data is in six pack spc. What is the capability of this process?

18
**Documents layout and flow process sequence Also documents:**

Standard Work Documents layout and flow process sequence Also documents: • Standard W.I.P. • Quality checks • Safety precautions Posted in cell Includes visual work instructions for each operation

19
Hypothesis Testing Enables us to determine if there is a statistically significant difference between the characteristics of interest of samples of data.

20
**Testing Method Selection Matrix**

There are many types of hypothesis tests we will learn to use depending on the type of data available for the inputs (Xs) and outputs (Ys). Variable Type Attribute Y Count Y Continuous Y Discrete X 1 or 2 Treatments Proportions 3 +Treatments Chi Square 1 or 2 Treatments Poisson 3 + Treatments Chi Square 1 or 2 Treatments T tests 3 +Treatments ANOVA Continuous X Logistic Regression Least Squares Regression

21
Your Turn 5 A Green Belt collected data on Gross Line Yield before and after a process change. Did the change make a statistically significant improvement (more is better) on Gross Line Yield? The data is in Gross Line Yield.mtw.

22
**Let’s get started! What’s Next?**

Completing our set of hypothesis testing tools More lean tools Designed experiments Control plans Design for Six Sigma Let’s get started!

23
**Blended Lean Six Sigma Black Belt Training – ABInBev**

Normal class introduction – “Welcome to the 3 Day session of the ASQ Lean Six Sigma Black Belt Blended training. We’re planning to cover several topics and areas during our time today. The scope and intent is to review some of the session materials that you have already completed—or in process of completing, to ensure that you’re comfortable with the pace of learning, the materials, and progress you have made to date on your project. Transition to next Answers to Week One Review Your Turn ©2010 ASQ. All Rights Reserved.

24
**Your Turn 1 Solution 1 Calc>Probability Distributions>Normal**

This will give the probability of less than 12.02, which we will subtract from 1 to get the answer. Minitab returns Normal with mean = 12 and standard deviation = 0.01 x P( X <= x ) So would be greater than oz.

25
Your Turn 1 Assume a sample is selected from normally distributed population with a mean of 12 oz and a standard deviation of .01 oz. What percent of the sample would be expected to have a value greater than 12.02? What percent of the sample would be expected to have a value less than 11.99? Ten percent of the sample would be expected to have X or less. What is X? Find the answers and draw graphs of the results using Minitab.

26
**Your Turn 1 Solution 1 Graph**

Graph>Probability Distribution Plot

27
**Your Turn 1 Solution 1 Graph**

28
**Your Turn 1 Solution 1 Graph**

29
**Your Turn 1 Solution 2 Graph**

Control+e to return to the last dialog box

30
**Your Turn 1 Solution 2 Graph**

31
**Your Turn 1 Solution 3 Graph**

Control+e to return to the last dialog box

32
**Your Turn 1 Solution 3 Graph**

33
Your Turn 2 Assume a fair coin is flipped 100 times. What is the probability of exactly 50 heads? What is the probability of greater than 60 heads? Assume a process creates .01 defects per unit. One hundred units were sampled. What is the probability there will be: Zero defects Two defects Find the answers with Minitab

34
Your Turn 2 Solution 1 Calc>Probability Distributions>Binomial Binomial with n = 100 and p = 0.5 x P( X = x )

35
**Control+e to return to the last dialog box**

Your Turn 2 Solution 2 Control+e to return to the last dialog box This will return the probability of 60 or less. Subtract from 1 to get the probability of greater than 60. Binomial with n = 100 and p = 0.5 x P( X <= x ) The probability of greater than 60 heads is

36
**Calc>Probability Distributions>Poisson**

Your Turn 2 Solution 3 Calc>Probability Distributions>Poisson .01 * 100 = 1 Poisson with mean = 1 x P( X = x )

37
**Control+e to return to the last dialog box**

Your Turn 2 Solution 3 Control+e to return to the last dialog box Poisson with mean = 1 x P( X = x )

38
Your Turn 3 A Green Belt conducted a gage R&R on a bottling line. He had three operators measure the temperature of the product at 20 locations in the line three times each. He sent the data in Temperature Measurement.mtw. What would you recommend?

39
Your Turn 3 Solution Assistant>Measurement Systems Analysis

40
Your Turn 3 Solution

41
Your Turn 3 Solution This is a good measurement system.

42
Your Turn 4 A Green Belt collected data on the fill volumes in cans. The specification limits are to with a target of 12. The data is in six pack spc. What is the capability of this process?

43
Your Turn 4 Solution Assistant>Capability Analysis

44
Your Turn 4 Solution

45
Your Turn 4 Solution

46
Your Turn 4 Solution Process control in marginal and capability is poor

47
Your Turn 5 A Green Belt collected data on Gross Line Yield before and after a process change. Did the change make a statistically significant improvement (more is better) on Gross Line Yield? The data is in Gross Line Yield.mtw.

48
Your Turn 5 Solution Assistant>Hypothesis Test

49
Your Turn 5 Solution

50
Your Turn 5 Solution He can conclude a statistically significant improvement was made.

Similar presentations

Presentation is loading. Please wait....

OK

Statistical Quality Control/Statistical Process Control

Statistical Quality Control/Statistical Process Control

© 2018 SlidePlayer.com Inc.

All rights reserved.

By using this website, you agree with our use of **cookies** to functioning of the site. More info in our Privacy Policy and Google Privacy & Terms.

Ads by Google

Ppt on corporate etiquettes meaning Ppt on bluetooth hacking device Ppt on intelligent manufacturing services Ppt on grease lubrication system Ppt on global warming download Ppt on life of albert einstein Ppt on cartesian product database Ppt on shell structures pdf Ppt on step down transformer Ppt on great industrialists of india