dmaic and tools

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Presentation Transcript

Six Sigma Yellow Belt Training : 

1 Six Sigma Yellow Belt Training Introduction to Statistical tools and DMAIC To Understand the need for improvement and how to do it

Why Yellow Belt : 

2 Why Yellow Belt Six Sigma Yellow Belt certification provides an overall insight to the techniques of Six Sigma, its metrics, and basic improvement methodologies

Why Yellow Belt : 

3 Six Sigma Yellow Belt certification improves: The effectiveness of employees in their support role of Six Sigma Personnel buy-in of Six Sigma Day-to-day workplace activities(resulting in a reduction of cycle times, improved quality, and less waste) Why Yellow Belt

Course structure : 

4 Course structure An introduction to Six Sigma Problem Solving using basic tools The DMAIC Understanding Data Using Basic Statistical Tools Ideas Generation & Selection Control Plans

What is Six Sigma? : 

5 It is a methodology for continuous improvement It is a set of statistical and other quality tools arranged in unique way It is a Quality Philosophy and a management technique What is Six Sigma?

History of Six Sigma : 

6 History of Six Sigma The roots of Six Sigma can be traced back to the early industrial era, during the eighteenth century in Europe Walter Shewhart showed how sigma deviations from the mean required a process correction In 1980, the term Six Sigma was used for this quality management process

The Japanese connection : 

7 The Japanese connection It all began when they took over a television-manufacturing unit of Motorola in 1970 Japanese management made sure that they placed a high emphasis on all the activities leading to production Bringing down the defect margin to only 5% defects

Core Concept of Six Sigma : 

8 Core Concept of Six Sigma Core concepts concentrate around defects and process variations Process Variability is the second Six Sigma core concept. Defects are measured by metrics known as Defects Per Million Opportunities (DPMO)

Path to Six Sigma : 

9 Sigma levels and Defects per million opportunities (DPMO) Path to Six Sigma

The Growth of Six Sigma : 

10 The Growth of Six Sigma

Problem Solving using basic tools : 

11 This is achieved through a methodology known as DMAIC, which is an acronym for Define opportunities Measure performance Analyze opportunity Improve performance Control performance Problem Solving using basic tools

Approach to DMAIC : 

12 Approach to DMAIC Practical Problem Statistical Problem Statistical Solution Practical Solution

Methodology : 

13 D Define M Measure A Analyze I Improve C Control Identify and state the practical problem Validate the practical problem by collecting data Convert the practical problem to a statistical one, define statistical goal and identify potential statistical solution Confirm and test the statistical solution Convert the statistical solution to a practical solution Methodology

Define : 

14 VoC - Who wants the project and why ? The scope of project / improvement Key team members / resources for the project Critical milestones and stakeholder review Budget allocation D Define M Measure A Analyze I Improve C Control Define

Measure : 

15 Ensure measurement system reliability Prepare data collection plan Collect data - Is tool used to measure the output variable flawed ? - Do all operators interpret the tool reading in the same way ? - How many data points do you need to collect ? How many days do you need to collect data for ? What is the sampling strategy ? Who will collect data and how will data get stored ? What could the potential drivers of variation be ? D Define M Measure A Analyze I Improve C Control Measure

Analyze : 

16 Understand statistical problem Baseline current process capability Define statistical improvement goal Identify drivers of variation (significant factors) D Define M Measure A Analyze I Improve C Control Analyze

Improve : 

17 Map improved process Pilot solution Identify operating tolerance on significant factors D Define M Measure A Analyze I Improve C Control Improve

Control : 

18 Ensure measurement system reliability for significant factors Improved process capability Sustenance Plan - Is tool used to measure the input / process variables flawed ? - Do all operators interpret the tool reading in the same way ? - Statistical Process Control - Mistake Proofing - Control Plan D Define M Measure A Analyze I Improve C Control Control

Tools : 

19 Tools Project Charter Process Map Pareto Chart Error Proofing Histogram Fishbone Diagram 5-Why Analysis FMEA Brainstorming Corrective Action Matrix Control Plan Control Charts

Problem solving task and tools : 

20 Problem solving task and tools

Problem solving task and tools : 

21 Problem solving task and tools

Project Charter sample : 

22 Project Charter sample

Process Map : 

23 Process Map A process map visually depicts the sequence of events to build a product or produce an outcome It may include additional information such as cycle time, inventory, and equipment information

5-Why Analysis : 

24 5-Why Analysis By repeatedly asking the question "Why" you can peel away the layers of symptoms that can lead to the root cause of a problem Benefits Of The 5 Whys It helps to quickly identify the root cause of a problem. It helps determine the relationship between different root causes of a problem. It can be learned quickly and doesn't require statistical analysis to be used

FMEA : 

25 FMEA Handout of Rate scale of S-O-D

Pareto Chart : 

26 Pareto Chart A Pareto chart is a special type of bar chart where the values being plotted are arranged in descending order (80:20 rule)

Error Proofing : 

27 Error Proofing Error proofing is an activity of awareness, detection and prevention of errors Also known as the Poke-yoke There are five error proofing principles: Elimination: of the possible error Replacement: is a change to a more reliable process Facilitation: occurs when the process is made easier to perform Detection: occurs when the error is found prior to the next operation Mitigation: minimizes the effect of the error

Histogram : 

28 Histogram A histogram is used to graphically summarize and display the distribution of a process data set

Fishbone Diagram : 

29 Fishbone Diagram Fishbone diagrams (also called Ishikawa diagrams or cause-and-effect diagrams) are diagrams that show the causes of a certain event Ishikawa diagrams were proposed by Kaoru Ishikawa The 6 M's Machine Method Materials Measurements Man Mother Nature (Environment)

Fishbone Diagram : 

30 A more modern selection of categories are Equipment Process People Materials Environment Management Causes should be derived from brainstorming sessions Causes should be specific, measurable, and controllable Fishbone Diagram

Brainstorming : 

31 Brainstorming Brainstorming is a group creativity technique designed to generate a large number of ideas for the solution of a problem There are four basic rules in brainstorming Focus on quantity Withhold criticism Welcome unusual ideas Combine and improve ideas

Exercise Brain storming : 

32 Exercise Brain storming

Corrective Action Matrix : 

33 Corrective Action Matrix No action is effective unless it is implemented, and no action gets implemented unless someone is responsible to make it happen The Corrective Action Matrix is used by problem-solving teams to keep track of who is doing what - by when

Control Plan : 

34 Control Plan It is a management tool To identify and monitor the activity required to control the critical inputs It should use a balanced control approach in six sigma, ISO-9000 A Control Plan is usually supported by a Control Chart which captures the specific measurements It is used in the control phase to identify and record controls, targets, and specification limits

Control Charts : 

35 Control Charts A control chart is a line graph that represents measurements of a process performance The chart also contains the Target Value for the attribute being measured the upper control limit (UCL) and the Lower Control Limit (LCL) These lines are determined from historical data Types of Control Chart: Among the most used are X-bar chart R chart P chart

All this sweat is to find out what are the causes of gaps in processes which is ultimately effecting the customer Because : 

36 All this sweat is to find out what are the causes of gaps in processes which is ultimately effecting the customer Because

By and large, customers don’t judge a product by averages like performance but by what they actually get out of each product : 

37 By and large, customers don’t judge a product by averages like performance but by what they actually get out of each product

Thank you : 

38 Thank you Questions