Six Sigma Principles for Defect Free Product Development


Published on

This presentation is the Part-I of the Product Development Manager’s Reference Guide: 6-Sigma DFSS Project Life Cycle framework for Defect Free Product Development.

Published in: Technology, Business
1 Comment

  • its a real good presentation n helpful to begin with.
    Are you sure you want to  Yes  No
    Your message goes here
No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Six Sigma Principles for Defect Free Product Development

  1. 1. © Copyright 2009 – Raman. K. 1 Product Development Manager’s Guide 6-Sigma DFSS Project Life Cycle framework for Defect Free Product Development Raman K. April 2009
  2. 2. © Copyright 2009 – Raman. K. 2 Topics  Part-I: Six-Sigma Principles (FREE!!!)  Part-II: Six-Sigma DFSS Methodology  Part-III: Six-Sigma DFSS Project Life Cycle (PLC)  Part-IV: DFSS PLC Framework for product development
  3. 3. © Copyright 2009 – Raman. K. 3 PART-I Six Sigma Principles
  4. 4. © Copyright 2009 – Raman. K. 4 What is Sigma σ?  The history of Six-sigma has its roots back in Gaussian Curve introduced by Gause. He floated the concept that in any process, most of the results are generally clustered around a particular average value. He was of opinion that quality of the process is directly related with the shape of the Gaussian curve.  Standard deviation is called “mean of the mean”. Used as criteria to understand how many items possess a particular characteristics near the mean of all the items.  Example: Marks of students vs number of students. There will be a mean value of marks obtained by total number of students. Mean = Total Marks of all / number of students  Calculate the difference in actual intake from mean. Difference = actual marks of a student- mean marks.  It can be positive or negative value. σ measure of the degree of dispersion of the data from the mean value.
  5. 5. © Copyright 2009 – Raman. K. 5 What is Sigma σ?.....  Plot the number of students possessing that difference value.  A data point is plotted at “0” with students obtaining marks exactly equal to mean value.  Students obtaining marks much less than mean value will be on left end.  So a distribution curve is plotted showing how many students obtain particular difference of actual marks from the mean is plotted.  The shape determines how many students deviates from mean value. Narrow shape means, deviation is less, flat shape means deviation is large.  A mathematical quantity is calculated named Sigma. σ = (Diff1)2 + (diff2)2 +……+ (diffn)2 N-1
  6. 6. © Copyright 2009 – Raman. K. 6 What is Sigma σ?..... • 1-σ: One standard deviation away from the mean in either direction on the horizontal axis (the blue area on the graph) accounts for somewhere around 68 percent of the people in this group. • 2-σ: Two standard deviations away from the mean (the blue and brown areas) account for roughly 95 percent of the people. • 3-σ: Three standard deviations (the blue, brown, green areas) account for about 99 percent of the people. • 6-σ: Six Standard deviation (blue, brown, green, grey areas) account for 99.99% of people.
  7. 7. © Copyright 2009 – Raman. K. 7 Sigma σ as measure of performance? • To measure performance some specified limits of minimum and maximum criteria of acceptable performance is to be defined. • If marks are the output, for passing, Minimum marks required is say 30 which becomes LSL and maximum marks can be 100 which become USL. • According to Gaussian, there will be large number of percentage of students who score marks near mean. There will be only few who are have just passed marginally (Left end of the curve) and very few who have score near to maximum marks (Right end of the curve) • So there are three criteria of measurement of the Performance: • Position of Mean (Toward centre, right or left?) • Shape of the curve (Narrow or broad?) • Expansion of curve (always within LSL & USL or outside?) • If all the students in the class has passed, surely the curve will exactly fit into LSL and USL and performance is called 6-sigma. • If 1 % of the students get failed, performance of the school remains less than 4-sigma. LSL USL
  8. 8. © Copyright 2009 – Raman. K. 8 Sigma σ in terms of customer satisfaction?  In last example if we replace people with number of specifications and variation of specifications of produced product from mean value, we will get a distribution showing how many specifications are outside customer specified limits.  If a product has to fully satisfy all the customer requirements, then there should not be any specifications falling outside 6-sigma dispersion from mean.  In that case product is exactly (almost 100%) as per the desire of the customer. Then we say we have achieved 6-sigma performance and customer satisfaction.  There is a 6-σ deviation means 99.99% of the requirements are met.  Same thing can be applied to manufacturing process or design. If the perfect ness of product produced is to be almost 100% it has to be within 6- sigma curve. Hence indicate no defect. Lesser the sigma level achieved, more will be the defects in the product/service/process
  9. 9. © Copyright 2009 – Raman. K. 9 Relationship between defects and σ-level?  Coined by Bill Smith of Motorola, when they found that traditionally calculating defects per thousands in manufacturing was not the enough. They evolved the concept of DPM and setup a method to measure and produce quality using extensive statistical methods.  Process capability is calculated using extensive statistical tools  Process capability in terms of σ is a symbol of quality for customer.
  10. 10. © Copyright 2009 – Raman. K. 10 Sigma-Level as mark of Quality  A process which can achieve quality of products in such a way that total numbers of defects are not more than 3.4 per million, is termed as Six-Sigma Process.  What is Quality Product from customer point of view?  Defect Free  As per expectations  Reliable  Defects and hence the poor quality has overall effect on the customers as well as business. Higher Costs Reduced Sales Product Variation Poor Quality Unhappy Customers
  11. 11. © Copyright 2009 – Raman. K. 11 6-σ Process Capability/performance LSL USL σ6 LSLUSL Cp − = σ µ 3 LSL− σ µ 3 −USL=pkC Lesser of or
  12. 12. © Copyright 2009 – Raman. K. 12 VOC and VOP Matching  It is not just enough to achieve 6-σ process capability (i.e. just 6-σ dispersion around mean) but also to ensure that overall process is within customer specified tolerance. So VOC must be contained within VOP. Voice of Process Performance Margins that Always Meets Customer Expectations 6 Sigma Process Capability Low Variation in Parts, Materials, & Cycle Time Acceptable LSL USL Voice of Customer 6 Sigma Process •Process operates inside the customer requirements •Defect free and no variation “pass thru” to the customer ~
  13. 13. © Copyright 2009 – Raman. K. 13 Bottom Lines of 6-σ Process  Totally customer oriented disposition which:  Deliver Defect Free product / service or process to customer  Product exactly or better than customer’s needs and expectations  Reduce process cost of achieving this capability repeatedly  6-σ integrate process, tools, methods and team together to achieve the specified performance.
  14. 14. © Copyright 2009 – Raman. K. 14 How to achieve 6-σ capability?  Toolset - Using a set of 6-σ Tool set (mathematical & statistical) to ensure previously mentioned 3 objectives. Usually contains set of software tools.  Methodology - A defined time and action frame to apply these tools. Usually referred by different names such as DMAIC, DFSS etc.  Process - A Organization level integrated framework to implement it, usually called PLC, may have some proprietary names.
  15. 15. © Copyright 2009 – Raman. K. 15 6-σ Toolset  What these tools do? – Perform some actions to reduce defects, detecting errors, matching VOC and VOP, defining proper design and process parameters, mapping customer and design requirements, mistake proofing the designs and calculating process capability, etc. to achieve 6-σ performance.  Types of tools – A range of spread sheets, Calculations, Statistical models and software which operate on underlying statistical theory of 6-σ
  16. 16. © Copyright 2009 – Raman. K. 16 6-σ Methodology  What is methodology? – An approach to apply 6-σ tools at proper time to keep the defects out of tolerance limits and confirming customer requirements match the design requirements or not while a product is being improved upon or being designed altogether new.  Types of methodologies – A wide range of terminologies are used for such methodologies:  DMAIC (Define, Measure, Analyze, Improve, Control)  DMADV (Define, Measure, Analyze, Design, Validate)  DMADOV (Define, Measure, Analyze, Design, Optimize, validate)  DCCDI (Define, Customer, Concept, Design, Implement)  DMEDI (Define, Measure, Explore, Develop, Implement)  IDOV (Identify, Design, Optimize, validate)
  17. 17. © Copyright 2009 – Raman. K. 17 6-σ Process  What is Process? – Process is a structured framework provided by an organization so that it can ensure that SUITABLE 6-Σ TOOLS are being applied TIMELY and the output of these tools is being VERIFIED to make any correction if needed.  This process is propitiatory and specific to the organization itself and is evolved after checking needs of the organization vs needs of its customers.  6-Sigma DFSS PLC - It may be named anything in any organization. For general reference, the process of implementing 6-σ quality in product development is called 6-Sigma DFSS PLC (Project Life Cycle)
  18. 18. © Copyright 2009 – Raman. K. 18 Next parts of this training package Contact the author for next set of parts as a single training package, contact the author or purchase the same from Six Sigma PLC Reference Guide for Managers  Part-II: Six-Sigma DFSS Methodology  Part-III: Six-Sigma DFSS Project Life Cycle (PLC)  Part-IV: DFSS PLC Framework for product development
  19. 19. © Copyright 2009 – Raman. K. 19 Author’s contact For any questions or training queries, contact the author: Raman K. Author has over 15 years of project management, product development and quality management experience in leading MNC product development corporations. He has earned numerous international certification awards - Certified Management Consultant (MSI USA/ MRA USA), Certified Six Sigma Green Belt Professional (Six Sigma India), Certified Quality Director (ACI USA), Certified Engineering Manager (SME USA), Certified Project Director (IAPPM USA), to name a few. His research and training interests are in learning, development, performance management, research management and product development. He holds MBA, Executive MBA, Masters in Technology and Bachelor in Technology. In addition to this, he has 60+ educational qualifications, credentials and certifications in his name. .