DFSS DMAIC

8/11/2019 DFSS DMAIC

1/21


2/21

Introduction:Six Sigma is a business management strategy originally developed by Motorola, USA in

1986 As of 2010, it is widely used in many sectors of industry, although its use is not without

controversy.

Six Sigma seeks to improve the quality of process outputs by identifying and removing the

causes of defects (errors) and minimizing variability in manufacturing and business

processes. It uses a set of quality management methods, including statistical methods, and

creates a special infrastructure of people within the organization (Black Belts, Gr een

Belts, etc.) who are experts in these methods. Each Six Sigma project carried out within an

organization follows a defined sequence of steps and has quantified financial targets (cost

reduction and/or profit increase).

Six Sigma:The term Six Sigma originated from terminology associated with manufacturing, specifically

terms associated with statistical modeling of manufacturing processes. The maturity of a

manufacturing process can be described by a sigma rating indicating its yield, or the

percentage of defect-free products it creates. A six sigma process is one in which

99.99966% of the products manufactured are statistically expected to be free of defects (3.4

defects per million). Motorola set a goal of six sigma for all of its manufact uring operations,

and this goal became a byword for the management and engineering practices used toachieve it.

Historical overviewSix Sigma originated as a set of practices designed to improve manufacturing processes

and eliminate defects, but its application was subsequently extended to other types of

business processes as well. In Six Sigma, a defect is defined as any process output that

does not meet customer specifications, or that could lead to creating an output that does not

meet customer specifications.

The core of Six Sigma was born at Motorola in the 1970s out of senior executive Art

Sundrys criticism of Motorolas bad quality. As a result of this criticism, the company

discovered a connection between increases in quality and decreases in costs of production.

At that time, the prevailing view was that quality costs extra money. In fact, it reduced total

costs by driving down the costs for repair or control. Bill Smith subsequently formulated the
http://www.assignmentpoint.com/business/report-on-social-networking-and-accounted-management-system-software.htmlhttp://www.assignmentpoint.com/business/report-on-social-networking-and-accounted-management-system-software.html


3/21

particulars of the methodology at Motorola in 1986. Six Sigma was heavily inspired by the

quality improvement methodologies of the six preceding decades, such as quality control,

TQM, and Zero Defects, based on the work of pioneers such as Shewhart, Deming, Juran,

Ishikawa, Taguchi and others.

Like its predecessors, Six Sigma doctrine asserts that: Continuous efforts to achieve stable and predictable process results (i.e., reduce process

variation) are of vital importance to business success.

Manufacturing and business processes have characteristics that can be measured,

analyzed, improved and controlled.

Achieving sustained quality improvement requires commitment from the entire

organization, particularly from top-level management.

Features that set Six Sigma apart from previous quality improvement initiatives include:

A clear focus on achieving measurable and quantifiable financial returns from any SixSigma project. An increased emphasis on strong and passionate management leadership

and support.

A special infrastructure of Champions, Master Black Belts, Black Belts, Green Belts,

etc. to lead and implement the Six Sigma approach.

A clear commitment to making decisions on the basis of verifiable data, rather than

assumptions and guesswork.

The term Six Sigma comes from a field of statistics k nown as process capability studies.

Originally, it referred to the ability of manufacturing processes to produce a very highproportion of output within specification. Processes that operate with six sigma quality over

the short term are assumed to produce long-term defect levels below defects per million

opportunities (DPMO). Six Sigmas implicit goal is to improve all processes to that level of

quality or better.

Six Sigma is a registered service mark and trademark of Motorola Inc. As of 2006 Motorola

reported over US$17 billion in savings from Six Sigma. Other early adopters of Six Sigma

who achieved well-publicized success include Honeywell (previously known as AlliedSignal)

and General Electric, where Jack Welch introduced the method. By the late 1990s, abouttwo-thirds of the Fortune 500 organizations had begun Six Sigma initiatives with the aim of

reducing costs and improving quality. In recent years, some practitioners have combined Six

Sigma ideas with lean manufacturing to create a methodology named Lean Six Sigma. The

Lean Six Sigma methodology views lean manufacturing, which addresses process flow and

waste issues, and Six Sigma, with its focus on variation and design, as complementary


4/21


5/21

Design details, optimize the design, and plan for design verification. This phase may require

simulations.

Verify the design, set up pilot runs, implement the production process and hand it over to the

process owner(s).

Quality management tools and methods used in Six SigmaWithin the individual phases of a DMAIC or DMADV project, Six Sigma utilizes many

established quality-management tools that are also used outside of Six Sigma. The following

table shows an overview of the main methods used.

5 Whys Accelerated life testing

Analysis of variance

ANOVA Gauge R&R

Axiomatic design

Business Process Mapping

Cause & effects diagram (also known as

fishbone or Ishikawa diagram)

Check sheet

Chi-squared test of independence and fits

Control chart

Correlation

Cost-benefit analysis

CTQ tree

Design of experiments

Failure mode and effects analysis (FMEA)

General linear model

Histograms

Pareto analysis Pareto chart

Pick chart

Process capability

Quality Function Deployment (QFD)

Quantitative marketing research through use

of Enterprise Feedback Management (EFM)

systems

Regression analysis

Root cause analysis

Run charts

Scatter diagram

SIPOC analysis

(Suppliers, Inputs, Process,Outputs, Custom

ers)

Stratification

Taguchi methods

Taguchi Loss Function TRIZ

Implementation rolesOne key innovation of Six Sigma involves the professionalizing of quality management

functions. Prior to Six Sigma, quality management in practice was largely relegated to the


6/21

production floor and to statisticians in a separate quality department. Formal Six Sigma

programs adopt a ranking terminology (similar to some martial arts systems) to define a

hierarchy (and career path) that cuts across all business functions.

Six Sigma identifies several key roles for its successful implementation. Executive

Leadership includes the CEO and other members of top management. They are responsiblefor setting up a vision for Six Sigma implementation. They also empower the other role

holders with the freedom and resources to explore new ideas for breakthrough

improvements.

Champions take responsibility for Six Sigma implementation across the organization in an

integrated manner. The Executive Leadership draws them from upper management.

Champions also act as mentors to Black Belts.

Master Black Belts , identified by champions, act as in-house coaches on Six Sigma. They

devote 100% of their time to Six Sigma. They assist champions and guide Black Belts andGreen Belts. Apart from statistical tasks, they spend their time on ensuring consistent

application of Six Sigma across various functions and departments.

Black Belts operate under Master Black Belts to apply Six Sigma methodology to specific

projects. They devote 100% of their time to Six Sigma. They primarily focus on Six Sigma

project execution, whereas Champions and Master Black Belts focus on identifying

projects/functions for Six Sigma.

Green Belts are the employees who take up Six Sigma implementation along with their

other job responsibilities, operating under the guidance of Black Belts.Some organizations use additional belt colours, such as Yellow Belts , for employees that

have basic training in Six Sigma tools.

CertificationCorporations such as early Six Sigma pioneers General Electric and Motorola developed

certification programs as part of their Six Sigma implementation, verifying individuals

command of the Six Sigma methods at the relevant skill level (Green Belt, Black Belt etc.).

Following this approach, many organizations in the 1990s starting offering Six Sigmacertifications to their employees Criteria for Green Belt and Black Belt certification vary;

some companies simply require participation in a course and a Six Sigma project. There is

no standard certification body, and different certification services are offered by various

quality associations and other providers against a fee. The American Society for Quality for

example requires Black Belt applicants to pass a written exam and to provide a signed
http://www.assignmentpoint.com/business/behavioral-approach-to-leadership.htmlhttp://www.assignmentpoint.com/business/behavioral-approach-to-leadership.html


7/21

affidavit stating that they have completed two projects, or one project combined with three

years practical experience in the body of knowledge. The International Quality Federation

offers an online certification exam that organizations can use for their internal certification

programs; it is statistically more demanding than the ASQ certification. Other providers

offering certification services include the Juran Institute, Six Sigma Qualtec, Air Academy Associates and others.

Origin and meaning of the term six sigma process

Graph of the normal distribution, which underlies the statistical assumptions of the Six Sigma

model. The Greek letter (sigma) marks the distance on the horizontal axis betwe en the

mean, , and the curves inflection point. The greater this distance, the greater is the spread

of values encountered. For the curve shown above, = 0 and = 1. The upper and lower

specification limits (USL, LSL) are at a distance of 6 from the m ean. Because of the

properties of the normal distribution, values lying that far away from the mean are extremely

unlikely. Even if the mean were to move right or left by 1.5 at some point in the future (1.5

sigma shift), there is still a good safety cushion. This is why Six Sigma aims to have

processes where the mean is at least 6 away from the nearest specification limit.

The term six sigma process comes from the notion that if one has six standard deviations

between the process mean and the nearest specification limit, as shown in the graph,

practically no items will fail to meet specifications. This is based on the calculation method

employed in process capability studies.

Capability studies measure the number of standard deviations between the process mean

and the nearest specification limit in sigma units. As process standard deviation goes up, or

the mean of the process moves away from the center of the tolerance, fewer standard
http://www.assignmentpoint.com/business/purpose-of-employee-training-development-process.htmlhttp://www.assignmentpoint.com/business/purpose-of-employee-training-development-process.html


8/21

deviations will fit between the mean and the nearest specification limit, decreasing the sigma

number and increasing the likelihood of items outside specification.

Role of the 1.5 sigma shift

Experience has shown that processes usually do not perform as well in the long term as they

do in the short term. As a result, the number of sigmas that will fit between the process meanand the nearest specification limit may well drop over time, compared to an initial short-term

study. To account for this real-life increase in process variation over time, an empirically-

based 1.5 sigma shift is introduced into the calculation. According to this idea, a process that

fits 6 sigma between the process mean and the nearest specification limit in a short-term

study will in the long term only fit 4.5 sigma either because the process mean will move

over time, or because the long-term standard deviation of the process will be greater than

that observed in the short term, or both.

Hence the widely accepted definition of a six sigma process is a process that produces 3.4defective parts per million opportunities (DPMO). This is based on the fact that a process

that is normally distributed will have 3.4 parts per million beyond a point that is 4.5 standard

deviations above or below the mean (one-sided capability study). So the 3.4 DPMO of a six

sigma process in fact corresponds to 4.5 sigma, namely 6 sigma minus the 1.5-sigma shift

introduced to account for long-term variation. This allows for the fact that special causes may

result in a deterioration in process performance over time, and is designed to prevent

underestimation of the defect levels likely to be encountered in real-life operation.


9/21


10/21

Sigma level DPMO Percent defective Percentage yield Short-term C pk Long-term C pk

1 691,462 69% 31% 0.33 0.17

2 308,538 31% 69% 0.67 0.17

3 66,807 6.7% 93.3% 1.00 0.5

4 6,210 0.62% 99.38% 1.33 0.83

5 233 0.023% 99.977% 1.67 1.17

6 3.4 0.00034% 99.99966% 2.00 1.5

7 0.019 0.0000019% 99.9999981% 2.33 1.83

Software used for Six Sigma

List of Six Sigma software packages

ApplicationSix Sigma mostly finds application in large organizations. An important factor in the spread of

Six Sigma was GEs 1998 announcement of $350 million in savings thanks to Six Sigma, a

figure that later grew to more than $1 billion. According to industry consultants like Thomas

Pyzdek and John Kullmann, companies with fewer than 500 employees are less suited to Six

Sigma implementation, or need to adapt the standard approach to make it work for them.

This is due both to the infrastructure of Black Belts that Six Sigma requires, and to the factthat large organizations present more opportunities for the kinds of improvements Six Sigma

is suited to bringing about.

CriticismLack of originality


11/21

Noted quality expert Joseph M. Juran has described Six Sigma as a basic vers ion of quality

improvement, stating that there is nothing new there. It includes what we used to call

facilitators. Theyve adopted more flamboyant terms, like belts with different colors. I think

that concept has merit to set apart, to create specialists who can be very helpful. Again,

thats not a new idea. The American Society for Quality long ago established certificates,such as for reliability engineers.

Role of consultants

The use of Black Belts as itinerant change agents has (controversially) f ostered an industry

of training and certification. Critics argue there is overselling of Six Sigma by too great a

number of consulting firms, many of which claim expertise in Six Sigma when they only have

a rudimentary understanding of the tools and techniques involved.

Potential negative effects

A Fortune article stated that of 58 large companies that have announced Six Sigmaprograms, 91 percent have trailed the S&P 500 since. The statement was attributed to an

analysis by Charles Holland of consulting firm Qualpro (which espouses a competing quality-

improvement process). The summary of the article is that Six Sigma is effective at what it is

intended to do, but that it is narrowly designed to fix an existing process and does not help

in coming up with new products or disruptive technologies. Advocates of Six Sigma have

argued that many of these claims are in error or ill-informed. A BusinessWeek article says

that James McNerneys introduction of Six Sigma at 3M had the effect of stifling creativity

and reports its removal from the research function. It cites two Wharton School professorswho say that Six Sigma leads to incremental innovation at the expense of blue skies

research. This phenomenon is further explored in the book, Going Lean , which describes a

related approach known as lean dynamics and provides data to show that Fords 6 Sigma

program did little to change its fortunes.

Based on arbitrary standards

While 3.4 defects per million opportunities might work well for certain products/processes, it

might not operate optimally or cost effectively for others. A pacemaker process might need

higher standards, for example, whereas a direct mail advertising campaign might need lowerstandards. The basis and justification for choosing 6 (as opposed to 5 or 7, for example) as

the number of standard deviations is not clearly explained. In addition, the Six Sigma model

assumes that the process data always conform to the normal distribution. The calculation of

defect rates for situations where the normal distribution model does not apply is not properly

addressed in the current Six Sigma literature.


12/21

Criticism of the 1.5 sigma shift

The statistician Donald J. Wheeler has dismissed the 1.5 sigma shift as goofy because of

its arbitrary nature. Its universal applicability is seen as doubtful.The 1.5 sigma shift has also

become contentious because it results in stated sigma levels that reflect short -term rather

than long-term performance: a process that has long-term defect levels corresponding to 4.5sigma performance is, by Six Sigma convention, described as a six sigma process. The

accepted Six Sigma scoring system thus cannot be equated to actual normal distribution

probabilities for the stated number of standard deviations, and this has been a key bone of

contention about how Six Sigma measures are defined. The fact that it is rarely explained

that a 6 sigma process will have long -term defect rates corresponding to 4.5 sigma

performance rather than actual 6 sigma performance has led several commentators to

express the opinion that Six Sigma is a confidence trick.


13/21

DFSS

DFSS stands for Design For Six Sigma - an approach to designing or re-designing a

new product and/or service for a commercial market, with a measurably high process-

sigma for performance from day one. The intension of DFSS is to bring such newproducts and/or services to market with a process performance of around 4.5 sigma or

better, for every customer requirement. This implies an ability to understand the

customer needs and to design and implement the new offering with a reliability of

delivery before launch rather than after!

DFSS a methodology

DFSS is an approach and attitude towards delivering new products and services with ahigh performance as measured by customer critical to quality metrics. Just as the Six

Sigma approach has the DMAIC methodology (Define, Measure, Analyse, Improve,

Control) by which processes can be improved, DFSS also has a methodology by which

new products and services can be designed and implemented.

DMAIC is now an industry standard methodology for Six Sigma, however DFSS does

not yet have such a universal offering. DMADV (Design, Measure, Analyse, Design,

Verify) is one approach, however there are several in use. In many engineering designdepartments, DFSS is regarded as design optimisation , and the IDOV (Identify, Design,

Optimise , Verify) methodology prevails, however this is focused very much on final

stage engineering optimization , and may miss many of the issues involved in actually

selecting good products and features that will meet customer needs!

To deliver a good methodology that is customer focused, encompasses the entire

business-to-market process, and deals effectively with both products and services, Geoff

Tennant uses the DCCDI methodology - Define, Customer, Concept, Design,Implement.


14/21

Differences between Six Sigma and DFSS

Six Sigma is a process improvement philosophy and methodology, whereas DFSS is

centred on designing new products and services. The main differences are that Six

Sigma focuses on one or two CTQ (Critical To Quality) metrics, looks at processes, andaims to improve the CTQ performance by about +1 process-sigma. In contrast, DFSS

focuses on every single CTQ that matters to every customer, looks at products and

services as well as the processes by which they are delivered, and aims to bring forth a

new product/service with a performance of about 4.5 sigma or better.

Other differences are that DFSS projects are often much larger and take longer, and are

often based on a long term business need for new products, rather than a short term

need to fix a customer problem.

In practicality the divide between a formal DFSS project and a 'simple' Six Sigma project

can be indistinct - at times there is a need for a Six Sigma project to radically improve

the capability (rather than, or as well as, performance) of a broken or non-existent

process using design or re-design.

DFSS only for manufacturing design

Certainly not! Design traditionally has been associated with products much more than for

services, however this is changing as companies realise that every product has

associated services, many of which may matter more to the customer than the

product! Engineers may be interested in using some of the 'six sigma' tools such as DOE

(Design Of Experiments) to 'micro-optimise' design parameters. This runs the risk of

turning out a perfect design but failing to deliver to all the customer requirements or a

real commercial and business need. A full approach to DFSS will consider every aspect

from the business NPI (New Product Introduction) strategy right through to ongoingcommercialization. Any good DFSS methodology and approach must work as a

framework for any type of design and for both products and services.


15/21


16/21

The main tools include QFD - Quality Function Deployment, FMEA - Failure Mode Effect

Analysis, DOE - Design Of Experiment, and simulation techniques. However, just as in

Six Sigma, the ability of the approach to be successful in use does not depend entirely

on the tools used. Six Sigma brings a methodology (DMAIC) as well as a wider, deeper

and more integrated use of existing tools. DFSS methodologies are about a wider,deeper and more integrated approach to commercial design, which involves everyone in

the process as well as the customer to deliver a better product/service and final

implementation!

Correct order for using these tools

If DFSS is to work successfully, it is important that it covers the full life-cycle of any newproduct or service. This begins when the organisation formally agrees the requirement

for something new, and ends when the new product/service is in full commercial

delivery.

New Product Introduction

The selection by the business of a concept product/service to fill a new need.

Benchmarking, customer survey, Multi Generation Planning (MGP), R&D and Sales and

Marking input. Business focus and team chartering with risk analysis.

Define

The start of the DFSS project for real. Plenty more benchmarking, customer survey andanalysis, and more work on a team charter to build a solid foundation for the project.


17/21

Customer (Measure)

The stage where the customers are fully identified and their needs collected and

analysed. Mostly work with Quality Function Deployment (QFD) but here the aim is to

identify the most appropriate set of CTQ (Critical To Quality) metrics to use to measure

and evaluate the design by. This comes from a set of customer needs, together with a

list of potential measures, and a lot of work on the first 'house of quality'. Hopefully too

the start of numerical limits and targets for each CTQ!

Concept (Analyse - conceptual design)

The team take the concept provided by the business for the new product/service andbegin to flesh out the concept to a working 'paper design'. This will require 'non-

technical' design and a second round of QFD to identify the best 'features' that have the

potential to deliver to the CTQs. Here we begin to move from CTQ to CTP - Critical To

Process metrics. The idea is that, if the process by which the product/service is

manufactured/delivered is 100%, then the product/service will also deliver to the

customer CTQs and hence deliver to all of the customer needs! The end of this stage is

a set of design concepts together with a set of CTPs that will constrain the formal and

technical design.

Design (technical design)

The team handover the 'design brief' and the designers then complete the work, using all

the CTPs as guides and evaluators to ensure that the design is perfect! Technical design

can be carried out by the project team for simpler and service-type design, or by more

technical and perhaps traditional design methods for more complex situations. Here we

can use DOE and other statistical optimisation techniques, as well as greater creativity

to bring inspired solutions that are proven to deliver. Simulation of both product, service

and process are important tools.


18/21


19/21

DMAIC

DMAIC (an abbreviation for Define, Measure, Analyze, Improve and Control ) refers to a data-

driven improvement cycle used for improving, optimizing and stabilizing business processes and

designs. The DMAIC improvement cycle is the core tool used to drive Six Sigma projects.

However, DMAIC is not exclusive to Six Sigma and can be used as the framework for other

improvement applications.

Steps

DMAIC is an abbreviation of the five improvement steps it comprises: Define, Measure,

Analyze, Improve and Control. All of the DMAIC process steps are required and always proceed

in the given order.

Define

The purpose of this step is to clearly articulate the business problem, goal, potential resources,

project scope and high-level project timeline. This information is typically captured within project

charter document. Write down what you currently know. Seek to clarify facts, set objectives and

form the project team. Define the following:

A problem

The customer(s)

Voice of the customer (VOC) and Critical to Quality (CTQs) what are the critical processoutputs?

The target process subject to DMAIC and other related business processes

Project targets or goal

Project boundaries or scope

A project charter is often created and agreed upon during the Define step.
http://en.wikipedia.org/wiki/Six_Sigmahttp://en.wikipedia.org/wiki/Voice_of_the_customerhttp://en.wikipedia.org/wiki/Critical_to_Qualityhttp://en.wikipedia.org/wiki/Critical_to_Qualityhttp://en.wikipedia.org/wiki/Voice_of_the_customerhttp://en.wikipedia.org/wiki/Six_Sigma


20/21

Measure

The purpose of this step is to objectively establish current baselines as the basis for

improvement. This is a data collection step, the purpose of which is to establish processperformance baselines. The performance metric baseline(s) from the Measure phase will be

compared to the performance metric at the conclusion of the project to determine objectively

whether significant improvement has been made. The team decides on what should be

measured and how to measure it. It is usual for teams to invest a lot of effort into assessing the

suitability of the proposed measurement systems. Good data is at the heart of the DMAIC

process:

Identify the gap between current and required performance.

Collect data to create a process performance capability baseline for the project metric, that

is, the process Y(s) (there may be more than one output).

Assess the measurement system (for example, a gauge study) for adequate accuracy and

precision.

Establish a high level process flow baseline. Additional detail can be filled in later.

Analyze

The purpose of this step is to identify, validate and select root cause for elimination. A large

number of potential root causes (process inputs, X) of the project problem are identified via root

cause analysis (for example a fishbone diagram) . The top 3-4 potential root causes are selected

using multi-voting or other consensus tool for further validation. A data collection plan is created

and data are collected to establish the relative contribution of each root causes to the project

metric, Y. This process is repeated until "valid" root causes can be identified. Within Six Sigma,

often complex analysis tools are used. However, it is acceptable to use basic tools if these are

appropriate. Of the "validated" root causes, all or some can be

List and prioritize potential causes of the problem

Prioritize the root causes (key process inputs) to pursue in the Improve step

Identify how the process inputs (Xs) affect the process outputs (Ys). Data is analyzed to

understand the magnitude of contribution of each root cause, X, to the project metric, Y.
http://en.wikipedia.org/wiki/Ishikawa_diagramhttp://en.wikipedia.org/wiki/Ishikawa_diagram


21/21

Statistical tests using p-values accompanied by Histograms, Pareto charts, and line plots

are often used to do this.

Detailed process maps can be created to help pin-point where in the process the root

causes reside, and what might be contributing to the occurrence.

Improve

The purpose of this step is to identify, test and implement a solution to the problem; in part or in

whole. Identify creative solutions to eliminate the key root causes in order to fix and prevent

process problems. Use brainstorming or techniques like Six Thinking Hats and Random Word.

Some projects can utilize complex analysis tools like DOE (Design of Experiments) , but try to

focus on obvious solutions if these are apparent.

Create innovative solutions

Focus on the simplest and easiest solutions

Test solutions using Plan-Do-Check-Act (PDCA) cycle

Based on PDCA results, attempt to anticipate any avoidable risks associated with the

"improvement" using FMEA

Create a detailed implementation plan

Deploy improvements

Control

The purpose of this step is to sustain the gains. Monitor the improvements to ensure continued

and sustainable success. Create a control plan. Update documents, business process and

training records as required.

A Control chart can be useful during the Control stage to assess the stability of the

improvements over time by serving as 1. a guide to continue monitoring the process and 2.

provide a response plan for each of the measures being monitored in case the process

becomes unstable.
http://en.wikipedia.org/wiki/Six_Thinking_Hatshttp://en.wikipedia.org/wiki/Random_stimulushttp://en.wikipedia.org/wiki/Design_of_Experimentshttp://en.wikipedia.org/wiki/PDCAhttp://en.wikipedia.org/wiki/Failure_mode_and_effects_analysishttp://en.wikipedia.org/wiki/Control_charthttp://en.wikipedia.org/wiki/Control_charthttp://en.wikipedia.org/wiki/Failure_mode_and_effects_analysishttp://en.wikipedia.org/wiki/PDCAhttp://en.wikipedia.org/wiki/Design_of_Experimentshttp://en.wikipedia.org/wiki/Random_stimulushttp://en.wikipedia.org/wiki/Six_Thinking_Hats

DFSS DMAIC

Documents

Transcript of DFSS DMAIC