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Unit #5. Six Sigma

Six Sigma

Six Sigma is a business management strategy originally developed by Motorola, USA in 1981.[1] As of 2010, it enjoys widespread application in many sectors of industry, although its application 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 manufacturingand business processes.[2] It uses a set of quality management methods, including statistical methods, and creates a special infrastructure of people within the organization (“Black Belts”, “Green Belts”, etc.) who are experts in these methods.[2] Each Six Sigma project carried out within an organization follows a defined sequence of steps and has quantified targets. These targets can be financial (cost reduction or profit increase) or whatever is critical to the customer of that process (cycle time, safety, delivery, etc.).[2]

The term six sigma originated from terminology associated with manufacturing, specifically terms associated with statistical modelling of manufacturingprocesses. 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 free of defects, compared to a one-sigma process in which only 31% are free of defects. Motorola set a goal of “six sigmas” for all of its manufacturing operations and this goal became a byword for the management and engineering practices used to achieve it.

Historical overview

Six 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.[3] 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.[2]

Bill Smith first formulated the particulars of the methodology at Motorola in 1986.[4] Six Sigma was heavily inspired by six preceding decades of quality improvement methodologies such as quality controlTQM, and Zero Defects,[5][6] based on the work of pioneers such as ShewhartDemingJuranIshikawaTaguchi 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 Six Sigma project.[2]
  • An increased emphasis on strong and passionate management leadership and support.[2]
  • A special infrastructure of “Champions,” “Master Black Belts,” “Black Belts,” “Yellow Belts”, etc. to lead and implement the Six Sigma approach.[2]
  • A clear commitment to making decisions on the basis of verifiable data, rather than assumptions and guesswork.[2]

The term “Six Sigma” comes from a field of statistics known as process capability studies. Originally, it referred to the ability of manufacturing processes to produce a very high proportion of output within specification. Processes that operate with “six sigma quality” over the short term are assumed to produce long-term defect levels below 3.4 defects per million opportunities (DPMO).[7][8] Six Sigma’s 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.[9] As of 2006 Motorola reported over US$17 billion in savings[10] 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.[11] By the late 1990s, about two-thirds of the Fortune 500 organizations had begun Six Sigma initiatives with the aim of reducing costs and improving quality.[12]

In recent years, some practitioners have combined Six Sigma ideas with lean manufacturing to yield a methodology named Lean Six Sigma.

Methods

Six Sigma projects follow two project methodologies inspired by Deming‘s Plan-Do-Check-Act Cycle. These methodologies, composed of five phases each, bear the acronyms DMAIC and DMADV.[12]

  • DMAIC is used for projects aimed at improving an existing business process.[12] DMAIC is pronounced as “duh-may-ick”.
  • DMADV is used for projects aimed at creating new product or process designs.[12] DMADV is pronounced as “duh-mad-vee”.

DMAIC

The DMAIC project methodology has five phases:

  • Define the problem, the voice of the customer, and the project goals, specifically.
  • Measure key aspects of the current process and collect relevant data.
  • Analyze the data to investigate and verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered. Seek out root cause of the defect under investigation.
  • Improve or optimize the current process based upon data analysis using techniques such as design of experimentspoka yoke or mistake proofing, and standard work to create a new, future state process. Set up pilot runs to establish process capability.
  • Control the future state process to ensure that any deviations from target are corrected before they result in defects. Control systems are implemented such as statistical process control, production boards, and visual workplaces and the process is continuously monitored.

The DMAIC model (Define, Measure, Analyze, Improve and Control) is a rigorous, disciplined process utilized by the Black Belts in leading the Six Sigma project team.

The model consists of defined phases and a series of tools within each phase. The tools are quantitative (statistical), qualitative, and implementation. Each Six Sigma project must complete all 5 phases in sequential order. However, based on the actual results obtained, it is possible that a project may cycle between the Measure – Analyze – Improve phases before entering into the Control phase.

Reactive Problem Solving or Breakthrough Improvement: Which One?

8D Problem Solving Process DMAIC
A general process for reacting to unforeseenchange in:

  • work process
  • manufacturing process
  • results
  • customer satisfaction
WHEN THE
PROCESS IS
USED
A proactive, tightly focused process for use by Six Sigma project teams commissioned by leadership to solve:

  • a systematic business process issue
  • a systematic work process issue
  • highly wasteful / inefficient processes
    • definition of problems
    • containment of the problem
    • analysis of data
    • understanding and elimination of root cause
    • creative ideas
    • more alternatives
    • teamwork
    • commitment
THE PROCESS
FOSTERS
  • a disciplined approach
  • elimination of unneeded work
  • focus on the control of input variables
  • shared responsibility
    • strong customer/supplier communication lines
    • critical measurement
    • confidence in results
    • there is a gap between the “as is” state and the documented standard
  • product does not meet print
  • process is out of control
    • when the customer requires evidence of problem resolution
USE IT WHEN
  • you need to improve the process of a
    particular, currently existing output
  • you are about to produce a new output, the need for which has recently been determined

Basic Concepts of Quality

The list below summarizes the concepts of quality on which the Quality Improvement Process is based.

These are contrasted with some conventional views on quality and quality improvement.

Definition of Quality Conformance to requirements –
internal and external customers
NOT Expensive, luxurious or top of the line
The PerformanceStandard Consistently meeting theestablished requirements NOT “Close enough” or “Almost”
We Meet RequirementsBy Knowing the requirements;preventing mistakes from occurring NOT Only finding and fixing mistakes;“fixing it in the field”
Quality ImprovementOpportunities Are

Selected By

Looking for areas aligned with thebusiness strategy and with the

greatest payback

NOT Picking at random. “firefighting”
We Can Measure OurSuccess By Measuring our work against factsand data such as customer

requirements and process

improvements

NOT Opinions, guessing or “gut feel”

Step 1: DEFINE

Description: Leadership identifies a process that is not meeting the strategic objectives, establishes the scope and

boundaries for the project and commissions a Black Belt to lead a Six Sigma project team.

Guidelines Tasks to do / Questions to Ask
1. The process owner has accountability
  • Are the wasteful processes defined as an output?
and authority to make changes in the
  • Which process requires improvement the most?
process.
  • Who is the process owner?
2. Standards are being followed.
  • Who are the subject matter experts?
3. Identify the current state, the
  • Who should participate in the improvement effort?
entitlement state, and GAP.
  • What are the boundaries for the process?
4. Team consists of a Black Belt,process employees, process owner
  • Who are the customers for this process?
  • What are the customers’ requirements?
and finance.
  • What is to be produced?
5. Process defined as an output
  • Draft specific description of each requirement in terms of physical and
statement. Boundaries should be measurable attributes of the output.
established by identifying suppliers,inputs, customers, and output.
  • Review agreed-upon customer requirements.
6. Identify internal customers by name.
  • Validate the detailed description with the customer
  • Define the project goals and savings.
Outcome Checklist
  • Project commissioned by Executive Champion.
Is this process the most critical facing your
  • Project Charter completed.
organization?
  • Improvement opportunity identified.
Has the Project Charter been completed?
  • Goals and savings identified.
Has a Black Belt been assigned?
  • Savings agreed to by Finance.
Has a process owner been identified?
Have the team members been identified?
  • Subject matter experts identified.
Have the boundaries, inputs, and outputs been
  • The improvement team members identified.
  • The customers of the process identified.
identified for the project? (initial Value Stream Map)Has Finance endorsed the projected savings?

Leadership Verification Questions – Step 1

Prioritize Identify wasteful process
  • How did you define the general project; what
  • How have you determined the boundaries to your process?
data did you use?
  • How does this process support external customer requirements?
    • How is this project aligned with the business
    • What documented standards are being followed for the wasteful
strategy? process
Select Project Commission Team
  • Based on current process response, where
  • Who is the Black Belt?
should you focus your attention and why?
  • Who are the subject matter experts?
  • Who will be responsible for implementation of this improvement?
  • What are the team’s next steps?

Step 2: MEASURE

Description: The Six Sigma project team develops a baseline for the current process by generating a process map and

identifying the input / output variables and the value adding / non-value adding steps. The team also determines the current

measurement system and validates the capability of the measurement system.

Guidelines Tasks to do / Questions to Ask
1.                   Search for existing
  • Benchmark other processes that have produced same or similar outputs.
documentation; don’treinvent the wheel.
  • Document the current work process. Add to Value Stream Map, begin detailed Process Maps, and do process layout (spaghetti chart)
2.                     Work process steps
  • Complete a process Failure Mode and Effects Analysis (FMEA).
must include majoractivities.
  • Review list of customer requirements and supplier specifications from the boundary worksheet. Record on Value Stream Map.
3.                 Complex work requires
  • Identify steps for elimination from detailed process maps:
more detailedinformation.
  • Does this operation / step contribute to the conformance of a specific customer requirement?
4.                 Measurements should
  • If this process is not done will the process fail?
be derived from
  • If the answer to both questions is no, remove the step.
customer requirements
  • Identify process and results measurements for each supplier specification.
and supplier
  • Identify any other measurements critical to producing an output that meets requirements.
specifications.5.                 Measurement plan
  • Identify critical success factors and their location in the process.
should be completed
  • Characterize the process and identify the primary sources of variation.
before work begins.
  • Complete the measurement system analysis.
Customer
  • Establish the baseline process capability.
requirements and / or
  • Establish the baseline process capacity (compare to takt time).
probable causes Hints: Suggested Process:
should support critical
  • Examine the decision blocks to determine if directly
  • Generate VSM &
success factors. supported by a customer requirement or cause and effect Detailed Process
6.                  Three types of diagram. (May use brief QFD.) Maps.
measurements:
  • Examine the tasks to determine if directly supported by a
  • Brainstorm proposed
Baseline, Process, and customer requirement or cause and effect diagram. measurements.
Results.
  • Examine the data collected and unit of measure to
  • Complete
7.                Need to make a clear,reasonable choice determine if directly supported by a customer requirement orcause and effect diagram. measurementjustification.
between gathering new
  • If related to customer requirement or cause and effect
  • Create check sheets
data or using existing diagram, then measure; otherwise, eliminate the for data collection
data. measurement.
  • Show location of any
  • Establish a plan for collecting and displaying data.
measurements onmaps.
Outcome Checklist
  • Identify systematic way of
  • Does the process documentation show a sequence of activities / tasks?
producing the output. (The
  • Are the activities / tasks at sufficient level of detail?
process as it currently
  • Does the work process documentation show inputs / outputs?
exists).
  • Does the process documentation identify decision points that will prevent errors?
    • Identify process steps for
    • Does the work process specifically enable each supplier specification?
elimination.
  • Have you verified the documentation with the employees working in the process to
    • Identify relevant measures
ensure reality?
  • Plan for collection of own data.
  • Is the documentation clear enough to be used for training a new employee?
  • Are the critical success factors identified?
    • Completed Process FMEA.
    • Have you included both in-process and results measures?
      • Completed current Value
      • Have you established a plan for collecting and displaying your data?
Stream Map
  • Will you be using existing data or collecting new data?
    • Completed Measurement
    • Have customer requirements been defined?
System Analysis.
  • Is each process specification related to a customer requirement?
  • Are measurements taken as early as possible in the process?

Leadership Verification Questions – Step 2: MEASURE

Map existing process

  • What methods did you use to ensure that the flowchart coincides with reality?
  • What steps did the team take to determine ownership of the process?
Elimination

  • What process did you use to determine which steps in the process required removal?
  • Have you identified any residual activities?
  • Am I doing this “just in case?”
Select Measures
How have you identified relevant data?

  • Does that information add to the ability to monitor/

improve my

process?

Collect Data and Complete Analysis

  • Based on current process response, where should the team focus its attention and why?
  • What data should I collect?
  • What is the purpose of this data collection?
  • In what unit of measure do I state my requirements?
  • What dimension will I use to define my key measurements?
  • When measuring a variable, do I have control over it or is it an input to the process?
  • Where is the earliest point in the process when I can collect the data?
  • Will my data collection points give me robust data?
    • Have I validated this data collection against my flowchart, procedure sheets, customer requirements, and my cause and effect diagram?
    • How will this measurement impact my ability to conform to customer requirements?
ProcessCapability

  • What is the
    baseline

process

capability?

Collect Data and Complete Analysis

  • Are control charts being used on the process “X’s” or “Y’s”?
  • Discuss the results from Minitab.

What is the baseline process capability (Cp; CpK, etc.)?

  • Is the process capable of meeting the internal and external customer requirements?
  • What is the estimated DPMO?
  • Show me the initial control plan.
  • What is the Rolled Throughput Yield?
Process Capacity

  • What is the
    baseline

process

capacity of the major steps of the process?

Collect Data and Complete Analysis

  • Compare process cycle times with customer data
  • Compare takt time with capacity of each step and identify constraints
  • Identify lead times for supplier and upstream processes
  • Identify inventory levels between each process step and for raw material
  • Compute capacity at 80% theoretical (only value adding steps) and 0 defects (entitlement capacity)
MeasurementSystem Analysis

  • Has the measurement system

analysis been

completed?

Collect Data and Complete Analysis

  • Based on the “R chart by operator” is the measurement system stable?
    • Based on the “X-bar chart by operator” what is the part to part variation vs. the measurement error?
    • Based on the “response by operator” chart what can you determine about bias?
    • Based on the “operator to part interaction” chart is there any interaction?
    • What is the total “R&R”?
    • Is this acceptable or what is the plan to improve?
Process FMEA

  • Has the

process FMEA

been

completed and

validated?

Collect Data and Complete Analysis

  • What factors contribute to the highest risk priority numbers (RPN)?
  • What is the Pareto analysis for the RPN’s?
  • Is there any relationship between the most significant RPN’s and the process X’s and Y’s?
    • What controls are in place to protect the customer from receiving defects due to factors with high RPN’s?

Step 3: ANALYZE

Description: Uses data and Six Sigma tools to establish the key process inputs that affect the output.

Guidelines Tasks to do / Questions to Ask
1.               All the key product performance characteristics should
  • Prepare several Pareto Charts by analyzing the data
be identified. from several perspectives, for example:
2.   Include employees, customers, and suppliers.
  • Time sequence, cycle times, takt time
3.                 What / How to measure should be decided before the
  • Type of product
work process begins.
  • Location in the process
4.           Customer requirements or probable causes should
  • Type of defect
support critical success factors.
  • Type of waste (7 Wastes)
5.             Measurements can be divided into before, during, and
  • Etc.
after measurements.
  • Locate the most prominent bar(s) from the Pareto charts
6.                Concentrate on the vital few measurements that provide and place this at the “head” of the fishbone diagram.
essential information about the quality of your output.
  • Perform root cause analysis by asking why five times and
7.              The customer may serve as a valuable resource for input display on a Fishbone.
and data.
  • Select critical success factors (before, during, after) based on the root cause analysis.
  • Collect information on the critical success factors and display appropriately.
  • Complete the Cause and Effect diagram.
  • Complete the ANOVA.
  • Evaluate the utilization of and data from SPC charts.
  • Complete the Multi-Vari studies.
  • Complete the Correlation and Regression analysis.
Outcome Checklist
  • A systematic plan for analyzing the data and identifying
Have Pareto diagrams been constructed?
potential root causes for the gap between actual Have you asked “why “ five times for each potential
performance (“current state”) and the desired outcome cause on the fishbone diagram?
(”entitlement”). Has the Cause and Effect diagram been completed?
  • Create future state Value Stream Map)
Are the SPC charts providing any meaningfulinformation?
Has the Multi-Vari study been completed?
Has the Correlation and Regression analysis provided auseful prediction equation?

Leadership Verification Questions – Step 3

Analyze Data

  • Am I using the proper tool to collect the data?
  • Have I collected enough data to draw valid conclusions?
  • Am I monitoring irrelevant data?
  • How do I validate that the data is pure?
  • What tools are most effective in interpreting the “voice of the process?”
  • What message do the graphs give me in terms of my ability to meet the requirements?
  • How could I further verify the messages seen the graphs?
  • What message do the graphs give me in terms of my ability to meet the requirements?
  • How could we further verify the message seen in the graphs?
  • Is the process in control?
  • How did we determine that?
  • Is the process within specifications?
  • Does it / can it conform to customer requirements? (Is the process capable?)
  • How have we confirmed these conclusions?
  • What are our plans for proceeding further with this analysis?
Identify Root Cause

  • Have Pareto diagrams been constructed?
  • Have you asked “why” five times for each potential cause on the fishbone diagram?
  • Have the key process variables been defined?
  • What are the results of the hypothesis testing?
  • Do you have sufficient information to proceed with the Design of Experiment (DOE)?

Step 4: IMPROVE

Description: Generate, select, and implement a trial solution to close the gap and meet the goals of the Six Sigma project.

The identified improvements will optimize the process outputs and eliminate / reduce defects and variation. The new process

operating conditions are validated.

The activities will be presented in 2 stages – the first directed at the development of a trial solution and the second at the

implementation of the solution.

Leadership Verification Question – Step 4A

Generate Trial Solutions Select a Trial Solution

  • Have all potential solutions                                                                                •       Have criteria been selected that will ensure conformance to customer

been identified?                                              requirements?

Implement a Trial Solution

  • Has an implementation plan been completed/
  • Has the implementation plan been reviewed with the customer?
  • Have milestones been identified as part of the implementation plan?
  • Have Critical Success Factors (measurement) been identified?
  • Has the DOE been completed?
  • Have the ANOVA and Correlation / Regression analysis been completed?
  • Is the implementation plan working?

Step 4B

Description: Confirm results and validate the improvements.

Guidelines Tasks to do / Questions to Ask
1. Process changes should be documented with a
  • Continue to meet with customers to identify changing
flowchart and procedure sheets update. requirements.
2. Process FMEA and control plan should be
  • Continue to monitor processes to identify areas for process
updated. improvement.
3. Changes should include the measurement
  • Benchmark other processes to identify better practices.
points in the process and check sheets.
  • Implement necessary changes.
4. Evaluation of conformance should be based on
  • Standardize process changes where applicable.
customer requirements and critical success
  • Identify new knowledge that is a result of the pilot. (Any side
5. factors.Customer provides you with confirmation of your

conformance.

effects or unexpected results, implementation problems, etc.)
Outcome Checklist
Verify that the trial solution is working and Have customer requirements been met?
meeting customer requirements. Has the customer confirmed these changes?
Are there opportunities for process improvements?
Have the following been updated:
Process FMEA
Future Value Stream and detailed Process Maps
Layout and process flow with documented standard work
Data collection process
Control plan
Have process optimization tools been utilized:
Process flow and layout?
Line balancing and One piece flow?
Kan-Ban?
Visual control?
Workplace Organization (5S)?
Have Poka-Yoke (Error Proof) devices been implemented?
Has the process capability for the revised process beendocumented?

Leadership Verification Questions – Step 4B

Confirm the solution works

  • Have customer requirements been

met?

  • Have these changes been confirmed

by the customer?

  • · Are there opportunities for process improvements?
  • · Have process optimization tools been implemented?
  • Have visual controls been

implemented?

Has the “desired state” been achieved?

  • If no:      Was your selected root cause removed?
    • · If not, have you revisited your criteria rating form for the solutions?
    • · What other root causes do you plan to explore?
    • Have you reviewed your measures to be sure they are robust?
    • If yes:  Have you developed your implementation plan?

Step 5: CONTROL

Description: Implement process changes and standardize the solution, assign responsibility to maintain the gains, return the

process to sustaining operations.

Guidelines

  1. All process documentation must be updated to reflect process changes.
  2. Methods for collecting data to ensure the conformance of the process must be

assessed and implemented.

Tasks to do / Questions to Ask

  • Verify the flowchart and procedure sheets (standard work) are reflecting reality.
  • Verify the measurement system is robust enough to be implemented system wide.
  • Incorporate what you learned from the pilot into the implementation plan.
  • Develop a plan to implement the solution.
  • Update all the documentation required by the Quality Management System.
  • Identify methods and tools used to train the employees on the new methods.
  • Implement changes as required.
  • Develop the final presentation for project closure.
  • Document the project savings.
Outcome

  • Process improvement changes have been implemented and have closed the performance gap.
  • Process documentation to support the Quality Management System has been updated and deployed.
    • ·Revised process is returned to the process owner and sustaining operations to maintain the gains and deploy continual improvement techniques as applicable.

Checklist

Have all flowcharts and procedure sheets been updated and to they reflect reality?

Has all of the required documentation been updated to ensure ISO compliance?

Quality Inspection Plan(s)

Process Specifications

Quality Specifications

Product Prints

Local Documents (Work Instructions)

Routings

Part Master

FMEA(s)

Layout and process flow (verify cycle times)

Load leveling, buffers, and kanbans used conjunction with production control systems

Has an implementation plan been completed?

Has the customer reviewed the implementation plan?

Have milestones been identified as part of the implementation plan?

Is the implementation plan working?

Has the process owner taken control of the revised process to maintain the gains?

Identify best practices and lessons learned during the project.

Leadership Verification Questions – Step 5

Implement process changes

  • What additional lessons were learned from the pilot?
Standardize the solution

  • Have all flowcharts and procedure

sheets been updated and do they

reflect reality?

  • Has all of the required documentation

been updated to ensure ISO

compliance?

  • Does the control plan focus on the X’s

rather than the Y’s?

  • _ Quality Inspection Plan(s)?
  • _ Process Specifications?
  • _ Quality Specifications?
  • _ Product Prints?
  • _ Local documents (Work Instructions / standard work)?
  • _ Routings?
  • _ Part Master?
  • _ FMEA(s)?
Recognize and reward the improvement

  • Has the team been adequately recognized for their accomplishments?
  • Have the best practices and lessons learned been documented?
    • Sponsor, black belt and team host the celebration for the regular workers and leaders who at this point are implementing and working in the improved process.

DMADV

The DMADV project methodology, also known as DFSS (“Design For Six Sigma”),[12] features five phases:

  • Define design goals that are consistent with customer demands and the enterprise strategy.
  • Measure and identify CTQs (characteristics that are Critical TQuality), product capabilities, production process capability, and risks.
  • Analyze to develop and design alternatives, create a high-level design and evaluate design capability to select the best design.
  • 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 Sigma

Within 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.

Implementation roles

One 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 production floor and tostatisticians in a separate quality department. Formal Six Sigma programs borrow martial arts ranking terminology to define a hierarchy (and career path) that cuts across all business functions.

Six Sigma identifies several key roles for its successful implementation.[13]

  • Executive Leadership includes the CEO and other members of top management. They are responsible for 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 and Green 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, the employees who take up Six Sigma implementation along with their other job responsibilities, operate under the guidance of Black Belts.
  • Yellow Belts, trained in the basic application of Six Sigma management tools, work with the Black Belt throughout the project stages and are often the closest to the work.

Certification

In the United States. Six Sigma certification for both green and black belts is offered by the Institute of Industrial Engineers[14] and by the American Society for Quality.[15]

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 σ (sigma) marks the distance on the horizontal axis between the mean, µ, and the curve’s inflection point. The greater this distance, the greater is the spread of values encountered. For the curve shown above, µ = 0 and σ = 1. The upper and lower specification limits (USL, LSL) are at a distance of 6σ from the mean. 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 1.5σ 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 6σ 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.[8] 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 deviations will fit between the mean and the nearest specification limit, decreasing the sigma number and increasing the likelihood of items outside specification.[8]

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.[8] As a result, the number of sigmas that will fit between the process mean and the nearest specification limit may well drop over time, compared to an initial short-term study.[8] To account for this real-life increase in process variation over time, an empirically-based 1.5 sigma shift is introduced into the calculation.[8][16] According to this idea, a process that fits six sigmas between the process mean and the nearest specification limit in a short-term study will in the long term only fit 4.5 sigmas – 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.[8]

Hence the widely accepted definition of a six sigma process as one that produces 3.4 defective 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).[8] So the 3.4 DPMO of a “Six Sigma” process in fact corresponds to 4.5 sigmas, namely 6 sigmas minus the 1.5 sigma shift introduced to account for long-term variation.[8] This takes account of special causes that may cause 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.[8]

Sigma levels

control chart depicting a process that experienced a 1.5 sigma drift in the process mean toward the upper specification limit starting at midnight. Control charts are used to maintain 6 sigma quality by signaling when quality professionals should investigate a process to find and eliminate special-cause variation.

See also: Three sigma rule

The table[17][18] below gives long-term DPMO values corresponding to various short-term sigma levels.

Note that these figures assume that the process mean will shift by 1.5 sigma toward the side with the critical specification limit. In other words, they assume that after the initial study determining the short-term sigma level, the long-term Cpk value will turn out to be 0.5 less than the short-term Cpk value. So, for example, the DPMO figure given for 1 sigma assumes that the long-term process mean will be 0.5 sigma beyond the specification limit (Cpk = –0.17), rather than 1 sigma within it, as it was in the short-term study (Cpk = 0.33). Note that the defect percentages only indicate defects exceeding the specification limit to which the process mean is nearest. Defects beyond the far specification limit are not included in the percentages.

Sigma level DPMO Percent defective Percentage yield Short-term Cpk Long-term Cpk
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

Main article: List of Six Sigma software packages

List of Six Sigma companies

Main article: List of Six Sigma companies

Criticism

Lack of originality

Noted quality expert Joseph M. Juran has described Six Sigma as “a basic version of quality improvement”, stating that “[t]here is nothing new there. It includes what we used to call facilitators. They’ve 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, that’s not a new idea. The American Society for Quality long ago established certificates, such as for reliability engineers.”[19]

Role of consultants

The use of “Black Belts” as itinerant change agents has (controversially) fostered a cottage 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.[2]

Potential negative effects

Fortune article stated that “of 58 large companies that have announced Six Sigma programs, 91 percent have trailed the S&P 500 since”. The statement is attributed to “an analysis by Charles Holland of consulting firm Qualpro (which espouses a competing quality-improvement process).”[20] 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.[21][22]

BusinessWeek article says that James McNerney‘s introduction of Six Sigma at 3M may have had the effect of stifling creativity. It cites two Wharton School professors who say that Six Sigma leads to incremental innovation at the expense of blue-sky work.[23] 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 Ford‘s “6 Sigma” program did little to change its fortunes.[24]

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 lower standards. 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.[2]

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.[25] Its universal applicability is seen as doubtful.[2]

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 4.5 sigma performance is, by Six Sigma convention, described as a “6 sigma process.”[8][26] 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.[26] 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.[8]

See also

Considering Six Sigma Best Practices

Successful Six Sigma efforts have several practices and characteristics in common. As you launch into your own Six Sigma journey, you can use these as landmarks to set your course and bearing. Even after you’ve been doing Six Sigma for a while, it’s a good idea to periodically compare what you do with what others have found to be most effective.

Set stretch goals

Six Sigma isn’t for the mildly ambitious manager or the person who wants to incrementally improve the output of a process. Instead, Six Sigma is for people who want to improve by leaps and bounds.

Six Sigma has repeatedly proven that it produces breakthrough improvement. But to achieve this, you have to combine the power of the Six Sigma method and tools with stretch goals, goals that almost seem too aggressive, too optimistic.

Specifically, a stretch goal represents a 70 percent improvement over current performance. For example, if your company’s profit margin is seven percent, you want to aim for 11.9 percent (a 70 percent increase). Or if a certain process or product is producing ten defects per 100 units, you want to reduce that number to three defects per 100 units (a 70 percent improvement).

Another common way to set the right stretch target is to benchmark yourself against your competition. A benchmark is the level of performance achieved by the best companies, organizations, functions, or processes in your industry. If someone else is doing it, you should be able to do it, too, right? Toyota, for example, is a company that is benchmarked for the time it takes them to introduce a brand-new vehicle design. Most companies take 36 to 48 months to bring a new vehicle to market; Toyota did it in about 24 for its hybrid car, the Prius, which also presented a technical challenge far beyond those of traditional gasoline-only cars.

Target tangible results

Typically, Six Sigma leads organizations to reduce their costs by as much as 20 to 30 percent of revenue. At the same time, these organizations increase their revenues by 10 percent or more.

To realize these returns, however, each Six Sigma project must be tied to a tangible financial measure of return — dollars saved, new revenue gained, specific costs avoided, and so on. These measured financial returns must be formally measured, tracked, and rolled up if you want to achieve the startling financial return that is a hallmark of Six Sigma. Without tying projects to tangible financial measures and tracking their financial impact, Six Sigma efforts naturally drift away from their financial potential.

In isolated cases, a Six Sigma project is not directly focused on cost reduction or revenue enhancement. Instead, it is targeted on a strategic objective of the organization. If you complete a project with an object of increasing brand awareness, for example, you’ll have difficulty quantifying how much that project improves the company’s bottom line. But if it enables the company’s key business strategies, the project is still worth the effort.

Determine outcomes

Every output or result is determined by a set of inputs. The natural outgrowth of this principle is that you actively go out and adjust and control the inputs in a way that enables you to reach your desired outcomes with certainty and consistency.

Think before you act

Too often, people jump into action and do something — anything — to solve a problem. They confuse action with effectiveness. Undoubtedly, this approach showcases activity, but it usually ends in a continuation of the problem or, at best, a suboptimal solution.

Six sigma’s DMAIC methodology forces you to shift the bulk of the activity of solving a problem into defining, measuring, and planning a solution. Each project starts with a detailed, in-depth definition of what the problem really is and what the objectives of the solution are. Next, extensive measurements are taken to verify the current performance of the process or system. This is followed by in-depth analysis of inputs, outputs, conditions, and causes-and-effects. Only after completion of all of these steps is an improvement solution attempted. The result of this upfront rigor is, almost always, an optimal solution that can be quickly and efficiently put in place. In the long-run, the front-loaded DMAIC approach solves the problem more quickly and with better, more consistent results than other approaches.

Put your faith in data

Without data, decisions are based on supposition, estimation, opinion, and sometimes wishful thinking. Data allows you to objectively identify and select the truly best ideas and solutions from among the many alternatives.

Making decisions based on data, however, is not easy. Data require you to suspend judgment and personal bias, to confront sometimes brutal and undesirable facts. You have to believe that, in the long-run, trusting data will consistently lead you to better and more rapid solutions.

Minimize variation

Most people think of excellence in terms of averages or single numbers — the average yield on a production line, the monthly cost to run a department, the rate of return on an investment. But the reality is that variation around these averages or single numbers — even when they are at acceptable levels — can often cause more damage than their level itself.

For example, having a high average number of orders is great. But if the day-to-day number of orders varies widely, it requires the company to have excess equipment and staff always on hand, just in case. When the number of orders varies to the low side, equipment and staff sit idle. The company would actually come out ahead if its average number of orders were lower but its day-to-day variation were smaller. That way equipment and staff needs would be steady and costs would be reduced.

Variation will always be present in the plans you design, the products you make, the transactions you conduct, the services you deliver. Even in the environment outside your control, events and circumstances change and vary in ways beyond your control.

Align projects with key goals

An important Six Sigma success factor is selecting projects that are aligned with the key goals and objectives of your organization. Six Sigma efforts that are successful and lasting are always made up of projects that are each specifically focused on moving an organization towards its stated objectives.

Celebrate success!

A Six Sigma initiative may start small with a single pilot project, or a deployment within a lone department. Others grow to include an entire global organization or accumulate staggering financial returns. Regardless, celebrate success.

Success is contagious. When the first, small victories are showcased and lauded — with recognition, rewards, praise, and publicity — people develop real interest. They build confidence and trust. They begin to believe in the power and potential of the method. Each successive victory becomes that much easier.

Involve the owner

Successful Six Sigma practitioners communicate with and involve the owner of the process or system they are working in. They solicit their input and provide feedback through all the stages of DMAIC. Then, when the time for change arrives, the owner jumps at the chance to implement the awaited improvements
Read more: http://www.dummies.com/how-to/content/considering-six-sigma-best-practices.html#ixzz0phUfcPqe

References

  1. ^ Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd.. p. 6. ISBN 0566083744.
  2. a b c d e f g h i j k Antony, Jiju. “Pros and cons of Six Sigma: an academic perspective”. Retrieved May 1, 2008.
  3. ^ “Motorola University – What is Six Sigma?”. Retrieved 2009-09-14. “[…] Six Sigma started as a defect reduction effort in manufacturing and was then applied to other business processes for the same purpose.”
  4. ^ “The Inventors of Six Sigma”. Retrieved January 29, 2006.
  5. ^ Stamatis, D. H. (2004). Six Sigma Fundamentals: A Complete Guide to the System, Methods, and ToolsNew York, New York: Productivity Press. p. 1. ISBN 9781563272929OCLC 52775178. “The practitioner of the six sigma methodology in any organization should expect to see the use of old and established tools and approaches in the pursuit of continual improvement and customer satisfaction. So much so that even TQM (total quality management) is revisited as a foundation of some of the approaches. In fact, one may define six sigma as “TQM on steroids.””
  6. ^ Montgomery, Douglas C. (2009). Statistical Quality Control: A Modern Introduction (6 ed.). Hoboken, New JerseyJohn Wiley & Sons. p. 23. ISBN 9780470233979OCLC 244727396. “During the 1950s and 1960s programs such as Zero Defects and Value Engineering abounded, but they had little impact on quality and productivity improvement. During the heyday of TQM in the 1980s, another popular program was the Quality Is Free initiative, in which management worked on identifying the cost of quality…”
  7. ^ “Motorola University Six Sigma Dictionary”. Retrieved January 29, 2006.
  8. a b c d e f g h i j k l Tennant, Geoff (2001). SIX SIGMA: SPC and TQM in Manufacturing and Services. Gower Publishing, Ltd.. pp. 25. ISBN 0566083744.
  9. ^ “Motorola Inc. – Motorola University”. Retrieved January 29, 2006.

10. ^ “About Motorola University”. Retrieved January 29, 2006.

11. ^ “Six Sigma: Where is it now?”. Retrieved May 22, 2008.

12. ^ a b c d e De Feo, Joseph A.; Barnard, William (2005). JURAN Institute’s Six Sigma Breakthrough and Beyond – Quality Performance Breakthrough Methods. Tata McGraw-Hill Publishing Company Limited.ISBN 0-07-059881-9.

13. ^ Harry, Mikel; Schroeder, Richard (2000). Six Sigma. Random House, Inc. ISBN 0-385-49437-8.

14. ^ “Institute of Industrial Engineers Six Sigma certifications”Norcross, GeorgiaInstitute of Industrial Engineers. Retrieved 2010-01-05.

15. ^ “Certification – ASQ”Milwaukee, WisconsinAmerican Society for Quality. Retrieved 2010-01-05.

16. ^ Harry, Mikel J. (1988). The Nature of six sigma quality. Rolling Meadows, Illinois: Motorola University Press. p. 25. ISBN 9781569460092.

17. ^ Gygi, Craig; DeCarlo, Neil; Williams, Bruce (2005). Six Sigma for Dummies. Hoboken, NJ: Wiley Publishing, Inc.. pp. Front inside cover, 23. ISBN 0-7645-6798-5.

18. ^ El-Haik, Basem; Suh, Nam P.. Axiomatic QualityJohn Wiley and Sons. p. 10. ISBN 9780471682738.

19. ^ Paton, Scott M. (August 2002). Juran: A Lifetime of Quality22. pp. 19–23. Retrieved 2009-04-01.

20. ^ Morris, Betsy (2006-07-11). “Tearing up the Jack Welch playbook”. Fortune. Retrieved 2006-11-26.

21. ^ Richardson, Karen (2007-01-07). “The ‘Six Sigma’ Factor for Home Depot”. Wall Street Journal Online. Retrieved October 15, 2007.

22. ^ Ficalora, Joe; Costello, Joe. “Wall Street Journal SBTI Rebuttal” (PDF). Sigma Breakthrough Technologies, Inc.. Retrieved October 15, 2007.

23. ^ Hindo, Brian (6 June 2007). “At 3M, a struggle between efficiency and creativity”. Business Week. Retrieved June 6, 2007.

24. ^ Ruffa, Stephen A. (2008). Going Lean: How the Best Companies Apply Lean Manufacturing Principles to Shatter Uncertainty, Drive Innovation, and Maximize Profits. AMACOM (a division of American Management Association). ISBN 0-8144-1057-X.

25. ^ Wheeler, Donald J. (2004). The Six Sigma Practitioner’s Guide to Data Analysis. SPC Press. p. 307. ISBN 9780945320623.

26. ^ a b *Pande, Peter S.; Neuman, Robert P.; Cavanagh, Roland R. (2001). The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance. New York: McGraw-Hill Professional. p. 229. ISBN 0071358064.

Further reading

One comment

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