TKC Enterprises, Inc.

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Defect Reduction
 

The Six Sigma problem solving methodology is the most effective tool we have found to quickly reduce and eliminate defects.  This team-based methodology works by systematically identifying and controlling the process variables that contribute to producing the defect.   It is a thorough process which is business-driven, team-based, data-centric, and scientific in its approach.  It includes many tools and processes we describe them in more detail below.  For each project we strategically select the tools that will expedite the benefits; we rarely apply the entire tool set.   Six-Sigma can be applied to any process including manufacturing or business processes. 

 

 

Why reduce defects?

Defect reduction improves efficiency, reduces costs, often improves customer satisfaction and ultimately translates into a competitive advantage for your company.  Here are some documented financial benefits of the Six Sigma process.

 
Table 2: Six Sigma Cost And Savings By Company
YearRevenue ($B)Invested ($B)% Revenue InvestedSavings ($B)% Revenue Savings
Motorola
1986-2001356.9(e)ND-16 14.5
Allied Signal
199815.1ND-0.5 23.3
GE
199679.20.20.30.20.2
199790.80.40.411.1
1998100.50.50.41.31.2
1999111.60.60.521.8
1996-1999382.11.60.44.4 31.2
Honeywell
199823.6ND-0.52.2
199923.7ND-0.62.5
200025.0ND-0.72.6
1998-200072.3ND-1.8 42.4
Ford
2000-200243.9ND-1 62.3
Key:
$B = $ Billions, United States
(e) = Estimated, Yearly Revenue 1986-1992 Could Not Be Found
ND = Not Disclosed
Note: Numbers Are Rounded To The Nearest Tenth

    


  Typical Six Sigma Opportunities

 

What are classic Six Sigma opportunities?

     In general Six Sigma's thorough and analytical approach is best applied to costly problems with no know solution.  It can be applied to transactional or manufacturing processes: 

 

 Manufacturing Opportunities

  • Low Yields
  •  
    High Customer Returns
  • Defects that require extra inspection in or out of your plant
  • High Scrap or Rework rates
  • Production below expectations
  • Non-customer driven overtime
  • Downtime
  • Premium Freight costs

 

 Transactional Projects

  • Long customer wait times
  • Long processing time
  • Errors in transaction
  • Paperwork cycle time

 

 

History and Six Sigma Usage

 

History of Six sigma

       Six Sigma finds its roots in Carl Frederick Gauss (1777-1855) who introduced the concept of the normal curve.  Then in the 1920’s Walter Shewhart showed that 3 sigma was a key process correction point.  It was a Motorola engineer named Bill Smith who coined the term "Six Sigma". (Incidentally, "Six Sigma" is a federally registered trademark of Motorola).

       When the Japanese took over a television-manufacturing unit of Motorola in 1970, the idea was advanced, and under Motorola’s Chairman Bob Galvin the methodology was further developed and given the emphasis to change the culture.  With this cultural shift of Six Sigma, Motorola documented more than $16 Billion in savings as a result of Six Sigma.

       Since then, hundreds of companies around the world have adopted Six Sigma as a way of doing business. This is a direct result of many of America's leaders openly praising the benefits of Six Sigma -- leaders such as Larry Bossidy of Allied Signal (now Honeywell), and Jack Welch of General Electric Company. Six Sigma has now evolved into a philosophy of doing business. 

 

References: 

Six Sigma is currently benefiting thousands of companies across the world including Motorola, GE, Toyota, Bank of America, Lear, Textron, JPMorgan, Citigroup, Merril Lynch, Washington Mutual, FleetBoston, Capital One, BlueCross & BlueShield.

 

 

 

Six Sigma Process and

Tools  

 

What are classic Six Sigma opportunities?

 

Our problem solving approach is 5 basic steps:  DMAIC

 

 

 

 

Each process step has tools associated with it, and often the tools are used in multiple steps.  Here are some of the Six Sigma Tools that we use and help companies use:

 

  Define

      Scope development

      Process Map

      Process Capability

      Cause and Effect Diagrams (C&E diagrams)

      Root Cause Analysis

      Failure Modes and Effects Analysis (FMEA)

 

  Measure

      Measurement System Analysis (MSA)

      Gauge Repeatability/Reproducibility (Gauge RR)

      Probability

      Hypothesis testing

     

  Analyze

      Probability

      Histograms

      Pattern and trend analysis

      Distribution analysis

      ANOVA

      Correlation

      General Linear Models

      Screening Design of Experiment (DOE)

      Hypothesis Testing

 

  Improve

      Modeling Design of Experiment (DOE)

      Improvement implementation

 

  Control

      Control planning

      Statistical Process Control (SPC)

      Control Charts