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Process Improvement Methodologies

Process Improvement Methodologies. References (sources of graphics): Fiore, Clifford, Accelerated Product Development: Combining Lean and Six Sigma for Peak Performance , Productivity Press, NY, NY, 2005.

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Process Improvement Methodologies

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  1. Process Improvement Methodologies References (sources of graphics): Fiore, Clifford, Accelerated Product Development: Combining Lean and Six Sigma for Peak Performance, Productivity Press, NY, NY, 2005. Hamilton, Bruce, “Toast Kaizen, An Introduction to Continuous Improvement & Lean Principles,” Greater Boston Manufacturing Partnership, University of Massachusetts, Boston, MA, 2005 (DVD). Insights On Implementation-Improved Flow: Collected Practices and Cases, Ralph Bernstein, Editor, Productivity Press, 2006. Jacobs, Robert F. and Chase, Richard B., Operations and Supply Management: The Core, 2nd Edition, McGraw-Hill/Irwin, NY, NY, 2008. Nahmias, Steven, Production & Operations Analysis, 5th Edition, McGraw-Hill/Irwin, NY, NY, 2005. Nave, Dave, “How to Compare Six Sigma, Lean, and the Theory of Constraints,” Quality Progress, March 2002, pgs 73 – 78.

  2. Comparison of Three Commonly Adopted Improvement Methodologies • See reference, How To Compare Six Sigma, Lean and the Theory of Constraints • Comparing the main points of the three improvement methodologies: Six Sigma, Lean Thinking, and Theory of Constraints

  3. Six Sigma Approach • Define, measure, analyze, improve, control (DMAIC) cycle

  4. Six Sigma Tools • Tools common to other quality programs are used in Six Sigma • Failure mode and effects analysis (FMEA) • Structured approach to identify, estimate, prioritize, and evaluate risk of possible failure at each stage of a process • Risk priority number (RPN) is calculated and is based on • Extent of damage resulting from failure (severity) • Probability failure takes place (occurrence) • Probability of detecting the failure (detection) • High RPN items are designated for improvement first • Example • Design of experiments (DOE) • Statistical approach used for determining the cause-and-effect relationship between process variables and an output variable • Approach allows for experimentation with many variables simultaneously

  5. Six Sigma Quality • To achieve a Six Sigma quality (according to the assumptions used by Motorola and GE) a process must produce no more than 3.4 defects per million opportunities • Assuming a process follows a normal distribution and given design limits of ± 6 σ there would be 2 defective parts per billion (0.000000002 fraction defective) • Motorola’s and GE’s value of 3.4 defects per million is due to the fact that a shift of 1.5 σ in the process mean is assumed • An example process • spec = 1.250 ± 0.005, μ = 1.250, σ = 0.002, UCL & LCL = 3 σ (μ and σ estimated from sample parameters) • Six Sigma process: μ = 1.250 in, σ = 0.000833 in (0.005 in/6) • Six Sigma process with a 1.5 σ shift to the mean: μ = 1.25125 in, σ = 0.000833 in

  6. Process Capability Index • Process capability index (Cpk) • For (Motorola’s and GE’s) Six Sigma process

  7. Example Problem

  8. Lean Case Study • Quality Parts Company

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