3.10 Summary

In this chapter, a discussion of the Measure phase of the DMAIC process has been presented with key topics:

• Definition of Measure

• Data type

• Data dimension and qualification

• Closed-loop data measurement system

• Flow charting

• Business metrics

• Cause-and-effect diagram

• Failure mode and effects analysis (FMEA) and failure mode, effects, and criticality analysis (FMECA)

• Data collection plan

• Data presentation plan (tables, charts, graphs, and basic statistics)

• Introduction to MINITAB tool

• Determining sample size

• Probabilistic data distributions (normal, Poisson, exponential, binomial, gamma, and Weibull)

• The Central Limit Theorem

• Calculating sigma (discrete and continuous data processes):

  • Defects per million opportunities (DPMO)

  • Errors per million opportunities (EPMO)

  • Sigma shift (long term vs. short term)

• Process capability indices

A project team must perform the following tasks before proceeding to Analyze, the next phase of the DMAIC process:

• Ensure completion of:

  • Selection and team approval of key measures

  • A data collection plan (with a decision made that historical data can be utilized or that data collection is needed)

  • Accounting for long-and short-term process variability

  • Baseline process performance in Sigma metrics

• Identify the following factors:

  • Input variables, process variables, and output variables

  • Key measures to identify business performance

  • Customer CTQs, defect opportunities, and process capability metric

  • Charts and processes used for display and communication of process variation

  • Gap between current performance and the customer-specified performance

  • Any "low-hanging fruit" (i.e., any product/process improvement that is obvious based on preliminary information and which is easy to implement) for immediate remedies to reduce the gap

  • Handy...