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Why should you attend?
Quality practitioners are most familiar with variation through its effects on product quality. Variation in product features is why purportedly interchangeable parts don't interchange, and generally accepted practices with which to deal with this have been around for decades.
Variation is also an issue in metrology, as reflected by measurement systems analysis (MSA, or gage reproducibility and repeatability). The issue differs from calibration, whose purpose is to ensure that, on average, a gage or instrument will return the correct measurement. MSA relates to precision, or how consistently the gage or instrument will return the same measurement (whether right or wrong) from the same item. Calibration and precision are both vital to ensure the correct results.
Goldratt's and Cox's The Goal shows meanwhile how variation in material processing and transfer times results in accumulation of inventory in a balanced factory with nominally adequate capacity. This is because time lost at the capacity-constraining resources is lost forever. Henry Ford, however, did what Goldratt showed to be impossible—ran a balanced factory at close to 100% capacity—by getting rid of the variation. Variation is similarly why lines of irate customers back up at service desks with nominally adequate capacity, and traffic jams appear literally out of nowhere during rush hour. The same issue carries over into project management where, if there is enough variation, an activity not on the critical path can in fact cause the project to finish late.
Areas Covered in the Session:
1. Variation and quality, the traditional application of variation.
· Don't blame the production worker when an incapable process (one with too much variation) cannot meet the specification limits consistently.
· A Six Sigma process is one that, in contrast, has six process standard deviations (sigmas) between its mean and the specification limits. This will deliver two nonconformances per billion opportunities if it remains centered on the nominal.
2. Variation and metrology; measurement systems analysis
· Calibration ensures that the gage will, on average, return the correct measurement. Precision means the gage will return the same measurement from the same part consistently.
· A gage that is not precise introduces the risk of accepting nonconforming work and rejecting work that meets specifications.
3. Variation and production control
· Variation in processing and material transfer times is why plants with nominally adequate capacity accumulate inventory. Henry Ford recognized this issue roughly 100 years ago, and designed his processes and logistics system to eliminate the variation in question.
· If removal of the variation is not possible, Goldratt's drum-buffer-rope (DBR) production control system can restrict inventory to the capacity constraining resource (constraint). DBR is also applicable to services.
4. Project management
· PERT (Project Evaluation and Review Technique) accounts for variation in task completion times but, in practice, excessive variation in completion time for an activity not on the critical path can in fact cause the project to finish late.
· The same issue carries over into production planning for products with complicated bills of materials (BOMs) because, if even one item is late, the product cannot be produced.
· Variation is why traffic jams appear seemingly out of nowhere during rush hour. Reduced rush hour speed limits can in fact increase throughput by eliminating stop-and-go traffic.
Attendees will receive a handout of the slides and accompanying notes, along with a customizable process for stakeholder-initiated CAPA (the kind that can be implemented by the process owner on the shop floor).
Who will benefit:
All quality practitioners and operations managers
William A. Levinson, P.E., is the principal of Levinson Productivity Systems, P.C. He is an ASQ Fellow, Certified Quality Engineer, Quality Auditor, Quality Manager, Reliability Engineer, and Six Sigma Black Belt. He is also the author of numerous books on quality, productivity, and management.