090528 Miller Process Forensics Talk @ Asq

Presented at ASQ Pensacola Chapter Meeting (05/28/09)

by

Richard W. Miller, Ph.D

Master 6-Sigma Black Belt

Fellow with Monsanto/Solutia ~30 years

President: Pensacola Process Optimization

(partnership with Raid Amin, UWF Statistics Professor)

Process Forensics: How to Use Capability Metrics (Pp, Ppk, Cp and Cpk) To Assess Process Problems/Opportunities

Over the past five years, I’ve formed an led seven teams whose goal it was to fix processes (improve yields, reduce waste, reduce cost and reduce variability). This work led directly to new insights into the processes, millions in annual savings and new strategies Implemented for continuously evaluating measurement systems and monitoring their capability. Recent Experience

This presentation will define the process capability metrics, highlight the importance of short-term versus long-term variability, then show how these metrics can define a process for the control engineer and, as importantly, allow upper management to assess that process’ current state of performance and its future capability. Additionally, I’ll present a new strategy I developed (called the 5/3 strategy) for continuously monitoring a measurement system's capability, i.e., the percentage of day-to-day process variation that's being contributed by the measurement system. It overcomes the faults of the typical Gauge R&R (one point in time measure versus continuous, special lab event versus blind to lab, special sample dependent versus routine sampling). Finally, on an entirely different subject, I’ll demonstrate the importance of using historical data in a resampling approach to setting spare-part inventory limits (estimated to typically save 25-50% of this type inventory capital), e.g., a large chemical company recently reported they had $14 million invested in spare parts. Today’s Presentation

Typical Processes

Restaurant’s Food Delivery

Hospital’s Care Delivery

Bank’s Customer Documentation

Nylon Polymer Production – my example

Part/Product Manufacturing

Process Concerns: Yield (Error Frequency), Quality, Variation, Cost Process Assessment: Routine Sampling, Charting & Testing

Measurement System Validation

Measurement System Continuous Validation Most Process Control Schemes are Highly Dependent on a Measurement System, and It’s Always Questioned. First Words from Most Line Engineers When They See a Problem: “ Bad Measurement. Lab Made a Mistake”) There are two major problems with traditional GRR studies. As Donald Ermer points out in his recent paper “Improved Gauge R&R Measurement Studies,” in March 2006 issue of Quality Progress, pp. 77-79 (and Don Wheeler in the 2006 edition of his book EMPIII Using Imperfect Data, Chapter 16, “ Gauge R&R Studies), “…the most significant error is the final variation ratios--percent equipment variation, percent appraiser variation and percent part variation. These are calculated using standard deviations instead of variances. The results obtained exaggerate the proportional effects of the equipment, appraiser and part variation. Therefore, this incorrect type of study cannot provide an index of whether the components of the measurement process are capable for the part of product under study.” Additional Problems with Gauge R&R • Special Treatment by the Lab • One Time, Static Analysis • Highly Dependent on Quality/Spread of Samples

Measurement System Validation Through ReSampling Simulation • 10,000 Iterations (Each Provides Estimate Measurement System Variation) • 10% Variation Due Measurement System

Observations

Variation of 5/3 and 15/3 Estimates are Similar and Far Less Than That Obtained from 5/2 Strategy;

Outlier Estimates Occur: 5/3 (5 of 50 > 20%), 5/2 (12 of 50 > 20%), 15/3 (2 of 50 > 20%).

Measurement System Strategies • 5 Samples Sub-Sampled 3x (5/3) • 5 Samples Sub-Sampled 2x (5/2) • 15 Samples Sub-Sampled 3x (15/3) “ 15/3 is Gauge R&R Simulation Assuming All Variation Arises from Operator Differences”

Process Control and Continuous Measurement System Validation

Process Control Charts 5/3 Measurement System Variance Partitioning

Process Capability Metrics and Process Forensics

Process Capability Metrics Specification Metric Imposed on Product “ Voice of Process” Ppk, Pp = Specification Metric Imposed on Process “ Ultimate Capability of Process” Cpk, Cp = Ppk = 2*Min (USL- μ , μ -LSL) 6 σ LT where USL=Upper Specification Limit and LSL= Lower Specification Limit Ppk, Pp, Cpk, Cp=1 means 99.73% of your population is within specifications (27 in 10,000 out of spec) Pp = (USL - LSL) 6 σ LT Ppk, Pp, Cpk, Cp=1.333 means 99.994% of your population is within specifications (6 in 100,000 out of spec) Cpk = 2*Min (USL- μ , μ -LSL) 6 σ ST Cp = (USL - LSL) 6 σ ST Process Targeting Process Variance Point to Point (MR) or Within Variance USL LSL µ

How Does One Use these Capability Metrics to Monitor/Control Processes? Management : Metrics Identify (1) Current Operation Characteristics and (2) What a Process’ Ultimate Capability Could Be; Line Engineer : (1) and (2) Above Plus (3) Strategies for Attacking Process Problems {Improve Targeting, Reduce Long-Term Variation, Reduce Short-Term Variation, Improve Measurement System}

Process Forensics “ Targeting & Variance” “ Chance to learn something about the process” Distributions of Different Sources of Variation Process Chart and Its Characterizations “ Process improvement leads to greater measurement system contribution.”

Examples of Process Forensics Utilizing Capability Metrics σ LT σ ST Specification Metric Imposed on Product “ Voice of Process” Ppk, Pp = Specification Metric Imposed on Process “ Ultimate Capability of Process” Cpk, Cp = USL LSL µ Capability Metric = σ LT or σ ST

Question of Resampling a Suspected Bad Lab Data Point 4.1 σ LT There’s often the very real possibility of a questionable measurement, either because of outright error or because of the distributional nature of the measurement system itself. Because this producer’s risk (risk of off-grading acceptable product) is often judged more important to the producer than the customer’s risk (risk of not off-grading unacceptable product), off graded material is given every opportunity to prove itself before committing to a rework strategy. The question becomes: if the same lot is re-measured, how likely is this new measure to then fall within specs.

Strategies for Attacking Variation In Multi-Position Process

Developing Strategies for Attacking Variation A Strategy for Positional Troubleshooting 280 Positions Making a Single Product 1 Position Makes 2,880 Bbns Monthly 280 Positions Make 806,400 Bbns Monthly 3.6% 36.8% 1.6% 0.3% 0.1% 0.01%

In Closing This Section, There are Two Points That I’ll Leave You With: • Continuous Measurement System Validation Adds Credibility to Our Lab Measurements and Identifies Those Needing Improvement • Process Forensics Utilizing Process Capability Metrics Identifies Process Problems: Targeting, Short- or Long-Term Variability

Capital Requirement Analysis for Spare Parts Inventory Company Currently has $14 Million of its Capital Tied Up in Spare Parts Pilot Study was Undertaken on 15 Parts