Statistics and Outliers

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# Statistics and Outliers - PowerPoint PPT Presentation

Statistics and Outliers. Aaron Saks Process Advancement Leader Boise, Inc 10/26/2011. Bio. Graduated in 2007 – ChemE and PSE Started career with Boise Inc, Wallula WA as a process engineer October 2008 went to work for Envoy Development

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### Statistics and Outliers

Aaron Saks

Boise, Inc

10/26/2011

Bio
• Graduated in 2007 – ChemE and PSE
• Started career with Boise Inc, Wallula WA as a process engineer
• October 2008 went to work for Envoy Development
• April 2010 returned to Boise as Process Advancement Leader, Wallula WA
• November 1st 2011 move to Boise, ID to become Project Manager for Boise Packaging
Statistics and Data
• Why is it important?
• Everything we really know, we know because of data.
• As a new engineer, we know how to apply math and logic to solve problems.
• We don’t really know how anything works.
• By focusing on the data we can learn, solve problems, and teach others.
• There is a lot of data out there.
• Statistics = The language of data.
Thinking Statistically
• We can’t just think in terms of the “average”.
• Need to think in terms of the distribution of data, and the probability of events occurring.
• What are good statistical tools for a new engineer?
• Six Sigma methods
• Understanding the common probability distributions and their mean and variance
• Understanding histograms and pareto charts
• Excel skills
Tear Strength

4.1% represents ~ 1640 tons below current spec

~40 tons (0.1%) rejected for below-spec MD tear

Current Target: 42

Ppkm: Run to Target and Reduce Variation
• Historically, papermakers would run “in the warning” all day, as long as the tests are within specification limits.
• This resulted in running off target, with different means run to run (Poor Quality).
• Needed a way to encourage (\$\$\$) running to targets, and reducing variation within the specs.
• Created a variation on the classical Process Capability metric “Cpk”.
• Result  a financial incentive for improving Quality.
Ppkm - Running to Target and Reducing Variation

Ppkm is an example of a process performance metric.

Ppkm captures both deviation from target and variation within specification limits.

If Ppkm >= 1, then the process is Capable: running to target and variation is well within specification limits

To improve Quality we award operators for the number for Key Product Properties that have a Ppkm value above 1.0.

Ppkm = 1.02

• Here is an example of a process that has a Ppkm>1, meaning it is fully capable of meeting customer expectations.
• Process is running to target – i.e. the mean is equal to the target
• Variation is well within the Specification (Red) limits.

Running to Target – Excessive variation

Ppkm = .65

Acceptable variation – but off Target

Outliers
• We spend most of our time working on the outliers:
• Process problems
• Lowering cost
• Increasing production
• Outliers exist in people too
• Top 20
• Middle 70
• Bottom 10
• The future leaders of tomorrow will be from the top 20.
Thoughts for a New Engineer
• Understand what is expected
• Focus on independent learning
• Always speak from facts and data
• Effective communication creates results
• Focus on business results and accomplishments
• You don’t have to be at the top to be a leader
Questions:
• What has been your biggest challenge?
• If you could go back to school what additional classes would you take?
• What's a typical day like?
• What kind of products does Boise make?
• How long do projects last?
• What ethical issues have you encountered?