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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

Statistics and Outliers

Aaron Saks

Process Advancement Leader

Boise, Inc



  • 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
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
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
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
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.

P pkm running to target and reducing variation
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


  • 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
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


  • 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?