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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?