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Statistics and Outliers

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

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  1. Statistics and Outliers Aaron Saks Process Advancement Leader Boise, Inc 10/26/2011

  2. 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

  3. 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.

  4. 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

  5. Tear Strength 4.1% represents ~ 1640 tons below current spec ~40 tons (0.1%) rejected for below-spec MD tear Current Target: 42

  6. 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.

  7. 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.

  8. 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.

  9. Running to Target – Excessive variation Ppkm = .65 Acceptable variation – but off Target

  10. 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.

  11. 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

  12. 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?

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