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shainin problem solving method

Variables Search: A Great Experimental Design for Troubleshooting Complex Systems

shainin problem solving method

  • Dec 8, 2011
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shainin problem solving method

A number of experimental designs have been developed to help scientists understand cause-and-effect relationships between parameters in complex systems. Variables Search is a very effective troubleshooting technique developed by Dorian Shainin , recipient of four major ASQ awards. Keki Bhote describes Variables Search and other Shainin problem-solving methods in World Class Quality: Using Design of Experiments to Make It Happen . Variables Search has several benefits compared to other experimental designs:

  • Much easier to learn and use
  • You quickly find out whether key parameters have been accounted for or overlooked
  • Relatively few experiments are required to pinpoint the critical variables. This is extremely important because experimentation is costly and time-consuming.
  • "Confounded" variables, where a scientist cannot determine whether a given response is due to a multivariable interaction or a single variable, is an issue with many Design of Experiment ( DOE ) techniques, e.g., fractional factorials, Taguchi orthogonal arrays, Plackett-Burman designs. Variables Search clearly dissociates the main and interaction effects from each other.
  • Some conditions are replicated, which helps assess experimental error

Variables Search Phase 1 - Determine whether the critical variables have been uncovered

shainin problem solving method

Referring to the Phase 1 flowchart, several guidelines should be kept in mind while creating a "Variables List":

  • Selecting Variables: It's better to include seemingly irrelevant variables on the list, rather than omitting them, in case those variables turn out to be significant.
  • Ranking Variables: While variables can be ranked arbitrarily, there's a benefit associated with placing the most influential variables highest on the list. Variables ranked highest will be examined first during Phase 2; consequently, the number of experiments will be reduced if this activity was done effectively.
  • Choosing Settings: Each (+) value should be chosen with the belief that it will lead to the desired outcome , while each (-) value should be selected with the thought it will lead to an unwanted result .

When carrying out the six tests mentioned in the Phase 1 flowchart, randomize these experiments to ensure that uncontrolled variables do not bias the results. A test design example for six variables is displayed in the table below.

shainin problem solving method

To verify you're on the right track, I recommend doing two experiments up front; one experiment with all variables set at their (+) values, the other with all variables set at their (-) levels. Did the (+) settings experiment achieve the desired effect, while the (-) settings lead to an adverse response? If not, then the Variables List must be revised. Either:

  • Reexamine the Variables List. Should more variables be added to the list?
  • It's possible the (+) and (-) levels of one or more variables were assigned incorrectly and they're canceling the influence of other variables. Should any (+) and (-) values be reassigned?

If necessary, repeat the initial set of experiments until the (+) settings lead to a good outcome and the (-) settings leads to a poor result. Once this occurs, carry out the four remaining Phase 1 experiments.

Examining the results, answer the two questions posed on the Phase 1 flowchart. To establish a 95% confidence level that the critical variables have indeed been uncovered, both questions must be answered "yes."

Variables Search Phase 2 - Pinpoint the critical variables

shainin problem solving method

Phase 2 consists of a series of paired experiments to screen variables for their significance. This is done by swapping the (+) and (-) values of one variable at a time. By keeping all other variables at the conditions established during the Phase 1 experiments, the effect of the changed variable is highlighted. The order of these variable swapping experiments should be based upon the ranking done in Phase 1. The first set of paired experiments is depicted in the table below.

shainin problem solving method

These paired experiments have three possible outcomes:

  • The response variable is not affected at all when the variable under study is switched. This indicates that particular variable is insignificant within the range of conditions tested.

shainin problem solving method

  • The outputs change somewhat. This means the variable being studied is significant and it is interacting with other variables.

shainin problem solving method

  • There is a complete reversal of outputs. This means the switched variable is the one and only critical variable.

shainin problem solving method

Continue with the paired experiments per the Phase 2 flowchart until one or more significant variables have been identified.

Variables Search Phase 3 - Confirm that every interacting variable has been identified

Once two interacting variables have been identified during Phase 2, a pair of experiments must be completed to confirm that only those variables are interacting. The (+) and (-) settings of these two variables must both be switched from conditions established during Phase 1. In the table below, Variables B and D are switched. If, as indicated, the results reverse completely, all interacting variables have been identified and no further experimentation is necessary. If this is not the case, return to Phase 2 to identify another key parameter and then repeat the Phase 3 confirmation experiments.

shainin problem solving method

To quantify the influences of individual variables in a multi-variable interaction, experimental results can be analyzed by various software programs that perform Analysis of Variance (ANOVA) calculations, or the Yates algorithm can be employed to manually calculate each variable's effects.

How can you can use the variables search method in your work or research?

Image of puzzled via flickr user andy.brandon50 under creative commons license..

Leveraging Shainin for Quicker and More Efficient Problem Solving: A Discussion with Ha Dao, Director at SSA & Company

Ha Dao

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  1. Introduction to the Shainin method

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    Typical problem solving methods rely on the problem solving team to have experience with the system and a clear understanding of how it works. Without that, experience-based and brainstorming methods are not guaranteed to find the root cause. ... Shainin, the certifying body, ensures that every team member who earns certification is capable of ...

  4. An Overview of the Shainin System for Quality Improvement

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  6. PDF An Overview of the Shainin SystemTM for Quality Improvement

    The Shainin SystemTM (SS) is the name given to a problem solving system, with its associated strategies and tools, developed by Dorian Shainin, and widely used and promoted in the manufacturing sector. Dorian Shainin also called this system Statistical Engineering, reflecting his engineering education and background. The consulting firm ...

  7. (PDF) Shainin Methodology: An Alternative or an ...

    system as the problem-solving methodolog y stands (Shainin, 1993): For every effect there is dominant root-cause. The fastest way to identify the root-cau se is through a search using

  8. An Overview of the Shainin System™ for Quality Improvement

    The Shainin System™ (SS) is the name given to a problem solving system, with its associated strategies and tools, developed by Dorian Shainin, and widely used and promoted in the manufacturing sector. ... Some specific SS tools are examined and compared with alternative methods. In our assessment, the Shainin System is valuable for many types ...

  9. An Overview of the Shainin System™ for Quality Improvement

    ABSTRACT The Shainin System™ (SS) is the name given to a problem solving system, with its associated strategies and tools, developed by Dorian Shainin, and widely used and promoted in the manufacturing sector. Dorian Shainin also called this system Statistical Engineering, reflecting his engineering education and background. The consulting firm, Shainin LLC, offers the system under the ...

  10. Variables Search: A Great Experimental Design for ...

    Variables Search is a very effective troubleshooting technique developed by Dorian Shainin, recipient of four major ASQ awards. Keki Bhote describes Variables Search and other Shainin problem-solving methods in World Class Quality: Using Design of Experiments to Make It Happen. Variables Search has several benefits compared to other ...

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  12. The Role of Statistics in Red X® Problem Solving

    Judgmental statistics are used to prove cause-effect relationships. In Red X ® Problem Solving we call this taking the Red X to court. A B vs. W™ test proves the identity of the Red X. A six pack achieves that proof with a 5% risk that we've been fooled by the data. B vs. C™ tests assess if a proposed improvement is better than the ...

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    The consulting firm, Shainin LLC, offers the system under the trademarked name Red X Strategy. Much of SS is neither well documented, nor adequately discussed in peer-reviewed journals. The goal of this article is to provide an overview of SS, a critical assessment, and a brief comparison with other industrial problem solving systems.

  15. Leveraging Shainin for Quicker and More Efficient Problem Solving: A

    Shainin can be used to complement the Lean Six Sigma methodology. I have worked with many clients in which Shainin problem solving skills allows the Green Belts or Black Belts to find and eradicate root causes of problem faster with fewer resources. Shainin is particularly powerful in the Analyze phase of the Six Sigma DMAIC.

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    Dorian Shainin (September 26, 1914 - January 7, 2000) was an American quality consultant, aeronautics engineer, author, and college professor most notable for his contributions in the fields of industrial problem solving, product reliability, and quality engineering, particularly the creation and development of the "Red X" concept.. Shainin (pronounced SHAY-nin), founder of the technical ...

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