Abstract
This chapter is all about the analysis tools you can use to solve problems. Although there are many analysis tools available, each tool is fit for a particular purpose and provides clues in its own way. Some provide inductive information, for example, whereas others provide deductive information. Each provides a technique for identifying the differences between acceptable and unacceptable parts, processes, or actions, which can further reduce the time you need to solve problems.
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Notes
- 1.
The many-level checks are basically individual inspections, checks, or audits that are conducted by more than one person individually. The checks are comprised of individual items that may have been created over time that have been recognized to create problems with the product or process being reviewed. These checks can range from observations for the proper tools, methods, and materials being used in an assembly operation. They can also include inspection, safety, and other considerations that are not included here.
- 2.
This is verified by the calculation of 8 divided by 252, which equals 0.031746. The 8 is from the total acceptable extremes combination of five good and five bad. The 252 is the total number of ways that the two samples can be listed without duplication or overlap. Therefore, the total of (1.0 – 0.031746) x 100 equals 96.8254%. That shows 95%+ confidence and that there is a significant difference between groups. There are only eight ways to get a total of seven or more extremes with a comparison of two groups of five.
- 3.
Refer to Appendix A for more comprehensive calculations and discussion.
- 4.
An outlier is a point of data that falls far away from the mean of the distribution from which it came. It is an anomaly in that it is significantly distant from the rest of the samples from which it came. In this case, the outlier could mingle with a sample from the other part distribution if they were not sufficiently far from each other.
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© 2014 Ralph R. Pawlak
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Pawlak, R.R. (2014). Choose and Use Analysis Tools. In: Industrial Problem Solving Simplified. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4302-6578-8_7
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DOI: https://doi.org/10.1007/978-1-4302-6578-8_7
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