Quality Progress

Analysis of product lifetime data generally requires fitting a suitable distribution to the data at hand. The fitted distribution is used to estimate quantities of interest, such as the fraction of product failing after various times in service and selected distribution percentiles (for example, the estimated time by which 1% of the product population is expected to fail). Disciplines Probability | Statistical Methodology Comments This article is published as Doganaksoy, N., Hahn, G.J., and Meeker, W.Q., (2020), Concerns in ID'ing a Suitable Distribution, Quality Progress, 53, December, 72–75. Posted with permission. This article is available at Iowa State University Digital Repository: https://lib.dr.iastate.edu/stat_las_pubs/327 447133415341545721157 47554975412752999495 345412132313154471334 47554975412752999495 345412132313154471334 47554975412752999495 345412132313154471334 47554975412752999495 345412132313154471334 47554975412752999495 345412132313154471334 Solving quality quandaries through statistics

Abstract Statistical significance (or hypothesis) tests, and the related concept of p-values, are popular tools in statistical data analysis. Unfortunately, the practical implications of statistical significance often turn out to be limited and are frequently misinterpreted and overstated, or even stated incorrectly.

The National Highway Traffic Safety Administration ( HTSA) in 2015 recalled 28 million vehicles equipped with Takata air bag due to inflators rupturing during deployment.' It was determined that moisture could penetrate the inflator canister and make the propellant more explosive over time. Disciplines Probability | Statistical Methodology | Statistical Models Comments This article is published as Doganaksoy, N., Hahn, G.J., and Meeker, W.Q., (2016), Identify and Act: Performing product life data analysis with unidentified subpopulations, Quality Progress, 49, December, 61–64. Posted with permission. This article is available at Iowa State University Digital Repository: https://lib.dr.iastate.edu/stat_las_pubs/323 HAHN AND WILLIAM Q. MEEKER

Last month, we considered four potential designs of varying sizes and a variety of their attributes for an engineering problem involving a screening design with seven factors. The engineer’s original request was to find a design with 14 runs that could estimate all of the main effects, as well as have some potential for finding important two-factor interactions and possibly curvature in the underlying surface. This assessment was that the proposed size of design was potentially a bit too ambitious for the experiment’s goals, so we explored three other competing designs that had slightly larger sizes but were able to improve several aspects of the design.

One of the common goals of running and analyzing a designed experiment is to find a location in the design space that optimizes the response of interest. Depending on the goal of the experiment, we may seek to maximize or minimize the response, or set the process to hit a particular target value. After the designed experiment, a response model is fitted and the optimal settings of the input factors are obtained based on the estimated response model. Furthermore, the suggested optimal settings of the input factors are then used in the production environment.

In many reliability evaluations, the units placed on life test are reduced-size versions of the actual product. This is often the result of practical limitations such as available test facilities. In the example the authors will consider, electrodes were used in an accelerated test to obtain time-to-failure information on dielectric insulation of generator armature bars that were four times as long as the test electrodes. The term "size" is used in a generic sense. In addition to length, it can, for example, also represent area or volume. In such situations, you must "upsize" the results of the statistical data analysis on the reducedsize test units to the full-size product. This column will cover a simple method to account for the effect of product size on reliability evaluations. These methods can be implemented using popular software packages such as JMP, Minitab and Weibull ++. Disciplines Statistical Methodology | Statistical Models Comments This article is published as Doganaksoy, N., Hahn, G.J., and Meeker, W.Q., (2015), Reliability Upsizing: How to adjust for size effect in product life data analysis, Quality Progress, 48, November, 54–57. Posted with permission. This article is available at Iowa State University Digital Repository: https://lib.dr.iastate.edu/stat_las_pubs/324 GERALD J. HAHN AND WILLIAM Q. MEEKER Reliability Upsizing How to adjust for size effect in product life data analysis IN MANY RELIABILITY evaluations, the units placed on life test are reduced-size versions of the actual product. This is often the result of practical limitations such as available test facilities. In the example we will consider, electrodes were used in an accelerated test to obtain tin1e-to-failure information on dielectric insulation of generator armature bars that were four times as long as the test electrodes. The term "size" is used in a generic sense. In addition to length, it can, for example, also represent area or volume. In such situations, you must "upsize" the results of the statistical data analysis on the reduced-size test units to the full-size product. This column will cover a simple method to account for the effect of product size on reliability evaluations. These methods can be implemented using popular software packages such as JMP, Minitab and

Effective presentation of statistical results to those with less statistical training, including managers and decision-makers requires planning, anticipation and thoughtful delivery. Here are several recommendations for effectively presenting statistical results.

Creating a Kaizen culture : align the organization, achieve breakthrough results, and sustain the gains

19世纪末,慈善家安德鲁·卡内基(Andrew Carnegie)捐款在美国建造了数千个图书馆.这些图书馆首次设立开架书库,允许读者(在美国统称读者为"patron",直译为"老主顾",也有"长期资助人"之意,体现了既亲近又恭敬的态度——译者注)进入自由浏览和借阅;而在此之前,大部分图书馆都是闭架书库,由馆员代为取书、归类.开架书库的设立让人们能在借阅前充分了解书中内容,极大提升了图书馆的服务质量.