This paper explains how you can use the SHEWHART procedure in SAS/QC software to make the following enhancements: display multiple sets of control limits that visualize the evolution of the process, visualize stratified variation, explore within-subgroup variation with box-and-whisker plots, and add information that improves the interpretability of the chart.
The RAREEVENTS procedure, which is new in SAS/QC 14.1, produces rare events charts. This paper presents an overview of PROC RAREEVENTS and illustrates how you can use rare events charts to improve health care quality.
This paper reviews the features of PROC OPTEX and shows them in action using examples from field trials and food science experimentation. PROC OPTEX is a useful tool for all these situations, doing the designing and freeing the scientist to think about the food and the biology.
This paper is about AFT models and it guides you through building AFT(accelerated failure time) models that predict time to failure.
This paper describes how you can use PROC RELIABILITY to estimate and compare MCFs.
This paper explains how statistical thinking and statistical process monitoring, which have been practiced in manufacturing for the past thirty years, are proving valuable for process improvement in business environments that range from health care to financial services. Basic examples drawn from real scenarios introduce the statistical concepts and show how to get started with SAS/QC software.
This paper, using an example from social media sentiment analysis, illustrates how the MVPMODEL, MVPMONITOR, and MVPDIAGNOSE procedures work together and demonstrates the power of the methods for discovering and diagnosing unusual variation.
This paper explains how statistical thinking and statistical process monitoring, which have been practiced in manufacturing for the past thirty years, are proving valuable for process improvement in business environments that range from health care to financial services. Basic examples drawn from real scenarios introduce the statistical concepts and show how to get started with SAS/QC software.
This paper provides examples that explain the use of SAS statistical software to analyze health care data with u charts, p charts, control charts for individual measurements, methods for discovering trends over time, basic forecasting methods, comparative histograms, analysis of means for rates and proportions, and model-based adjustments of mortality rates.
Attribute control charts have discrete jumps in the quantities plotted on the charts, which means that the chart designer has only a discrete set of unique control limits to choose from when designing a chart. These charts have a small set of in-control Average Run Lengths (ARLs) from which to determine the appropriate control scheme. In a chart with randomized control limits the operational control limit in an epoch is determined by a random choice from among a set of control limits. The resulting control chart will then have a predetermined in-control ARL. These charts can be thought of as ones with optimal ARL properties. SAS programs for designing and operating these charts will be provided.
This paper describes two methods for the analysis of degradation of product performance or material properties over time. The first uses the SAS/QC RELIABILITY procedure with pseudo-failure times to predict a given percentile of the failure time distribution, and the second uses the SAS/STAT NLMIXED procedure to fit concave degradation models, and some SAS macros to estimate the failure distribution.
This paper will describe the data warehouse/decision support/data mining system that we have developed to improve disk drive manufacturing yields in the IBM Storage Technology Division.
The SAS system is used as the basis of the EDAS – the Engineering Data Analysis System - an application developed for engineers at Motorola’s Advanced Products Research and Development Laboratory. SAS products discussed in this paper include SAS/AF, QC, GRAPH, STAT, and others. The intended audience is anyone interested in semiconductor data analysis.
This paper discusses some of the emerging business problems in quality improvement and how the field has evolved. The presentation covers what information is delivered with a data warehouse and how that information is delivered, steps are laid out for building a Quality Data Warehouse, and finally, some important additional points on exploiting the Quality Data Warehouse are covered.
This paper discusses The RELIABILITY procedure, a recent addition to SAS/QC software. It provides tools for reliability and survival data analysis as well as for recurrence data analysis.
In this paper we consider the use of modern methods for analyzing time-to-failure data that can be implemented using SAS software.
This paper introduces an algorithm for searching for D-optimal experimental designs in the presence of certain kinds of non-exchangeability-in particular, when there are mixed covariates associated with units and/or when the units have a non-trivial covariance structure; this algorithm extends and improves on the one of Cook and Nachtsheim (1989) for finding optimal block designs.
This paper demonstrates how to solve the problem of finding saturated second-order two-level designs by applying the OPTEX procedure of SAS/QC software.
Computer methods are used to explore saturated designs which provide for optimal estimation of main effects and interactions between two-level factors. A series of designs is thus discovered, related to a known series but better for k > 6. Also, a relationship is discovered between two different classes designs which should be fruitful for future research.
This paper illustrates the use of SAS software to analyze health care data with u charts, p charts, control charts for individual measurements, analysis of means for rates and proportions, simultaneous confidence intervals for proportions, and basic forecasting methods.
This paper demonstrates the use of SAS procedures for statistical modeling in conjunction with the SHEWHART procedure.
Papers are in Portable Document Format (PDF) and can be viewed with the free Adobe Acrobat Reader.
Powerpoint presentations and SAS programs can be downloaded as zip files.