Summary of Key Points and Terminology
Chapter 8 – Measuring and Controlling Quality
• Measurement is the act of collecting data to quantify the values of product, service, process, and other business metrics. Measures and indicators refer to the numerical results obtained from measurement. Many organizations use the acronym SMART to characterize good measures and indicators: simple, measurable, actionable, related (to customer requirements and to each other), and timely.
• A unit of work is the output of a process or an individual process step. A nonconformance is any defect or error associated with a unit of work. In manufacturing we often use the term defect, and in service applications, we generally use the term error to describe a nonconformance. A nonconforming unit of work is one that has one or more nonconformances.
• An attribute measurement characterizes the presence or absence of nonconformances in a unit of work, or the number of nonconformances in a unit of work. Attribute measurements often are collected by visual inspection and expressed as proportions and counts. Variable measurements apply to dimensional quantities such as length, weight, and time, or any value on a continuous scale of measurement.
• Throughput yield (TY) is the number of units that have no nonconformances. Rolled throughput yield (RTY) is the proportion of conforming units that results from a series of process steps.
• Defects per million opportunities (dpmo) = (Number of defects discovered)/opportunities for error × 1,000,000. In services, the term often used as an analogy to dpmo is errors per million opportunities (epmo).
• The cost of quality (COQ) is a way to translate quality problems into the language of upper management--money. Through the use of quality cost information, management identifies opportunities for quality improvement. Quality cost information also aids in budgeting and cost control and serves as a scoreboard to evaluate an organization’s success.
• Quality costs generally are categorized into prevention, appraisal, internal failure, and external failure costs. In manufacturing, such costs are typically product-oriented, while in services they are labor dependent.
• Metrology--the science of measurement – is defined broadly as the collection of people, equipment, facilities, methods, and procedures used to assure the correctness or adequacy of measurements, and is a vital part of global competitiveness.
• Accuracy is defined as the closeness of agreement between an observed value and an accepted reference value or standard. Precision is defined as the closeness of agreement between randomly selected individual measurements or results.
• Calibration is the process of verifying the capability and performance of an item of measuring and test equipment compared to traceable measurement standards. Measurements made using uncalibrated or inadequately calibrated equipment can lead to erroneous and costly decisions. Many government regulations and commercial contracts require regulated organizations or contractors to verify that the measurements they make are traceable to a reference standard.
• Repeatability, or equipment variation, is the variation in multiple measurements by an individual using the same instrument. Reproducibility, or operator variation, is the variation in the same measuring instrument when it is used by different individuals to measure the same parts, and indicates how robust the measuring process is to the operator and environmental conditions. Repeatability and reproducibility require a study of variation and can be addressed through statistical analysis.
• A repeatability and reproducibility (R&R) study is a study of variation in a measurement system using statistical analysis.
• Process capability is the range over which the natural variation of a process occurs as determined by the system of common causes; that is, what the process can achieve under stable conditions. The relationship between the natural variation and specifications is often quantified by a measure known as the process capability index, Cp.
• A process capability study is a carefully planned study designed to yield specific information about the performance of a process under specified operating conditions. Three types of studies are a peak performance study, process characterization study, and component variability study.
• Pre-control is a technique for monitoring process capability over time. It is particularly suited to machining applications, but should only be used when process capability is rather good.
• Statistical process control (SPC) is a methodology for monitoring a process to identify special causes of variation and signal the need to take corrective action when appropriate. When special causes are present, the process is deemed to be out of control. If the variation in the process is due to common causes alone, the process is said to be in statistical control. Histograms alone do not allow you to distinguish between common and special causes of variation.
• A control chart is simply a run chart to which two horizontal lines, called control limits are added: the upper control limit (UCL) and lower control limit (LCL). The process for constructing and using a control chart includes preparation, data collection, determination of trial control limits, analysis and interpretation, estimation of process capability using the control chart data, and use a problem-solving tool.
• A process is in control if no points are outside control limits; the number of points above and below the center line is about the same; the points seem to fall randomly above and below the center line; and most points (but not all) are near the center line, with only a few close to the control limits.
• Typical out-of-control conditions are represented by sudden shifts in the mean value, cycles, trends, hugging of the center line, hugging of the control limits, and instability.
• Control charts for variables data include: x- and R-charts;x - and s-charts; and individual and moving range charts. x - and s-charts are alternatives tox – and R-charts for larger sample sizes. The sample standard deviation provides a better indication of process variability than the range. Individuals charts are useful when every item can be inspected and when a long lead time exists for producing an item. Moving ranges are used to measure the variability in individuals charts.
• Charts for attributes include p-, np-, c- and u-charts. The np-chart is an alternative to the p-chart, and controls the number nonconforming for attributes data. Charts for defects include the c-chart and u-chart. The c-chart is used for constant sample size and the u-chart is used for variable sample size.
• In designing control charts, one must be concerned with how the sample data are taken, the sample size, the sampling frequency, and the location of the control limits. These factors influence the amount of useful information obtained from the charts, the ability to detect process changes, the potential for error, and the cost of application.
• ISO 9000places increase emphasis on the use of statistical methods. An ISO standard, 11462-1, has been designed to provide guidance for organizations wishing to use SPC to meet these requirements.
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