Measuring and Controlling Quality Part 1
Lectures one and two will consist of two parts which will focus on the basic concepts of statistical process control.
You will also describe ways to measure quality, evaluate measurement systems, assess conformance to specifications, and use statistical process control to monitor manufacturing and service processes. Part I of this lecture will focus on Measurement for Quality Control, Measurement System Evaluation and Process Capability Measurement.
Measurement for Quality Control
The concept of control was introduced in a previous lecture. Quality control seeks to ensure that processes perform in a stable and predictable fashion by identifying when corrective action is needed. Good data and measurement systems are the basis for effective quality control as well as for quality improvement.
Measurement, Measures and indicators
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.
Measurement System Evaluation
Process Capability Measurement
To define Measurement as 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. Good measures and indicators must be: simple, measurable, actionable, related (to customer requirements and to each other), and timely.
To learn that 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 the term defect is commonly used, and in service applications, the term error describes a nonconformance. A nonconforming unit of work is one that has one or more nonconformances.
To establish that 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.
To identify metrics used in SPC, which fall into the categories of attributes or variables. Variable measurements are concerned with the degree of conformance to specifications, where attribute data counts the presence or absence of a characteristic. Collecting attribute data is usually easier than collecting variable data because the assessment can usually be done more quickly by a simple visual inspection or count, whereas variable data require the use of some type of measuring instrument.
To introduce the concept of effects 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).
To explore the concept of the cost of quality (COQ) as 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, is aided in budgeting and cost control, and can use it 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.
To define metrology--the science of measurement – 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, including characteristics such as: accuracy, precision, repeatability or equipment variation, reproducibility or operator variation, calibration and traceability.
To appreciate that 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.
To learn that 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.
Lecture Summary:
This lecture describes concepts of statistics, statistical thinking, statistical methodology, sampling, experimental design, and process capability. You should be encouraged to take a “big picture” perspective on this framework, rather than the approach of: “How do I get the right answer?”