Quality In ISO 9001 Standards

The Eight Dimensions of Quality

1. Performance

2. Reliability

3. Durability

4. Serviceability

5. Aesthetics

6. Features

7. Perceived Quality

8. Conformance to Standards

Terminology

Every product possesses a number of elements that jointly describe what the user or consumer thinks of us as quality. These parameters are often called quality characteristics. Sometimes these are called critical-to-quality (CTQ) characteristics. Quality characteristics may be of several types:

1. Physical: length, weight, voltage, viscosity

2. Sensory: taste, appearance, color

3. Time Orientation: reliablility, durability, serviceablity.

Since variability can only be described in statistical terms, statistical methods play a central role in quality improvement efforts. In the application of statistical methods to quality engineering, it is fairly typical to classify data on quality characteristics as either attributes or variables data. Variables data are usually continuous measurements, such as length, voltage, or viscosity. Attributes data, on the other hand, are usually discrete data, often taking the form of counts. We will describe statistical-based quality engineering tools for dealing with both types of data.

The Eight Dimensions of Quality1. Performance2. Reliability3. Durability4. Serviceability5. Aesthetics6. Features7. Perceived Quality8. Conformance to StandardsTerminologyEvery product possesses a number of elements that jointly describe what the user or consumer thinks of us as quality. These parameters are often called quality characteristics. Sometimes these are called critical-to-quality (CTQ) characteristics. Quality characteristics may be of several types:1. Physical: length, weight, voltage, viscosity2. Sensory: taste, appearance, color3. Time Orientation: reliablility, durability, serviceablity.Since variability can only be described in statistical terms, statistical methods play a central role in quality improvement efforts. In the application of statistical methods to quality engineering, it is fairly typical to classify data on quality characteristics as either attributes or variables data. Variables data are usually continuous measurements, such as length, voltage, or viscosity. Attributes data, on the other hand, are usually discrete data, often taking the form of counts. We will describe statistical-based quality engineering tools for dealing with both types of data.