Samenvatting
Samenvatting Managing and Improving Quality (E_IBK3_MIQ)
- Instelling
- Vrije Universiteit Amsterdam (VU)
Samenvatting van de hoofdstukken uit het boek aangevuld door de hoorcolleges.
[Meer zien]Voorbeeld 4 van de 99 pagina's
Voorbeeld 4 van de 99 pagina's
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Hoorcollege 1Reading Chapter 1
Titel Introduction to Quality
What is quality?
Quality is a multifaceted entity.
A subjective term for which each person or sector has its own definition.
Traditional view of Quality, “meet the requirements of the user”.
Fit for use
Quality of design (Variations in grades or levels of Quality are intentional) [translate all of the expectations
into the product].
Quality of conformance (How well the product conforms to the specifications required by the design) [how
well are these expectations incorporated in the end product?].
The traditional view of quality has become associated more with conformance aspect of quality than with
design.
Less focus on the customer, more on “conformance-to-specification”.
Modern view of quality
Quality is inversely proportional to variability. Kwaliteit is omgekeerd evenredig aan variabiliteit.
High variability means lower quality.
Figure 1.2: sample comparison. USA has quite a large variability around the target value, very much scattered. The
Japanese one is very much centered, less variability.
In quality measuring you need to take a sample of the whole population.
Hoorcollege 1 1
, Customer doesn’t see the mean of the process, s/he only sees the variability around the target that you have not
removed - Jack Welch (retired CEO - GE).
What is quality improvement?
How did the Japanese company succeed?
Systematic and effective use of quality methods.
Quality Improvement is the reduction of variability in processes and products.
Excessive variability in process performance often results in waste.
Quality Improvement is the reduction of waste.
What about service industries? How do you define waste there?
Quality terminology
Quality / Critical-To-Quality Characteristics (CTQ)
Every product possesses a number of elements that jointly describe what the user or consumer thinks of as
quality
Physical: length, weight, voltage, viscosity
Sensory: taste, appearance, color
Time Orientation: reliability, durability, serviceability
Quality Engineering
Set of operational, managerial, and technical activities.
To ensure nominal value for quality characteristics.
To ensure minimum variability around nominal values.
Variability, units are not identical!
Sources for variability (material, performance, equipment, operator, ..)
Boeing 787
Was planned to take-off in 2008
First commercial flight in 2011
56 airlines were disappointed (total order of $144 billion)
What went wrong:
Outsourcing engineering and construction before the product was fully
designed and tested.
$2 billion cost
Hoorcollege 1 2
, Statistical methods.
Data on quality characteristics:
Variables data, usually continuous measurements, such as length, voltage, or viscosity.
Attributes data, usually discrete data, often taking the form of counts.
Specifications
A reference to evaluate quality characteristics.
For a product: desired measurements for quality characteristics.
In the service industries: maximum amount of time to process an order or to provide a particular service.
(Cycle Time)
Nominal / Target Value: A value of a measurement that corresponds to the desired value for that quality
characteristic.
Usually bounded by a range.
Upper Specification Limit (USL): The largest allowable value for a quality characteristic.
Lower Specification Limit (LSL): The smallest allowable value for a quality characteristic.
Nonconforming Product: Products that fail to meet one or more of their specifications.
Nonconformity: Specific type of failure.
Defective, Defects
Defective: a nonconforming product.
Nonconformities that affect the use of the product: defects.
Concurrent Engineering
A team approach to design, with different specialists working together with the product designer at the
earliest stages of the product design process.
Statistical methods
Statistical process control
Design of experiments
Acceptance-sampling
Hoorcollege 1 3
, Statistical Process Control (SPC)
Control chart: one of the primary techniques of statistical process control (SPC)
Classically, control charts are applied to the output variable(s) in a system
In some cases, they can be usefully applied to the inputs as well.
Design of experiments
To systematically vary the controllable input factors and determining the effect of these factors on the output
product parameters.
Off-line improvement technique (at early stage of production).
Leads to a model of the process.
Factorial design, in which factors are varied together in such a way that all possible combinations of factor
levels are tested.
Hoorcollege 1 4
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