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College aantekeningen Managing and improving Quality (MIQ) (MIQ) (lecture notes)
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Lecture notes Managing and improving qualityYousef Ghiami
(Logistics and transport management masters)
Lecture 1 Introduction to quality (ch 1)
The more we invest in quality programs, the less costs there are in
waist and rework.
Dimensions of quality
There are 8 components or dimensions of quality.
In the service sector, there are 3 more components to consider
What is “Quality”?
• Quality is a multifaceted entity.
• A subjective term for which each person or sector has its own definition (The American Society for
Quality). Depending on the sector we are in, the quality is different. But it is all about meeting the
requirements.
• 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)
- Quality of conformance (How well the product conforms to the specifications required by
the design)
• 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
It is related to the variability. The more variability, the less quality you see in the operation/ product.
The target value in the US had a large standard deviation, because there were more transmissions. In
Japan there was less variability and therefore less variance.
1
,- Customer doesn’t see the mean of the process, (s) he only sees the variability around the target
that you have not removed.
What is quality improvement?
* How did the Japanese company succeed? -> Systematic and effective use of quality methods. Tried
to reduce variability as much as they can.
• 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? For example a bank, a loan not
processed well, it takes more time than needed. There could be variation in time.
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. It depends on what is applicable.
- Physical: length, weight, voltage, viscosity
- Sensory: taste, appearance, colour
- Time Orientation: reliability, durability, serviceability
• Quality Engineering
- Set of operational, managerial, and technical activities.
- To ensure nominal value for quality characteristics. (best value for that measure)
- To ensure minimum variability around nominal values.
• Variability, units are not identical!
- Sources for variability (material, performance, equipment, operator, ..)
- Example Boeing 787. It was the plan to take off in 2008, but in reality is was 2011. They had large
orders, 56 airlines were disappointed.
What went wrong: outsourcing engineering and construction before the product was fully designed
and tested. The designs did not match, the manufacturers had variation. Then the components had
to send back, which took a lot of time.
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. Number of failure
• 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
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,quality characteristic. It is almost impossible to obtain always, so there will be variation. So there is a
range, upper and lower specification.
• 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, to reduce the
variability
Statistical methods
There is normal (raw) input, and control inputs, but also uncontrollable inputs. Those uncontrollable
often cause variability. The problem is that they are difficult to tackle.
the output is compared with the reference, and then action is taken to either
rework or remove it.
1. 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
2. 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). Not on mass-
production, but on samples.
• 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.
3
, 3. Acceptance- sampling
* Inspection and classification of - A sample
of units, Randomly selected, From a larger
batch.
- you try to make a decision about a whole
batch (lot)
• Occurs at two points: Incoming raw
materials, or Components and final
production.
Modern quality assurance systems
- Less emphasis on acceptance-sampling, because it is very passive. The lot is already produced, the
whole lot is already made. With the other methods, you can make adjustments earlier in time, in
order to reduce the costs of rejection.
- Focuses more on spc and designed experiment
Quality engineering
The primary objective: systematic reduction of variability in the key
quality characteristics of a product.
Quality and productivity
• Producing high-quality products in the modern industrial environment is not easy.
• A significant aspect of the problem is the rapid evolution of technology.
• Too little attention is paid to achieving all dimensions of an optimal process: economy, efficiency,
productivity, and quality.
• Effective quality improvement can be instrumental in increasing productivity and reducing cost
Manufacturing example
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