Process:

-> DEF: Any collection of activities to achieve some results, typically creating added value for the customer

• INDUSTRIAL PROCESS: “any process that comes in physical contact with the hardware or software that will be delivered to an external customer, up to the point the product is packaged”
• BUSINESS or ADMINISTRATIVE PROCESS: all service processes and processes supporting the industrial ones (billing, payroll, etc.)

-> Most processes (e.g., purchasing or product design) are cross-functional, spanning various functions areas and organizational charts

📌Customers/users are 5 times more likely to abandon a company for its poor business processes than for its poor product (Harrington, 1991).

Process Monitoring:

-> OBJ: check for the stability of the ouptut over time.

• Is the SPC: Satistical Process Control
• v=v*: controllable parameters, parameters locked at a target level
• d= uncontrollable factors

Measurement System Performance – Taxonomy:

• TRUENESS: difference between the average of repeated measurements and the true value of the measured feature (if the difference exists: systematic error or bias)
• PRECISION: ability of the measurement system to replicate the reading of the same item

MEASUREMENT TRUENESS: closeness of agreement between the average of an infinite number of replicate measured quantity values and a reference quantity value.

• Is not a quantity and can not be expressed numerically, but measures for closeness of agreement are given in ISO 5725
• Is inversely related to systematic measurement error, but is not related t random measurmenet error
• Measurement accuracy should not be used for measurement and vice versa.

MEASUREMENT ACCURACY: closeness of agreement between a measured quantity value and a true quantity value of a measurand.

• Is not a quantity and is not given a numerical quantity value. Is said to be more accurate when offers a smaller measurement error.
• Should not be used for measurement trueness and shoudn’t be used as measurmenet precision.

RESOLUTION: smallest change in a quantity being measured that casuses a perceptible change in the corresponding indication.

• Can depend on: noise (internal or external), friction, quantity being measured.

MEASUREMENT PRECISION: closeness of agreement between indications or measured quantity values obtained by replicate measurements on the same or similar objects nder specified conditions.

• Usually expessed numerically by measures of imprecision, such a standard deviation, variance or coefficient of variation under the specified conditions of measurment.
• Repeatability conditions of measurment, intermediate precision conditions of measurement or reproducibility conditions of measurement.
• Used to define measurement repeatability , intermediata

Gauge R&R (Repeatibility & Reproducibility):

• REPEATIBILITY: dispersion of measurements of the same measurand, when measurements are acquired in the same conditions (the same method, the same operator, the same instrument, the same place, the same usage conditions, measurements taken at short interval time)
• REPRODUCIBILITY: measures the dispersion when one or more of the usage conditions are changing.

-> R&R: study is required to trust the measurement instrument.

Quality Data Modelling:

Assumptions > Reference  Model:

-> In basic statistics and traditional Statistical Process Monitoring

-> Assuming: Normality distributed data Independence Constant variance -> Distribution is stable overtime (always a normal distribution)

:Normaly distributed data (many different causes of variability, none of them dominant) : independence (iid: idependent and randomly distributed)

Unstable:	Stable:	Unstable but predictable:

Appropriate Model:

Assumptions	Hypothesis Test (to check the assumption)	Remedy in case of violation
“Independence” (random pattern)	Runs test Bartlett’s test LBQ’s	Gapping Batching (Linear) regression Time Series (ARIMA)
Normal Distribution	Normality test	Transform Data