Statistical process control (SPC) concerns the use of statistical techniques and/or statistical or stochastic control

algorithms to achieve one or more of the following objectives:

a) to increase knowledge about a process;

b) to steer a process to behave in the desired way;

c) to reduce variation of final-product parameters, or in other ways improve performance of a process.

These guidelines give the elements for implementing an SPC system to achieve these objectives. The common

economic objective of statistical process control is to increase good process outputs produced for a given amount

of resource inputs.

NOTE 1 SPC operates most efficiently by controlling variation of a process parameter or an in-process product parameter

that is correlated with a final-product parameter; and/or by increasing the process's robustness against this variation. A

supplier's final-product parameter may be a process parameter to the next downstream supplier's process.

NOTE 2 Although SPC is concerned with manufactured goods, it is also applicable to processes producing services or

transactions (for example, those involving data, communications, software, or movement of materials).

This part of ISO 11462 specifies SPC system guidelines for use

_ when a supplier's capability to reduce variation in processes associated with design or production needs to be

proven or improved; or

_ when a supplier is beginning SPC implementation to achieve such capability.

These guidelines are not intended for contractual, regulatory or certification use.