ISO 22514-8:2014 プロセス管理における統計的手法—機能とパフォーマンス—パート8：マルチステート生産プロセスのマシンパフォーマンス | ページ 6

3.1

production tool

machine or production machinery performing all the operations necessary for production, from delivered supplies through product deliverable

3.2

process

set of interrelated or interacting activities which transforms inputs into outputs

Note 1 to entry: Inputs to a process are generally outputs of other processes.

Note 2 to entry: Processes in an organization are generally planned and carried out under controlled conditions to add value.

Note 3 to entry: A process where the conformity of the resulting product cannot be readily or economically verified is frequently referred to as a “special process”.

Note 4 to entry: This set includes all the factor resources necessary: production tools, labour, operating procedures, maintenance, etc.

[SOURCE:ISO 9000:2005, 3.4.1]

3.3

equipment (or tools)

interchangeable component of a production tool for producing different products, and which cannot be considered a wear-out component

3.4

process operation

step in the production process leading to a final or intermediate product status

3.5

toleranced characteristic of the product

quantitative characteristic of the product, and for which the upper specification limits (ISO 3534-2) and/or lower specification limits (ISO 3534-2) are prescribed

3.6

dispersion interval (or dispersion of a characteristic)

interval within which all items are produced

Note 1 to entry: Where the dispersion interval is estimated based on statistical methods, it is estimated based on its reference interval (ISO 3534-2).

Note 2 to entry: Any one process carries as many dispersion intervals as it does characteristics produced. For example, a product presenting four different characteristics, i.e. length, width, height, and weight, is produced including systematic (controllable) and random (uncontrollable) sources of variation by a single production tool in a single operation. This operation is thus associated with four different dispersion intervals.

3.7

intrinsic dispersion interval (or instantaneous dispersion)

observable dispersion interval for a characteristic observed on produced items over a period during which the process implementation parameters have not varied: same operator, same method, same equipment, same batch of homogeneous raw materials, same temperature, etc.

Note 1 to entry: The underlying statistical distribution is called intrinsic (or instantaneous) distribution.

Note 2 to entry: In the event of drift in a process setting (such as drift caused by tool wear-out), it is common practice to include this drift in the production dispersion instead of integrating it into the estimate of intrinsic dispersion.

Note 3 to entry: This intrinsic dispersion interval is also called instantaneous dispersion because it affects production at a given point in time.

Note 4 to entry: Any one process operation carries as many intrinsic dispersion intervals as it does characteristics produced. A product presenting four different characteristics, i.e. length, width, height, and weight, is produced in a single operation. This operation is thus associated with four different intrinsic dispersion intervals.

Note 5 to entry: The intrinsic dispersion interval is same as natural or inherent spread.

Note 6 to entry: In some industries, the intrinsic dispersion interval is called “production tool dispersion”; the production tool featuring machine and its equipment.

3.8

intrinsic factor

internal condition to the production process and involved in the intrinsic dispersion interval, and which has different aspects, each produced item comes across only one of these aspects

3.9

process state

specific configuration of the full set of intrinsic factors ここで, each intrinsic factor takes one of its states

Note 1 to entry: One process state generates one statistical distribution. The statistical distributions tied to the different states of the process can be similar or different.

Note 2 to entry: For a simple process that only produces one part at a time using single equipment and a single quality of inputs, there will, a priori, be only one state. From the moment that several parts are produced simultaneously under different conditions (different equipment, different positions in the batch load, etc.), there will, a priori, be different states.

Note 3 to entry: If the production process simultaneously handles a set of p parts, then there can be p different states.

3.10

multi-state (production) process

3.11

local intrinsic dispersion (interval)

3.12

global intrinsic dispersion (interval)

observable intrinsic dispersion interval when pooling the results of the combination of different process states

3.13

production dispersion (interval)

observable dispersion interval for a characteristic, observed on produced items over a typical representative period during which the different process implementation parameters may have varied

Note 2 to entry: The underlying statistical distribution is called production distribution.

Note 3 to entry: The production timeframe observed is not standardized. Depending on how the capability indices are used, this time frame is set either internally by the product manufacturer or contractually by agreement between supplier and customer.

3.14

measurement uncertainty

parameter, associated with the result of a measurement, that characterizes the dispersion of the values that could reasonably be attributed to the measurand (quantity-of-interest)

Note 1 to entry: The parameter defining an interval bounding the result of a measurement and that can be expected to encompass a large fraction of the distribution of values that could reasonably be attributed to the measurand, is called enlarged uncertainty.

[SOURCE:adapted to the VIM]

Note 2 to entry: This part of ISO 22514 works on the basis that enlarged uncertainty is evaluated at a 95,44 % confidence level, as is common practice.