ISO 8000-66:2021

INTERNATIONAL ISO
STANDARD 8000-66
First edition
2021-10
Data quality —
Part 66:
Data quality management: Assessment
indicators for data processing in
manufacturing operations
Reference number
© ISO 2021
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Published in Switzerland
ii
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Process maturity assessment . 2
5 Manufacturing operations management . 2
5.1 Scope of manufacturing operations management . 2
5.2 Production scheduling . 6
5.2.1 Purpose of production scheduling. 6
5.2.2 Outcomes of production scheduling . 6
5.2.3 Production scheduling activities . 7
5.3 Production control — Process support engineering . 7
5.3.1 Purpose of production control — Process support engineering . 7
5.3.2 Outcomes of production control — Process support engineering . 7
5.3.3 Production control activities — Process support engineering . 8
5.4 Production control — Production operations control . 8
5.4.1 Purpose of production control — Production operations control. 8
5.4.2 Outcomes of production control — Production operations control . 8
5.4.3 Production control activities — Production operations control . 9
5.5 Production control — Production operations planning. 9
5.5.1 Purpose of production control — Production operations planning . 9
5.5.2 Outcomes of production control — Production operations planning . 9
5.5.3 Production control activities — Production operations planning . 9
5.6 Material and energy control . 10
5.6.1 Purpose of material and energy control . 10
5.6.2 Outcomes of material and energy control . 10
5.6.3 Material and energy control activities. 10
5.7 Product inventory control . 10
5.7.1 Purpose of product inventory control . 10
5.7.2 Outcomes of product inventory control . 10
5.7.3 Product inventory control activities . 11
5.8 Quality assurance . 11
5.8.1 Purpose of quality assurance . 11
5.8.2 Outcomes of quality assurance. 11
5.8.3 Quality assurance activities . 11
5.9 Maintenance management . 12
5.9.1 Purpose of maintenance management .12
5.9.2 Outcomes of maintenance management .12
5.9.3 Maintenance management activities .12
6 Assessing process capability.13
7 Work products .15
Annex A (informative) Document identification .19
Annex B (informative) Process description structure comparison .20
Annex C (informative) Work product list .21
Bibliography .23
iii
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
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ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
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For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and
expressions related to conformity assessment, as well as information about ISO's adherence to
the World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT), see
www.iso.org/iso/foreword.html.
This document was prepared by Technical Committee ISO/TC 184, Automation systems and integration,
Subcommittee SC 4, Industrial data.
A list of all parts in the ISO 8000 series can be found on the ISO website.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html.
iv
Introduction
Digital data delivers value by enhancing all aspects of organizational performance, including:
— operational effectiveness and efficiency;
— safety;
— reputation with customers and the wider public;
— compliance with statutory regulations;
— consumer costs, revenues and stock prices.
The influence on performance originates from data being the formalized representation of information.
This information enables organizations to make reliable decisions. This decision making can be
performed by human beings directly and also by automated data processing including artificial
intelligence systems.
Through widespread adoption of digital computing and associated communication technologies,
organizations become dependent on digital data. This dependency amplifies the negative consequences
of the lack of quality in this data. These consequences are the decrease of organizational performance.
The biggest impact of digital data comes from two key factors:
— the data having a structure that reflects the nature of the subject matter;
— the data also being computer processable (machine readable) rather than just being for a person to
read and understand.
ISO 9000 explains that quality is not an abstract concept of absolute perfection. Quality is actually the
conformance of characteristics to requirements and, thus, any item of data can be of high quality for
one use but not for another use that has differing requirements.
EXAMPLE 1 When storing start times for meetings, a calendar application requires less precision than a
control system would for storing the times at which to activate a propulsion unit during a spaceflight.
The nature of digital data is fundamental to establishing requirements that are relevant to the specific
decisions that are made by each organization.
EXAMPLE 2 ISO/TS 8000-1 identifies that data has syntactic (format), semantic (meaning) and pragmatic
(usefulness) characteristics.
To support the delivery of high-quality data, the ISO 8000 series addresses:
— data governance, data quality management and maturity assessment;
EXAMPLE 3 ISO 8000-61 specifies a process reference model for data quality management.
— creating and applying requirements for data and information;
EXAMPLE 4 ISO 8000-110 specifies how to exchange characteristic data that is master data.
— monitoring and measuring data and information quality;
EXAMPLE 5 ISO 8000-8 specifies approaches to measuring data and information quality.
— improving data and, consequently, information quality;
EXAMPLE 6 ISO/TS 8000-81 specifies an approach to data profiling, which identifies opportunities to
improve data quality.
— issues that are specific to the type of content in a data set.
v
EXAMPLE 7 ISO/TS 8000-311 specifies how to address quality considerations for product shape data.
Data quality management covers all aspects of data processing, including creating, collecting, storing,
maintaining, transferring, exploiting and presenting data to deliver information.
Effective data quality management is systemic and systematic, requiring an understanding of the
root causes of data quality issues. This understanding is the basis for not just correcting existing
nonconformities but also implementing solutions that prevent future reoccurrence of those
nonconformities.
EXAMPLE 8 If a data set includes dates in multiple formats including “yyyy-mm-dd”, “mm-dd-yy” and “dd-mm-
yy”, then data cleansing can correct the consistency of the values. Such cleansing requires additional information,
however, to resolve ambiguous entries (such as, “04-05-20”) and cannot address any process issues and people
issues, including training, that have caused the inconsistency.
As a contribution to this overall capability of the ISO 8000 series, this document s
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