ISO 8000-66:2021

Data quality - Part 66: Data quality management: Assessment indicators for data processing in manufacturing operations

This document specifies assessment indicators to support the assessment of organizational process maturity for data quality management in the context of manufacturing operations management as specified by IEC 62264‑1. The following are within scope of this document: - assessment indicators that are work products generated by data processing (as specified by ISO 8000‑61) and, thus, enable rating of process performance, a process attribute specified by ISO/IEC 33020; - the role played by each work product in the processes of manufacturing operations management; - the connection of each work product to the outcomes of the processes of manufacturing operations management. The following are outside the scope of this document: - assessment indicators for any of the other process attributes specified by ISO/IEC 33020; - methods or procedures to measure process capability.

Qualité des données — Partie 66: Gestion de la qualité des données : Indicateurs d'évaluation pour le traitement des données dans les opérations de fabrication

General Information

• Status: Published
• Publication Date: 04-Oct-2021
• ICS: 25.040.40 - Industrial process measurement and control
• Technical Committee: ISO/TC 184/SC 4 - Industrial data
• Drafting Committee: ISO/TC 184/SC 4/WG 13 - Industrial Data Quality
• Current Stage: 6060 - International Standard published
• Start Date: 05-Oct-2021
• Due Date: 18-Oct-2021
• Completion Date: 05-Oct-2021

Overview

ISO 8000-66:2021 - "Data quality - Part 66: Data quality management: Assessment indicators for data processing in manufacturing operations" specifies assessment indicators to support organizational process maturity evaluation for data quality management in manufacturing. It focuses on assessment indicators that are work products produced by data processing (as defined in ISO 8000‑61), the role each work product plays in manufacturing operations management (per IEC 62264‑1), and how those work products connect to process outcomes. The standard does not define measurement methods for process capability or address other process attributes beyond process performance.

Key technical topics and requirements

• Assessment indicators as work products: Indicators are defined as the outputs of data processing that enable rating of process performance (aligned with ISO/IEC 33020 process attributes).
• Mapping to manufacturing processes: Links work products to specific manufacturing operations activities (e.g., production scheduling, production control, material and energy control, inventory control, quality assurance, maintenance management - see Clause 5).
• Process maturity assessment context: Intended for implementations that conform to the ISO 8000‑61 data quality process reference model and assessed according to ISO 8000‑62.
• Scope limitations: Excludes indicators for process attributes other than performance and excludes procedures for measuring process capability.

Practical applications

• Improve data governance and operational decision‑making by identifying which data products indicate process performance in manufacturing.
• Support digital transformation and integration projects by clarifying the role of data outputs (work products) in MES, ERP and control systems.
• Provide a structured basis for internal or external process maturity assessments focused on data quality management in manufacturing environments.
• Help prioritize data quality improvements that directly affect manufacturing outcomes such as throughput, quality assurance, maintenance effectiveness and inventory accuracy.

Who should use this standard

• Data quality managers and data governance teams in manufacturing organizations
• Manufacturing operations managers, production planners and process engineers
• IT/OT architects, MES/ERP integrators and system implementers
• Auditors and consultants conducting maturity assessments or advising on data quality management

Related standards

• ISO 8000‑2 (Vocabulary)
• ISO 8000‑61 (Data quality management: Process reference model)
• ISO 8000‑62 (Organizational process maturity assessment)
• IEC 62264‑1 (Enterprise‑control system integration - Models and terminology)
• ISO/IEC 33020 (Process assessment attributes)

By using ISO 8000‑66:2021 together with the referenced ISO 8000 and IEC standards, organizations can more precisely assess and improve the quality of manufacturing data that drives operational performance.

Standards Content (Sample)

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
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on
the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below
or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: [phone]
Email: [e-mail]
Website: www.iso.org
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
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
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
constitute an endorsement.
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 supports the application
of ISO 8000-62 to determine the process maturity of data quality management in manufacturing
organizations. This support is provided by specifying assessment indicators for data processing in
manufacturing operations management specified by IEC 62264-1.
Organizations can use this document on its own or in conjunction with other parts of the ISO 8000
series.
This document supports activities that affect:
— one or more information systems;
— data flows within the organization and with external organizations;
— any phase of the data life cycle.
By implementing parts of the ISO 8000 series, an organization achieves the following benefits:
— establishing reliable foundations for digital transformation;
— recognizing how data in digital form has become a fundamental asset class that organizations rely
on to deliver value;
— securing evidence-based trustworthiness of data and information for all stakeholders;
— creating portable data that protects against the loss of intellectual property and that is reusable
across the organization and applications;
— achieving traceability of data back to original sources;
— ensuring all stakeholders work with common understanding of explicit data requirements.
ISO/TS 8000-1 provides a detailed explanation of the structure and scope of the whole ISO 8000 series.
Annex A contains an identifier that unambiguously identifies this document in an open information
system.
vi
INTERNATIONAL STANDARD ISO 8000-66:2021(E)
Data quality —
Part 66:
Data quality management: Assessment indicators for data
processing in manufacturing operations
1 Scope
This document specifies assessment indicators to support the assessment of organizational process
maturity for data quality management in the context of manufacturing operations management as
specified by IEC 62264-1.
The following are within scope of this document:
— assessment indicators that are work products generated by data processing (as specified by
ISO 8000-61) and, thus, enable rating of process performance, a process attribute specified by ISO/
IEC 33020;
— the role played by each work product in the processes of manufacturing operations management;
— the connection of each work product to the outcomes of the processes of manufacturing operations
management.
The following are outside the scope of this document:
— assessment indicators for any of the other process attributes specified by ISO/IEC 33020;
— methods or procedures to measure process capability.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO 8000-2, Data quality — Part 2: Vocabulary
ISO 8000-61, Data quality — Part 61: Data quality management: Process reference model
ISO 8000-62, Data quality — Part 62: Data quality management: Organizational process maturity
assessment: Application of standards relating to process assessment
IEC 62264-1, Enterprise-control system integration — Part 1: Models and terminology
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 8000-2 and IEC 62264-1 apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
NOTE The term "product" appears in both ISO 8000-2 and IEC 62264-1 but with different definitions. Both
definitions provide, however, a useful and relevant explanation of the meaning of the term.
4 Process maturity assessment
Given the fundamental role of data in decision making, any type of organization can deliver significant
benefits through data quality management. This delivery is sustainable, however, only when the
organization understands and continually improves existing capability to perform data quality
management. This understanding is the primary outcome of process maturity assessment.
This document applies to process maturity assessment in the specific context of (see Figure 1):
— implementations of the data processing as specified by the process reference model for data quality
management in ISO 8000-61;
— implementations of the data processing as part of manufacturing operations management as
specified by the functional model in IEC 62264-1 and as identified by this document (see Clause 5).
In this context, the process maturity assessment shall:
— conform to ISO 8000-62;
— assess implementations of data processing that conforms to ISO 8000-61;
— perform process attribute rating of process performance using the work products specified by
Clause 7.
NOTE 1 Process performance is a process attribute specified by ISO/IEC 33020 (see Clause 6).
NOTE 2 These work products are assessment indicators that conform to the requirements of ISO/IEC 33004.
NOTE 3 The work products are information inputs to and outputs from individual processes of manufacturing
operations management.
This document harmonizes the different ways of describing processes in IEC 62264-1, ISO 8000-61 and
ISO/IEC 33063 (see Annex B).
5 Manufacturing operations management
5.1 Scope of manufacturing operations management
IEC 62264-1 specifies manufacturing operations management to cover the categories of:
— production operations management;
— inventory operations management;
— quality operations management;
— maintenance operations management.
Within these categories are eight functions of manufacturing operations management (see Table 1).
These functions are connected by a series of information flows (see Figures 2 to 4).
NOTE See ISO/IEC 19505-1 for details on the notation in this diagram.
Figure 1 — Key concepts covered by this document and related standards
This document provides details on these eight functions, each one with the following process
descriptions:
— production scheduling (see 5.2);
— production control — process support engineering (see 5.3);
— production control — production operations control (see 5.4);
— production control — production operations planning (see 5.5);
— material and energy control (see 5.6);
— product inventory control (see 5.7);
— quality assurance (see 5.8);
— maintenance management (see 5.9).
Table 1 — Categories and constituent functions of manufacturing operations management as
specified by IEC 62264-1
Category Function
Production operations management Production scheduling (A11)
Production control: process support engineering (A12)
Production control: production operations control (A13)
Production control: production operations planning (A14)
Inventory operations management Material and energy control (A3)
Product inventory control (A2)
Quality operations management Quality assurance (A5)
Maintenance operations management Maintenance management (A4)
NOTE  The identifier in brackets (i.e. “A11”) is the node number of the corresponding function in the model of manufacturing
operations management represented by Figures 2 to 4.
Each process description consists of the following information:
— process label: identifying the process;
NOTE 1 The process label is also known as the process name.
— process purpose: describing the benefit that the process delivers to the executing organization or
other stakeholders;
— process outcomes: identifying the information generated or modified by the function;
NOTE 2 These outcomes are specified by IEC 62264-1.
— process activities: identifying at a generic level how the function delivers the outcomes.
NOTE 3 This content builds on the constituent detailed functions specified by IEC 62264-1.
NOTE 4 This approach to process descriptions is consistent with ISO 8000-61.
NOTE See ISO/IEC/IEEE 31320-1 for details on the notation in this diagram.
Figure 2 — A-0 context diagram for manufacturing operations management
NOTE See ISO/IEC/IEEE 31320-1 for details on the notation in this diagram.
Figure 3 — A0 diagram for prepare and perform manufacturing operations management
NOTE See ISO/IEC/IEEE 31320-1 for details on the notation in this diagram.
Figure 4 — A1 diagram for perform production scheduling and control
5.2 Production scheduling
5.2.1 Purpose of production scheduling
The purpose of production scheduling is to arrange, control and optimize work and workloads in
manufacturing operations. This scheduling is the basis for allocating plant and machinery resources,
planning human resources and production processes and purchasing materials.
5.2.2 Outcomes of production scheduling
The process generates the following information items:
a) production schedule;
b) actual production versus planned production;
c) production capacity and resource availability;
d) current order status.
5.2.3 Production scheduling activities
The following are the production scheduling activities:
— Determine production schedule: The production process is planned by allocating available resources
(e.g. plant, personnel, materials, tools, energy, environment) to meet production orders.
— Identify long-term raw material requirements: Identify the purchasing sources between the main
and subsidiary materials, establish the purchasing schedule considering the quantity, unit, source,
price and inventory status.
— Determine pack-out schedule for end products: The final assembly schedule is possibly only for
final mixing, cutting and packaging regardless of assembly. Develop a schedule for the production
of the finished product to manufacture the product to the specific order of the customer in the
environment of custom-made or custom-assembled. Due to limited production capacity and
availability of materials, the process schedule is established after a customer order is received.
— Determine available product for sales: Identify the quantity of products that can be shipped by
identifying inventory status and order status and finished products according to the production
schedule.
5.3 Production control — Process support engineering
5.3.1 Purpose of production control — Process support engineering
Process support engineering ensures the availability and readiness of production processes that are
effective and efficient.
5.3.2 Outcomes of production control — Process support engineering
The process generates the following information items:
a) minor equipment and process modifications;
NOTE 1 These modifications can include new design drawings.
b) instructions on how to handle equipment;
NOTE 2 These instructions can include standard operating procedures.
c) instructions on how to make products;
NOTE 3 These instructions include production rules and the standard materials, equipment, and other
resources used.
d) material safety data sheets;
e) instructions on how to install equipment;
NOTE 4 This equipment can include vendor equipment.
f) environmental and safety operating limits and constraints;
g) engineering standards and online operating instructions.
NOTE 5 These standards cover process equipment design techniques and process operational methods.
5.3.3 Production control activities — Process support engineering
The following are the process support engineering activities:
— Issue requests for modification or maintenance: Request for equipment repairs, process changes
and equipment maintenance are issued.
— Coordinate maintenance and engineering functions: Execute maintenance to facilitate engineering
functions of the equipment.
— Provide technical standards and methods to operations and maintenance functions: Technical
standards and methods appropriate to operational processes and maintenance functions are
provided.
— Follow up on equipment and process performance: Analyse the results of equipment usage and
determine performance of equipment suitable for production. It also analyses process performance
to identify improvements.
— Provide technical support to operators: Addressing technical problems raised by operators
regarding machinery, product quality and operational safety. Technology supports are provided in
a timely manner to meet technical requirements.
— Follow up on technological developments: Prioritize technology development and ensure that
technological capacity leads to practical performance.
5.4 Production control — Production operations control
5.4.1 Purpose of production control — Production operations control
Production operations control ensures that production meets requirements (including demand
requirements) and that other processes are informed about the current status of production.
5.4.2 Outcomes of production control — Production operations control
The process generates the following information items:
a) status of production requests;
b) production data;
NOTE 1 This can include data to calculate production costs and performance.
c) process data;
NOTE 2 This can include equipment performance feedback.
d) status of resources;
e) status of maintenance work order requests;
f) requests for maintenance;
g) diagnostic and self-test results;
h) process history;
i) requests for support from process support engineering;
j) requests for analysis of material.
5.4.3 Production control activities — Production operations control
The following are the production operations control activities:
— Produce product according to schedule and specifications: The production of a product conforms
with the applicable production schedule and the product conforms with applicable specifications.
— Report production, process and resource information: Identify the inf
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