IEC TR 63283-5:2024
(Main)Industrial-process measurement, control and automation – Smart manufacturing – Part 5: Market and innovation trends analysis
Industrial-process measurement, control and automation – Smart manufacturing – Part 5: Market and innovation trends analysis
IEC TR 63283-5:2024 describes the market and innovation trend analysis affecting smart manufacturing (SM). The market and innovation trends will influence the evolution of smart manufacturing and it will be important to have good insights on these trends. Specific aspects of the market trends are the evolution of the business cases that is assumed to highlight new supplier chain models, new revenue streams, new customer services, and/or new customer segments.
The document will address the following topics:
• Market watch: Identify the important, likely, and/or disruptive market trends (e.g. mass customization) from an end-to-end perspective, which impact smart manufacturing topics/aspects. This includes the end-user, producers, supply chain, regulators, etc.
• Business model watch: Identify the new business model trends from an end-to-end perspective, which impact smart manufacturing.
• Technological watch: Identify the important, likely, and/or disruptive innovations (AI chipsets, 6G, quantum computing, etc.) describing the impacted smart manufacturing topics/aspects; this topic will focus on those technologies that are still under development but is assumed to influence (or is assumed to be influenced by) smart manufacturing.
There are many more new trends which are used in SM. In this document, only some frequently discussed trends are presented. Some technologies are considered to have priority according to their maturity.
This work will focus on how they can be used in SM.
General Information
Standards Content (Sample)
IEC TR 63283-5 ®
Edition 1.0 2024-11
TECHNICAL
REPORT
Industrial-process measurement, control and automation – Smart manufacturing –
Part 5: Market and innovation trends analysis
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IEC TR 63283-5 ®
Edition 1.0 2024-11
TECHNICAL
REPORT
Industrial-process measurement, control and automation – Smart manufacturing –
Part 5: Market and innovation trends analysis
INTERNATIONAL
ELECTROTECHNICAL
COMMISSION
ICS 25.040.40 ISBN 978-2-8327-0022-8
– 2 – IEC TR 63283-5:2024 © IEC 2024
CONTENTS
FOREWORD . 4
INTRODUCTION . 6
1 Scope . 7
2 Normative references . 7
3 Terms, definitions, abbreviated terms and acronyms . 7
3.1 Terms and definitions . 8
3.2 Abbreviated terms and acronyms . 9
4 Smart manufacturing trend analysis . 11
4.1 Trend analysis template . 11
4.2 Market watch . 12
4.2.1 General . 12
4.2.2 Mass customization . 12
4.2.3 Value based service along the life of an asset . 14
4.2.4 Artificial intelligence in whatever form of usage . 16
4.2.5 Distribution of analysed information (edge versus cloud) . 18
4.2.6 Collaborative safety (Safety 2.0) . 25
4.2.7 Digital factory . 29
4.2.8 Zero-defect manufacturing . 30
4.3 Business model watch . 35
4.3.1 General . 35
4.3.2 Platform business models . 35
4.3.3 Data driven business models . 39
4.3.4 Service-driven and performance-based business models . 44
4.4 Technology watch . 45
4.4.1 General . 45
4.4.2 6G . 45
4.4.3 Quantum computing/networking . 48
4.4.4 AI chipsets/Tools . 51
4.4.5 5G fixed networks . 54
4.4.6 Semantic interoperability . 56
5 Summary . 63
Bibliography . 64
Figure 1 – Business context of "Mass customization" . 12
Figure 2 – Business context of value-based services for production resources. 14
Figure 3 – Business context of "Artificial Intelligence" . 16
Figure 4 – Digital platforms for the industrial world orchestrate applications across IoT
devices, edge, and cloud . 18
Figure 5 – Real time risk assessment and control . 25
Figure 6 – Digital twin operating in parallel with the physical world . 29
Figure 7 – ZDM trend development based on research outcomes 1987-2018 . 31
Figure 8 – Value added processes in platform ecosystems . 35
Figure 9 – Value added processes in the context of a brokerage platform . 36
Figure 10 – Value added processes in the context of an IIoT platform . 37
Figure 11 – Value added processes in the context of an edge management system . 38
Figure 12 – Value added processes in the context of a cloud platform . 39
Figure 13 – Potential value from data and analytics . 40
Figure 14 – Data and analytics transformation steps . 41
Figure 15 – Data driven business model – value add (example industry goods) . 42
Figure 16 – 6G Key features . 46
Figure 17 – Heterogeneous network . 46
Figure 18 – AI industrial structure and technology stack . 51
Figure 19 – Overview of AI chip related technologies . 52
Figure 20 – Defining AI, PwC broad definition AI . 54
Figure 21 – Evolution of fixed networks . 55
Figure 22 – Different levels of interoperability . 56
Figure 23 – Semantic interoperability . 57
Figure 24 – Semantic web Cake. 58
Figure 25 – Typical response of traditional companies to unplanned events . 59
Figure 26 – Typical response of agile companies to unplanned events. 60
Figure 27 – The McKinsey digital compass maps industry 4.0 applications to the 8
main value drivers. 61
Figure 28 – Strategic path for future common OT and IT standardization for semantical
interoperability . 62
– 4 – IEC TR 63283-5:2024 © IEC 2024
INTERNATIONAL ELECTROTECHNICAL COMMISSION
____________
INDUSTRIAL-PROCESS MEASUREMENT, CONTROL
AND AUTOMATION – SMART MANUFACTURING –
Part 5: Market and innovation trends analysis
FOREWORD
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IEC TR 63283-5 has been prepared by IEC technical committee 65: Industrial-process
measurement, control and automation. It is a Technical Report.
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