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在制造业中从人工智能中释放价值(英).pdf
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在制造业中从人工智能中释放价值(英).pdf
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Unlocking Value from
Artificial Intelligence
in Manufacturing
WHITE PAPER
DECEMBER 2022
In collaboration with MEXT Technology Center
Contents
Foreword
Executive summary
Introduction
1 Unlocking value in manufacturing through AI
2 Shedding light on common barriers to industrial AI adoption
3 A collection of AI applications in manufacturing
4 A step-by-step approach to implementing scalable industrial AI applications
Conclusion
Contributors
Endnotes
3
4
5
6
8
11
17
21
22
25
Cover: Jian Fan, Getty Images – Inside: Getty Images
© 2022 World Economic Forum. All rights
reserved. No part of this publication may
be reproduced or transmitted in any form
or by any means, including photocopying
and recording, or by any information
storage and retrieval system.
Disclaimer
This document is published by the World
Economic Forum as a contribution to a
project, insight area or interaction. The
findings, interpretations and conclusions
expressed herein are a result of a
collaborative process facilitated and
endorsed by the World Economic Forum
but whose results do not necessarily
represent the views of the World Economic
Forum, nor the entirety of its Members,
Partners or other stakeholders.
Unlocking Value from Artificial Intelligence in Manufacturing 2
Foreword
Türkiye has established itself as a key global player
in advanced manufacturing and aims to boost
its position through Fourth Industrial Revolution
technologies. In recent decades, the country has
made significant efforts to position itself as a global
innovation hub, excelling in developing state-of-the-
art technologies in ground-breaking companies in
various fields. Artificial intelligence (AI) technology
applications are part of this effort. In principle, AI
could unlock more than $13 trillion in the global
economy and boost GDP by 2% per year.
1
However, companies struggle to tap into the value
that AI applications can create.
This paper seeks to uncover the hidden potential of
AI in the manufacturing sector and the respective
end-to-end systems by providing practical use
cases and critical enablers to help harness its
potential. Coupled with the energy crisis and
material shortages facing the world, manufacturing
players need to go beyond traditional operating
methods to drive efficiency and sustainability.
The twin challenges of technological progress
and socio-political distress call for new forms
of cooperation that respond to heightened
demand for localization while recognizing the
drivers of connectivity that shape global impact.
Acknowledging this, the Centre for the Fourth
Industrial Revolution in Türkiye – mandated by the
Ministry of Industry and Technology and established
by the Turkish Employers’ Association of Metal
Industries (MESS) – joined the World Economic
Forum’s Centre for the Fourth Industrial Revolution
Network, the foremost platform helping leaders
anticipate emerging technologies and drive their
inclusive and sustainable adoption. The network links
on-the-ground experience and action with global
network-based collaboration, learning and scaling.
This white paper is an output of the ongoing
partnership between the Forum’s Platform for
Shaping the Future of Advanced Manufacturing and
Value Chains and Platform for Shaping the Future
of Technology Governance: Artificial Intelligence
and Machine Learning, the Centre for the Fourth
Industrial Revolution Affiliate in Türkiye and MESS.
It highlights case studies from organizations
on the impact, feasibility and scalability of AI in
manufacturing. It identifies several opportunities and
lessons from the community on how to increase
operational efficiency, sustainability and workforce
engagement in manufacturing and value chains by
using AI.
We hope this report will provide decision-makers
with a better understanding of how to unlock the
untapped potential of industrial artificial intelligence
(AI). We look forward to collaborating with you to
deploy these technologies responsibly.
Unlocking Value from
Artificial Intelligence
in Manufacturing
December 2022
Özgür Burak Akkol
Chairman, Turkish Employers’
Association of Metal Industries
Jeremy Jurgens
Managing Director,
World Economic Forum
Unlocking Value from Artificial Intelligence in Manufacturing 3
Executive summary
Recent global developments and an ever-growing
list of shocks and disruptions have put further
strain on already shaken global value chains.
The complexity of current challenges impacting
manufacturing and value chains calls for the need
to go beyond the traditional means of driving
productivity to uncover the next wave of value for
businesses, the workforce and the environment.
Artificial intelligence (AI) is a crucial enabler of
industry transformation, opening new ways to
address business problems and unlock innovation
while driving operational performance, sustainability
and inclusion. Even though the impact of AI
applications on manufacturing processes is known,
the full opportunity from their deployment is still to
be uncovered due to a number of organizational
and technical roadblocks.
Recognizing this need, the Centre for the Fourth
Industrial Revolution Türkiye, together with the
World Economic Forum’s Platform for Shaping
the Future of Advanced Manufacturing and Value
Chains and Platform for Shaping the Future of
Technology Governance: Artificial Intelligence and
Machine Learning, convened industry, technology
and academic experts to shed light on these
challenges and propose a step-by-step approach
to overcome them. The consultations revealed six
main challenges hindering the adoption and scaling
of AI applications in manufacturing:
1. A mismatch between AI capabilities and
operational needs
2. The absence of a strategic approach and
leadership communication
3. Insufficient skills at the intersection of AI and
operations
4. Data availability and the absence of a data
governance structure
5. A lack of explainable AI models in manufacturing
6. Significant customization efforts across
manufacturing use cases
The consultations show that leading manufacturers
have successfully overcome the challenges
mentioned above, implementing a variety of AI
applications and achieving a positive impact
on operational performance, sustainability and
workforce engagement, mainly in six areas: health
and safety, quality, maintenance, production
processes, the supply chain, and energy
management.
While opportunities enabled by AI in manufacturing
are promising and attracting many leaders,
organizations are looking for a common framework
that outlines how to implement AI solutions and
ensure a successful return on investment.
Based on the consultations, this white paper
presents one step-by-step process as an example
of how it is possible to overcome barriers, using
the AI Navigator
2
developed by the INC Invention
Center as a reference:
Phase 0: Initiation to build the fundamentals –
strategy, data and workforce
Phase 1: Ideation to identify potential use cases and
conduct a pre-selection
Phase 2: Assessment to select use cases and
identify priorities via gap analysis
Phase 3: Feasibility to complete all required tests
and studies
Phase 4: Implementation, which requires iteration
and piloting using agile project management
Moving forward, the World Economic Forum and
the Centre for the Fourth Industrial Revolution
Türkiye will continue to work closely with
stakeholders in the Centre for the Fourth Industrial
Revolution Network and across industries to
accelerate the journey to capture value from AI
in manufacturing globally. It will offer the Turkish
Employers’ Association of Metal Industries (MESS)
Technology Centre as a unique testing and
collaboration system for businesses to pilot new
AI applications and foster a collaborative approach
among a diverse group of stakeholders to ensure
the right AI capabilities are built in manufacturing
and rolled out worldwide.
Unlocking Value from Artificial Intelligence in Manufacturing 4
Introduction
Companies across value chains are now facing
an energy crisis and material and key component
shortages, even as they are still recovering from and
adapting to COVID-19 impacts. The complexity of
the challenges impacting operations calls for the
need to go beyond the traditional means of driving
productivity to uncover the next wave of value and
address sustainability and workforce challenges.
Artificial intelligence (AI) can enable a new era in the
digital transformation journey, offering tremendous
potential to transform industries to gain greater
efficiency, sustainability and workforce engagement
by generating new insights from large amounts of
data. However, despite this promising value creation
potential, the deployment of AI in manufacturing
and value chains is still below expected levels.
Based on a global survey conducted over the last
four years of more than 3,000 companies across
industries and geographies, a growing number of
companies recognize the business imperative to
improve their AI competencies:
– 70% of respondents understand how AI can
generate business value
– 59% have an AI strategy in place
– 57% affirm that their companies are piloting or
deploying AI.
Despite these trends, only 1 in 10 companies
believe they generate significant financial benefits
with AI.
3
While manufacturers acknowledge the importance
and urgency of embedding AI in their processes
and while leading companies have already
internalized it in their business processes, many
are becoming disillusioned with their efforts to
capture value from it and lag in developing the right
AI capabilities.
Understanding the purpose and role of AI is key to
solving manufacturing challenges. With a problem-
oriented approach, AI efforts can be linked to
clear business targets, giving business units and
business functions a joint interest in making the
transformation successful.
4
This white paper sheds light on the benefits that can
be achieved through industrial AI and the successful
AI applications implemented across industries,
lessons learned and tangible impacts. Consultations
conducted with the multistakeholder initiative
community find that industrial AI helps people work
in a smarter, safer and more efficient way. However,
to unlock its full potential, companies require an
understanding of current barriers to adoption and a
structured approach to overcome them. Therefore,
this paper also presents one example of a step-by-
step guide to successfully implementing scalable
industrial AI use cases.
Unlocking Value from Artificial Intelligence in Manufacturing 5
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