Collaborative Knowledge Management Through Product Lifecycle: A Computational Perspective

295 Pages·2023·7.647 MB·English

by  Hongwei Wang, Gongzhuang Peng

Hongwei Wang
Gongzhuang Peng
Collaborative
Knowledge
Management
Through Product
Lifecycle
A Computational Perspective
Collaborative Knowledge Management Through
Product Lifecycle
·
Hongwei Wang Gongzhuang Peng
Collaborative Knowledge
Management Through
Product Lifecycle
A Computational Perspective
Hongwei Wang Gongzhuang Peng
ZJU-UIUC Joint Institute National Engineering Research Center for
Zhejiang University Advanced Rolling and Intelligent
Haining, Zhejiang, China Manufacturing
University of Science and Technology
Beijing
Beijing, China
ISBN 978-981-19-9625-2 ISBN 978-981-19-9626-9 (eBook)
https://doi.org/10.1007/978-981-19-9626-9
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature
Singapore Pte Ltd. 2023
This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether
the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse
of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and
transmission or information storage and retrieval, electronic adaptation, computer software, or by similar
or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors, and the editors are safe to assume that the advice and information in this book
are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or
the editors give a warranty, expressed or implied, with respect to the material contained herein or for any
errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional
claims in published maps and institutional affiliations.
This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd.
The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721,
Singapore
Preface
Over the past three decades, the manufacturing industry has developed very fast. On
the one hand, the complexity of modern products has been increasing in terms of
their structure, function, and technological requirements. These products, from the
small ones such as smart phones and integrated circuits to the big ones like electric
cars and high-performance aero-engines, have brought dramatic change to people’s
life. On the other hand, the severe competition across the global supply chain has
raised demanding requirements for manufacturing enterprises not only to reduce cost
and lead time but also to improve their capabilities of reacting to challenges through
the whole product lifecycle.
The diversified application of information technology (IT), without doubt, is a
major element in the innovation of the manufacturing industry. Since 1980s, there
have been great efforts, from both industry and academia, on developing effective
and efficient IT systems under the umbrella of computer-integrated manufacturing
to improve the management of data, technologies, and processes. Recently, as the
development of artificial intelligence (AI), there has been great interest in intelli-
gent manufacturing and the global intelligent manufacturing network has been a
new paradigm. The addressing of issues relative to the integrated and collaborative
nature of modern product development as well as the sustainable and intelligent
requirements has become a new trend of innovation in manufacturing. Specifically,
the integrated nature emphasizes the integration of multidisciplinary resources in
a distributed environment. The collaborative perspective concerns the collaborative
work of team members of multiple roles as well as the adaptation of models and
the interoperability between systems and platforms. The sustainability perspective
involves achieving the balance between the efficiency of manufacturing processes
and the constraints imposed on these processes in terms of sustainable concern. Last
but not the least, the intelligent perspective focuses on the development of intelligent
methods to effectively utilize information and knowledge in the product design and
manufacturing process so as to achieve swift and resilient response market needs.
In this context, we need to reconsider the development of effective IT and intelli-
gent methods to meet the new challenges mentioned above. In particular, there is a
v
vi Preface
great need of effective support for the management of product design and develop-
ment knowledge through the lifecycle. The previous methods for this support have
some drawbacks: (1) focusing on data without enough attention to model; (2) valuing
information but missing context; (3) valuing process but overlooking users; and (4)
focusing on query but overlooking interaction. This book precisely aims to provide
some insights into these drawbacks. Different from the previous ones on enterprise
knowledge management (KM) which are more focused on operation and innova-
tion management, this book has a specific focus on the collaborative nature of KM
from a particular computational perspective, i.e., addressing the interface between
IT and KM. The main reason for this unique perspective is that, as the development
of state-of-the-art technologies such as big data, industrial Internet of things (IoT)
and cloud computing, a huge amount of data has been generated. In this sense, the
effective support of KM throughout the product design and manufacturing process
should heavily rely upon this data, and thus there is an urgent need of research on the
computing power and algorithms useful for this purpose. Additionally, discovery of
knowledge from both the product data and the complex process, whereby this data is
generated, is also of highly importance for the next-generation KM systems. As such,
this book precisely covers case studies from the design and manufacturing process
of complex products and focuses on the computational issues such as knowledge
modeling, knowledge storage and retrieval, and knowledge reasoning and reuse.
The authors believe that this book is relevant to a wide range of readers such as the
students, researchers, and practitioners of intelligent manufacturing, advanced KM
systems, enterprise intelligent computing, and industrial applications of AI. More-
over, this topic of this book is highly interdisciplinary, and as such, it is suitable
for faculty and students from diversified disciplines such as computer and elec-
tronic engineering, mechanical and manufacturing engineering, automatic control,
and management science and engineering. This book covers topics like knowledge
modeling and reasoning—since knowledge is a key concept in education, the under-
graduates with interest on these topics can also refer to the methods detailed in this
book.
The authors would like to thank the help from the previous and current students—
they are Dr. Hao Qin, Mr. Yufei Zhang, Mr. Zixuan Wang, Mr. Haibo Wang, Miss. Qi
Li, and Miss. Mengxuan Li. The first author appreciates the help and support from
his former colleagues at both the University of Cambridge and the University of
Portsmouth. The authors are really grateful to the editors and officers from Springer
Nature who have been both so professional in handling the publication and so patient
while the publication process was delayed for various reasons. The authors also
would like to thank their families for their generous love, understanding, and support,
without which, it would not have been possible to complete this big work. This is the
first time that the authors make an effort to put their research work into a book, and
as such, there must be shortcomings and limitations. We hope that the readers would
understand and help us improve, and the authors will try our best to improve the work
Preface vii
in the future. Every exiting thing has a start—we wish that this publication be a great
start for more interesting and useful work on collaborative knowledge management.
Haining, China Hongwei Wang
Beijing, China Gongzhuang Peng
Acknowledgements This research is supported by the National Key R&D Program of China under
the grant number 2020YFB1707803, and the National Natural Science Foundation of China under
the grant number 61903031.
Contents
1 Knowledge Management Through Product Lifecycle .............. 1
1.1 The Role of Knowledge Management Through
Product Lifecycle ........................................... 3
1.1.1 Product Design Knowledge ............................ 3
1.1.2 Product Manufacturing Knowledge ..................... 8
1.1.3 Production Scheduling Knowledge ..................... 9
1.1.4 Assembly Knowledge ................................ 10
1.1.5 Diagnosis and Maintenance Knowledge ................. 12
1.2 The Essence of Knowledge and Its Relationships with Data
and Information ............................................ 13
1.3 The Forms and Characteristics of Different Kinds
of Knowledge .............................................. 16
1.3.1 Knowledge from Mechanism, Experience and Data ....... 17
1.3.2 Tacit and Explicit Knowledge .......................... 18
1.3.3 Product and Process Knowledge ........................ 19
1.4 The Variety of Knowledge Needs in the Modern Context ......... 23
1.5 Knowledge Management Methodologies ....................... 24
1.5.1 Knowledge Capture .................................. 27
1.5.2 Knowledge Representation ............................ 30
1.5.3 Knowledge Retrieval ................................. 32
1.5.4 Knowledge Reuse .................................... 32
1.6 Discussion ................................................ 35
References ..................................................... 36
2 The Collaborative Knowledge Management Paradigm ............. 39
2.1 The Need for Collaborative Knowledge Management ............ 39
2.1.1 Collaboration Between Multidisciplinary Engineers ....... 40
2.1.2 Collaboration of Lifecycle Activities .................... 41
2.1.3 Collaboration of Multi-source Knowledge Resources ...... 43
2.2 Collaborative Knowledge Management Architecture
and the Key Enabling Technologies ........................... 46
ix
x Contents
2.2.1 Integrated and Collaborative Knowledge Management
Architecture ......................................... 47
2.2.2 Enabling Technology for IKCM—Platform
Interoperability ...................................... 48
2.2.3 Enabling Technology for IKCM—Data Interoperability ... 49
2.2.4 Enabling Technology for IKCM—Integrated
Knowledge Representation Model ...................... 50
2.2.5 Enabling Technology for IKCM—Intelligent
Knowledge Service ................................... 50
2.3 Collaborative Knowledge Representation Model ................ 50
2.3.1 Construction of the Designer Network .................. 51
2.3.2 Construction of the Product Network ................... 52
2.3.3 Construction of the Issues Network ..................... 53
2.3.4 Construction of the Knowledge Resource Network ........ 54
2.3.5 Application ......................................... 55
2.4 Collaborative Knowledge Management in Intelligent Manufacturing 58
2.5 Discussion ................................................ 62
References ..................................................... 63
3 Representation and Modeling of Knowledge for Collaborative
Knowledge Management ........................................ 65
3.1 Background ............................................... 65
3.2 Knowledge Capture in the Collaborative Working Environment ... 66
3.2.1 Knowledge Mining from Text Using Deep Learning
Based Methods ...................................... 72
3.2.2 Knowledge Capture from CAD Models Based
on the Formal Description ............................. 76
3.2.3 Capture of Process Knowledge Based on the
RFBSE Model ....................................... 78
3.3 Collaborative Design Knowledge Modeling .................... 84
3.3.1 Multi-level Knowledge Representation Based
on the BOM Language ................................ 87
3.3.2 Project-Process-Activity (P2A) Knowledge Model ........ 91
3.3.3 RFBSE Knowledge Representation Model ............... 98
3.3.4 The C-RFBS Model .................................. 110
3.4 Discussion ................................................ 120
References ..................................................... 121
4 Collaborative Design Knowledge Retrieval ........................ 123
4.1 Overview .................................................. 123
4.2 Knowledge Retrieval Based on Keyword ....................... 124
4.2.1 Introduction to Information Retrieval ................... 124
4.2.2 Extracting Terms from Knowledge Models .............. 126
4.2.3 Quantifying Similarities and Ranking Retrieved Results ... 129
4.2.4 Implementation of a Keyword-Based Retrieval System .... 131
4.3 Retrieval of Structured Design Knowledge ..................... 137
Contents xi
4.3.1 Using the Feature Information of Nodes ................. 140
4.3.2 Returning Nodes Group as the Results .................. 140
4.3.3 Using Complex Queries ............................... 154
4.3.4 Implementation and Evaluation of the Retrieval
System with the Structured Information ................. 157
4.4 Towards Semantic Retrieval of Knowledge Model ............... 164
4.4.1 Extracting Concepts Categories Information ............. 165
4.4.2 Extracting Context Information ........................ 167
4.4.3 Utilisation of Semantic Information ..................... 173
4.4.4 Implementation and Evaluation ........................ 176
4.5 Discussion ................................................ 183
References ..................................................... 184
5 Collaborative Design Knowledge Reuse .......................... 187
5.1 Overview .................................................. 187
5.2 Collaborative Design Knowledge Retrieval ..................... 188
5.2.1 Product Design Knowledge Retrieval ................... 189
5.2.2 Event Knowledge Retrieval ............................ 191
5.3 Knowledge Recommendation ................................ 195
5.4 Collaborative Knowledge Reasoning .......................... 197
5.4.1 Case-Based Reasoning ................................ 197
5.4.2 Ontology-Based Reasoning ............................ 202
5.4.3 Collaborative Reasoning of Design Knowledge Based
on the Bayesian Approach ............................. 208
5.5 Knowledge-Assisted Decision Making ........................ 212
5.5.1 Knowledge Reasoning Based on the Context ............. 212
5.5.2 The Traditional Decision Support System and Its Limitation 215
5.5.3 Knowledge-Based Decision Support System ............. 216
5.5.4 Knowledge Reuse in the Collaborative Design Process .... 218
5.5.5 Case Study of Knowledge Reuse in the
Assembly Process .................................... 220
References ..................................................... 226
6 The Merging of Knowledge Management and New Information
Technologies ................................................... 229
6.1 Big Data Technology ....................................... 230
6.1.1 Overview of Big Data ................................ 230
6.1.2 Knowledge Management in Big Data ................... 232
6.1.3 Case Study .......................................... 235
6.2 Internet of Things (IoT) Technology ........................... 240
6.2.1 Overview of IoT ..................................... 240
6.2.2 Knowledge Management in IoT ........................ 243
6.2.3 Case Study .......................................... 246
6.3 Digital Twins .............................................. 251
6.3.1 Overview of Digital Twins ............................ 251
6.3.2 Knowledge Management in Digital Twins ............... 253