Intelligent Robots and Cobots E-Book
173,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Serie: Industry 5.0 Transformation Applications
- Sprache: Englisch
The book provides a comprehensive study of how new technological advances utilize robots and Cobots (collaborative robots that work safely alongside humans) to increase manufacturing efficiency.
Industry 5.0 focuses on using collaborative robots, or cobots, enabling users to design with greater freedom. This book, structured into 18 chapters and three sections - Fundamentals; Applications; and Challenges – reflect the current and emerging market trends that shape industrial growth. Each chapter explores how businesses incorporating hardware and software like AI, cognitive computing, blockchain, IIoT, and more—are capitalizing on these innovations to maintain a competitive edge. The research and development in the areas of technology has increased the cost-effectiveness and acceptance of these IoT-enabled devices in many different industries. Various sectors including manufacturing, healthcare, transportation, and agriculture sectors, have begun incorporating robots and cobots into their operations. They are aiming to increase their productivity, reduce the downtime of their equipment, and optimize resource utilization.
The individual chapters examine the following subjects:
Investigation on Deployment of Microservices for Swarm Intelligence of Collaborative Robots • Cobot-Aided System for Hydroponically Grown Plants • Low/No-Code Software Development of Cobots Using Advanced Graphical User Interface • Role of Cobots Over Industrial Robots in Industry 5.0 Activities • Cobot Collaboration in the Healthcare Industry • Robotic Arm for Industry Automation • Artificial Intelligence–Driven Cobots for Innovative Industry 5.0 Workforce • Comprehensive Analysis on Design, Working, and Manufacturing of Soft Robots • Workforce for Industry 5.0: The Work of Future and the Future of Work • Security Issues and Trends of Industrial Robots and Cobots • Aviation Bots for Decongesting Airports • Self-Contained Study and Evolution of Cobots in Intelligent Transportation Systems • Smart Architecture for Data Analytics in Collaborative Robots • Contribution of Blockchain Technology for the Cobot’s Cybersecurity Issues • Security Issues and Trends of Industrial Robots and Cobots • Cloud-Based Cobots for Industry 5.0: A Human-Centric Solution • Future Workforce for Industry 5.0.
Audience
The book’s primary audience is researchers and post-graduate students in robotics and cobots, industrial engineers, production and manufacturing engineers working on artificial intelligence and logistics.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 617
Veröffentlichungsjahr: 2024
Ähnliche
Table of Contents
Cover
Table of Contents
Series Page
Title Page
Copyright Page
Dedication Page
Preface
Acknowledgement
Part 1: Fundamentals
1 Cobots for Industry 5.0 Transformation
1.1 Introduction
1.2 Related Works
1.3 IoT for Industries
1.4 Issues with Cobots in Industry 5.0
1.5 Cobots in Industries
1.6 Automation and Cobots
1.7 Conclusion
References
2 Cobots as an Enabling Technique for Industry 5.0: A Conceptual Framework
2.1 Introduction
2.2 Industry 5.0 at a Glance
2.3 Industry 4.0 vs. Industry 5.0
2.4 Key Differences Between Robots and Cobots
2.5 Cobots as an Enabling Technique for Industry 5.0
2.6 The Contribution of Cobots Across Different Sectors
2.7 A Conceptual Cobot–Based Cyber-Physical System
2.8 The Risk and Security Issues with Respect to Cobots and Their Mitigations
2.9 Conclusion
References
3 Role of Cobots and Industrial Robots in Industry 5.0
3.1 Introduction
3.2 Role of Cobots
3.3 Programming Flowchart
3.4 Objectives of Research in Cobots
3.5 Capabilities and Features of Cobots for Industrial Applications
3.6 Industrial Developments and Different Degrees of Collaboration by Cobots
3.7 Cobot Applications
3.8 Challenges Faced by Cobots
3.9 Economic Impact of Cobots
3.10 Components Required
3.11 Integration of Cobots with Other Technologies
3.12 Discussion
3.13 Future Scope
3.14 Conclusion
References
4 The Evolution of Cobots in Intelligent Transportation Systems
4.1 Introduction
4.2 Uncovering Challenges in Intelligent Transportation System
4.3 The Role and Application of Cobots in Manufacturing and Logistics
4.4 Advancing Technologies Facilitating Robot and Cobot Operations in Intelligent Transportation Systems
4.5 Redefining Smart Transportation: The Synergy of Robotics, Cobots, and Predictive Analytics in ITS
4.6 A Comparative Analysis of Cobot and Predictive Protocols in Enhancing Safety and Sustainability in ITS
4.7 Advanced Analytics and Insights in Intelligent Transportation Systems
4.8 Conclusion
References
5 Low/No-Code Software Development of Cobots Using Advanced Graphical User Interface
5.1 Introduction
5.2 Cobots
5.3 Design of Low/No-Code–Based Cobot Development
5.4 Graphical User Interface Features
5.5 RPA vs. Low Code No Code in Cobot Development: “Low Code or RPA? Who Wins?”
5.6 Conclusion
5.7 Pros and Cons
References
6 Future Workforce for Industry 5.0
6.1 Introduction
6.2 Underlying Principles of Industry 5.0
6.3 Benefits for Workers in Industry 5.0
6.4 Challenges for Workers in Industry 5.0
6.5 Industry 5.0 and Employee Skills
6.6 Issues Related to Integration of Robots into Organizations
6.7 Considerations for Integration of Humans and Smart Machines in Industry 5.0
6.8 Reskilling and Upskilling the Workforce for Industry 5.0
6.9 Conclusion
References
Part 2: Applications
7 Intelligent Robots and Cobots: Concepts and Applications for Industry 5.0 Transformation
7.1 Introduction
7.2 Systematic Review
7.3 Concepts of Intelligent Robots and Cobots
7.4 Benefits of Intelligent Robots and Cobots
7.5 Application Areas
7.6 Challenges and Considerations
7.7 Future Prospects and Impacts
7.8 Conclusion
References
8 Artificial Intelligence–Driven Cobots for Innovative Industry 5.0 Workforce
8.1 Introduction
8.2 Literature Review
8.3 Revolution of Industry 5.0
8.4 Robotic Collaboration
8.5 Technological Issues with AI in the Cobot Age of Industry 5.0
8.6 Conclusion
References
9 Cobot Collaboration in the Healthcare Industry
9.1 Introduction
9.2 Cobots and Their Role
9.3 Impact of Cobot
9.4 The Challenges of Deploying Cobots at Scale
9.5 Cobot Background
9.6 Benefits of Cobots
9.7 The Need for Cobot Regulation Frameworks
9.8 The Hardware Sector will be Led by Robotic Arms and Sensors
9.9 Testing in Laboratories and Care for Patients Have a Lot of Possibilities
9.10 APAC Significant Gains
9.11 Human Factors and Errors
9.12 Robots Lending a Hand During the COVID-19 Outbreak
9.13 Universal Robots Cobots in Healthcare
9.14 What Role Can Cobots Play in Enhancing Healthcare Brand Experiences?
9.15 The Rise of the Health Companion
9.16 Cobots are Revolutionizing the Field of Medicine
9.17 Manufacturing of Medical Devices
9.18 Applications Outside of Healthcare
9.19 Next Steps of Cobot
9.20 Conclusion
References
10 Robotic Arm for Industry Automation
10.1 Introduction
10.2 Robotic Arm and Their Role in Industry
10.3 Desof Robotic Arm
10.4 Construction of Robotic Arm
10.5 Mechanism of a Robotic Arm
10.6 Working of Robotic Arm
10.7 How Robotic Arm are Automated
10.8 Industrial Automated Robotic Arm Application
10.9 Future Scope
10.10 Conclusion
References
11 Cloud-Based Cobots for Industry 5.0: A Human-Centric Solution
11.1 Introduction
11.2 Web 5.0
11.3 Applications and Benefits of Industry 5.0
11.4 Industry 5.0 Poses the Following Opportunities and Challenges
11.5 What Does Industry 5.0 Mean for your Strategy?
11.6 Understanding the Architecture and Key-Components of a Cloud-Based Cobot System
11.7 A Cloud-Based Cobot System Typically Consists of Several Key Components
11.8 Robot Collaboration Rather Than Competition
11.9 Web 5.0–Enabled Technologies and Cloud-Connected Robots
11.10 Security and Data Privacy Concerns in Cloud-Based Cobot Systems
11.11 6G Mobile Telecommunications
11.12 Case Studies of Successful Implementation of Cloud-Based Cobots in Industry 5.0
11.13 Challenges and Future Considerations for the Integration of Cloud-Based Cobots in Industry 5.0
11.14 Conclusion
References
12 Aviation Bots for Decongesting Airports
Abbreviations
12.1 Introduction
12.2 Aviation Resources
12.3 Understanding Real-Time Results
12.4 Resource Sharing and Sourcing
12.5 Current Aviation Bots and Their Limitations
12.6 Future Bots in Aviation
12.7 Conclusion
References
Part 3: Challenges
13 Cobot-Aided System for Hydroponically Grown Plants
13.1 Introduction
13.2 Hydroponic System
13.3 Cobot
13.4 Cobot-Aided Hydroponic System
13.5 iPONICS: IoT-Based Monitoring and Control System for Hydroponics Greenhouses
13.6 Existing Literature
13.7 IoT-Cobot Integrated System Architecture
13.8 Results
Conclusion
References
14 Data Analytics and Collaborative Robots in Smart Territory: Research Methodology, Applications, and Open Challenges
14.1 Introduction
14.2 Advancements in Data Analytics for Collaborative Robots
14.3 Challenges in Analysis of the Sensory Data
14.4 Research Gaps in Cobot-Enabled Data Analytics
14.5 Research Methodology in Cobot-Driven Data Analytics
14.6 Deployment of Tools and Techniques in Context-Aware Cobots
14.7 Provisions of Smart Architecture for Data Analytics in Collaborative Robots
14.8 Advanced Sensory-Based Framework for Big Data Analytics
14.9 Taxonomical Categorization of Collaborative Cobots
14.10 Use Cases of Cobots and Data Analytics
14.11 Futuristic Opportunities in Data Analytics for Collaborative Robots
14.12 Conclusion
References
15 Comprehensive Analysis on Design, Working, and Manufacturing of Soft Robots
15.1 Introduction
15.2 Design of Soft Robots
15.3 Working and Control of Soft Robots
15.4 Composite Soft Robots
15.5 Graphene Oxide Soft Robots
15.6 Application in Minimally Invasive Surgery
15.7 Challenges of Soft Robots
15.8 Future Scope and Development
15.9 Conclusion
References
16 Investigation on Deployment of Microservices for Swarm Intelligence of Collaborative Robots
16.1 Introduction
16.2 Related Work
16.3 Objective and Focus of the Work
16.4 Experimental Arrangement
16.5 Reliability Assessment
16.6 Overall Discussion
16.7 Conclusion
References
17 Security Issues and Trends of Industrial Robots and Cobots
17.1 Introduction
17.2 Cobots and Industrial Bots
17.3 Security of Cobots and Other Bots
17.4 Mitigation Strategies
17.5 Conclusions
References
18 Blockchain Technology for the Cobot’s Cybersecurity Issues
18.1 Introduction
18.2 Literature Review
18.3 Introduction to Cybersecurity
18.4 Cybersecurity Challenges
18.5 Introduction to Blockchain Technology
18.6 Security Features of Blockchain in Cobot’s Cybersecurity
18.7 Application Areas
18.8 Challenges and Considerations Cobot’s Cybersecurity
18.9 Conclusion
References
Index
Also of Interest
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Industry 4.0 versus Industry 5.0 from the perspective of robots and ...
Table 2.2 Key differences between robots and cobots.
Table 2.3 Cobot benefits mapped to industry 5.0 traits.
Table 2.4 Cobotic grippers and their application.
Chapter 4
Table 4.1 Enabling cobot-driven technologies of ITS.
Chapter 5
Table 5.1 Comparison between low/no code and RPA [10].
Chapter 7
Table 7.1 Modern society has reached its limits.
Chapter 11
Table 11.1 Comparative study between Web 1.0-3.0.
Chapter 12
Table 12.1 Phonetic pronunciation in aviation.
Table 12.2 NLP tools used in aviation.
Chapter 13
Table 13.1 Literature survey.
Table 13.2 The advantages of the proposed Cobot-aided hydroponic system over t...
Chapter 16
Table 16.1 Failure count range and frequency.
Table 16.2 Assessment of case III with ADT for test of normality.
Table 16.3 Overall observation.
List of Illustrations
Chapter 1
Figure 1.1 Relationships and dependencies related to automation using cobots....
Chapter 2
Figure 2.1 The industrial revolution over the years.
Figure 2.2 Primary benefits offered by cobots.
Figure 2.3 Application of cobots across different sectors.
Figure 2.4 Workflow strategy for designing a cobot.
Figure 2.5 The key attributes of a cobot for HMI.
Figure 2.6 A layered-wise conceptual framework for the design of a cobot.
Figure 2.7 Cobotic application risk evaluation using the Pilz Hazard Rating.
Chapter 3
Figure 3.1 Activities carried out by cobot arm.
Figure 3.2 Programming flowchart.
Figure 3.3 Components of a cobot.
Figure 3.4 Sensors in robots.
Figure 3.5 Industrial 4.0.
Figure 3.6 Different degrees of cobots.
Figure 3.7 Applications.
Figure 3.8 FANUC Cr15ia.
Figure 3.9 Challenges of cobots.
Figure 3.10 Economic impact.
Figure 3.11 Components required.
Chapter 4
Figure 4.1 MIR500 autonomous mobile robot with obstacle avoidance and navigati...
Figure 4.2 Functional diagram of an operational cobot.
Figure 4.3 Schematic representation of cobot.
Chapter 5
Figure 5.1 Timeline of cobots [20].
Figure 5.2 Growth of Cobots in terms of revenue [3].
Figure 5.3 Architectural design of COBOT using low/no-code software [4].
Figure 5.4 Working of GUI [6].
Chapter 7
Figure 7.1 Industry 5.0 technologies.
Figure 7.2 Block diagram for Industry 5.0.
Figure 7.3 Future of Industry 5.0 in society.
Figure 7.4 Frontiers | Redefining safety in light of human–robot interaction....
Figure 7.5 Robot learning toward smart robotic manufacturing.
Figure 7.6 Benefits of collaborative robots.
Figure 7.7 Enabling technologies and potential applications.
Figure 7.8 Industry 5.0 challenges and perspectives.
Figure 7.9 Industry 5.0 and Society 5.0.
Chapter 8
Figure 8.1 The five industrial revolutions.
Figure 8.2 Industrial evolution from 1.0 to 5.0 [2].
Figure 8.3 Robotics by 2050 [encompass.com].
Figure 8.4 Applications of Industry 5.0.
Chapter 9
Figure 9.1 Relationships and dependencies during cobot utilities [20].
Figure 9.2 Categorized work in cobot.
Chapter 10
Figure 10.1 Statistics of robotic arm.
Figure 10.2 Specification of a robotic arm.
Figure 10.3 Procedure of robotic arm working.
Figure 10.4 Robotic arm application.
Chapter 11
Figure 11.1 Industry growth with web versions (https://doi.org/10.1016/j.jii.2...
Figure 11.2 Applications and benefits of Industry 5.0.
Figure 11.3 Applications of Industry 5.0 (https://doi.org/10.1016/j.jii.2021.1...
Figure 11.4 Different dimensions of Industry 5.0 in the surrounding of human (...
Figure 11.5 Opportunities of Industry 5.0.
Figure 11.6 Challenges of Industry 5.0.
Figure 11.7 Industry 5.0 strategies.
Figure 11.8 Web 5.0–enabled technologies (https://doi.org/10.1016/j.jii.2021.1...
Chapter 12
Figure 12.1 airBot interface.
Figure 12.2 Interfacing with the airBot.
Figure 12.3 airBot showing SOP of Assam.
Figure 12.4 Mailbot interface.
Figure 12.5 Working of MailBot.
Figure 12.6 Response of MailBot.
Figure 12.7 MailBot response to user’s email.
Figure 12.8 COVID-19 guidelines of AAI, Assam.
Chapter 13
Figure 13.1 Types of hydroponic systems [1].
Figure 13.2 Types of Cobots [2].
Figure 13.3 Workflow of the proposed Cobot-aided hydroponic system.
Figure 13.4 The topology of iPONICS WSN [3].
Figure 13.5 Taxonomy for smart hydroponic systems [4].
Figure 13.6 Hydroponic IoT system architecture [5].
Figure 13.7 Architecture of the integrated system.
Figure 13.8 Flowchart of the algorithm used in the proposed system.
Figure 13.9 A pie chart of the responses to the question “How can this system ...
Chapter 14
Figure 14.1 Big data use cases over the past years.
Figure 14.2 Challenges in Internet-of-Things data analytics.
Figure 14.3 Data analytical tools in cobot-driven units.
Figure 14.4 Internet-of-Things architecture for big data analytics.
Figure 14.5 Comparison of search interests on Internet of Things–based Cobots ...
Figure 14.6 Various practical uses of data analytics for the Internet of Thing...
Chapter 15
Figure 15.1 Some design principles of soft robots.
Figure 15.2 Steps under designing of soft robots.
Figure 15.3 Working and control of soft robots: an illustration.
Figure 15.4 Comparison between various mechanical parameters of Cotton and Ray...
Figure 15.5 Challenges to soft robotics.
Figure 15.6 Methodologies in future development of soft robots.
Chapter 16
Figure 16.1 Block diagram of experimental arrangement.
Figure 16.2 Flowchart of assessment framework for evaluating the performance o...
Figure 16.3 NP plot for response time of the service.
Figure 16.4 HG plot for response time of the service.
Figure 16.5 Data plot of failure count for the service.
Figure 16.6 Normal CDF plot of observed fault count.
Chapter 17
Figure 17.1 IT security attack categorization.
Figure 17.2 Illustration of an attack tree for cobot attack.
Chapter 18
Figure 18.1 Advantages of cybersecurity.
Figure 18.2 Cybersecurity challenges in cobots.
Figure 18.3 Cybersecurity challenges in cobots.
Figure 18.4 Cybersecurity challenges in cobots.
Figure 18.5 Cybersecurity with blockchain.
Figure 18.6 Cybersecurity with blockchain.
Figure 18.7 Blockchain technology is going to improve the way cybersecurity.
Figure 18.8 Blockchain technology transforming cybersecurity.
Figure 18.9 Cobots’ multipurpose uses.
Figure 18.10 Cobot threat modeling life cycle.
Guide
Cover Page
Table of Contents
Series Page
Title Page
Copyright Page
Dedication Page
Preface
Acknowledgement
Begin Reading
Index
Also of Interest
WILEY END USER LICENSE AGREEMENT
Pages
ii
iii
iv
v
xxi
xxii
xxiii
xxiv
xxv
xxvii
1
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
401
402
403
404
405
406
407
408
409
Scrivener Publishing100 Cummings Center, Suite 541JBeverly, MA 01915-6106
Industry 5.0 Transformation Applications
Series Editors: Dr. S. Balamurugan (sbnbala@gmail) and Dr. Sheng-Lung Peng
The increase in technological advancements in the areas of artificial intelligence (AI), machine learning (ML) and data analytics has led to the next industrial revolution “Industry 5.0”. The transformation to Industry 5.0 collaborates human intelligence with machines to customize efficient solutions. This book series covers various subjects under promising application areas of Industry 5.0 such as smart manufacturing, intelligent traffic, cloud manufacturing, real-time productivity optimization, augmented reality and virtual reality, etc., as well as titles supporting technologies for promoting potential applications of Industry 5.0, such as collaborative robots (Cobots), edge computing, Internet of Everything, big data analytics, digital twins, 6G and beyond, blockchain, quantum computing and hyper-intelligent networks.
Publishers at ScrivenerMartin Scrivener ([email protected])Phillip Carmical ([email protected])
Intelligent Robots and Cobots
Industry 5.0 Applications
Edited by
V. Ramasamy
Dept. of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamilnadu, India
S. Balamurugan
Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India
and
Sheng-Lung Peng
Dept. of Creative Technologies and Product Design, National Taipei University of Business, Taiwan
This edition first published 2025 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA© 2025 Scrivener Publishing LLCFor more information about Scrivener publications please visit www.scrivenerpublishing.com.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.
Wiley Global Headquarters111 River Street, Hoboken, NJ 07030, USA
For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com.
Limit of Liability/Disclaimer of WarrantyWhile the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials, or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read.
Library of Congress Cataloging-in-Publication Data
ISBN 978-1-394-19817-7
Front cover image courtesy of Adobe FireflyCover design by Russell Richardson
The editorial team extends heartfelt dedication to their families—parents, spouses, and children—for their boundless support throughout the creation of this work. Additionally, the editors express sincere gratitude to their colleagues at their esteemed institution for their unwavering love, blessings, and encouragement. Finally, this book is respectfully dedicated to the entire research community, whose collective efforts continue to enrich our understanding of the world.
Preface
Advancements in science and technology are rapidly modernizing human lifestyles, especially in the 21st century. Industries are increasingly leveraging automation and cutting-edge technology to streamline tasks and meet evolving demands. Industry 1.0 was built on “water and steam,” Industry 2.0 harnessed “advanced electrical technology,” Industry 3.0 introduced automation through electronics and IT, and Industry 4.0 brought forth intelligent, autonomous robots. Now, Industry 5.0 focuses on using collaborative robots, or cobots, enabling users to design with greater freedom. To fully realize this potential, the IT industry must contribute more creatively to future industrial needs. This book, structured into 18 chapters and three sections - Fundamentals; Applications; and Challenges - reflects the current and emerging market trends that shape industrial growth. Each chapter explores how businesses incorporating hardware and software— like AI, cognitive computing, blockchain, IIoT, and more—are capitalizing on these innovations to maintain a competitive edge.
The research and development in the area of technology has increased the cost-effectiveness and acceptance of these IoT-enabled devices in many different industries. Various sectors including manufacturing, healthcare sectors, transportation sector, and the agriculture sector have begun incorporating robots and cobots into their operations. They are aiming to increase their productivity, reduce the downtime of their equipment, and optimize resource utilization. Chapter 1 offers a comprehensive review of how robots and cobots in the Industrial Internet of Things (IIoT) have the potential to revolutionize businesses, serving as a valuable resource for researchers interested in this transformative technology.
Chapter 2 focuses on the role of cobots in the successful implementation of Industry 5.0, examining their potential applications across various industries. It compares the functions of robots and cobots, highlighting their key differences, and introduces a conceptual cobot-based cyber-physical system. The chapter also investigates the explicit use of human intelligence in different applications and discusses the risks and security threats to cobots, along with mitigation techniques.
Chapter 3 explores how cobots offer the most significant value in scenarios where human proximity is essential. The direct interaction between humans and robots can be either the greatest advantage or limitation of collaborative systems, depending on its impact on human factors like ergonomics and psychological stress. Recent case studies have demonstrated the successful implementation of cobots across various industries, establishing their role in the Industry 5.0 revolution, especially in the health sector.
Chapter 4 offers a comprehensive exploration of the dynamic interaction between robots, cobots, and smart transportation, highlighting their transformative potential. The use of robotic technology, particularly collaborative robots, or cobots, has made a profound impact on the evolution of transportation within smart cities. It also examines various machine learning methods and IoT applications that enhance synergy within Intelligent Transportation Systems (ITS).
Chapter 5 explores low/no-code development, a method that enables application design and development using interactive graphical interfaces, eliminating the need for traditional coding. Low/No-code development platforms established a new paradigm in application development, offering ease of use around the environment that allowed non-IT professionals to build applications with very minimal or no coding experience. This approach allows non-IT professionals to create applications without writing a single line of code.
Chapter 6 provides critical insights into the benefits that Industry 5.0 offers to the workforce, as well as the challenges workers will face during this transition to the Fifth Industrial Revolution. It outlines the skills workers need to be equipped for Industry 5.0 and addresses the issues surrounding the integration of technology with the human workforce. The chapter also offers considerations for managers when merging technology with human resources and provides recommendations for reskilling and upskilling workers to prepare them for the future of work.
Chapter 7 delves into the concepts and applications of intelligent robots and cobots within the context of Industry 5.0 transformation. It provides an overview of Industry 5.0, emphasizing its goal of merging human capabilities with advanced technologies, and examines the characteristics, functionalities, and potential benefits of intelligent robots and cobots.
Chapter 8 reviews multiple human-machine collaboration strategies studied to guide businesses and researchers in making informed decisions in Industry 5.0, where human-machine collaboration is the primary focus. The objective of intelligent process automation is to assist cobots in establishing both production objectives and industrial plant safety measures. The chapter emphasizes how Industry 5.0 aims to transform human-technology interactions through Artificial Intelligence.
Chapter 9 delves into the development of a vision-guided robotic device, also known as a cobot, designed for performing a variety of precise tasks. Cobots can be used for hygienic and precise manipulation and assembly of medical equipment or implants, reducing the danger of human contamination, penetrating illnesses, and maintaining clean environments. The chapter highlights how cobots’ ease of programming, installation, and collaboration helps maximize throughput and maintain consistent quality.
Chapter 10 covers the design, construction, applications, and role of robotic arms in the industry. A computer-aided design (CAD) model of a robotic arm is developed using CREO/SolidWorks and analyzed with ANSYS, demonstrating the crucial role of material properties under various loading conditions. The chapter aims to create a robotic arm that is highly accurate, precise, lightweight, and easily transportable.
Chapter 11 explores the potential of Industry 5.0, which aims to overcome challenges by fostering collaboration between robots and humans, rather than competition. Industry 5.0 is expected to profit from different promising advances and applications empowering expanded creation and unconstrained conveyance of modified items. It thoroughly discusses the various applications of Industry 5.0, including intelligent healthcare, cloud manufacturing, supply chain management, and production.
Collection of proper aviation resources determines how the chatbots and robots are going to perform and up to what accuracy. Translation analysis determines the accuracy of translations and transliterations, whereas other parameters determine how that particular aviation bots interact with passengers. Chapter 12 focuses on effectively managing the development of various bots related to the aviation industry.
Chapter 13 explores hydroponics, a soil-less plant cultivation method within horticulture, and examines how cobots can streamline this process and enhance plant survival. Existing traditional farming systems can lead to soil degradation, reduced crop yields, and water scarcity due to high water usage for irrigation. Together, hydroponics and cobots create a more efficient and effective system for plant growth.
Chapter 14 highlights the latest advancements in big data analytics for cobots, addressing the challenges researchers face within IoT environments. Data analytics for IoT within the realm of cobots involves collecting, processing, and analyzing the copious data generated by IoT devices to extract insights and inform decision-making. Cobots and other IoT devices produce various data types, ranging from structured to unstructured, originating from sources like sensors and wearables. It discusses gaps in analytics, research methodologies, and data management techniques.
Chapter 15 focuses on the design and control of soft robots, reviewing commonly used manufacturing materials and their characteristics. Soft robots are well-known for their ability to control the range of force in which they act such as the ones used in material prehension. Also, soft robots are smart robots. It highlights the diverse applications of soft robots in everyday life, such as wearables, mechanical motion, surgeries, and more.
Chapter 16 introduces an innovative model where collaborative robots (cobots) leverage microservices and swarm intelligence within a shared industrial workspace. Evaluating the deployment of the collaborative robot service is necessary in the industrial sectors as well as for researchers. This chapter also addresses deployment constraints, evaluation processes, and service performance when applying swarm intelligence via microservices. The work will also highlight the deployment constraint and performance aspects of service while utilizing the swarm intelligence through microservices.
Chapter 17 examines the security of industrial robots and cobots, beginning with an introduction to the Fourth Industrial Revolution and its various facets. Because, when dealing with a cobot, it is recommended to have a heightened knowledge of the many areas of cyber security and how they relate to the safety of the system. It then explores the vulnerabilities and attacks that industrial robots and cobots may encounter.
The integration of cobots into interconnected networks and their reliance on digital communication channels raise significant cybersecurity concerns. Traditional security measures such as firewalls and encryption mechanisms may not be sufficient to safeguard cobots against evolving cyber threats. Chapter 18 examines how blockchain technology can address cybersecurity issues related to cobots. The blockchain-based smart contracts can play a vital role in securing interactions between cobots and their human operators or other entities. Smart contracts enable the establishment of predefined rules and protocols, ensuring that cobots execute only authorized actions.
We hope that readers will find this book beneficial. The editors are grateful to the reviewers who have contributed to improving the quality of the book through their constructive comments. The editors also thank Martin Scrivener and Scrivener Publishing for their support and publication.
Editor(s):Dr. V. Ramasamy
Associate Professor in the Department of CSE at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (Deemed to be University), Chennai, Tamilnadu, India
Dr. S. Balamurugan
Director-Research and Development, Intelligent Research Consultancy Services (iRCS), Coimbatore, Tamilnadu, India
Dr. Sheng-Lung Peng
Professor and the Director of the Department of Creative Technologies and Product Design, National Taipei University of Business, Taiwan
November 2024
Acknowledgement
The editorial team extends heartfelt gratitude to our institution for fostering an encouraging research environment that laid the foundation for this proposal. We are deeply appreciative of the diverse group of contributors from various nations and offer special thanks to the reviewers worldwide who have diligently examined each chapter to maintain the book’s high standards. Their insightful feedback has been invaluable. We sincerely thank all parties involved for their dedication and willingness to take on tasks that pushed them beyond their usual comfort zones. We look forward to reuniting with you in the next edition of our publication.
Part 1FUNDAMENTALS
1Cobots for Industry 5.0 Transformation
Ahmed F. Siddiqui1, Aditya J. Paul1, Sushruta Mishra1* and S. Balamurugan2
1Kalinga Institute of Industrial Technology, Deemed to be University, Bhubaneswar, Odisha, India
2Albert Einstein Engineering and Research Labs (AEER Labs), Vice Chairman-Renewable Energy Society of India (RESI), Tamil Nadu, India
Abstract
The potential of cobots in the Industrial Internet of Things (IIoT) to transform the industries has been examined in this research article. The research and development in the area of technology has increased the cost-effectiveness and acceptance of these IoT-enabled devices in many different industries. Various sectors including manufacturing, healthcare sectors, transportation sector, and the agriculture sector have begun incorporating robots and cobots into their operations. They are aiming to increase their productivity, reduce the downtime of their equipment, and optimize resource utilization. This article looks into the different ways that cobots are being used in these sectors. It highlights their role in enhancing industrial processes. Also, the article addresses potential challenges in deploying robots and cobots in businesses. These challenges such as acceptance issues and compatibility issues need to be addressed. The advantages of deploying cobots in IIoT settings are also demonstrated, which also showcases how this technology can lead to significant improvements across various industries. Overall, this article provides us a comprehensive review of how robots and cobots in IIoT have the potential to revolutionize businesses and serves as a valuable resource for other researchers who are interested in this transformative technology.
Keywords: Robots, cobots, Internet of Things (IoT), Industrial Internet of Things (IIoT), Industry 4.0, Industry 5.0, cyber-physical systems (CPS)
1.1 Introduction
The Internet of Things, also known as IoT, intelligently connects our surrounding items and raises the quality of life by using embedded sensors and networks. It is a relatively new global networking infrastructure that connects various networks to enable the process of gathering, processing, managing, and distributing data via actual physical devices and appliances using pervasive sensory, communication, networking, and information processing technologies. It is rapidly developing in the field of contemporary wireless telecommunications [1–3]. This infrastructure is made up of a sizable number of physical items that are controlled and monitored online in addition to internet-connected equipments and devices. Their value comes from the ability of the equipments and devices to communicate with one another and their surroundings to achieve common objectives [4]. In domain-specific applications, smart devices and the activities that they are designed to perform can produce dependable, effective, and secure services [1, 3]. The term “Things” in the Internet of Things refers to both physical and non-physical objects. It includes robots, cobots, and other machines; it may also include human and animal bodies and data collected from sensors. IoT can capture the data, share it, and also analyze it. It is of great use for the industry and can result in several advantages. Adopting the IoT-based technologies in order to track and monitor products can improve the efficiency of the industry when it comes to manufacturing and also reduce the time it takes to deliver the goods. Development of robots and cobots is made possible by IoT-engineered mechanisms and software systems, which greatly minimizes and eradicates equipment breakdown, process defects, and human errors across the entire process. IoT enhances operations and offers a variety of creative solutions, such as creating a new business model [5]. During the implementation of the IoT in large-scale industrial applications, numerous challenges have been faced, encompassing issues related to power consumption, expandability, linkages, and data-related matters (communication, data rate, time delay, and standardization), as well as the aspects of safety and protection. Nonetheless, certain industries have already successfully used IoT technologies, such as the healthcare services, supply chain, and infrastructure monitoring [2, 6, 7]. Industries all around the world are looking for robotic solutions aspiring to bring a revolution in their production and manufacturing processes; they are aiming to boost efficiency and throughput and also make it cost-effective while minimizing the need of human labor. Currently, conventional industrial robots are primarily utilized by large manufacturers engaged in high-volume production. Small- and medium-sized businesses (SMEs) constitute a substantial 98% of the European manufacturing sector and have yet to catch up with advanced robotic automation for their operations. SMEs are trying to use robots to boost their productivity and also to keep up with the market demands. Robotic automation can help the SMEs to become more cost effective in their manufacturing processes; this also allows them to compete with others [8]. The swift integration of cobots is completely transforming the manufacturing procedures of small-and mid-sized businesses (SMBs). These cobots offer ease of use; they also occupy very less space and collaborate with human operators easily in shared workspaces. The ability of cobots to work along with human workers makes them very useful. An increasing number of SMEs are trying to use cobots in activities where they can integrate it. There are vast possibilities for better efficiency and better production processes [9].
The following points will be discussed in the paper:
Discuss how IoT is essential for industries.
Discuss the issues with acceptance of cobots.
Discuss how cobots function in the industries.
Discuss how cobots collaborate and result in automation.
1.2 Related Works
Industry 4.0’s foundational idea of intelligent manufacturing depicts a system that can adapt to a variety of shifting circumstances and goods. Flexible lines autonomously modify manufacturing procedures to accommodate various product types and varying environmental circumstances [10]. Consequently, this results in heightened excellence, productivity, and adaptability, alongside extensive and eco-friendly production of personalized goods, as fewer resources are utilized [11].
In 2011, a German initiative led by the Federal government in collaboration with academic institutions and businesses had introduced the concept of “Industry 4.0.” A significant strategic endeavor of this initiative was to develop innovative manufacturing techniques, aimed at boosting the productivity and efficiency of local industries [12].
A burgeoning innovation known as a cyber-physical system (CPS) focuses on integrating computational applications as a network of interconnected physical and digital elements that oversee real-time automation in industrial infrastructures [13].
Researchers of [14] developed a smart collaborative balancing method for ruthlessly altering the instrumentation of system operation and successfully optimizing the job pattern. The relevant problems are addressed by matrix operation using a single congestion interval. The invasion defense system is also covered and displayed. Then, concrete suggestions for coordinating different network tactics are made.
In an architecture developed by researchers of [15], it integrates deep convolutional neural networks with actual network information for early identification of distributed-denial-of-service (DDoS) assaults organized by a botnet overseeing malevolent gadgets. These surrogate devices autonomously execute SMS flooding, quiet calls, signaling, or a combination of these strategies, with the goal of orchestrating DDoS attacks within a cluster, potentially disrupting the functioning of CPSs. These attacks target various services including the Internet, calls, and SMS, or it may be a combination of these. This poses significant threats to the system’s functionalities and makes it compromised. Gushev [16] focuses on the computation framework, which uses a particular framework to develop these concepts.
The modern business world is made up of a network of connected companies and organizations that actively participate in the extensive supplier network [17]. In this dynamic world, supply chain management and logistics have experienced significant paradigm and systemic changes [18] and are vulnerable to a wide range of threats. This process is now an essential component of how any organization functions and efficient administration of this procedure is now undeniably essential for the sustainability of the enterprises in an ever-changing and fiercely competitive setting [2]. However, technological advancements have improved business-to-business communication and made it easier to transport and monitor physical goods throughout the network of supply chain.
Smart household appliances are an Industry 4.0 enabler that have the ability to improve consumer happiness, and they help with energy economy, better personalization, and big data analytics. The interconnected network of objects elevates instant communication, data gathering, and analytical capabilities, revolutionizing traditional enterprises into a digital model [19]. Now, it is that data is a valuable resource to help consumers demand cheap smart products and systems with higher levels of personalization than ever before [20]. The household device industry has been one of the forerunners in implementing cutting-edge technologies, such as IoT and Cloud, since the early 2010s [21]. Through a seamless cooperation, IoT enables sensing, acting, and real-time data transmission skills [22, 23]. The crucial IoT benefit depends on making it possible to handle vast amounts of data by using big data analytics [24]. With the help of IoT, it can be made possible for the different types of sensors to share data in real-time for a variety of purposes. This may include managing pollution and tracking traffic flow, and they can also help in managing road intersections [25]. A separate network link like Bluetooth or GSM is used to assist in the development of IoT-enabled smart homes. This enables remote tracking and management of household appliances. Also, people have the option to use a virtual helper such as Amazon Alexa, Google Nest, Apple Siri, or Microsoft Cortana. This enables effortless voice command over intelligent home devices [26]. An increasing array of commonplace objects is undergoing transformation into intelligent, IoT-enabled merchandise, and collaborative robots. The aim is to establish an extensive array of interconnected products utilizing suitable Industry 5.0 technologies, encompassing, among others, fridges, laundry machines, automated dishwashers, stoves, drying appliances, air conditioning units, and heating systems [27]. The advent of innovative Industry 5.0 advancements has ignited a revolution in intelligent home applications, although there are indications that affordable customized items may not be readily accessible in the near future. The primary value of creating smart products lies in utilities, intelligent urban centers, and interconnected networks [28].
Research predicts an exponential growth in the global market sales of cobots, projected to reach $11.5 billion in 2025 from $116 million in 2015, with around 700,000 units sold [29]. The researcher made it very clear that cobots revolutionize human ergonomics and revolutionize manufacturing productivity. However, a triumphant implementation of cutting-edge technology demands more than just financial investment; the pivotal role of employee attitudes and acceptance cannot be underestimated. Their unwavering support and acceptance are paramount to the technology’s triumphant integration and ultimate success [30].
1.3 IoT for Industries
The current collection of literature concerning Industry 5.0 predominantly centers on futuristic and interdisciplinary viewpoints. Unlike Industry 4.0, which primarily concentrates on utilizing digital tech to tackle particular manufacturing obstacles and boost efficiency, Industry 5.0 adopts a wider and all-encompassing methodology. This new paradigm aims to create a more customer-centric environment, embracing a holistic purpose that goes beyond mere technological advancements. Industry 5.0 envisions a future where manufacturing processes seamlessly integrate with human expertise and creativity to produce goods and services that cater precisely to the needs and preferences of customers. Rather than solely relying on automation and smart technologies, Industry 5.0 emphasizes the harmonious coexistence of humans and machines, fostering a collaborative and inclusive work environment. Moreover, Industry 5.0 extends its reach beyond manufacturing sectors, seeking to revolutionize and optimize processes across various industries. This cross-sectoral approach envisions a synergy between sectors, with shared knowledge and innovation propelling a more interconnected and efficient economy [31].
1.4 Issues with Cobots in Industry 5.0
Collaborative robots (cobots) are increasingly utilized in Industry 5.0, yet employee acceptance remains a challenge. The conventional technology acceptance model falls short in explaining this phenomenon for cobots integrated with artificial intelligence (AI). Anthropomorphism, attributing human-like traits to cobots, also fails to elucidate the issue. The issues that employees have come from factors like trust; they also have a fear of job displacement and uncertainty about working alongside intelligent machines. A proper study of human–cobot interaction is very necessary to understand employee attitudes in a better way. Researchers should consider psychological aspects as well as socio-cultural aspects that may affect the employee’s behavior. They should also look into usefulness, the ease of using cobots, and compatibility with other already existing workflows. Also, the ethical concerns in regard to privacy and data security must be addressed to build trust. To improve acceptance, we need industries to focus on educating the employees, training them, and involving them in the technology adoption process. Addressing the issues that the employees face can lead to a more harmonious and productive human–cobot collaboration.
Anthropomorphism involves attributing human-like attributes such as emotions, intentions, motivations, imagination, or actual behavior to non-human entities. Interestingly, robot acceptance indicates a clear willingness of the user group to start using and employing the technology for its intended purposes. This tells us that the group is open and ready to start using robots and consider them as important tools that can help save some time and reduce human effort as well [32].
Interactive human–robot interaction (IHRI) stands as a vital domain within cognitive ergonomics. Its primary objective lies in ensuring optimal compatibility between human cognitive abilities and robots during interactions. By employing psychological models and concepts from cognitive science, IHRI aims to identify key factors influencing cognitive functions. The ultimate goal is to minimize errors, reduce unnecessary cognitive burden, and alleviate psychological pressure experienced by employees. By doing so, IHRI seeks to create a workplace environment that fosters safety, well-being, and high performance. In essence, this research embraces the cognitive ergonomics approach to delve deeper into understanding and enhancing the dynamics of human–robot interactions for the benefit of both human workers and robotic systems [33].
As a solution to address the issue of low cobot acceptance at the mechanism level, enhancing employees’ robot use self-efficacy through diverse training methods proves promising. Prior to implementing cobots in the factory, comprehensive training sessions can be conducted. The comprehensive training programs involve various activities, including educating employees on cobot principles, providing surrogate experiences through interactions with small toy robots, and engaging in collaborative work under professional guidance to create successful experiences. By empowering employees with essential knowledge and practical skills, the apprehension and concerns related to cobots and any perceived threat they may pose can be effectively minimized.
This systematic approach allows employees to develop a greater sense of confidence and competence in utilizing cobots effectively. Through hands-on training and real-life application, the training process empowers employees to overcome initial hesitations and uncertainties, paving the way for increased acceptance and integration of cobots into their daily work routines. Consequently, the successful implementation of such training initiatives fosters a harmonious human–robot collaboration, ultimately contributing to improved productivity, safety, and job satisfaction in the workplace.
1.5 Cobots in Industries
Industry 4.0 was contemplated as a way out to tackle both technical and societal challenges, harnessing the remarkable advancements in IoT and CPSs. This transformative idea led to the rise of the Work 4.0 model in Germany, initiating vital discussions about the substantial effects of Industry 4.0 on everyday work and society as a whole [34]. However, it seems Industry 4.0 has mainly focused on technological advancements, possibly overlooking its broader impact on society. To accomplish a complete and beneficial transformation, it is crucial to find equilibrium, recognizing the ethical and societal aspects of this industrial revolution. Adopting inclusivity and sustainability can lead Industry 4.0 toward a brighter and more prosperous future, where technology and society coexist in ideal harmony. Industry 5.0 complements Industry 4.0 with a focus on human-centric design, sustainability, and resilience.
By making use of advanced materials including smart properties with integrated sensors makes industrial workplaces safer and improves how people work together. Simultaneously advanced technologies like cutting-edge virtual reality and cooperative automation help things run more smoothly and efficiently. Sustainability is prioritized through environmentally friendly practices, aiming for a resilient and ecologically conscious industry. By emphasizing human requirements and promoting adaptability, Industry 5.0 visualizes a future where technology brings about positive change for both individuals and the planet. Cobots, also referred to as collaborative robots, are provided with various sensors, taking advantage of advanced industrial robotics technology. These exceptional machines are implemented in factories and various industrial settings where they are provided with robust vision systems. In contrast to conventional industrial robots, cobots are designed with safety features, to assure effective collaboration with human workers. The primary aim of cobots is to place humans at the heart of the manufacturing process and alleviate them from performing arduous, hazardous, or monotonous tasks. Importantly, cobots are not meant to replace human workers; instead, they work alongside operators, complementing their skills and capabilities. Once installed, cobots are intended to remain stationary at their designated work site, streamlining and enhancing the overall production process [35–37].
Businesses are growing more attracted to the benefits of utilizing these robots in various industries, which in result making the cobot sector a promising area of rapid growth. Due to their versatility and effectiveness, cobots are being used across diverse production settings, leading notable advancements in the industrial robotics industry. Through seamless collaboration with human operators, these transformative robots are reshaping manufacturing and improving previously labor-intensive or dangerous tasks. The increasing popularity of cobots in the business world is evidence of their capabilities for transforming work processes and raising productivity [38, 39].
Cobots are cutting-edge machines engineered with an unwavering focus on safety. Their advanced collision sensors ensure the utmost protection of human workers during any interaction. Cobots, armed with collaborative arms incorporating force boundaries, ensure that unintended collisions are harmless to human workers. Moreover, these remarkable machines showcase a hand-guided tool, empowering operators to assume direct control, even in automation, and responding exclusively to the operator’s instructions. The soaring popularity of cobots knows no bounds, transcending traditional and unconventional sectors alike. However, successful integration demands meticulous management during the initial deployment stages. Sporting a distinctive design featuring force-sensing technology, cobots stand head and shoulders above other robots in the field. Their collaborative nature, working side by side with humans, offering assistance or acting as guides, showcases their exceptional responsiveness to human commands and actions, setting them apart from fully autonomous counterparts. In a realm where innovation meets safety, cobots reign supreme [40, 41].
1.6 Automation and Cobots
The transformation of the innovative collaborative machines of the manufacturing process is done by the laborious activities. These activities include gathering components, conducting quality checks, and feeding machines. All these tasks help humans to shorten the prolonged duration of work. Because these robots turn out to be the value assistants, one would be able to witness them working with the human operators with harmony. This, in turn, enhances the efficiency and productivity of the manufacturing process. Improved production outcomes can only be expected via the mixture of human ingenuity and robotic precision. The cobots are the machines, which are significantly designed to carry out specific functions. These can also help in moving the necessary objects while working. The cobots are well innovated to open new avenues for streamlined and efficient manufacturing processes. If the goal is to achieve a balance between human expertise and technological advancement, then cobots prove to be the best things to embrace as it helps in optimizing operations making the work easy for the manufacturers.
The industrial segment has been highly benefited from the cobot applications in the manufacturing process. The benefits include cost effective designing, flexibility of work, and easy work. However, having an enhanced and swift flexibility in the manufacturing process proves to be somehow not so valuable as it does not impact on performance enhancement and adaptability to the production lines. The cobots have been very widely recognized in the workstation areas where they are catering to the needs of the SMBs. Currently, with the advancement in technology with the cobots, the world has seen advancements in securing human operators, effortless configurability, and friendly user interface (UI). With this, we have seen high acceptance rates with positive feedback and improved performances in the collaborative tasks. There are some other factors as well, which might need an extensive analysis. These include giving emphasis on dependability, operator acceptance, successful interaction with humans, and many more. The cobots have been developed in such a way that it can cater to the needs of the coworkers alongside lowering their work stress, which, in turn, helps in alleviating work pressure [42].
Although the robotics has been here for over a decade, the current era has been some great advancements. This advancement has enhanced the versatility in the manufacturing sector. As well-known by now, the cobots are extensively designed to be artificially intelligent machines that are autonomous and are capable of doing independent work assigned. This is now possible by the direct interaction with the humans in the workstation. It also maintains a physical demeanor at the place. The past decade has seen substantial increase in the use of robots because the population has accepted it to share the workload and safety purpose. The concept of the cobots or collaborative robots enables better human decision making and flexible environments. The best advantage to the advancement in cobots is their factory automation contribution alongside the lightweight designs that they receive to get accommodated to any place.
Figure 1.1 Relationships and dependencies related to automation using cobots.
In Figure 1.1, there is a comprehensive image provided. This showcases the application of cobots within the industrial landscape in relation to degrees of collaboration, relationships, interdependencies, etc. The illustrative description throws light on the important practices or collaboration degrees. The practices include assistive modes of team work, concurrent, consecutive, and autonomous. These provide some distinctive insights to the dynamic interactions between the humans and the collaborative robots in the industrial setting [43, 44].
The popularity of the cobots is rising, and they have now become a part of the advanced Industry 5.0. The cobots have well positioned themselves at the vanguard of the transforming era of technological advancements. The best use of their ability (which is collaboration with humans) has no doubt helped in enhancing factory automation and more flexibility in the manufacturing that leads to a great innovative shift in collaborative manufacturing. With this, one can say that a perfectly synced human–robot synergy will help in boosting efficiency, productivity, and overall manufacturing excellence [45–47].
1.7 Conclusion
The increase in the advancement of the robotic technologies has greatly impacted the manufacturing, expanding of the horizons of potentials, and adaptability within the industries into a more productive and new era. The very forefront of the transformation of this new developmental technology includes the collaborative robot transformation or one can say “cobots” that has highly exalted and exemplified the interactions between human and intelligence and technological innovation. What is more, the cobots are different from their predecessors. These cobots are highly capable of independent functioning, possess extreme AI ability, and are autonomous in nature. Apart from this, the cobots are also found to be engaged in collaborative tasks with the human counterparts in the shared workspaces.
The transformation of Industry 4.0 model to the new Industry 5.0 has embodied a new transformation in the technology, which can be seen with a comprehensive perspective. Customer-centricity and eco-conscious practices can be envisioned into a manufacturing landscape where the two take the center of the stage. With this, it aims to harmonize the creativity and ingenuity of humans in relation with the machine efficiency, which further results in well-tailored goods and services that will align with the preference of the consumers. The main focus of the new industry 5.0 has been shifted toward the convergence of human expertise and technological prowess serving as a cornerstone. This also encourages an act of collaborative as well as inclusive work environment.
Speaking about the cobots, they play the pivotal roles in the Industry 5.0 narrative. Cobots have found their place in the industrial sector and have possessed an array of sensors and technological advancements. This has further enhanced their function to seamlessly operate in the grounds of factories and industries. Unlike the past robots, these new cobots have been made to have learnt the human safety and interaction processes. They function as valuable assistants to their human friends that also complement human skills. So, there seems to be less or no chance of replacing them.
Although the cobots have advanced, integration of the cobots in the Industry 5.0 has also faced challenges. The machines do face challenges like efficiency and innovations; also, they are prone to face challenges of acceptance and adoption by the employees. This situation arises due to the pivotal concerns of the employees such as job displacement and uncertainty and necessitates a comprehensive exploration of the interaction between human and robots. The attitude of the employees also depends on the psychological and social cultural factors that come into the scene once the cobots appear. Hence, this has urged the researchers to delve deeper into the ergonomics and reduce the boundaries to ensure a happy and well-settled human–cobot collaboration.
Lastly, Industry 5.0 has definitely pioneered a big transformation that transcends the mere technological advancement. The main focus of this Industry 5.0 has been on maintaining the synergy between human creativity and technological prowess where the collaboration between humans and the machines in the future will be paramount. Cobots are believed to be the embodying spirits, which will bridge the gaps between human expertise and innovation. However, addressing the challenges in making cobots accepted into society will help the researchers to unlock the machine’s full potential. This will again help the human race to enter into a more profitable and productive era where a harmonious collaboration between human and robot will be seen.
References
1. Lin, J., Yu, W., Zhang, N., Yang, X., Zhang, H., Zhao, W., A survey on Internet of Things: Architecture, enabling technologies, security and privacy, and applications.
IEEE Internet Things J.
, 4, 5, 1125–1142, 2017.
2. Da Xu, L., He, W., Li, S., Internet of Things in industries: A survey.
IEEE Trans. Ind. Inform.
, 10, 4, 2233–2243, 2014.
3. Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M., Internet of Things, A survey on enabling technologies, protocols, and applications.
IEEE Commun. Surv. Tutor.
, 17, 4, 2347–2376, 2015.
4. Atzori, L., Iera, A., Morabito, G., The Internet of Things: A survey.
Comput. Netw.
, 54, 15, 2787–2805, 2010.
5. Bughin, J., Chui, M., Manyika, J., An executive’s guide to the Internet of Things.
McKinsey Q.
, Mckinsey&Company, 2, 9, 89–105, 2015.
6. Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M., Internet of Things (IoT): A vision, architectural elements, and future directions.
Future Gener. Comput. Syst.
, 29, 7, 1645–1660, 2013.
7. Kim, S. and Kim, S., A multi-criteria approach toward discovering killer IoT application in Korea.
Technol. Forecasting Social Change
, 102, 143–155, 2016.
8. Pieskä, S., Kaarela, J., Mäkelä, J., Simulation and programming experiences of collaborative robots for small-scale manufacturing.
2018 2nd International Symposium on Small-Scale Intelligent Manufacturing Systems, SIMS
, IEEE, pp. 1–4, 2018.
9. Holm, M. and Schnell, M., Challenges for manufacturing SMEs in the introduction of collaborative robots.
10. Wern, C.W., Ramulu, M., Shukla, A., Investigation of stresses in the orthogonal cutting of fiber-reinforced plastics.
Exp. Mech.
, 36, 1, 33–41, 1996.
11. El-Gallab, M. and Sklad, M., Machining of Al/SiC particulate metal matrix composites.
J. Mater. Process. Technol.
, 83, 1-3, 277–285, 1998.
12. Takeyama, H. and Iijima, N., Machinability of glassfiber reinforced plastics and application of ultrasonic machining.
CIRP Ann.
, 37, 1, 93–96, 1988.
