1. Waschull S, Bokhorst JAC, Molleman E et al (2020) Work design in future industrial production:transforming towards cyber-physical systems. Comput Ind Eng. 139:105679
2. Javed Y, Felemban M, Shawly T et al (2019) A partition-driven integrated security architecture for cyber-physical systems. arXiv:190103018[csSY]
3. Van Der Zeeuw A, Van Deursen AJ, Jansen G (2019) Inequalities in the social use of the internet of things:a capital and skills perspective. New Media Soc 21(6):1344-1361
4. Habibi M, Fazli M, Movaghar A (2019) Efficient distribution of requests in federated cloud computing environments utilizing statistical multiplexing. Future Gener Comput Syst 90:451-460
5. Yan H, Yu P, Long D (2019) Study on deep unsupervised learning optimization algorithm based on cloud computing. In:2019 international conference on intelligent transportation, Big data & smart city (ICITBS), pp 679-681
6. He B, Pan QJ, Deng ZQ (2018) Product carbon footprint for product life cycle under uncertainty. J Clean Prod 187:459-472
7. Radhi H (2019) Multi-objective optimization of turning process during machining of AISI 1025 on CNC machine using multiobjective particle swarm optimization. Univ Thi-Qar J Eng Sci 10(1):65-70
8. He B, Cao XY, Gu ZC (2020) Kinematics of underactuated robotics for product carbon footprint. J Clean Prod 257:120491
9. Chiaverini S, Siciliano B, Egeland O (1994) Review of the damped least-squares inverse kinematics with experiments on an industrial robot manipulator. IEEE Trans Control Syst Technol 2(2):123-134
10. Altintas Y, Yang J, Kilic ZM (2019) Virtual prediction and constraint of contour errors induced by cutting force disturbances on multi-axis CNC machine tools. CIRP Ann 68(1):377-380
11. Zheng P, Wang HH, Sang ZQ et al (2018) Smart manufacturing systems for Industry 4.0:conceptual framework, scenarios, and future perspectives. Front Mech Eng 13(2):137-150
12. Tao F, Qi QL, Liu A et al (2018) Data-driven smart manufacturing. J Manuf Syst 48:157-169
13. Zhong RY, Xu X, Klotz E et al (2017) Intelligent manufacturing in the context of Industry 4.0:a review. Engineering 3(5):616-630
14. Yadav A, Jayswal SC (2017) Modelling of flexible manufacturing system:a review. Int J Prod Res 56(7):2464-2487
15. Li BH, Hou BC, Yu WT et al (2017) Applications of artificial intelligence in intelligent manufacturing:a review. Front Inf Technol Electron Eng 18(1):86-96
16. Kusiak A (2017) Smart manufacturing. Int J Prod Res 56(1/2):508-517
17. He B, Hua YC (2017) Feature-based integrated product model for low-carbon conceptual design. J Eng Des 28(6):408-432
18. Bouzary H, Frank Chen F (2018) Service optimal selection and composition in cloud manufacturing:a comprehensive survey. Int J Adv Manuf Technol 97(1/4):795-808
19. Bouzary H, Chen FF, Krishnaiyer K (2018) Service matching and selection in cloud manufacturing:a state-of-the-art review. Procedia Manuf 26:1128-1136
20. Bauer D, Stock D, Bauernhansl T (2017) Movement towards service-orientation and app-orientation in manufacturing it. Procedia CIRP 62:199-204
21. Giret A, Garcia E, Botti V (2016) An engineering framework for service-oriented intelligent manufacturing systems. Comput Ind 81:116-127
22. Cao Y, Wang SL, Kang L et al (2015) Study on machining service modes and resource selection strategies in cloud manufacturing. Int J Adv Manuf Technol 81(1/4):597-613
23. He B, Zhang D, Gu ZC et al (2020) Skeleton model-based product low carbon design optimization. J Clean Prod. https://doi.org/10.1016/j.jclepro.2020.121687
24. Grossmann IE (2019) Optimization and management in manufacturing engineering:resource collaborative optimization and management through the internet of things. Optim Methods Softw 34(1):220-223
25. Soni R, Bhatia M, Singh T (2019) Digital twin:intersection of mind and machine. Int J Comput Intell IoT 2(3):667-670
26. Zheng P, Lin Y, Chen CH et al (2018) Smart, connected open architecture product:an IT-driven co-creation paradigm with lifecycle personalization concerns. Int J Prod Res 57(8):2571-2584
27. Nikolakis N, Alexopoulos K, Xanthakis E et al (2019) The digital twin implementation for linking the virtual representation of human-based production tasks to their physical counterpart in the factory-floor. Int J Comput Integr Manuf 32(1):1-12
28. Wang SY, Wan JF, Zhang DQ et al (2016) Towards smart factory for Industry 4.0:a self-organized multi-agent system with big data based feedback and coordination. Comput Netw 101:158-168
29. Grieves M (2014) Digital twin:manufacturing excellence through virtual factory replication. White paper, pp 1-7
30. Abdulmotaleb ES (2018) Digital twins:the convergence of multimedia technologies. IEEE Multimed 25(2):87-92
31. Negri E, Fumagalli L, Macchi M (2017) A review of the roles of digital twin in CPS-based production systems. Procedia Manuf 11:939-948
32. Chhetri MB, Krishnaswamy S, Loke SW (2004) Smart virtual counterparts for learning communities. In:Bussler C et al (eds) Web information systems-WISE 2004 workshops, WISE 2004. Springer, Berlin, pp 125-134
33. Glaessgen E, Stargel D (2012) The digital twin paradigm for future NASA and U.S. Air force vehicles. In:201253rd AIAA/ASME/ASCE/AHS/ASC Structures, structural dynamics and materials conference, pp 1-14
34. Lee J, Bagheri B, Kao HA (2015) A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf Lett 3:18-23
35. Söderberg R, Wärmefjord K, Carlson JS et al (2017) Toward a digital twin for real-time geometry assurance in individualized production. CIRP Ann 66(1):137-140
36. Bolton RN, McColl-Kennedy JR, Cheung L et al (2018) Customer experience challenges:bringing together digital, physical and social realms. J Serv Manag 29(5):776-808
37. Tao F, Sui FY, Liu A et al (2019) Digital twin-driven product design framework. Int J Prod Res. 57(12):3935-3953
38. Hu LW, Nguyen NT, Tao WJ et al (2018) Modeling of cloudbased digital twins for smart manufacturing with mt connect. Procedia Manuf 26:1193-1203
39. Tao F, Cheng JF, Qi QL et al (2017) Digital twin-driven product design, manufacturing and service with big data. Int J Adv Manuf Technol 94(9/12):3563-3576
40. Schleich B, Anwer N, Mathieu L et al (2017) Shaping the digital twin for design and production engineering. CIRP Ann 66(1):141-144
41. Haag S, Anderl R (2018) Digital twin-proof of concept. Manuf Lett 15:64-66
42. Guo JP, Zhao N, Sun L et al (2018) Modular based flexible digital twin for factory design. J Ambient Intell Hum Comput 10(3):1189-1200
43. Bao JS, Guo DS, Li J et al (2018) The modelling and operations for the digital twin in the context of manufacturing. Enterp Inf Syst 13(4):534-556
44. Cheng Y, Tao F, Xu LD et al (2016) Advanced manufacturing systems:supply-demand matching of manufacturing resource based on complex networks and internet of things. Enterp Inf Syst 12(7):780-797
45. Bilberg A, Malik AA (2019) Digital twin driven human-robot collaborative assembly. CIRP Ann 68(1):499-502
46. Um J, Weyer S, Quint F (2017) Plug-and-simulate within modular assembly line enabled by digital twins and the use of automation ML. IFAC-PapersOnLine 50(1):15904-15909
47. Qi QL, Tao F, Zuo Y et al (2018) Digital twin service towards smart manufacturing. Procedia CIRP 72:237-242
48. Leng JW, Zhang H, Yan DX et al (2018) Digital twin-driven manufacturing cyber-physical system for parallel controlling of smart workshop. J Ambient Intell Hum Comput 10(3):1155-1166
49. Cheng Y, Zhang YP, Ji P et al (2018) Cyber-physical integration for moving digital factories forward towards smart manufacturing:a survey. Int J Adv Manuf Technol 97(1/4):1209-1221
50. Meng SH, Tang SL, Zhu YH et al (2019) Digital twin-driven control method for robotic automatic assembly system. IOP Conf Ser Mater Sci Eng 493:012128
51. Xiang F, Zhi Z, Jiang GZ (2018) Digital twins technology and its data fusion in iron and steel product life cycle. In:2018 IEEE 15th international conference on networking, sensing and control (ICNSC), pp 1-5
52. Zhang H, Liu Q, Chen X et al (2017) A digital twin-based approach for designing and multi-objective optimization of hollow glass production line. IEEE Access 5:26901-26911
53. Zhuang CB, Liu JH, Xiong H (2018) Digital twin-based smart production management and control framework for the complex product assembly shop-floor. Int J Adv Manuf Technol 96(1/4):1149-1163
54. Liu Q, Zhang H, Leng JW et al (2018) Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system. Int J Prod Res 57:3903-3919
55. Liau Y, Lee H, Ryu K (2018) Digital twin concept for smart injection molding. IOP Conf Ser Mater Sci Eng 324:012077
56. Botkina D, Hedlind M, Olsson B et al (2018) Digital twin of a cutting tool. Procedia CIRP 72:215-218
57. Pairet È, Ardón P, Liu X et al (2019) A digital twin for human- robot interaction. In:201914th ACM/IEEE international conference on human-robot interaction (HRI), pp 372-372
58. Voinov N, Chernorutsky I, Drobintsev P et al (2017) An approach to net-centric control automation of technological processes within industrial IoT systems. Adv Manuf 5(4):388-393
59. Uhlemann THJ, Schock C, Lehmann C et al (2017) The digital twin:demonstrating the potential of real time data acquisition in production systems. Procedia Manuf 9:113-120
60. Coronado PDU, Lynn R, Louhichi W et al (2018) Part data integration in the shop floor digital twin:mobile and cloud technologies to enable a manufacturing execution system. J Manuf Syst 48:25-33
61. Schluse M, Priggemeyer M, Atorf L et al (2018) Experimentable digital twins-streamlining simulation-based systems engineering for Industry 4.0. IEEE Trans Ind Inf 14(4):1722-1731
62. Macchi M, Roda I, Negri E et al (2018) Exploring the role of digital twin for asset lifecycle management. IFAC-PapersOnLine 51(11):790-795
63. Kunath M, Winkler H (2018) Integrating the digital twin of the manufacturing system into a decision support system for improving the order management process. Procedia CIRP 72:225-231
64. Biesinger F, Meike D, Kraß B et al (2018) A case study for a digital twin of body-in-white production systems general concept for automated updating of planning projects in the digital factory. In:2018 IEEE 23rd international conference on emerging technologies and factory automation (ETFA), pp 19-26
65. Vachálek J, Bartalský L, Rovný O et al (2017) The digital twin of an industrial production line within the Industry 4.0 concept. In:201721st international conference on process control (PC), pp 258-262
66. Uhlemann THJ, Lehmann C, Steinhilper R (2017) The digital twin:realizing the cyber-physical production system for Industry 4.0. Procedia CIRP 61:335-340
67. Tao F, Zhang M (2017) Digital twin shop-floor:a new shopfloor paradigm towards smart manufacturing. IEEE Access 5:20418-20427
68. He B, Deng ZQ, Huang S et al (2014) Application of unascertained number for the integration of carbon footprint in conceptual design. Proc Inst Mech Eng J Eng Manuf 229(11):2088-2092
69. Martinez HV, Neely AD, Ouyang A et al (2019) Service business model innovation:the digital twin technology. EurOMA. https://doi.org/10.17863/CAM.35482
70. Liu Y, Zhang L, Yang Y et al (2019) A novel cloud-based framework for the elderly healthcare services using digital twin. IEEE Access 7:49088-49101
71. Balachandar S, Chinnaiyan R (2019) Reliable digital twin for connected footballer. In:International conference on computer networks and communication technologies. pp 185-191
72. Guivarch D, Mermoz E, Marino Y et al (2019) Creation of helicopter dynamic systems digital twin using multibody simulations. CIRP Ann 68(1):133-136
73. Tao F, Zhang M, Liu YS et al (2018) Digital twin driven prognostics and health management for complex equipment. CIRP Ann 67(1):169-172
74. Lynn R, Chen A, Locks S et al (2015) Intelligent and accessible data flow architectures for manufacturing system optimization. In:Umeda S, Nakano M, Mizuyama H et al (eds) Advances in production management systems:innovative production management towards sustainable growth. Springer, Berlin, pp 27-35
75. Luo W, Hu T, Zhang C et al (2018) Digital twin for CNC machine tool:modeling and using strategy. J Ambient Intell Hum Comput 10(3):1129-1140
76. Li CZ, Mahadevan S, Ling Y et al (2017) Dynamic bayesian network for aircraft wing health monitoring digital twin. AIAA J 55(3):930-941
77. Kaebernick H, Kara S, Sun M (2003) Sustainable product development and manufacturing by considering environmental requirements. Robot Comput Integr Manuf 19(6):461-468
78. Rusinko C (2007) Green manufacturing:an evaluation of environmentally sustainable manufacturing practices and their impact on competitive outcomes. IEEE Trans Eng Manag 54(3):445-454
79. Miller G, Pawloski J, Standridge CR (2010) A case study of lean, sustainable manufacturing. J Ind Eng Manag 3(1):11-32
80. Akbar M, Irohara T (2018) Scheduling for sustainable manufacturing:a review. J Clean Prod 205:866-883
81. Carvalho N, Chaim O, Cazarini E et al (2018) Manufacturing in the fourth industrial revolution:a positive prospect in sustainable manufacturing. Procedia Manuf 21:671-678
82. Gbededo MA, Liyanage K, Garza-Reyes JA (2018) Towards a life cycle sustainability analysis:a systematic review of approaches to sustainable manufacturing. J Clean Prod 184:1002-1015
83. Koren Y, Gu X, Badurdeen F et al (2018) Sustainable living factories for next generation manufacturing. Procedia Manuf 21:26-36
84. Stoycheva S, Marchese D, Paul C et al (2018) Multi-criteria decision analysis framework for sustainable manufacturing in automotive industry. J Clean Prod 187:257-272
85. Moldavska A, Welo T (2019) A holistic approach to corporate sustainability assessment:incorporating sustainable development goals into sustainable manufacturing performance evaluation. J Manuf Syst 50:53-68
86. Physicsweb. http://www.Miit.Gov.Cn/n1146295/n1652858/n1652930/n3757016/c6429243/content.Html. Accessed 14 Aug 2018
87. Stock T, Seliger G (2016) Opportunities of sustainable manufacturing in Industry 4.0. Procedia CIRP 40:536-541
88. Garetti M, Taisch M (2012) Sustainable manufacturing:trends and research challenges. Prod Plan Control 23(2/3):83-104
89. He B, Zhou GF, Hou SC et al (2016) An approach to computational co-evolutionary product design. Int J Adv Manuf Technol 90(1/4):249-265
90. Kang HS, Lee JY, Choi S et al (2016) Smart manufacturing:past research, present findings, and future directions. Int J Precis Eng Manuf Green Technol 3(1):111-128
91. Walshe K, McKee M, McCarthy M et al (2013) Health systems and policy research in Europe:Horizon 2020. Lancet 382(9893):668-669
92. Hemphill TA (2014) Policy debate:the US advanced manufacturing initiative:will it be implemented as an innovation-or industrial-policy? Innovation 16(1):67-70
93. Lewis P, Bell K (2019) Understanding the UK's productivity problems:new technological solutions or a case for the renewal of old institutions? Employ Relat Int J 41(2):296-312
94. Radanliev P, De Roure D, Nurse JR et al (2019) New developments in cyber physical systems, the internet of things and the digital economy-discussion on future developments in the industrial internet of things and Industry 4.0. Preprints 2019, 2019030094
95. Yeung G (2019) ‘Made in China 2025’:the development of a new energy vehicle industry in China. Area Dev Policy 4(1):39-59
96. Zhou GH, Zhang C, Li Z et al (2019) Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing. Int J Prod Res 58:1034-1051
97. Lohtander M, Ahonen N, Lanz M et al (2018) Micro manufacturing unit and the corresponding 3D-model for the digital twin. Procedia Manuf 25:55-61
98. Zhang YZ, Mu LM, Shen GX et al (2019) Fault diagnosis strategy of CNC machine tools based on cascading failure. J Intell Manuf 30(5):2193-2202
99. Villalonga A, Beruvides G, Castaño F et al (2018) Conditionbased monitoring architecture for CNC machine tools based on global knowledge. IFAC-PapersOnLine 51(11):200-204
100. Yang HT, Li L, Zhang SD et al (2019) Critical point determination method of thermal-force coupling deformation of CNC machine tool bed. In:Tenth international symposium on precision engineering measurements and instrumentation, pp 1105325
101. Wei XY, Miao EM, Liu H et al (2019) Two-dimensional thermal error compensation modeling for worktable of CNC machine tools. Int J Adv Manuf Technol 101(1/4):501-509
102. Jiang ZP, Gao D, Lu Y et al (2019) Electrical energy consumption of CNC machine tools based on empirical modeling. Int J Adv Manuf Technol 100(9/12):2255-2267
103. Krimpenis AA, Fountas NA (2016) Balancing multiple criteria in formulation of weighted, single-objective genetic algorithm optimization for CNC machining problems. Adv Manuf 4(2):178-188
104. Xu X (2017) Machine tool 4.0 for the new era of manufacturing. Int J Adv Manuf Technol 92(5/8):1893-1900
105. Jeon JW, Ha YY (2000) A generalized approach for the acceleration and deceleration of industrial robots and CNC machine tools. IEEE Trans Ind Electron 47(1):133-139
106. Kim DI, Kim S (1996) An iterative learning control method with application for CNC machine tools. IEEE Trans Ind Appl 32(1):66-72
107. Keller A, Kamath A, Perera U (1982) Reliability analysis of CNC machine tools. Reliab Eng 3(6):449-473
108. Yamato S, Yamada Y, Nakanishi K et al (2018) Integrated inprocess chatter monitoring and automatic suppression with adaptive pitch control in parallel turning. Adv Manuf 6(3):291-300
109. He B, Wang J, Huang S et al (2015) Low-carbon product design for product life cycle. J Eng Des 26(10-12):321-339
110. Li YJ, Wang GC, Cui HY et al (2019) Dynamic characteristics and optimization research on PVDF piezoelectric film force sensor for steel ball cold heading machine. ISA Trans 94:265-275
111. He B, Xue HJ, Liu LL et al (2019) Rigid-flexible coupling virtual prototyping-based approach to the failure mode, effects, and criticality analysis. Int J Adv Manuf Technol 100(5/8):1695-1717
112. Li ZM (2016) The knowledge expression for the low carbon economy of cold heading machine. J Low Carbon Econ 05(02):20-25
113. Zhang SL, Wang S, Jing FS et al (2019) A sensorless hand guiding scheme based on model identification and control for industrial robot. IEEE Trans Ind Inf 15:5204-5213
114. Pérez L, Diez E, Usamentiaga R et al (2019) Industrial robot control and operator training using virtual reality interfaces. Comput Ind 109:114-120
115. Wu JH, Han X, Tao YR (2019) Kinematic response of industrial robot with uncertain-but-bounded parameters using interval analysis method. J Mech Sci Technol 33(1):333-340
116. Chen Z, Zhou W (2017) Path planning for a space-based manipulator system based on quantum genetic algorithm. J Robot. 3207950
117. Guo S, Fang TT, Song T et al (2018) Tracking and localization for omni-directional mobile industrial robot using reflectors. Adv Manuf 6(1):118-125
118. Slavkovic N, Zivanovic S, Milutinovic D (2019) An indirect method of industrial robot programming for machining tasks based on STEP-NC. Int J Comput Integr Manuf 32(1):43-57
119. Lyu H, Liu Y, Guo JY et al (2019) Tool-path generation for industrial robotic surface-based application. Adv Manuf 7(1):64-72
120. Berg J, Lottermoser A, Richter C et al (2019) Human-robotinteraction for mobile industrial robot teams. Procedia CIRP 79:614-619
121. Norrlof M (2002) An adaptive iterative learning control algorithm with experiments on an industrial robot. IEEE Trans Rob Autom 18(2):245-251
122. Gao Z, Zeng L, He B et al (2018) Type synthesis of non-holonomic spherical constraint underactuated parallel robotics. Acta Astronaut 152:509-520
123. He B, Wang S, Liu Y (2019) Underactuated robotics:a review. Int J Adv Robot Syst 16(4):1-29
124. He B, Zhang P, Liu W et al (2017) Dynamics analysis and numerical simulation of a novel underactuated robot wrist. Proc Inst Mech Eng J Eng Manuf 231(12):2145-2158
125. Fúnez Guerra C, Reyes-Bozo L, Vyhmeister E et al (2019) Viability analysis of underground mining machinery using green hydrogen as a fuel. Int J Hydrogen Energy 45:5112-5121
126. Islam MS, Peter N, Wiens T (2019) Simulation and experiment of vibrational or acoustic communication in mining and oil-gas drill strings. Trans Can Soc Mech Eng 43:454-462
127. Andreev V, Voronkova L, Lybianoi D (2019) Innovative technology of manufacturing of reusable metallurgical equipment with increased operational resistance from the blast furnace cast iron of the first melting. J Mater Sci Res Rev 2:1-8
128. Indri M, Lachello L, Lazzero I et al (2019) Smart sensors applications for a new paradigm of a production line. Sensors 19(3):650. https://doi.org/10.3390/s19030650
129. Dong X, Ma R (2019) Optimization of the LPCVD equipment intergraded production system of the solar cell production line. AIP Conf Proc 2122(1):1-5
130. Wang J, Li D (2019) Task scheduling based on a hybrid heuristic algorithm for smart production line with fog computing. Sensors 19(5):1-18
131. Hwang I, Jang YJ, Choi H (2018) Overhead shuttle design for a flat panel display production line considering the contactless power supply capacity. Comput Ind Eng 126:232-242
132. Gao Y, Lyu H, Hou Y et al (2019) Real-time modeling and simulation method of digital twin production line. In:2019 IEEE 8th joint international information technology and artificial intelligence conference (ITAIC), pp 1639-1642
133. He B, Wang J, Deng ZQ (2015) Cost-constrained low-carbon product design. Int J Adv Manuf Technol 79(9/12):1821-1828
134. Andiappan V, Benjamin MFD, Tan RR et al (2019) An integrated framework to address criticality in biomass tri-generation systems via redundancy allocation. Process Integr Optim Sustain 3(1):65-73
135. Guan D, Feng S, Zhang L et al (2019) Mesoscale simulation for heavy petroleum system using structural unit and dissipative particle dynamics (SU-DPD) frameworks. Energy Fuel 33(2):1049-1060
136. Lemu HG (2014) Current status and challenges of using geometric tolerance information in intelligent manufacturing systems. Adv Manuf 2(1):13-21
137. Sun J, Xi J, Chen X et al (2011) A CAD/CAM system for fabrication of facial prostheses. Rapid Prototyp J 17(4):253-261
138. Lv YQ, Lin DP (2017) Design an intelligent real-time operation planning system in distributed manufacturing network. Ind Manag Data Syst 117(4):742-753
139. Gu X, Jin XN, Ni J et al (2015) Manufacturing system design for resilience. Procedia CIRP 36:135-140
140. Maturana F, Shen W, Norrie DH (1999) Metamorph:an adaptive agent-based architecture for intelligent manufacturing. Int J Prod Res 37(10):2159-2173
141. He B, Hou S, Song W (2015) Integrating engineering design and analysis using a parameter constraint graph approach. Simulation 91(7):625-647
142. He B, Hua Y (2016) Synthesis of mechanisms integrated with motion and force transformation. Int J Precis Eng Manuf 17(12):1643-1649
143. He B, Huang S (2016) Functional synthesis of mechanisms under cost consideration. Proc Inst Mech Eng J Eng Manuf 230(1):91-99
144. He B, Song W, Wang Y (2015) Computational conceptual design using space matrix. J Comput Inf Sci Eng 15(1):1-7
145. He B, Song W, Wang YG (2013) A feature-based approach towards an integrated product model in intelligent design. Int J Adv Manuf Technol 69(1/4):15-30
146. He B, Zhang P, Wang J (2014) Automated synthesis of mechanisms with consideration of mechanical efficiency. J Eng Des 25(4/6):213-237
147. He B, Zhang P, Zhu N et al (2016) Skeleton model-based approach to integrated engineering design and analysis. Int J Adv Manuf Technol 85(5):1105-1115
148. He B, Ostrosi E, Pfaender F et al (2014) Intelligent engineering design of complex city:a co-evolution model. In:Cha J, Chou SY, Stjepandic J et al (eds) Moving integrated product development to service clouds in the global economy. IOS Press, Amsterdam, pp 434-443
149. He B, Luo T, Huang S (2019) Product sustainability assessment for product life cycle. J Clean Prod 206:238-250
150. He B, Deng ZQ, Huang S et al (2015) Application of unascertained number for the integration of carbon footprint in conceptual design. Proc Inst Mech Eng J Eng Manuf 229(11):2088-2092
151. Yu QY, He B (2020) Automated sustainable low-carbon design of offshore platform for product life cycle. In:Tan J (ed) Advances in mechanical design. Springer, Berlin, pp 1-17
152. He B, Huang S, Wang J (2015) Product low-carbon design using dynamic programming algorithm. Int J Precis Eng Manuf Green Technol 2(1):37-42
153. He B, Tang W, Wang J (2015) Product model integrated with carbon footprint for low-carbon design. Int J Precis Eng Manuf 16(11):2383-2388
154. He B, Feng P (2012) Guiding conceptual design through functional space exploration. Int J Adv Manuf Technol 66(9/12):1999-2011
155. Gregor M, Hercko J, Fusko M et al (2019) Zilina intelligent manufacturing system:best practice of cooperation between university and research center. In:Caganova D, Balog M, Knapcikova L et al (eds) Smart technology trends in industrial and business management. Springer, Berlin, pp 183-198
156. He B, Li FF, Cao XY et al (2020) Product sustainable design:a review from the environmental, economic, and social aspects. ASME J Comput Inf Sci Eng 20:040801
157. He B, Wang YG, Song W et al (2014) Design resource management for virtual prototyping in product collaborative design. Proc Inst Mech Eng J Eng Manuf 229(12):2284-2300
158. Simeone A, Caggiano A, Boun L et al (2019) Intelligent cloud manufacturing platform for efficient resource sharing in smart manufacturing networks. Procedia CIRP 79:233-238
159. Wang S, Liang YC, Li WD et al (2018) Big data enabled intelligent immune system for energy efficient manufacturing management. J Clean Prod 195:507-520
160. Stadnicka D, Litwin P, Antonelli D (2019) Human factor in intelligent manufacturing systems-knowledge acquisition and motivation. Procedia CIRP 79:718-723
161. He B, Tang W, Wang J et al (2015) Low-carbon conceptual design based on product life cycle assessment. Int J Adv Manuf Technol 81(5/8):863-874
162. Tao F, Cheng Y, Xu LD et al (2014) CCIOT-CMFG:cloud computing and internet of things-based cloud manufacturing service system. IEEE Trans Ind Inf 10(2):1435-1442
163. Lin YC, Hung MH, Huang HC et al (2017) Development of advanced manufacturing cloud of things (AMCOT)-a smart manufacturing platform. IEEE Rob Autom Lett 2(3):1809-1816
164. He B, Zhang P, Liu L (2014) Simultaneous functional synthesis of mechanisms with mechanical efficiency and cost. Int J Adv Manuf Technol 75(5/8):659-665
165. Zhang YF, Qian C, Lyu JX et al (2017) Agent and cyberphysical system based self-organizing and self-adaptive intelligent shopfloor. IEEE Trans Ind Inf 13(2):737-747
166. Lee CKM, Zhang SZ, Ng KKH (2017) Development of an industrial internet of things suite for smart factory towards reindustrialization. Adv Manuf 5(4):335-343
167. He B, Niu YC, Hou SC et al (2018) Sustainable design from functional domain to physical domain. J Clean Prod 197:1296-1306
168. Helo P, Suorsa M, Hao Y et al (2014) Toward a cloud-based manufacturing execution system for distributed manufacturing. Comput Ind 65(4):646-656
169. Guo QL, Zhang M (2009) A novel approach for multi-agentbased intelligent manufacturing system. Inf Sci 179(18):3079-3090
170. Ji X, He G, Xu JJ et al (2016) Study on the mode of intelligent chemical industry based on cyber-physical system and its implementation. Adv Eng Software 99:18-26
171. Tao F, Zuo Y, Xu LD et al (2014) IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans Ind Inf 10(2):1547-1557
172. Jain P, Poon J, Singh JP et al (2019) A digital twin approach for fault diagnosis in distributed photovoltaic system. IEEE Trans Power Electron 35:940-956
173. Liu MZ, Ma J, Lin L et al (2014) Intelligent assembly system for mechanical products and key technology based on internet of things. J Intell Manuf 28(2):271-299
174. Tang H, Li D, Wang SY et al (2018) Casoa:an architecture for agent-based manufacturing system in the context of Industry 4.0. IEEE Access 6:12746-12754
175. Chaplin J, Bakker O, de Silva L et al (2015) Evolvable assembly systems:a distributed architecture for intelligent manufacturing. IFAC-PapersOnLine 48(3):2065-2070
176. Wang KS (2013) Towards zero-defect manufacturing (ZDM)- a data mining approach. Adv Manuf 1(1):62-74
177. Liu C, Jiang PY (2016) A cyber-physical system architecture in shop floor for intelligent manufacturing. Procedia CIRP 56:372-377
178. Wan JF, Yi ML, Li D et al (2016) Mobile services for customization manufacturing systems:an example of Industry 4.0. IEEE Access 4:8977-8986
179. Zhao QJ, Cao P, Tu DW (2014) Toward intelligent manufacturing:label characters marking and recognition method for steel products with machine vision. Adv Manuf 2(1):3-12
180. Liu CW, Chien CF (2013) An intelligent system for wafer bin map defect diagnosis:an empirical study for semiconductor manufacturing. Eng Appl Artif Intell 26(5/6):1479-1486
181. Strandhagen JW, Alfnes E, Strandhagen JO et al (2017) The fit of Industry 4.0 applications in manufacturing logistics:a multiple case study. Adv Manuf 5(4):344-358
182. Chen RY (2017) An intelligent value stream-based approach to collaboration of food traceability cyber physical system by fog computing. Food Control 71:124-136
183. Maoudj A, Bouzouia B, Hentout A et al (2017) Distributed multi-agent scheduling and control system for robotic flexible assembly cells. J Intell Manuf 30(4):1629-1644
184. Barenji AV, Barenji RV, Hashemipour M (2016) Flexible testing platform for employment of RFID-enabled multi-agent system on flexible assembly line. Adv Eng Softw 91:1-11
185. Wang KS (2014) Intelligent and integrated RFID (II-RFID) system for improving traceability in manufacturing. Adv Manuf 2(2):106-120
186. Zhong RY, Dai QY, Qu T et al (2013) RFID-enabled real-time manufacturing execution system for mass-customization production. Robot Comput Integr Manuf 29(2):283-292
187. Leng JW, Jiang PY (2017) Dynamic scheduling in RFID-driven discrete manufacturing system by using multi-layer network metrics as heuristic information. J Intell Manuf 30(3):979-994
188. Guo ZX, Wong WK, Guo CX (2013) A cloud-based intelligent decision-making system for order tracking and allocation in apparel manufacturing. Int J Prod Res 52(4):1100-1115
189. Qiu C (2018) Implementation of vehicle mobile sales cloud management system based on intelligent community. In:201814th international conference on computational intelligence and security (CIS), pp 341-344
190. Zhang XY, Ming XG, Liu ZW et al (2019) An overall framework and subsystems for smart manufacturing integrated system (SMIS) from multi-layers based on multi-perspectives. Int J Adv Manuf Technol 103:703-722
191. He B, Liu YJ, Zeng LB et al (2020) Product carbon footprint across sustainable supply chain. J Clean Prod 241:118320
192. Sun HT, Peng C, Zhou P et al (2017) A brief overview on secure control of networked systems. Adv Manuf 5(3):243-250
193. McFarlane D, Sarma S, Chirn JL et al (2003) Auto ID systems and intelligent manufacturing control. Eng Appl Artif Intell 16(4):365-376
194. Cui FZ, Xu ZZ, Wang XK et al (2018) A dual-system cooperative co-evolutionary algorithm for satellite equipment layout optimization. Proc Inst Mech Eng G J Aerosp Eng 232(13):2432-2457
195. Malik AA, Bilberg A (2018) Phygital workspace as a digital twin for design & planning of smart factories, pp 1-2
196. Yin Y, Sun L, Guo C (2008) A policy of conflict negotiation based on fuzzy matter element particle swarm optimization in distributed collaborative creative design. Comput Aided Des 40(10/11):1009-1014
197. Wang Y, Ma HS, Yang JH et al (2017) Industry 4.0:a way from mass customization to mass personalization production. Adv Manuf 5(4):311-320
198. Rødseth H, Schjølberg P, Marhaug A (2017) Deep digital maintenance. Adv Manuf 5(4):299-310
199. Gamboa Quintanilla F, Cardin O, L'Anton A et al (2016) A modeling framework for manufacturing services in service-oriented holonic manufacturing systems. Eng Appl Artif Intell 55:26-36
200. He B, Zhu XR, Zhang D (2020) Boundary encryption-based Monte Carlo learning method for workspace modeling. ASME J Comp Inf Sci Eng. 20:034502. https://doi.org/10.1115/1. 4046816
201. Li F, Zhang L, Liu YK et al (2017) A clustering network-based approach to service composition in cloud manufacturing. Int J Comput Integr Manuf 30(12):1331-1342
202. Lu YQ, Xu X (2017) A semantic web-based framework for service composition in a cloud manufacturing environment. J Manuf Syst 42:69-81
203. Zhang S, Xu YB, Zhang WY et al (2017) A new fuzzy QOSaware manufacture service composition method using extended flower pollination algorithm. J Intell Manuf 30(5):2069-2083
204. Zhou JJ, Yao XF (2016) A hybrid artificial bee colony algorithm for optimal selection of QOS-based cloud manufacturing service composition. Int J Adv Manuf Technol 88(9/12):3371-3387
205. Yao F, Yao YP, Xing LN et al (2019) An intelligent scheduling algorithm for complex manufacturing system simulation with frequent synchronizations in a cloud environment. Memet Comput 11:357-370
206. Ruiz N, Giret A, Botti V et al (2014) An intelligent simulation environment for manufacturing systems. Comput Ind Eng 76:148-168
207. Zheng Y, Yang S, Cheng HC (2018) An application framework of digital twin and its case study. J Ambient Intell Hum Comput 10(3):1141-1153
208. Zhang C, Zhou G (2019) A view-based 3D CAD model reuse framework enabling product lifecycle reuse. Adv Eng Softw 127:82-89
209. He B, Tang W, Huang S et al (2015) Towards low-carbon product architecture using structural optimization for lightweight. Int J Adv Manuf Technol 83(5/8):1419-1429
210. Bodrow W (2014) The dynamic of professional knowledge utilized in software applications for process controlling. Adv Manuf 2(2):173-178
211. Giret A, Trentesaux D, Salido MA et al (2017) A holonic multiagent methodology to design sustainable intelligent manufacturing control systems. J Clean Prod 167:1370-1386
212. Zhang C, Zhou G, Lu Q et al (2017) Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development. Int J Prod Res 55(23):7187-7203
213. Chai JF, Hu XM, Qu HW et al (2018) Production line 3D visualization monitoring system design based on OpenGL. Adv Manuf 6(1):126-135
214. Huang PB, Zhang HJ, Lin YC (2017) Development of a grey online modeling surface roughness monitoring system in end milling operations. J Intell Manuf 30(4):1923-1936
215. Li Z, Wang Y, Wang KS (2017) Intelligent predictive maintenance for fault diagnosis and prognosis in machine centers:Industry 4.0 scenario. Adv Manuf 5(4):377-387
216. Kim J, Hwangbo H (2019) Real-time early warning system for sustainable and intelligent plastic film manufacturing. Sustainability 11(5):1490-1503
217. Guo ZX, Ngai EWT, Yang C et al (2015) An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment. Int J Prod Econ 159:16-28
218. Tan DP, Zhang LB, Ai QL (2016) An embedded self-adapting network service framework for networked manufacturing system. J Intell Manuf 30(2):539-556
219. Arica E, Powell DJ (2014) A framework for ICT-enabled realtime production planning and control. Adv Manuf 2(2):158-164
220. Su Y, Ding X, Zheng H et al (2009) A new method of remote control for embedded terminal based on browser/server/terminal model. In:2009 Pacific-Asia conference on circuits, communications and systems, pp 151-154
221. Theorin A, Bengtsson K, Provost J et al (2016) An event-driven manufacturing information system architecture for Industry 4.0. Int J Prod Res 55(5):1297-1311
222. Xiao X, Wang SF, Zhang LJ et al (2018) Complexity analysis of manufacturing service ecosystem:a mapping-based computational experiment approach. Int J Prod Res 57(2):357-378
223. Baxter D, Roy R, Doultsinou A et al (2009) A knowledge management framework to support product-service systems design. Int J Comput Integr Manuf 22(12):1073-1088
224. Matsas M, Pintzos G, Kapnia A et al (2017) An integrated collaborative platform for managing product-service across their life cycle. Procedia CIRP 59:220-226
225. Balta EC, Lin Y, Barton K et al (2018) Production as a service:a digital manufacturing framework for optimizing utilization. IEEE Trans Autom Sci Eng 15(4):1483-1493
226. Cheng Y, Bi LN, Tao F et al (2018) Hypernetwork-based manufacturing service scheduling for distributed and collaborative manufacturing operations towards smart manufacturing. J Intell Manuf. https://doi.org/10.1007/s10845-018-1417-8
227. Ren M, Ren L, Jain H (2018) Manufacturing service composition model based on synergy effect:a social network analysis approach. Appl Soft Comput 70:288-300
228. Siderska J, Jadaan KS (2018) Cloud manufacturing:a serviceoriented manufacturing paradigm. A review paper. Eng Manag Prod Serv 10(1):22-31
229. He B, Feng PE (2012) Research on collaborative conceptual design based on distributed knowledge resource. Int J Adv Manuf Technol 66(5/8):645-662
230. Yang YF, Yang B, Wang SL et al (2019) A dynamic ant-colony genetic algorithm for cloud service composition optimization. Int J Adv Manuf Technol 102(1/4):355-368
231. Zhou JJ, Yao XF (2017) A hybrid approach combining modified artificial bee colony and cuckoo search algorithms for multiobjective cloud manufacturing service composition. Int J Prod Res 55(16):4765-4784
232. Zhang CL, Sheng BY, Yin XY et al (2017) Research and development of off-line services for the 3D automatic printing machine based on cloud manufacturing. J Ambient Intell Hum Comput 10(3):1109-1128
233. Huang BQ, Li CH, Tao F (2013) A chaos control optimal algorithm for QOS-based service composition selection in cloud manufacturing system. Enterp Inf Syst 8(4):445-463
234. Guo L, Wang SL, Kang L et al (2015) Agent-based manufacturing service discovery method for cloud manufacturing. Int J Adv Manuf Technol 81(9/12):2167-2181
235. Song TX, Liu HM, Wei CM et al (2014) Common engines of cloud manufacturing service platform for SMES. Int J Adv Manuf Technol 73(1/4):557-569
236. DeSmit Z, Elhabashy AE, Wells LJ et al (2017) An approach to cyber-physical vulnerability assessment for intelligent manufacturing systems. J Manuf Syst 43:339-351
237. Wang KS, Sharma VS, Zhang ZY (2014) SCADA data based condition monitoring of wind turbines. Adv Manuf 2(1):61-69
238. Feng Y, Huang BQ (2018) Cloud manufacturing service QOS prediction based on neighbourhood enhanced matrix factorization. J Intell Manuf. https://doi.org/10.1007/s10845-018-1409-8
239. Lartigau J, Xu XF, Nie LS et al (2015) Cloud manufacturing service composition based on QOS with geo-perspective transportation using an improved artificial bee colony optimisation algorithm. Int J Prod Res 53(14):4380-4404
240. Wang KS, Li Z, Braaten J et al (2015) Interpretation and compensation of backlash error data in machine centers for intelligent predictive maintenance using ANNs. Adv Manuf 3(2):97-104
241. Liu ZW, Ming XG (2019) A framework with revised roughDEMATEL to capture and evaluate requirements for smart industrial product-service system of systems. Int J Prod Res 57:7104-7122
242. Liu Q, Liu ZH, Xu WJ et al (2019) Human-robot collaboration in disassembly for sustainable manufacturing. Int J Prod Res 57:4027-4044
243. Dyllick T, Rost Z (2017) Towards true product sustainability. J Clean Prod 162:346-360
244. He B, Gu ZC (2016) Sustainable design synthesis for product environmental footprints. Des Stud 45:159-186
245. He B, Xiao JL, Deng ZQ (2018) Product design evaluation for product environmental footprint. J Clean Prod 172:3066-3080
246. Manfredi S, Allacker K, Pelletier N et al (2012) Product environmental footprint (PEF) guide. European Commission
247. He B, Shao Y, Wang S et al (2019) Product environmental footprints assessment for product life cycle. J Clean Prod 233:446-460
