State of the Art and Future Directions of Digital Twins for Production Logistics: A Systematic Literature Review
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. Descriptive Analyses
Backward Reference Search
3.2. Content Analyses
3.3. Definitions of Digital Twins
3.3.1. Three Dimensions by Grieves
3.3.2. Definition by Glaessgen and Stargel
3.3.3. Five Dimensions by Tao et al.
3.3.4. Similarities and Differences of DT Definitions
3.4. Systematic Evaluation of the Identified Literature
3.4.1. Enabling Concepts
3.4.2. Areas of Operation and State of Development
3.4.3. Virtual Model Creation
3.4.4. Enterprise Information Systems
3.4.5. Decentralized Applications
3.4.6. Machinery Prognostics and Maintenance Management
3.5. Case Study Analyses
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Appropriateness | Records | Records [%] |
---|---|---|
Total | 93 | 100.00 |
High-appropriate papers | 24 | 25.81 |
Medium-appropriate papers | 23 | 24.73 |
Low-appropriate papers | 46 | 49.46 |
Source | Records | Records [%] |
---|---|---|
Applied Sciences Switzerland | 5 | 5.38 |
Journal of Manufacturing Systems | 4 | 4.30 |
Sensors | 4 | 4.30 |
Academy of Strategic Management Journal | 3 | 3.23 |
IEEE Access | 3 | 3.23 |
IFAC Papersonline | 3 | 3.23 |
Robotics and Computer Integrated Manufacturing | 3 | 3.23 |
EAI Endorsed Transactions on Energy Web | 2 | 2.15 |
International Journal of Computer Integrated Manufacturing | 2 | 2.15 |
Procedia CIRP | 2 | 2.15 |
Others | 62 | 66.67 |
Countries | Records |
---|---|
Germany | 26 |
China | 14 |
Russian Federation | 9 |
Hong Kong | 8 |
Italy | 7 |
South Korea | 6 |
United Kingdom | 5 |
United States | 4 |
Portugal | 4 |
Romania | 4 |
Hungary | 3 |
Slovakia | 3 |
Slovenia | 3 |
Affiliation | Records |
---|---|
The University of Hong Kong | 7 |
Jinan University | 6 |
Peter the Great St. Petersburg Polytechnic University | 3 |
Otto von Guericke University of Magdeburg | 3 |
Technical University of Cluj-Napoca | 3 |
Univerza v Ljubljani | 3 |
Macau University of Science and Technology | 3 |
Southern University of Science and Technology | 3 |
Index Keywords | Author Keywords | ||
---|---|---|---|
Digital Twin | 56.99% | Digital Twin (application) | 70.97% |
(Smart) Manufacturing (companies) | 24.73% | (Discrete Event/Logistics/Factory) simulation (model) | 18.28% |
Cyber-Physical Systems | 16.13% | Industry 4.0 | 17.20% |
Embedded systems | 15.05% | (Production/In-house/Digital/Smart/multi-modal) logistics (4.0) | 13.98% |
Life cycle | 15.05% | Cyber-Physical (production) Systems | 10.75% |
Industry 4.0 | 13.98% | (Smart) Supply Chain (management /digitization/control) | 8.60% |
Decision-making | 11.83% | Internet of Things (IoT) | 7.53% |
(Production) Logistics (processes) | 11.83% | Big Data | 6.45% |
Supply Chains | 10.75% | Decision (support/making) | 5.38% |
(Industrial) Internet of Things (IoT) | 10.75% | Smart manufacturing | 4.30% |
ID | Ref. No. | Authors and Year | No. of Citations |
---|---|---|---|
1 | [17] | Tao and Zhang, 2017 | 5 |
2 | [13] | Tao et al. 2018 | 5 |
3 | [11] | Kritzinger et al. 2018 | 4 |
4 | [22] | Zheng et al. 2019 | 3 |
5 | [27] | Tao et al. 2018 | 3 |
6 | [12] | Tao et al. 2019 | 3 |
7 | [28] | Tao et al. 2018 | 3 |
8 | [29] | Uhlemann et al. 2017 | 3 |
Ref. No. | Author and Year | DT Definition | Virtual Model | Type | Application Domain |
---|---|---|---|---|---|
[30] | Ceolho et al. 2021 | Tao et al. | DES | case study | Distribution Center, Automotive |
[31] | Guo et al. 2021 | Tao et al. | DES | case study | Electronics |
[32] | Jiang et al. 2021 | Tao et al. | DES | case study | Aerospace |
[33] | Pan et al. 2021 | Tao et al. | MDO | case study | Paint Manufacturer |
[34] | Vachalek et al. 2021 | Grieves | DES | case study | Laboratory |
[35] | Aglianos et al. 2020 | Glaessgen and Stargel | - | review | - |
[36] | Agostino et al. 2020 | Glaessgen and Stargel | DES | case study | Automotive |
[37] | Grigoriev et al. 2020 | Grieves | - | concept | - |
[38] | Hauge et al. 2020 | Tao et al. | GE | case study | Laboratory |
[39] | Hu et al. 2020 | Tao et al. | PS | case study | Electronics |
[40] | Makarova et al. 2020 | other | DES | case study | Automotive |
[21] | Sommer et al. 2020 | other | DES | case study | not assignable |
[41] | Wang and Wu, 2020 | Glaessgen and Stargel | AM | case study | not assignable |
[42] | Wang et al. 2020 | Tao et al. Glaessgen and Stargel | TWMLR | case study | Metalworking |
[43] | Herakovic et al. 2019 | Tao et al. | ABS | case study | Laboratory |
[44] | Nikolakis et al. 2019 | Grieves | CRS | case study | Warehouse |
[12] | Tao et al. 2019 | Tao et al. | - | review | - |
[22] | Zheng et al. 2019 | Tao et al. | PS | case study | Metalworking |
[45] | Krajcovic et al. 2018 | other | - | case study | not assignable |
[11] | Kritzinger et al. 2018 | other | - | review | - |
[19] | Kuehn, 2018 | other | - | concept | - |
[13] | Tao et al. 2018 | Tao et al. | - | concept | - |
[27] | Tao et al. 2018 | Tao et al. | PS | case study | Energy |
[46] | Yao et al. 2018 | Grieves | DES/AGV Simulator | case study | Laboratory |
[47] | Bottani et al. 2017 | other | DES/AGV Simulator | case study | not assignable |
[48] | Brenner and Hummel, 2017 | other | KD | case study | Laboratory |
[17] | Tao and Zhang, 2017 | Tao et al. | - | concept | - |
[29] | Uhlemann et al. 2017 | other | - | concept | - |
Cluster | Records | Records [%] |
---|---|---|
Enablers and Implementation Concepts | 5 | 17.86 |
Areas of Operation and State of Development | 3 | 10.71 |
Virtual Model Creation | 4 | 14.29 |
Enterprise Information Systems | 6 | 21.43 |
Decentralized Applications | 7 | 25.00 |
Machinery Prognostics and Maintenance Management | 3 | 10.71 |
Ref. No. | Authors and Year | Five Dimensions of Tao et al. | Fulfillment | ||||
---|---|---|---|---|---|---|---|
Physical Entity | Virtual Model | DT Data | Service System | Connection | |||
[30] | Ceolho et al. 2021 | x | x | 40% | |||
[31] | Guo et al. 2021 | x | x | x | x | 80% | |
[32] | Jiang et al. 2021 | x | x | x | 60% | ||
[33] | Pan et al. 2021 | x | x | 40% | |||
[34] | Vachalek et al. 2021 | x (lab) | x | x | 60% | ||
[36] | Agostino et al. 2020 | x | x | x | 60% | ||
[38] | Hauge et al. 2020 | x (lab) | x | x | 60% | ||
[39] | Hu et al. 2020 | x | x | x | x | x | 100% |
[40] | Makarova et al. 2020 | x | x | x | 60% | ||
[21] | Sommer et al. 2020 | x | x | 40% | |||
[41] | Wang and Wu, 2020 | x | x | x | x | x | 100% |
[42] | Wang et al. 2020 | x | x | x | x | x | 100% |
[43] | Herakovic et al. 2019 | x (lab) | x | x | x | x | 100% |
[44] | Nikolakis et al. 2019 | x | x | x | 60% | ||
[22] | Zheng et al. 2019 | x | x | x | x | x | 100% |
[45] | Krajcovic et al. 2018 | x | 20% | ||||
[27] | Tao et al. 2018 | x | x | x | x | x | 100% |
[46] | Yao et al. 2018 | x (lab) | x | x | x | x | 100% |
[47] | Bottani et al. 2017 | x | x | 40% | |||
[48] | Brenner and Hummel, 2017 | x (lab) | x | x | 60% | ||
Allocation | 90% | 90% | 70% | 60% | 35% |
Abbr. | Name | Records | Records [%] |
---|---|---|---|
DES | Discrete Event Simulation | 9 | 45.00 |
PS | Physical Simulation | 3 | 15.00 |
AGV Simulator | Automated Guided Vehicle Simulation | 2 | 10.00 |
ABS | Agent-based Simulation | 1 | 5.00 |
AM | Analytical Model | 1 | 5.00 |
CRS | Catmull-Rom Spline | 1 | 5.00 |
GE | Game Engine | 1 | 5.00 |
KD | Knowledge Database | 1 | 5.00 |
MDO | Multidisciplinary Design Optimization | 1 | 5.00 |
TWMLR | Time-Weighted Multiple Linear Regression | 1 | 5.00 |
Objective | Records | Records [%] |
---|---|---|
monitoring | 5 | 25.00 |
production scheduling | 3 | 15.00 |
AGV control | 3 | 15.00 |
overall equipment effectiveness (OEE) | 3 | 15.00 |
line balance rate | 2 | 10.00 |
reaction time | 2 | 10.00 |
workstation design | 2 | 10.00 |
lead time | 2 | 10.00 |
per capita productivity | 1 | 5.00 |
number of operators | 1 | 5.00 |
warehouse costs | 1 | 5.00 |
energy consumption | 1 | 5.00 |
travel distance | 1 | 5.00 |
travel time | 1 | 5.00 |
shop-floor management | 1 | 5.00 |
Domain | Records | Records [%] |
---|---|---|
laboratory production | 5 | 25.00 |
not assignable | 4 | 20.00 |
automotive | 3 | 15.00 |
electronics | 2 | 10.00 |
metalworking | 2 | 10.00 |
distribution center | 1 | 5.00 |
aerospace | 1 | 5.00 |
warehouse | 1 | 5.00 |
energy | 1 | 5.00 |
others | 1 | 5.00 |
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Kaiblinger, A.; Woschank, M. State of the Art and Future Directions of Digital Twins for Production Logistics: A Systematic Literature Review. Appl. Sci. 2022, 12, 669. https://doi.org/10.3390/app12020669
Kaiblinger A, Woschank M. State of the Art and Future Directions of Digital Twins for Production Logistics: A Systematic Literature Review. Applied Sciences. 2022; 12(2):669. https://doi.org/10.3390/app12020669
Chicago/Turabian StyleKaiblinger, Alexander, and Manuel Woschank. 2022. "State of the Art and Future Directions of Digital Twins for Production Logistics: A Systematic Literature Review" Applied Sciences 12, no. 2: 669. https://doi.org/10.3390/app12020669
APA StyleKaiblinger, A., & Woschank, M. (2022). State of the Art and Future Directions of Digital Twins for Production Logistics: A Systematic Literature Review. Applied Sciences, 12(2), 669. https://doi.org/10.3390/app12020669