The impact of Industry 4.0 on bottleneck analysis in production and manufacturing: Current trends and future perspectives

Ehsan Mahmoodi; Masood Fathi; Morteza Ghobakhloo

doi:10.1016/j.cie.2022.108801

journal article Open Access Dec 01, 2022

The impact of Industry 4.0 on bottleneck analysis in production and manufacturing: Current trends and future perspectives

Ehsan Mahmoodi

Masood Fathi

Morteza Ghobakhloo

Computers & Industrial Engineering Vol. 174 pp. 108801 · Elsevier BV

View at Publisher Save 10.1016/j.cie.2022.108801

Topics

No keywords indexed for this article. Browse by subject →

References

82

[1]

Akter "Transforming business using digital innovations: The application of AI, blockchain, cloud and data analytics" Annals of Operations Research (2022) 10.1007/s10479-020-03620-w

[2]

Alavian "Smart production systems: Automating decision-making in manufacturing environment" International Journal of Production Research (2019) 10.1080/00207543.2019.1600765

[3]

Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems

V. Alcácer, V. Cruz-Machado

Engineering Science and Technology, an Internation... 2019 10.1016/j.jestch.2019.01.006

[4]

Benitez "Industry 4.0 innovation ecosystems: An evolutionary perspective on value cocreation" International Journal of Production Economics (2020) 10.1016/j.ijpe.2020.107735

[5]

Betterton "Detecting bottlenecks in serial production lines – a focus on interdeparture time variance" International Journal of Production Research (2012) 10.1080/00207543.2011.596847

[6]

Brettel "How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective" International Journal of Information and Communication Engineering (2014)

[7]

Büchi "Smart factory performance and Industry 4.0" Technological Forecasting and Social Change (2020) 10.1016/j.techfore.2019.119790

[8]

Implementing Industry 4.0 principles

Héctor Cañas, Josefa Mula, Manuel Díaz-Madroñero et al.

Computers & Industrial Engineering 2021 10.1016/j.cie.2021.107379

[9]

Cayo "A shifting bottleneck procedure with multiple objectives in a complex manufacturing environment" Production Engineering (2020) 10.1007/s11740-019-00947-7

[10]

Chang, C. L., Wu, H. Y., & Chen, C. K. (2016). Heuristic methods for Q-time bottleneck dispatching. E-Manufacturing and Design Collaboration Symposium 2016, EMDC 2016 - Proceedings.

[11]

Ching "Industry 4.0 applications for sustainable manufacturing: A systematic literature review and a roadmap to sustainable development" Journal of Cleaner Production (2021)

[12]

Culot "Behind the definition of Industry 4.0: Analysis and open questions" International Journal of Production Economics (2020) 10.1016/j.ijpe.2020.107617

[13]

de Paula Ferreira "Simulation in industry 4.0: A state-of-the-art review" Computers & Industrial Engineering (2020) 10.1016/j.cie.2020.106868

[14]

Espinoza Pérez "Mass customized/personalized manufacturing in Industry 4.0 and blockchain: Research challenges, main problems, and the design of an information architecture" Information Fusion (2022) 10.1016/j.inffus.2021.09.021

[15]

Estrada-Jimenez "Characteristics of Adaptable Control of Production Systems and the Role of Self-organization Towards Smart Manufacturing" IFIP Advances in Information and Communication Technology (2021)

[16]

Fang "A Parallel Gated Recurrent Units (P-GRUs) network for the shifting lateness bottleneck prediction in make-to-order production system" Computers & Industrial Engineering (2020) 10.1016/j.cie.2019.106246

[17]

Industry 4.0 technologies: Implementation patterns in manufacturing companies

Alejandro Germán Frank, Lucas Santos Dalenogare, Néstor Fabián Ayala

International Journal of Production Economics 2019 10.1016/j.ijpe.2019.01.004

[18]

Gao, S., Higashi, T., Kobayashi, T., Taneda, K., Rubrico, J. I. U., & Ota, J. (2020). Buffer Allocation via Bottleneck-Based Variable Neighborhood Search. Applied Sciences 2020, Vol. 10, Page 8569, 10(23), 8569. 10.3390/app10238569

[19]

The future of manufacturing industry: a strategic roadmap toward Industry 4.0

Morteza Ghobakhloo

Journal of Manufacturing Technology Management 2018 10.1108/jmtm-02-2018-0057

[20]

Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing

Morteza Ghobakhloo, Masood Fathi

Journal of Manufacturing Technology Management 2020 10.1108/jmtm-11-2018-0417

[21]

Ghobakhloo "Industry 4.0 ten years on: A bibliometric and systematic review of concepts, sustainability value drivers, and success determinants" Journal of Cleaner Production (2021) 10.1016/j.jclepro.2021.127052

[22]

Goldratt (1986)

[23]

Grassi "On the modelling of a decentralized production control system in the Industry 4.0 environment" IFAC-PapersOnLine (2020) 10.1016/j.ifacol.2020.12.2850

[24]

Hao "Text mining approach for bottleneck detection and analysis in printed circuit board manufacturing" Computers & Industrial Engineering (2021) 10.1016/j.cie.2021.107121

[25]

Hofmann "Augmented Go & See: An approach for improved bottleneck identification in production lines" Procedia Manufacturing (2019) 10.1016/j.promfg.2019.03.023

[26]

Hoshino "Multirobot coordination for flexible batch manufacturing systems experiencing bottlenecks" IEEE Transactions on Automation Science and Engineering (2010) 10.1109/tase.2010.2047857

[27]

Huang "A proactive task dispatching method based on future bottleneck prediction for the smart factory" International Journal of Computer Integrated Manufacturing (2019) 10.1080/0951192x.2019.1571241

[28]

Hwang "Developing performance measurement system for Internet of Things and smart factory environment" International journal of production research (2017) 10.1080/00207543.2016.1245883

[29]

Jia "Closed Bernoulli lines with finite buffers: Real-time performance analysis, completion time bottleneck and carrier control" International Journal of Control (2021) 10.1080/00207179.2019.1690690

[30]

Lai "Data-driven dynamic bottleneck detection in complex manufacturing systems" Journal of Manufacturing Systems (2021) 10.1016/j.jmsy.2021.07.016

[31]

Lai, X., Shui, H., & Ni, J. (2018). A Two-Layer Long Short-Term Memory Network for Bottleneck Prediction in Multi-Job Manufacturing Systems. ASME 2018 13th International Manufacturing Science and Engineering Conference, MSEC 2018, 3. 10.1115/msec2018-6678

[32]

Industry 4.0

Heiner Lasi, Peter Fettke, Hans-Georg Kemper et al.

Business & Information Systems Engineering 2014 10.1007/s12599-014-0334-4

[33]

Langer "Simulation study of a bottleneck-based dispatching policy for a maintenance workforce" International Journal of Production Research (2010) 10.1080/00207540802555769

[34]

Lei "Identification approach for bottleneck clusters in a job shop based on theory of constraints and sensitivity analysis" Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (2017) 10.1177/0954405415583884

[35]

Prescriptive analytics: Literature review and research challenges

Katerina Lepenioti, Alexandros Bousdekis, Dimitris Apostolou et al.

International Journal of Information Management 2020 10.1016/j.ijinfomgt.2019.04.003

[36]

Li "A systematic-theoretic analysis of data-driven throughput bottleneck detection of production systems" Journal of Manufacturing Systems (2018) 10.1016/j.jmsy.2018.03.001

[37]

Li "Real time production improvement through bottleneck control" International Journal of Production Research (2009) 10.1080/00207540802244240

[38]

Li, L., Chang, Q., Ni, J., Xiao, G., & Biller, S. (2007). Bottleneck detection of manufacturing systems using data driven method. ISAM 2007 - IEEE International Symposium on Assembly and Manufacturing, 76–81. 10.1109/isam.2007.4288452

[39]

Li "Throughput bottleneck prediction of manufacturing systems using time series analysis" Journal of Manufacturing Science and Engineering, Transactions of the ASME (2011) 10.1115/1.4003786

[40]

Llopis, J., Lacasa, A., Garcia, E., & Montés, N. (2021). Towards Real Time Bottleneck Detection using Miniterms. Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics, 165–170. 10.5220/0010552900002994

[41]

Lugaresi "Automated manufacturing system discovery and digital twin generation" Journal of Manufacturing Systems (2021) 10.1016/j.jmsy.2021.01.005

[42]

Martins, A., Costelha, H., & Neves, C. (2019). Shop Floor Virtualization and Industry 4.0. 19th IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2019. 10.1109/icarsc.2019.8733657

[43]

Mathiyazhagan "Integrating lean and agile practices for achieving global sustainability goals in Indian manufacturing industries" Technological Forecasting and Social Change (2021) 10.1016/j.techfore.2021.120982

[44]

Immediate impacts of COVID-19 pandemic on bean value chain in selected countries in sub-Saharan Africa

Eileen Bogweh Nchanji, Cosmas Kweyu Lutomia, Rowland Chirwa et al.

Agricultural Systems 2021 10.1016/j.agsy.2020.103034

[45]

Possik "Lean techniques impact evaluation methodology based on a co-simulation framework for manufacturing systems" International Journal of Computer Integrated Manufacturing (2021) 10.1080/0951192x.2021.1972468

[46]

Rocha "Bottleneck prediction and data-driven discrete-event simulation for a balanced manufacturing line" Procedia Computer Science (2022) 10.1016/j.procs.2022.01.314

[47]

Roser, C., Subramaniyan, M., Skoogh, A., & Johansson, B. (2021). An Enhanced Data-Driven Algorithm for Shifting Bottleneck Detection. IFIP Advances in Information and Communication Technology, 630 IFIP, 683–689. 10.1007/978-3-030-85874-2_74

[48]

Senna "Prioritizing barriers for the adoption of Industry 4.0 technologies" Computers & Industrial Engineering (2022) 10.1016/j.cie.2022.108428

[49]

Schmenner "The Pursuit of Productivity" Production and Operations Management (2015) 10.1111/poms.12230

[50]

Sharifi "Agile manufacturing in practice Application of a methodology" International Journal of Operations and Production Management (2001) 10.1108/01443570110390462

Showing 50 of 82 references

Metrics

50

Citations

82

References

Details

Published: Dec 01, 2022
Vol/Issue: 174
Pages: 108801
License: View

Authors

Cite This Article

Ehsan Mahmoodi, Masood Fathi, Morteza Ghobakhloo (2022). The impact of Industry 4.0 on bottleneck analysis in production and manufacturing: Current trends and future perspectives. Computers & Industrial Engineering, 174, 108801. https://doi.org/10.1016/j.cie.2022.108801

The impact of Industry 4.0 on bottleneck analysis in production and manufacturing: Current trends and future perspectives

You May Also Like