The DOI matches its Crossref record; 31 of the 32 references it cites were found in a registry or an index.
Design and application of Internet of things-based warehouse management system for smart logistics
Open accessAbstract
Warehouse operations need to change due to the increasing complexity and variety of customer orders. The demand for real-time data and contextual information is requried because of the highly customised orders, which tend to be of small batch size but with high variety. Since the orders frequently change according to customer requirements, the synchronisation of purchase orders to support production to ensure on-time order fulfilment is of high importance. However, the inefficient and inaccurate order picking process has adverse effects on the order fulfilment. The objective of this paper is to propose an Internet of things (IoT)-based warehouse management system with an advanced data analytical approach using computational intelligence techniques to enable smart logistics for Industry 4.0. Based on the data collected from a case company, the proposed IoT-based WMS shows that the warehouse productivity, picking accuracy and efficiency can be improved and it is robust to order variability.
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“Smart transportation enabled by AIoT covers traffic participants (e.g., smart internet of vehicles [256]), traffic infrastructures [257], and industry applications (e.g., smart connected logistics [258]).”
From Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things (2021) · cites this paper as [258]
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Cites
A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems
Lee, J., Bagheri, B., & Kao, H.-A. (2015) · Manufacturing Letters · doi:10.1016/j.mfglet.2014.12.001 · Cited by 5,113
Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014) · Business & Information Systems Engineering · doi:10.1007/s12599-014-0334-4 · Cited by 4,276
Design and Control of Warehouse Order Picking: a literature reviewPreprint
de Koster, R. B. M., Le-Duc, T., & Roodbergen, K. J. (n.d.) · RePEc: Research Papers in Economics · Cited by 1,961
Waller, M. A., & Fawcett, S. E. (2013) · Journal of Business Logistics · doi:10.1111/jbl.12010 · Cited by 1,522
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Software-Defined Industrial Internet of Things in the Context of Industry 4.0
Wan, J., Tang, S., Shu, Z., Li, D., Wang, S., Imran, M. A., & Vasilakos, A. V. (2016) · IEEE Sensors Journal · doi:10.1109/jsen.2016.2565621 · Cited by 691
Leitão, P., Colombo, A. W., & Karnouskos, S. (2015) · Computers in Industry · doi:10.1016/j.compind.2015.08.004 · Cited by 674
Visual Computing as a Key Enabling Technology for Industrie 4.0 and Industrial Internet
Posada, J., Toro, C., Barandiarán, Í., Oyarzun, D., Stricker, D., Amicis, R. D., Pinto, E. B., Eisert, P., Döllner, J., & Vallarino, I. (2015) · IEEE Computer Graphics and Applications · doi:10.1109/mcg.2015.45 · Cited by 618
Toward a Physical Internet: meeting the global logistics sustainability grand challenge
Montreuil, B. (2011) · Logistics Research · doi:10.1007/s12159-011-0045-x · Cited by 596
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Research works printed but not linked: 2
- 10.1016/j.ejor.2006.07.009 · DOI · Paper page
- Wan J., 2016, IEEE Sensors Journal, 16, 7373
Cited by
Sorted by citations
Zhang, J., & Tao, D. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3039359 · Cited by 774
“Smart transportation enabled by AIoT covers traffic participants (e.g., smart internet of vehicles [256]), traffic infrastructures [257], and industry applications (e.g., smart connected logistics [258]).”
BackgroundZheng, T., Ardolino, M., Bacchetti, A., & Perona, M. (2020) · International Journal of Production Research · doi:10.1080/00207543.2020.1824085 · Cited by 744
“Fuzzy logic incorporated with machine learning algorithms can support and improve the order picking process (Lee et al. 2018).”
MethodInternet of things for smart factories in industry 4.0, a review
Soori, M., Behrooz Arezoo, B., & Dastres, R. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.04.006 · Cited by 636
Smart logistics based on the internet of things technology: an overview
Ding, Y., Jin, M., Sen, L., & Feng, D. (2020) · International Journal of Logistics Research and Applications · doi:10.1080/13675567.2020.1757053 · Cited by 448
“space utilisation, misplaced stocks, and errors in inventory records (Lee et al. 2018; Lim, Bahr, and Leung 2013; Poon et al. 2009).”
BackgroundIndustry 4.0 and supply chain sustainability: framework and future research directions
Bag, S., Telukdarie, A., Pretorius, J. H. C., & Gupta, S. (2018) · Benchmarking An International Journal · doi:10.1108/bij-03-2018-0056 · Cited by 396
Metadata
- Authors
- Lee, C. K. M., Lv, Y., Ng, K. K. H., Ho, W., & Choy, K. L.
- Affiliations
- Hong Kong Polytechnic University (HK)
- Wuhan University of Technology (CN)
- The University of Melbourne (AU)
- Corresponding author
- Lv, Yaqiong
- Venue
- International Journal of Production Research
- Publisher
- Informa UK Limited
- Published
- 2017-10-27
- Volume
- 56
- Issue
- 8
- Pages
- 2753-2768
- ISSN
- 0020-7543 (ISSN-L)
- 1366-588X
- OpenAlex
- W2766877481
- Cited by
- 431
- References
- 32
- Citations by year
- 2026: 21 · 2025: 47 · 2024: 48 · 2023: 88 · 2022: 62 · 2021: 69 · 2020: 59 · 2019: 29 · 2018: 8
- FWCI
- 28.78
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- International Journal of Production Research (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion)
- Funders
- Collabroative Reserach (H-ZDAR)
- Collaborative Research (H-ZDAR)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Advanced Manufacturing and Logistics Optimization
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Keywords
- Internet of Things, warehouse management systems, smart logistics, order picking, order fulfillment, order variability, Industry 4.0, real-time analytics, computational intelligence, warehouse productivity
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