Artificial Intelligence Approach to Business Process Re-Engineering the Information Flow of Warehouse Shipping Orders: An Italian Case Study
Source abstract
Abstract
Artificial intelligence is revolutionizing and significantly shaping the work environment. It not only presents an innovative and unique challenge, but it also creates numerous opportunities in various sectors. This study aims to examine a case of artificial intelligence use in the logistics sector, specifically the implementation of text recognition algorithms that use advanced artificial intelligence technology to perform tasks and activities typically carried out by human operators. The implementation under analysis was carried out at an Italian company in Tolentino, in the province of Macerata. The implementation of this tool focuses on the ability to autonomously read shipping notes, with the aim of simplifying the flow of information in the goods receipt phase and reducing the workload of warehouse staff. As illustrated in the following chapters, when artificial intelligence follows several trainings, technical improvements and structural changes in shipping notes, the flow is greatly simplified, significantly facilitating this logistics phase.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Manufacturing and Logistics Optimization · Law, logistics, and international trade · Business Process Modeling and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Industrial Engineering and Mathematical Sciences, Marche Polytechnic University, Via Brecce Bianche 12, 60131 Ancona, Italy
References (22)
Show source-provided references
1. Rethinking text rectification for scene text recognition10.1016/j.eswa.2023.119647 ↗
2. An improved correlation method for character recognition
3. Classification of handprinted Kanji characters by the structured segment matching method10.1016/0167-8655(83)90089-2 ↗
4. Iijima, T., Genchi, H., and Mori, K. (November, January 30). A theory of character recognition by pattern matching method. Proceedings of the 1st International Journal of Current Pharmaceutical Review and Research (IJCPR’73), Washington, DC, USA.
5. Recognition of Printed Chinese Characters
6. Yamamoto, S., Nakajima, A., and Nakata, K. (November, January 30). Chinese character recognition by hierarchical pattern matching. Proceedings of the 1st International Journal of Current Pharmaceutical Review and Research (IJCPR’73), Washington, DC, USA.
7. Methods of combining multiple classifiers and their applications to handwriting recognition10.1109/21.155943 ↗
8. On combining classifiers10.1109/34.667881 ↗
9. The construction and application of knowledge navigator model (KNM™): An evaluation of knowledge management maturity10.1016/j.eswa.2008.03.005 ↗
10. Zouhri, C., Khedher, F., Ahlaqqach, M., Babay, A., Hlyal, M., and Alami, J.E. (2023, January 5–6). Application of Artificial Intelligence for Improving Internal Logistics in the Garment Industry: A Literature Review. Proceedings of the 2023 9th International Conference on Optimization and Applications (ICOA), AbuDhabi, United Arab Emirates.10.1109/ICOA58279.2023.10308836 ↗
11. Saxena, P., Sharma, S., and Jora, R.B. (2023, January 17–18). Impact of Emotional Intelligence and Artificial Intelligence on Employee Retention: A Review of the Service Industry. Proceedings of the 2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India.10.1109/ICACCS57279.2023.10113017 ↗
12. Ghouati, S., El Amri, A., and Oulfarsi, S. (2022, January 25–27). The impact of Artificial Intelligence on Supply Chain: Literature review and conceptual framework. Proceedings of the 2022 14th International Colloquium of Logistics and Supply Chain Management (LOGISTIQUA), El Jadida, Morocco.10.1109/LOGISTIQUA55056.2022.9938119 ↗
13. Shatat, A., and Shatat, A. (2022, January 22–23). The Use of Artificial Intelligence Capabilities in Logistics and Supply Chain Management: Major Challenges and Key Benefits. Proceedings of the 2022 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS), Manama, Bahrain.10.1109/ICETSIS55481.2022.9888901 ↗
14. Horowitz, M.C. (2018). Artificial Intelligence, International Competition, and the Balance of Power, Texas National Security Review.
15. Staff, V.B. (2024, September 28). Why Do 87% of Data Science Projects Never Make It into Production. Available online: https://venturebeat.com/ai/why-do-87-of-data-science-projects-never-make-it-into-production/.
16. Gong, X. (2022, January 17–19). Optimization Algorithm of Logistics Warehousing and Distribution Path based on Artificial Intelligence Technology. Proceedings of the 2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE), Frankfurt, Germany.10.1109/ISAIEE57420.2022.00083 ↗
17. Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges10.1016/j.jmsy.2024.02.010 ↗
18. Xu, W., and Zhao, L. (2023, January 9–11). The Influence of Artificial Intelligence on Workers’ View of Technology. Proceedings of the 2023 International Conference on Machine Learning and Cybernetics (ICMLC), Adelaide, Australia.10.1109/ICMLC58545.2023.10327952 ↗
19. Sheng, F., Chen, Z., and Xu, B. (2019, January 20–25). NRTR: A no-recurrence sequence-to-sequence model for scene text recognition. Proceedings of the 2019 International Conference on Document Analysis and Recognition (ICDAR), Sydney, NSW, Australia.10.1109/ICDAR.2019.00130 ↗
20. Wan, Q., Ji, H., and Shen, L. (2019, January 15–20). Self-attention based text knowledge mining for text detection. Proceedings of the IEEE/CVF Conference on Computer Vision and Recognition, Long Beach, CA, USA.
21. Nguyen, N.-L., Lam, G.-H., Vo, H.-T., Do, T.-H., Tran, A.-T., and Cho, S. (2022, January 19–21). Improving Scene Text Recognition With A Combinative Image Augmentation Approach. Proceedings of the 2022 13th International Conference on Information and Communication Technology Convergence (ICTC), Jeju Island, Republic of Korea.10.1109/ICTC55196.2022.9952873 ↗
22. Wan, Q., Ji, H., and Shen, L. (2021, January 19–25). Self-attention based Text Knowledge Mining for Text Detection. Proceedings of the 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA.10.1109/CVPR46437.2021.00592 ↗