The fusion of Lean Manufacturing with Industry 4.0 technologies towards a new pillar for improving supply chain performance, the case of the automotive industry in Morocco

Authors

DOI:

https://doi.org/10.56294/dm2025473

Keywords:

Supply Chain resilience, Lean Manufacturing, JIT, Artificial Intelligence, Industry 4.0

Abstract

In response to the COVID-19 pandemic, a Moroccan automotive glass company embarked on a strategic overhaul to improve its supply chain performance and resilience. Faced with excessive working capital tied up in inventory (Working Capital = $200M), the company chose to integrate advanced artificial intelligence (AI) technologies with Lean Manufacturing principles, including Just-In-Time (JIT) production and workload balancing. The goal was to lower inventory levels while maintaining a high service rate to meet customer demands. AI tools have played a crucial role in predicting quality defects and forecasting equipment availability, facilitating streamlined operations and cost reduction. This initiative also aims to enhance the supply chain's ability to withstand and adapt to future disruptions

References

[1] Manzouri, Malihe, et Mohd Nizam Ab Rahman. 2013. « Adaptation of Theories of Supply Chain Management to the Lean Supply Chain Management ». International Journal of Logistics Systems and Management 14 (1): 38. https://doi.org/10.1504/IJLSM.2013.051019.

[2] Sethanan, K., Pitakaso, R., & Veerakittikul, K. (2020). Applying a Value Stream Mapping (VSM) to Improve Supply Chain Performance of Agricultural Products: A Case of Thai Exported Canned Lychee. Agriculture, 10(10), 442. https://doi.org/10.3390/agriculture10100442

[3] Marksberry, Phillip, Fazleena Badurdeen, Bob Gregory, et Ken Kreafle. 2010. « Management Directed Kaizen: Toyota’s Jishuken Process for Management Development ». Journal of Manufacturing Technology Management 21 (6): 670‑86. https://doi.org/10.1108/17410381011063987.

[4] Meunier, Frédéric. s.d. « Aléa et Temps Réel dans la Supply Chain : Outils Mathématiques ». Paris : Hermes Science Publications.

[5] Master Planning and Scheduling: An Essential Guide to Competitive Manufacturing - John F. Proud, Eric Deutsch - Google Livres

[6] H. Lakhouil and A. Soulhi, "Supply Chain Resilience Assessment in the 4.0 Era," 2024 IEEE 12th International Symposium on Signal, Image, Video and Communications (ISIVC), Marrakech, Morocco, 2024, pp. 1-7, doi: 10.1109/ISIVC61350.2024.10577939.

[7] Ponomarov, Serhiy Y., et Mary C. Holcomb. 2009. « Understanding the Concept of Supply Chain Resilience ». The International Journal of Logistics Management 20 (1): 124‑43. https://doi.org/10.1108/09574090910954873.

[8] Rachid, EL GADROURI. s. d. « Digital Supply Chain: Concepts, Emergence et Outils Technologiques. » 3.

[9] Ram Kumar, S., V. Nimesh Nathan, S.I. Mohammed Ashique, V. Rajkumar, et P. Arun Karthick. 2021. « Productivity Enhancement and Cycle Time Reduction in Toyota Production System through Jishuken Activity – Case Study ». Materials Today: Proceedings 37:964‑66. https://doi.org/10.1016/j.matpr.2020.06.181.

[10] Saengchai, Sakapas, et Kittisak Jermsittiparsert. 2019. « Coping Strategy to Counter the Challenges towards Implementation of Industry 4.0 in Thailand: Role of Supply Chain Agility and Resilience » 8 (5)

[11] Mimoun, GUENFOUDI. s. d. « LA LOGISTIQUE 4.0 : UNE REALITE » 4.

[12] Marinagi, Catherine, Panagiotis Reklitis, Panagiotis Trivellas, et Damianos Sakas. 2023. « The Impact of Industry 4.0 Technologies on Key Performance Indicators for a Resilient Supply Chain 4.0 ». Sustainability 15 (6): 5185. https://doi.org/10.3390/su15065185.

[13] Singh, Chandra Shekhar, Gunjan Soni, et Gaurav Kumar Badhotiya. 2019. « Performance Indicators for Supply Chain Resilience: Review and Conceptual Framework ». Journal of Industrial Engineering International 15 (S1): 105‑17. https://doi.org/10.1007/s40092-019-00322-2.

[14] Spieske, Alexander, Maximilian Gebhardt, Matthias Kopyto, Hendrik Birkel, et Evi Hartmann. 2023. « The Future of Industry 4.0 and Supply Chain Resilience after the COVID-19 Pandemic: Empirical Evidence from a Delphi Study ». Computers & Industrial Engineering 181 (juillet):109344. https://doi.org/10.1016/j.cie.2023.109344.

[15] Tortorella, Guilherme Luz, Rogério Feroldi Miorando, et Carlos Ernani Fries. 2018. « On the Relationship between Lean Supply Chain Management and Performance Improvement by Adopting Industry 4.0 Technologies ».

[16] Ugochukwu, Paschal, Jon Engstrom, et Jostein Langstrand. 2012. « LEAN IN THE SUPPLY CHAIN: A LITERATURE REVIEW ». Management and Production Engineering Review 3 (4).

[17] Vanichchinchai, Assadej. 2019. « The Effect of Lean Manufacturing on a Supply Chain Relationship and Performance ». Sustainability 11 (20): 5751. https://doi.org/10.3390/su11205751.

[18] C. S. Singh, G. Soni, et G. K. Badhotiya, « Performance indicators for supply chain resilience: review and conceptual framework », J Ind Eng Int, vol. 15, no S1, p. 105‑117, déc. 2019, doi: 10.1007/s40092-019-00322-2.

[19] I. Ehrenhuber, H. Treiblmaier, C. E. Nowitzki, et M. Gerschberger, « Toward a framework for supply chain resilience », IJSCOR, vol. 1, no 4, p. 339, 2015, doi: 10.1504/IJSCOR.2015.075084.

[20] M. Moufaddal, A. Benghabrit, et I. Bouhaddou, « Industry 4.0: A roadmap to digital Supply Chains », in 2019 1st International Conference on Smart Systems and Data Science (ICSSD), Rabat, Morocco: IEEE, oct. 2019, p. 1‑9. doi: 10.1109/ICSSD47982.2019.9002751.

[21] A. Haddud et A. Khare, « The Impact of Digitizing Supply Chains on Lean Operations », in Marktorientiertes Produkt- und Produktionsmanagement in digitalen Umwelten, A. Khare, D. Kessler, et J. Wirsam, Éd., Wiesbaden: Springer Fachmedien Wiesbaden, 2018, p. 27‑46. doi: 10.1007/978-3-658-21637-5_3.

[22] E. G. Rachid, « Digital Supply Chain : Concepts, Emergence et Outils Technologiques. », vol. 3.

[23] L. Hatim et S. Aziz, « SUPPLY CHAIN RISK ASSESSMENT WITH FUZZY LOGIC APPLIED TO THE FAILURE MODE AND EFFECT ANALYSIS METHOD », . Vol., no 10, 2023.

[24] Lakhouil H, Soulhi A. Fuzzy Decision-Making Model for the inventory leveling under uncertainty condition. Data and Metadata 2024;3:142. https://doi.org/10.56294/dm2024142.

[25] Pimor, Yves, et Michel Fender. 2008. Logistique: production, distribution, soutien. 5e éd. Paris: L’Usine nouvelle: Dunod.

Downloads

Published

2025-01-01

Issue

Section

Original

How to Cite

1.
Lakhouil H, soulhi A. The fusion of Lean Manufacturing with Industry 4.0 technologies towards a new pillar for improving supply chain performance, the case of the automotive industry in Morocco. Data and Metadata [Internet]. 2025 Jan. 1 [cited 2024 Dec. 13];4:473. Available from: https://dm.ageditor.ar/index.php/dm/article/view/473