Welcome to Francis Academic Press

Academic Journal of Business & Management, 2024, 6(1); doi: 10.25236/AJBM.2024.060111.

Research on Supply Chain Collaboration in Smart Manufacturing Based on Demand Forecasting

Author(s)

Yichen Pan

Corresponding Author:
Yichen Pan
Affiliation(s)

Miami University, Oxford, Ohio 45056, United States

Abstract

Smart manufacturing through supply chain collaboration refers to the use of advanced information technology and data analysis means to carry out refined management and collaborative optimization of each link in the supply chain, so as to achieve efficient coordination and cooperation among production, circulation, and service links. As the basis of supply chain collaboration, demand forecasting is of great significance to the smart manufacturing industry. Carrying out supply chain collaboration in smart manufacturing based on demand forecasting could improve the accuracy of production planning, reduce inventory costs, shorten the delivery cycle, enhance the flexibility of the supply chain, and optimize resource allocation, with the aim of improving the competitiveness and profitability of enterprises. In this paper, the significance of demand forecasting for supply chain collaboration in smart manufacturing is explored. The strategy of smart manufacturing supply chain collaboration based on demand forecasting is also investigated.

Keywords

demand forecasting; smart manufacturing; supply chain collaboration

Cite This Paper

Yichen Pan. Research on Supply Chain Collaboration in Smart Manufacturing Based on Demand Forecasting. Academic Journal of Business & Management (2024) Vol. 6, Issue 1: 79-84. https://doi.org/10.25236/AJBM.2024.060111.

References

[1] Lanxiang X. Towards Green Innovation by China’s Industrial Policy: Evidence From Made in China 2025[J]. Frontiers in Environmental Science,2022,10.

[2] GAO B, ZHU L. The Industrial Internet of Things: A Competitive Advantage in the Era of Smart Manufacturing[J].Political Economy Quarterly, 2023,2(01):135-155.

[3] WU Yongqing. Research on Supply Chain Collaboration Model for Intelligent Manufacturing [D]. Nanjing University of Posts and Telecommunications,2021.DOI:10.27251/d.cnki.gnjdc.2021.001529.

[4] Qiu Fusheng. Application of Intelligent Supply Chain in Intelligent Manufacturing (Upper)[J]. Logistics Technology and Application,2019,24(09):110-116.

[5] Chai, T. Y.. Collaboration between industrial artificial intelligence and industrial internet for production process intelligence and its future prospect[J]. Control Engineering,2023,30(08):1378-1388.DOI:10.14107/j.cnki.kzgc.20230492.

[6] Yang H, Kumara S, Bukkapatnam S T S, et al. The internet of things for smart manufacturing: A review[J]. IISE transactions, 2019, 51(11): 1190-1216.

[7] Kim M, Jeong J, Bae S. Demand forecasting based on machine learning for mass customization in smart manufacturing[C]//Proceedings of the 2019 International Conference on Data Mining and Machine Learning. 2019: 6-11.

[8] Tripathi V, Chattopadhyaya S, Mukhopadhyay A K, et al. Development of a data-driven decision-making system using lean and smart manufacturing concept in industry 4.0: A case study[J]. Mathematical Problems in Engineering, 2022.

[9] Wang ZM. Research on Supply Chain Cost Management of Manufacturing Enterprises in the Digital Era[D].Chang Jiang University,2023.