Data-Driven Supplier Management Framework: Integrating Machine Learning Models into Planning and Assessment Strategies

Civil aircraft programmes are distinguished by their considerable scale and duration. They also involve synergies with numerous suppliers. By establishing an effective evaluation mechanism for supplier programme management, the main manufacturer can regularly audit and monitor the quality of the supplier's work and the progress of the development to identify and correct problems in the supplier's project development process in good time.This paper presents in-depth applications of computer technology, such as machine learning-based prediction models and optimisation algorithms, to further improve the efficiency and accuracy of supplier planning control. In addition, this paper proposes a practical and efficient appraisal strategy for supplier program control, aiming to improve suppliers' program execution capability and project delivery quality.By establishing three rating levels, A, B and C, in the programme evaluation, the rating level directly affects the allocation of research and development funds to stimulate supplier enthusiasm and initiative.

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Publication Details

Published
2025-03-14
DOI
https://doi.org/10.1145/3736426.3736474
Primary Topic
Oil and Gas Production Techniques
Type
article
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article

Data-Driven Supplier Management Framework: Integrating Machine Learning Models into Planning and Assessment Strategies

Shiyin Wang, Y. N. Gao, Nuo Lin
Oil and Gas Production Techniques
article

Data-Driven Supplier Management Framework: Integrating Machine Learning Models into Planning and Assessment Strategies

Shiyin Wang, Y. N. Gao, Nuo Lin
article en

Abstract

Civil aircraft programmes are distinguished by their considerable scale and duration. They also involve synergies with numerous suppliers. By establishing an effective evaluation mechanism for supplier programme management, the main manufacturer can regularly audit and monitor the quality of the supplier's work and the progress of the development to identify and correct problems in the supplier's project development process in good time.This paper presents in-depth applications of computer technology, such as machine learning-based prediction models and optimisation algorithms, to further improve the efficiency and accuracy of supplier planning control. In addition, this paper proposes a practical and efficient appraisal strategy for supplier program control, aiming to improve suppliers' program execution capability and project delivery quality.By establishing three rating levels, A, B and C, in the programme evaluation, the rating level directly affects the allocation of research and development funds to stimulate supplier enthusiasm and initiative.

Openalex Percentile: Top 80%
Oil and Gas Production Techniques
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Data-Driven Supplier Management Framework: Integrating Machine Learning Models into Planning and Assessment Strategies — Shiyin Wang, Y. N. Gao, et al. · (2025) | TGRS Research Map | TGRS