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Main Author: Ding, Junchun
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2511.05899
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author Ding, Junchun
author_facet Ding, Junchun
contents Under the market background of increasingly personalized product demand and compressed response cycle, the traditional manufacturing model with standardized mass production as the core has been difficult to meet the dual expectations of customers for differentiation and fast delivery. In order to improve the efficiency of resource allocation and market response, automobile manufacturers need to build a production system that takes into account cost and flexibility. Based on the delayed response manufacturing strategy, this study built an order response node configuration model suitable for automotive manufacturing scenarios, focusing on the positioning of order driven intervention points in the production process. The model comprehensively considers the structural cost changes brought by process adjustment, the dynamic characteristics of the changes of unit manufacturing cost and intermediate inventory cost at different stages with the location of nodes, and introduces delivery time constraints to embed time factors into the inventory decision logic to enhance the practicality of the model and the adaptation of realistic constraints. In terms of solution methods, this paper adopts function fitting and simulation analysis methods, combined with mathematical modeling tools, systematically describes the change trend of total cost, and verifies the rationality and effectiveness of the model structure and solution through actual enterprise cases. The research results provide a theoretical basis and decision support for automobile manufacturing enterprises to realize the synergy of flexible production and cost control in the environment of variable demand, and also provide an empirical reference for the implementation path and system optimization of subsequent relevant strategies.
format Preprint
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spellingShingle Research On CODP Localization Decision Model Of Automotive Supply Chain Based On Delayed Manufacturing Strategy
Ding, Junchun
Social and Information Networks
Under the market background of increasingly personalized product demand and compressed response cycle, the traditional manufacturing model with standardized mass production as the core has been difficult to meet the dual expectations of customers for differentiation and fast delivery. In order to improve the efficiency of resource allocation and market response, automobile manufacturers need to build a production system that takes into account cost and flexibility. Based on the delayed response manufacturing strategy, this study built an order response node configuration model suitable for automotive manufacturing scenarios, focusing on the positioning of order driven intervention points in the production process. The model comprehensively considers the structural cost changes brought by process adjustment, the dynamic characteristics of the changes of unit manufacturing cost and intermediate inventory cost at different stages with the location of nodes, and introduces delivery time constraints to embed time factors into the inventory decision logic to enhance the practicality of the model and the adaptation of realistic constraints. In terms of solution methods, this paper adopts function fitting and simulation analysis methods, combined with mathematical modeling tools, systematically describes the change trend of total cost, and verifies the rationality and effectiveness of the model structure and solution through actual enterprise cases. The research results provide a theoretical basis and decision support for automobile manufacturing enterprises to realize the synergy of flexible production and cost control in the environment of variable demand, and also provide an empirical reference for the implementation path and system optimization of subsequent relevant strategies.
title Research On CODP Localization Decision Model Of Automotive Supply Chain Based On Delayed Manufacturing Strategy
topic Social and Information Networks
url https://arxiv.org/abs/2511.05899