Predictable inventory management within dairy supply chain operations

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:AI/MLをサプライチェーン最適化に適用する研究の現状を把握するためのレビューとして有用。

🏢実務担当者:在庫管理の効率化によるコスト削減と廃棄物削減の可能性を理解するための入門資料。

Purpose With the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC management Design/methodology/approach Preferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics. Findings As a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map. Practical implications Many sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set. Originality/value This paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.

• openalex https://doi.org/10.1108/ijrdm-01-2023-0051first seen 2026-08-02 17:43:49