Selection of Heavy Metal Detection Technologies and Improvement of Operational Efficiency in Food Enterprises for Whole Life Cycle Costs

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Authors: Xueting Liu
Cited by: 0

Abstract

As the global industrialization process accelerates, environmental pollution continues to worsen, and heavy metal contamination has become one of the top priorities in food safety. Food companies must prioritize heavy metal testing as a critical component of their food safety regulatory efforts to ensure food safety. Therefore, this paper analyzes the optimal path for food companies in selecting heavy metal testing technologies and the process of enhancing their lifecycle operational efficiency from a dual perspective of food safety and business operations, incorporating the core theoretical principles of lifecycle cost management. A framework has been established to quantify and analyze cost factors across all stages of the lifecycle, including equipment procurement, post-purchase staff training and daily maintenance, and final equipment disposal. This framework provides scientific recommendations based on cost analysis for decision-makers in food companies when selecting heavy metal detection technologies. Additionally, from the perspective of economic performance ratios such as detection costs, it offers practical and actionable suggestions for selecting appropriate heavy metal detection technologies. Analysis has shown that adopting a technology selection process based on lifecycle cost analysis can effectively improve heavy metal detection quality while reducing overall corporate costs. Through the exploration of combining and integrating technological innovation and management innovation, this study provides valuable methods and insights for promoting the modernization and transformation of the food industry.

Fields of Study & Subjects

Life Cycle Costing Analysis Food Safety and Hygiene Management and Optimization Techniques

Publication details

Journal / source
International Journal of Computer Information Systems and Industrial Management Applications
Volume
18
Pages
11–11
Publication date
13 January 2026
Language
EN