Selection of Heavy Metal Detection Technologies and Improvement of Operational Efficiency in Food Enterprises for Whole Life Cycle Costs
DOI:
https://doi.org/10.70917/ijcisim-2026-0064Keywords:
food safety; heavy metal detection; lifecycle cost; operational efficiency; technology selectionAbstract
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.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Xueting Liu

This work is licensed under a Creative Commons Attribution 4.0 International License.