Citation :

Asha Kiran Ganesna, "Supply Chain Visibility and End-to-End Traceability: Enhancing Food Safety and Consumer Trust in the Consumer Products Industry," International Journal of Computer Trends and Technology (IJCTT), vol. 74, no. 8, pp. 18-27, 2026. Crossref, https://doi.org/10.14445/22312803/IJCTT-V74I8P103

Abstract

The consumer products industry has prioritized food safety incidents and opaque supply chains, as they are no longer an afterthought for them; it's become a strategic priority. This article discusses the practical benefits for foodborne illness risk reduction, quicker recalls, and consumer-trust restoration that can be achieved through end-to-end supply chain visibility, built on the Internet of Things, distributed ledger technology, and the power of artificial intelligence and machine learning. It suggests a 5-layer reference architecture covering data capture, connectivity, data integration and trust, AI/ML analytics and end-user visibility applications, and outlines AI/ML use cases such as anomaly detection, predictive quality scoring, computer-vision quality control, and graph-based trace-back, plus a “workflow” spanning incident to recall enabling continuous model retraining. The article also examines obstacles to implementation, such as data standardization, integration with legacy systems, and cost, and ends with a vision of digital twins, generative AI, and predictive recall. The tables and diagrams illustrate a comprehensive analysis to provide a structured and evidence-based reference for practitioners and researchers on designing and evaluating modern traceability programs.

Keywords

AI/ML Analytics, Consumer Trust, EPCIS/Blockchain, Food Safety, Supply Chain Traceability.

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