QR-code enabled product traceability system: a Big Data perspective

Product traceability can ensure high level of product: quality, integrity and availability. It is defined as the ability to track & trace individual items throughout their whole lifecycle from manufacturing to recycling. This includes real-time data about product physical location (ability to Track) and product historical data (ability to Trace). The need of such systems that can ensure product traceability within the Supply Chain is becoming increasingly important in multiple domains such as: food, pharmaceutical and cosmetics Supply chains because of the proliferation of counterfeit items, product diversions and grey market. To address this problem, multiple industry sectors are becoming more client-oriented and needs faster response to deal with such issues. However, current traceability systems didn’t consider systems interoperability which is an important factor in system adoption by supply chain actors. This paper presents a comparative study between several works on product traceability and proposes a standardized traceability system architecture. The proposed architecture includes all the supply chain actors over the whole product lifecycle. We consider a collaborative working between supply chain actors to ensure system integrity and guarantee safety and quality to consumers. We also propose a data management system that can collect, store, analyze and visualize data based on Big Data technologies. We demonstrate that using Big Data technologies can ensure system interoperability between the different supply chain actors. We also discuss several product identification systems and propose the use of QR-Code which can reduce traceability costs and guarantee a high level of security. Finally, we propose a multi-agent system-based simulation that can simulate product behavior in the supply chain. This simulator will be used to generate product data which will allow us to develop anti-counterfeit and non-conform products. We will also include a high-level of security tests to detect fraudulent access to database.