Abstract
Internet technologies allow supply chains to use virtualizations dynamically in operational management processes. This will improve support for food companies in dealing with perishable products, unpredictable supply variations and stringent food safety and sustainability requirements. Virtualization enables supply chain actors to monitor, control, plan and optimize business processes remotely and in real-time through the Internet, based on virtual objects instead of observation on-site. This paper analyses the concept of virtual food supply chains from an Internet of Things perspective and proposes an architecture to implement enabling information systems. As a proof of concept, the architecture is applied to a case study of a fish supply chain. These developments are expected to establish a basis for virtual supply chain optimization, simulation and decision support based on on-line operational data. In the Internet of Things food supply chains can become self-adaptive systems in which smart objects operate, decide and learn autonomously.
Highlights
The food sector is a challenging domain from a supply chain management perspective
Food supply chains can be monitored, controlled, planned and optimized remotely and in real-time via the Internet based on virtual objects instead of observation on site
This paper especially looks at virtualization from a virtual things perspective, which is related to the Internet of Things (IoT) concept
Summary
The food sector is a challenging domain from a supply chain management perspective. It needs advanced control systems that can deal with perishable products, unpredictable supply variations and stringent food safety and sustainability requirements. Virtualization is a promising approach to meet these challenges It allows for simulation and optimization of food processes using software systems instead of conducting physical experiments (Singh and Erdogdu, 2004). With current Internet technologies virtualization can be used dynamically in the operational management of food supply chains (Saguy et al, 2013; Porter and Heppelmann, 2014; Verdouw et al, 2015). This may include the monitoring of temperature, microbiological information and other food quality parameters (Abad et al, 2009; Heising et al, 2013; Jedermann et al, 2014) The representation of these data in virtual objects allows for advanced capabilities that go beyond tracking and tracing, such as food quality deviation management, (re)planning and optimization functionalities (Verdouw et al, 2015). The third part describes how the architecture is applied to and validated in a case study of a fish supply chain
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
