Victor Prodonoff Jr., Yoon Min Hwang, Rick Mitchell, Samuel Bloch Da Silva

Auto-ID Lab, University of Cambridge, UK; Auto-ID Lab, ICU, Korea; IfM/CTM, University of Cambridge, UK; Embraer S.A., Brazil

This paper presents results from investigation performed within the Aerospace Identification Technologies Programme into methods for business case analysis and return on investment models. It focuses on aerospace logistics, as requested by Programme sponsors, and looks more specifically into the benefits from improved Tracking and Tracing to inventory management and decision-making in industrial operations. The research builds on previous work carried out within the Programme, yet its main contribution is the introduction of decision trees to the ROI analysis process. These are used as a tool for understanding and taking risk into account when designing the adoption path for automatic identification technologies.

Béla Pátkai, Lila Theodorou, Duncan McFarlane, Victor Prodonoff Jr.

Auto-ID Lab, University of Cambridge, UK

The complex task of identifying and monitoring mobile objects remotely for example, perishable goods, containers, vehicles and machine parts requires the efficient integration of sensors and a number of other technologies. This case study aims at analysing the requirements for such an integrated system and evaluating the functionality, applications and applicability of the GlobalTrak product of the System Planning Corporation against these requirements.