Purpose The purpose of this paper is to present the findings of a recent study conducted with the objective of addressing the problem of failure of baggage carts in the high-speed baggage tunnel at Heathrow Terminal 5 by the development of an innovative condition-based maintenance (CBM) system designed to meet the requirements of 21st century airport systems and Industry 4.0. Design/methodology/approach An empirical experimental approach to this action research was taken to install a vibration condition monitoring pilot test in the north tunnel at Terminal 5. Vibration data were collected over a 6-month period and analysed to find the threshold of good quality tyres and those with worn bearings that needed replacement. The results were compared with existing measures to demonstrate that vibration monitoring could be used as a predictive model for CBM. Findings The findings demonstrated a clear trend of increasing vibration velocity with age and use of the baggage cart wheels caused by wheel mass unbalanced inertia that was transmitted to the tracks as vibration. As a result, preventative maintenance is essential to ensure the smooth running of airport baggage. This research demonstrates that a healthy wheel produces vibration of under 60 mm/s whereas a damaged wheel measures up to 100 mm/s peak to peak velocity and this can be used in real-time condition monitoring to prevent baggage cart failure. It can also run as an autonomous system linked to AI and Industry 4.0 airport logic. Originality/value Whilst vibration monitoring has been used to measure movement in static structures such as bridges and used in rotating machinery such as railway wheels (Tondon and Choudhury, 1999); this is unique as it is the first time it has been applied on a stationary structure (tracks) carrying high-speed rotating machinery (baggage cart wheels). This technique has been patented and proven in the pilot study and is in the process of being rolled out to all Heathrow terminal connection tunnels. It has implications for all other airports worldwide and, with new economic sensors, to other applications that rely on moving conveyor belts.

Purpose:The findings of a recent study are presented, which was conducted with the objective of addressing the problem of the failure of baggage carts within the high-speed baggage tunnel at Heathrow Terminal 5 through the development of an innovative condition-based maintenance system designed to meet the requirements of 21 st century airport systems and Industry 4.0.Methodology: An empirical experimental approach to this action research was taken to install a vibration condition monitoring pilot test in the north tunnel at Terminal 5. Vibration data were collected over a 6-month period and analysed to determine the threshold for good quality tyres and those with worn bearings that needed replacing. The results were compared with existing measures to demonstrate that vibration monitoring could be used as a predictive model for condition-based maintenance. Findings:The findings demonstrated a clear trend of increasing vibration velocity with age, with the wheel mass unbalanced inertia of the carts being transmitted to the tracks as vibration. This research demonstrates that a healthy wheel produces a vibration of less than 60mm/s whereas a damaged wheel measures up to 100 mm/s peak to peak velocity, which can be used in real-time condition monitoring to prevent baggage cart failure. It can also run as an autonomous system linked to AI and Industry 4.0 airport logic.Originality/Value: Whilst vibration monitoring has been used to measure movement in static structures, such as bridges, and in rotating machinery, such as railway wheels (Tondon and Choudhury, 1999) this application is unique as it is the first time vibration monitoring has been applied to a stationary structure (tracks) carrying high-speed rotating machinery (baggage cart wheels). This technique has been patented and proven in the pilot study and is in the process of being rolled out across all Heathrow terminal connection tunnels. It has implications for all other airports world-wide, and also to other applications that rely on moving conveyor belts.

is a doctoral student at the University of Buckingham and holds a German Dpl.Ing in Scientific Engineering from the University of Bochum and a MSc in Operational Excellence from the University of Buckingham. As a baggage handling system designer and project manager, leading a worldwide initiative on behalf of Siemens, Frank has enabled the adoption of condition monitoring for baggage handling systems in major airports globally. After graduating in Engineering in 1994 Frank joined DEMAG, covering E design and logistics, then Mannesman in 1998, to develop material handling systems, which then became his specialism.

PurposeThe aim of this paper is to develop a contribution to knowledge that adds to the empirical evidence of predictive condition-based maintenance by demonstrating how the availability and reliability of current assets can be improved without costly capital investment, resulting in overall system performance improvementsDesign/methodology/approachThe empirical, experimental approach, technical action research (TAR), was designed to study a major Middle Eastern airport baggage handling operation. A predictive condition-based maintenance prototype station was installed to monitor the condition of a highly complex system of static and moving assets.FindingsThe research provides evidence that the performance frontier for airport baggage handling systems can be improved using automated dynamic monitoring of the vibration and digital image data on baggage trays as they pass a service station. The introduction of low-end innovation, which combines advanced technology and low-cost hardware, reduced asset failures in this complex, high-speed operating environment.Originality/valueThe originality derives from the application of existing hardware with the combination of edge and cloud computing software through architectural innovation, resulting in adaptations to an existing baggage handling system within the context of a time-critical logistics system.

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