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Data-Driven Asset Health Index – an application to evaluate Quay Cranes in container ports

Author

Listed:
  • Adolfo Crespo Del Castillo
  • Manu Sasidharan
  • Corbinian Nentwich
  • Jorge Merino
  • Ajith Kumar Parlikad

Abstract

Ports worldwide seek for more efficient and sustainable operations, relying on critical and valuable assets as their cranes. Internet of Things (IoT) technologies enable a better understanding of critical assets’ behaviour and lifecycle based on data, and development of asset management decision support tools. The Asset Health Index (AHI) is an asset condition score, designed to characterise the state of complex assets. This paper describes the process of developing a data-driven AHI. IoT sensors and Programmable Logic Controllers (PLC) in real operation time, together with information systems, and other more traditional sources of data are some of the data sources for the AHI. The index captures and quantifies dimensions affecting the asset lifecycle, allowing the comparison of the condition of assets and prioritise maintenance investments. The case study is conducted in Quay Cranes of the Port of Felixstowe (UK) as the object of this study and proof of concept.

Suggested Citation

  • Adolfo Crespo Del Castillo & Manu Sasidharan & Corbinian Nentwich & Jorge Merino & Ajith Kumar Parlikad, 2024. "Data-Driven Asset Health Index – an application to evaluate Quay Cranes in container ports," Maritime Policy & Management, Taylor & Francis Journals, vol. 51(8), pages 1805-1823, November.
    • Handle: RePEc:taf:marpmg:v:51:y:2024:i:8:p:1805-1823
    DOI: 10.1080/03088839.2023.2231449
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