An Intelligent Decision Support System for the Empty Unit Load Device Repositioning Problem in Air Cargo Industry

Döppner, Daniel A.; Derckx, Patrick; Schoder, Detlef

doi:10.24251/hicss.2018.156

Cited by 5 publications

(4 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Future designs of drone cargo systems may benefit from international standardisation to help reduce the needs for such tests, using technologies similar to the large commercial aircraft standardised air freight containers and pallets, known as 'unit load devices' [58].…”

Section: Operational Aspectsmentioning

confidence: 99%

Investigating the Crash Protection Performance of a Medical Carrier Bag for Drone Transport

McLeod,

Cherrett,

Oakey

et al. 2024

Logistics

View full text Add to dashboard Cite

Background: Drone transport regulations in Europe require a crash-protected container (CPC) to be used for the carriage of dangerous goods. With increasing interest in the use of drones for medical logistics, the motivation behind this research was to investigate whether the existing approved medical carriers could also pass as CPCs. To date, there has been little practical experimentation on or theoretical research into the crash protection performance of medical containers. Methods: Addressing this gap, this paper reports findings from a series of drop test experiments to investigate the crashworthiness of a standard medical carrier bag used by the National Health Service (NHS) in the UK. Th drop tests were performed from heights of up to 122 m using standard medical carriers containing bags of dyed saline to examine the robustness of the carrier and whether it could contain any leakages, a key requirement for transporting dangerous goods. Results: The tests found that the medical carrier failed on some drops, with the zipped lid being identified as the main weakness. Conclusions: A new understanding of the carrier’s terminal velocity, impact acceleration, and failure mechanisms were gained and subsequent strengthening and waterproofing remedial measures recommended. New insights and practical recommendations are provided relating to performing formal drop tests and how to conduct these using a drone.

show abstract

Section: Operational Aspectsmentioning

confidence: 99%

Investigating the Crash Protection Performance of a Medical Carrier Bag for Drone Transport

McLeod,

Cherrett,

Oakey

et al. 2024

Logistics

View full text Add to dashboard Cite

show abstract

“…To achieve this, the case company employs ULD dispatchers who continuously monitor and control the company's logistic network and reallocate the ULD stocks. This problem is called the empty ULD repositioning (EUR) problem [15].…”

Section: Brief Case Descriptionmentioning

confidence: 99%

“…Artifact development has passed through three iterations and has produced multiple knowledge moments. The first iteration focused on developing an intelligent decision-support system using rule-based expert system technology to prove that the complex decision making of EUR can be supported by IT [15,18]. In the second iteration, the focus shifted to dividing labor between human and machine components and identifying a purposeful level of task automation [17].…”

Section: Brief Case Descriptionmentioning

confidence: 99%

“…In the second iteration, the focus shifted to dividing labor between human and machine components and identifying a purposeful level of task automation [17]. The third iteration focused on an emerging co-evolution that became apparent when the ULD dispatchers interacted with the artifact [16]. This study is positioned after the third iteration and is based on our learnings and reflections from the previous iterations.…”

Section: Brief Case Descriptionmentioning

confidence: 99%

See 1 more Smart Citation

Symbiotic Co-Evolution in Collaborative Human-Machine Decision Making: Exploration of a Multi-Year Design Science Research Project in the Air Cargo Industry

Döppner¹,

Derckx²,

Schoder³

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

Self Cite

View full text Add to dashboard Cite

The work world is set to undergo major changes thanks to advancements in automation and artificial intelligence and is beginning to promote new forms of collaboration. The transition from a technologysupporting environment to a collaborative environment in which people and technology work together to achieve their goals requires a fundamental change in the way we design, build, and ultimately deploy information systems. Most work on information system design focuses on the effective augmentation of humans. However, little is known about constructing a sustainable mutually beneficial collaboration between human and machine. To better understand this relationship, we perform a case study drawing on ethnographic evidence collected during a multi-year design science research project with a major service provider for unit load device management in the air cargo industry that resulted in an artifact for human-machine collaboration (HMC). Our study takes a closer look at the co-evolution that emerges from the collaboration between human and artificial agents over time, in which both parties influence each other, the underlying tasks, and their environment. Our analysis reveals three facets of symbiotic co-evolution: agents' evolution, activity evolution, and structural evolution. The findings contribute to the HMC knowledge base and have implications for future HMC design initiatives.

show abstract

Big data analytics for intelligent transportation systems

Dimitrakopoulos¹,

Uden²,

Varlamis³

2020

The Future of Intelligent Transport Systems

View full text Add to dashboard Cite

An Intelligent Decision Support System for the Empty Unit Load Device Repositioning Problem in Air Cargo Industry

Cited by 5 publications

References 2 publications

Investigating the Crash Protection Performance of a Medical Carrier Bag for Drone Transport

Investigating the Crash Protection Performance of a Medical Carrier Bag for Drone Transport

Symbiotic Co-Evolution in Collaborative Human-Machine Decision Making: Exploration of a Multi-Year Design Science Research Project in the Air Cargo Industry

Big data analytics for intelligent transportation systems

Contact Info

Product

Resources

About