Caldwell, S (2024) Empirical Decision-Making Tools as Applied to Seaports in the Industry 4.0 Paradigm. Doctoral thesis, Liverpool John Moores University.

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Abstract

Purpose: Seaports are regarded as vital nodes within maritime supply chain operations that represent 80% of globalised trade by volume when compared to other nodes of transportation. They represent logistical hubs that constitute as the interface between land and sea transportation, facilitating the processing and storing of a variety of diverse cargoes; break-bulk, liquid, containerised, refrigerated, passenger, and roll-on/ roll-off for on-ward delivery to suppliers and end users. By their operating nature, seaports and container terminals are characterised by conservatism, fragmentation, complexity, and uncertainty making them ideal candidates for strategic decision-support tools that underpin the sustained competitive advantages facilitated by Industry 4.0 embedded technologies. Method: A range of data mapping techniques have been surveyed and the author proposes an observational modelling approach adapted from an existing visualisation technique (Value Stream Mapping/ VSM) as the route to improved strategic decision-support capabilities. The suitability of these techniques to map seaport operations was underpinned by a series of semi-structured interviews, in-depth interviews, and a process walk-through. Research Implications: This approach values practitioner-led, direct measurement and data collection with a process of considered planning for potential future states focused upon digital technologies and automation. The research integrates academic and practitioner literature, facilitating the development of a new mapping technique (Empirical Decision-Making Tools). integrated as part of a decision-support framework. 2 Practical Implications The EDMTs represent a dynamic range of visualisation tools (Process-Flow Mapping, Supply Chain Data Matrix, Decision-Point Analysis, Accuracy Completeness Amplification Mapping, and Key Characteristics of a Seaport) that are applicable to seaports that vary in size, capacity, handling specification, location, and Industry 4.0 readiness. The increased demand for time-critical decision support is addressed by their adaptability to deliver real-time visualisations of the current operational state that underpin a method of continuous improvement within a future representation of an ideal operating state. This facilitates an enhanced understanding in terms of both asset management and situational awareness of disparate and scarce resources of the seaport (berth occupation duration, labour allocation, crane capacity, throughput rate, and vessel turnaround time).

Item Type:	Thesis (Doctoral)
Uncontrolled Keywords:	Supply Chain Management (SCM); ), Data Visualisation; Big Data Analytics (BDA); Industry 4.0; Port Community Systems (PCS); Smart Seaports; , Value Stream Mapping (VSM); Empirical Decision-Making Tools (EDMTs)
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering
Divisions:	Engineering
SWORD Depositor:	A Symplectic
Date Deposited:	05 Dec 2024 18:00
Last Modified:	05 Dec 2024 18:00
DOI or ID number:	10.24377/LJMU.t.00024910
Supervisors:	Darlington, R
URI:	https://researchonline.ljmu.ac.uk/id/eprint/24910

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