Browsing by Author "Schaefer, Dirk"

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    Industry 4.0: a systematic review of legacy manufacturing system digital retrofitting
    (EDP Sciences, 2022-11-07) Alqoud, Abdulrahman; Schaefer, Dirk; Milisavljevic-Syed, Jelena
    Industry 4.0 technologies and digitalised processes are essential for implementing smart manufacturing within vertically and horizontally integrated production environments. These technologies offer new ways to generate revenue from data-driven services and enable predictive maintenance based on real-time data analytics. They also provide autonomous manufacturing scheduling and resource allocation facilitated by cloud computing technologies and the industrial Internet of Things (IoT). Although the fourth industrial revolution has been underway for more than a decade, the manufacturing sector is still grappling with the process of upgrading manufacturing systems and processes to Industry 4.0-conforming technologies and standards. Small and medium enterprises (SMEs) in particular, cannot always afford to replace their legacy systems with state-of-the-art machines but must look for financially viable alternatives. One such alternative is retrofitting, whereby old manufacturing systems are upgraded with sensors and IoT components to integrate them into a digital workflows across an enterprise. Unfortunately, to date, the scope and systematic process of legacy system retrofitting, and integration are not well understood and currently represent a large gap in the literature. In this article, the authors present an in-depth systematic review of case studies and available literature on legacy system retrofitting. A total of 32 papers met the selection criteria and were particularly relevant to the topic. Three digital retrofitting approaches are identified and compared. The results include insights common technologies used in retrofitting, hardware and software components typically required, and suitable communication protocols for establishing interoperability across the enterprise. These form an initial basis for a theoretical decision-making framework and associated retrofitting guide tool to be developed.
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    Towards pre-emptive resilience in military supply chains: a compromise decision support model-based approach
    (Taylor & Francis, 2023-06-09) Sani, Shehu; Schaefer, Dirk; Milisavljevic-Syed, Jelena
    The complex and dynamic nature of military supply chains (MSC) requires constant vigilance to sense potential vulnerabilities. Several studies have employed decision support models for the optimization of their operations. These models are often limited to a best single-point solution unsuitable for complex MSC constellations. In this article, the authors present a novel approach based on decision support models to explore a range of satisficing solutions against disruptions in MSCs using a compromise Decision Support Problem (cDSP) construct and Decision Support in the Design of Engineered Systems (DSIDES). Two cases were evaluated: (1) a baseline scenario with no disruption and (2) with disruption to achieve target values of three goals: (1) minimizing lead time, (2) maximizing demand fulfilment and (3) maximizing vehicle utilization. The results obtained in Case 1 identified a more stable solution space with minimal deviations from the target value, while in Case 2 the solution space was unstable with deviations from the target values.