Browsing by Author "Li, Jiahong"

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    Charting the course: standardization of quality assurance in digital twin applications across product lifecycle
    (Elsevier, 2024-11-27) Milisavljevic-Syed, Jelena; Khan, Mohammed; Xia, Hanbing; Li, Jiahong; Salonitis, Konstantinos
    Digital twins hold immense promise in accelerating scientific discovery and revolutionizing industries. The use cases for digital twins are diverse and proliferating, with applications across multiple areas of science, technology, and society, and their potential is wide-reaching. Despite the growing use of quality assurance approaches, standards, and frameworks in digital twins, the promise of digital twin benefits remains more aspirational than reality. Consequently, the confidence level in the prediction of these models is questionable. There is a lack of guidance on establishing standardization and interoperability as a foundation for integration of platforms, systems, and stakeholders within the digital twin ecosystem. To address this gap, we propose guidance for standardized quality assurance of digital twins in simulating product lifecycles, aiming to enhance regulatory decision-making. This proposed guidance is a step towards development of framework for standardized quality assurance of digital twins.
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    Integrating blockchain with digital product passports for managing reverse supply chain
    (Elsevier, 2025) Xia, Hanbing; Li, Jiahong; Li, Qian Jan; Milisavljevic-Syed, Jelena; Salonitis, Konstantinos
    The reverse supply chain (RSC), vital for circular economies, faces considerable challenges, including transparency deficits, trust issues, and inefficient information sharing. Blockchain can enhance transparency and traceability in circular economy practices, but it has limitations in providing detailed, product-specific lifecycle data. In contrast, the digital product passport (DPP) is designed to provide this detailed information, offering comprehensive, high-quality data across a product’s entire lifecycle. By integrating DPP, the inherent data limitations of blockchain can be overcame, making it a more useful tool in promoting sustainable practices. The aim of this research is to explore integrating blockchain technology and the DPP to manage RSC for circular economy practices. To achieve this, a novel conceptual framework is presented that merge blockchain with DPP, potentially enhancing information efficiency throughout the entire lifecycle of end-of-life products and reducing uncertainties in RSC processes.
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    Predictive maintenance servitisation pathways
    (Elsevier, 2024) Li, Jiahong; Milisavljevic-Syed, Jelena; Salonitis, Konstantinos
    The competition within the manufacturing industry is becoming increasingly intense in the Industry 4.0 era. Some manufacturers are transforming their traditional product-selling business model into product-service combos to gain customer loyalty and new sources of revenue through the so-called manufacturing servitisation. Predictive maintenance (PdM) is a strategy that significantly overlaps with manufacturing servitisation in terms of enabling technologies, including IoT, Big Data, Cloud Computing, etc. PdM is expected to both maximise productivity and minimise maintenance costs. Although much attention has been given to PdM and manufacturing servitisation, previous studies have ignored the synergy of PdM and manufacturing servitisation. This paper highlights the importance and feasibility of implementing PdM servitisation. Additionally, by analysing practical PdM servitisation cases, three PdM servitisation pathways are defined. Finally, the defined pathways are discussed, and future research directions are proposed.
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    Realisation of responsive and sustainable reconfigurable manufacturing systems
    (Taylor and Francis, 2023-07-18) Milisavljevic-Syed, Jelena; Li, Jiahong; Xia, Hanbing
    There is a lack of a design method for the manufacturing system reconfiguration to cope with the changing demand and evolving production technologies while minimising energy consumption. The key drivers for the new industrial paradigm are flexibility and sustainable manufacturing, which have been studied independently in the prior research. The aim of this research is to study two drivers simultaneously by designing robust models and analysing manufacturing system configurations to achieve feasible solutions in any scenario that may arise due to evolving, incomplete, and unforeseen production requirements, while minimising energy usage during product manufacture. To achieve this goal, this research develops a robustly validated pre-emptive decision engineering framework (DEF) for the manufacturing system reconfiguration process to manage future uncertainty of future conditions and identifies current production vulnerabilities and alternative production portfolios. In this research, a robust RMS reconfiguration strategy is designed using a compromise decision support problem (cDSP), and decentralised decision-making designs are explored through the use of game theory. The findings provide a new production system for adaptable, responsive, and sustainable manufacturing processes in the dynamic global economy. These results can empower stakeholders to make timely design decisions that lead to significant cost savings and sustainable manufacturing.
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    Transformation of the product lifecycle value chain towards industry 5.0
    (Elsevier, 2024-06) Xia, Hanbing; Li, Jiahong; Milisavljevic-Syed, Jelena; Salonitis, Konstantinos
    The transition from Industry 4.0 to Industry 5.0 has broadened the focus of enterprises, moving beyond their organisational boundaries limits to embrace the interconnected structure within the product lifecycle value chain. Despite this shift, there remains a significant gap in research on the framework for transforming the product lifecycle value chain from Industry 4.0 to Industry 5.0. Thus, building upon the achievements of Industry 4.0, the proposed value chain transformation frameworks are proposed, which can improve sustainability and resilience while considering human needs. The frameworks offer enterprises a comprehensive understanding of the structure and strategic approach required for the Industry 5.0 product lifecycle value chain transformation. Finally, the authors summarise six research challenges and opportunities and eleven research questions to advance the transformation of the Industry 5.0 product lifecycle value chain.