Browsing by Author "Higgins, Nigel"
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Item Open Access Challenges of digital twin in high value manufacturing(SAE International, 2018-10-30) Singh, Sumit; Shehab, Essam; Higgins, Nigel; Fowler, Kevin; Tomiyama, Tetsuo; Fowler, ChrisDigital Twin (DT) is a dynamic digital representation of a real-world asset, process or system. Industry 4.0 has recognised DT as the game changer for manufacturing industries in their digital transformation journey. DT will play a significant role in improving consistency, seamless process development and the possibility of reuse in subsequent stages across the complete lifecycle of the product. As the concept of DT is novel, there are several challenges that exist related to its phase of development and implementation, especially in high value manufacturing sector. The paper presents a thematic analysis of current academic literature and industrial knowledge. Based on this, eleven key challenges of DT were identified and further discussed. This work is intended to provide an understanding of the current state of knowledge around DT and formulate the future research directions.Item Open Access Data management for developing digital twin ontology model(Sage, 2020-12-09) Singh, Sumit; Shehab, Essam; Higgins, Nigel; Fowler, Kevin; Reynolds, Dylan; Erkoyuncu, John Ahmet; Gadd, PeterDigital Twin (DT) is the imitation of the real world product, process or system. Digital Twin is the ideal solution for data-driven optimisations in different phases of the product lifecycle. With the rapid growth in DT research, data management for digital twin is a challenging field for both industries and academia. The challenges for DT data management are analysed in this article are data variety, big data & data mining and DT dynamics. The current research proposes a novel concept of DT ontology model and methodology to address these data management challenges. The DT ontology model captures and models the conceptual knowledge of the DT domain. Using the proposed methodology, such domain knowledge is transformed into a minimum data model structure to map, query and manage databases for DT applications. The proposed research is further validated using a case study based on Condition-Based Monitoring (CBM) DT application. The query formulation around minimum data model structure further shows the effectiveness of the current approach by returning accurate results, along with maintaining semantics and conceptual relationships along DT lifecycle. The method not only provides flexibility to retain knowledge along DT lifecycle but also helps users and developers to design, maintain and query databases effectively for DT applications and systems of different scale and complexitiesItem Open Access Towards information management framework for digital twin in aircraft manufacturing(Elsevier, 2021-02-10) Singh, Sumit; Shehab, Essam; Higgins, Nigel; Fowler, Kevin; Erkoyuncu, John Ahmet; Gadd, PeterAircraft manufacturing industries often evolve in the ecosystem of complex designs and manufacturing processes associated with large volume of information generated along the lifecycle. Digital Twin (DT) technology has the potential of leveraging such information to provide useful insights benefiting the overall business in many ways. Information Management (IM) for DT is still an ongoing challenge for many industries, thus leaving a considerable research gap. In this paper, an IM framework for DT in the aircraft manufacturing sector is proposed. The key phases and elements of IM are discussed on which the framework is constructed. The potential application of the framework along aircraft lifecycle is further discussed. The framework not only provides an effective approach to managing information but also opens new research prospects in DT domain.