Towards a Semantic Knowledge Management Framework for Laminated Composites

The engineering of laminated composite structures is a complex task for design engineers and manufacturers, requiring significant management of manufacturing process and materials information. Ontologies are becoming increasingly commonplace for semantically representing knowledge in a formal manner that facilitates sharing of rich information between people and applications. Moreover, ontologies can support first-order logic and reasoning by rule engines that enhance automation. To support the engineering of laminated composite structures, this work developed a novel Semantic LAminated Composites Knowledge management System (SLACKS) that is based on a suite of ontologies for laminated composites materials and design for manufacturing (DFM) and their integration into a previously developed engineering design framework. By leveraging information from CAD/FEA tools and materials data from online public databases, SLACKS uniquely enables software tools and people to interoperate, to improve communication and automate reasoning during the design process. With SLACKS, this research shows the power of integrating relevant domains of the product lifecycle, such as design, analysis, manufacturing and materials selection through the engineering case study of a wind turbine blade. The integration reveals a usable product lifecycle knowledge tool that can facilitate efficient knowledge creation, retrieval and reuse, from design inception to manufacturing of the product

Data integration support for offshore decommissioning waste management

Offshore oil and gas platforms have a design life of about 25 years whereas the techniques and tools used for managing their data are constantly evolving. Therefore, data captured about platforms during their lifetimes will be in varying forms. Additionally, due to the many stakeholders involved with a facility over its life cycle, information representation of its components varies. These challenges make data integration difficult. Over the years, data integration technology application in the oil and gas industry has focused on meeting the needs of asset life cycle stages other than decommissioning. This is the case because most assets are just reaching the end of their design lives. Currently, limited work has been done on integrating life cycle data for offshore decommissioning purposes, and reports by industry stakeholders underscore this need. This thesis proposes a method for the integration of the common data types relevant in oil and gas decommissioning. The key features of the method are that it (i) ensures semantic homogeneity using knowledge representation languages (Semantic Web) and domain specific reference data (ISO 15926); and (ii) allows stakeholders to continue to use their current applications. Prototypes of the framework have been implemented using open source software applications and performance measures made. The work of this thesis has been motivated by the business case of reusing offshore decommissioning waste items. The framework developed is generic and can be applied whenever there is a need to integrate and query disparate data involving oil and gas assets. The prototypes presented show how the data management challenges associated with assessing the suitability of decommissioned offshore facility items for reuse can be addressed. The performance of the prototypes show that significant time and effort is saved compared to the state-of‐the‐art solution. The ability to do this effectively and efficiently during decommissioning will advance the oil the oil and gas industry’s transition toward a circular economy and help save on cost

Technology challenges of stealth unmanned combat aerial vehicles

The ever-changing battlefield environment, as well as the emergence of global command and control architectures currently used by armed forces around the globe, requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned Combat Aerial Vehicles (UCAVs) aim to integrate such advanced technologies while also increasing the tactical capabilities of combat aircraft. This paper provides a summary of the technical and operational design challenges specific to UCAVs, focusing on high-performance, and stealth designs. After a brief historical overview, the main technology demonstrator programmes currently under development are presented. The key technologies affecting UCAV design are identified and discussed. Finally, this paper briefly presents the main issues related to airworthiness, navigation, and ethical concerns behind UAV/UCAV operations

Model Based Definition: Finally, the Engineering Drawing Killer?

The Engineering drawing has stood as the universal method of translating design intent since the first standard was formalized in 1927 as BS308. Further development of national and international standards has been informed by advances in CADCAM technology and the need for transfer of complex yet unambiguous definition between organisations. The emergence of model based definition (MBD) has driven a new workflow where the engineering drawing is no longer required. Instead, the dataset includes semantic, machine readable, tolerancing of surfaces and features for integration into manufacturing and metrology procedures. Despite the advantages of MBD, it has been largely ignored in UK Higher Education. However MBD is the ideal method for teaching and learning geometrical tolerancing since it ignores the theoretically exact dimensions and housekeeping, concentrating on the functional limits. Further, it utilises the 3D workspace that students are increasingly familiar with

A process model in platform independent and neutral formal representation for design engineering automation

An engineering design process as part of product development (PD) needs to satisfy ever-changing customer demands by striking a balance between time, cost and quality. In order to achieve a faster lead-time, improved quality and reduced PD costs for increased profits, automation methods have been developed with the help of virtual engineering. There are various methods of achieving Design Engineering Automation (DEA) with Computer-Aided (CAx) tools such as CAD/CAE/CAM, Product Lifecycle Management (PLM) and Knowledge Based Engineering (KBE). For example, Computer Aided Design (CAD) tools enable Geometry Automation (GA), PLM systems allow for sharing and exchange of product knowledge throughout the PD lifecycle. Traditional automation methods are specific to individual products and are hard-coded and bound by the proprietary tool format. Also, existing CAx tools and PLM systems offer bespoke islands of automation as compared to KBE. KBE as a design method incorporates complete design intent by including re-usable geometric, non-geometric product knowledge as well as engineering process knowledge for DEA including various processes such as mechanical design, analysis and manufacturing. It has been recognised, through an extensive literature review, that a research gap exists in the form of a generic and structured method of knowledge modelling, both informal and formal modelling, of mechanical design process with manufacturing knowledge (DFM/DFA) as part of model based systems engineering (MBSE) for DEA with a KBE approach. There is a lack of a structured technique for knowledge modelling, which can provide a standardised method to use platform independent and neutral formal standards for DEA with generative modelling for mechanical product design process and DFM with preserved semantics. The neutral formal representation through computer or machine understandable format provides open standard usage. This thesis provides a contribution to knowledge by addressing this gap in two-steps: • In the first step, a coherent process model, GPM-DEA is developed as part of MBSE which can be used for modelling of mechanical design with manufacturing knowledge utilising hybrid approach, based on strengths of existing modelling standards such as IDEF0, UML, SysML and addition of constructs as per author’s Metamodel. The structured process model is highly granular with complex interdependencies such as activities, object, function, rule association and includes the effect of the process model on the product at both component and geometric attributes. • In the second step, a method is provided to map the schema of the process model to equivalent platform independent and neutral formal standards using OWL/SWRL ontology for system development using Protégé tool, enabling machine interpretability with semantic clarity for DEA with generative modelling by building queries and reasoning on set of generic SWRL functions developed by the author. Model development has been performed with the aid of literature analysis and pilot use-cases. Experimental verification with test use-cases has confirmed the reasoning and querying capability on formal axioms in generating accurate results. Some of the other key strengths are that knowledgebase is generic, scalable and extensible, hence provides re-usability and wider design space exploration. The generative modelling capability allows the model to generate activities and objects based on functional requirements of the mechanical design process with DFM/DFA and rules based on logic. With the help of application programming interface, a platform specific DEA system such as a KBE tool or a CAD tool enabling GA and a web page incorporating engineering knowledge for decision support can consume relevant part of the knowledgebase

"Built Environment Digital Twining"

A digital twin is a digital replica of a real-world physical entity (El Saddik 2018). The concept is already widely used in the manufacturing sector. In the built environment sector, digital twins are gradually entering the conversation as they can offer substantial value to all associated stakeholders. This report is the outcome of the International Workshop on Built Environment Digital Twinning, which was co-sponsored by the Institute for Advanced Study of Technical University of Munich (TUM-IAS) and Siemens AG

Measurement and Evaluation for Prognostics and Health Management (PHM) for Manufacturing Operations – Summary of an Interactive Workshop Highlighting PHM Trends

Personnel from the National Institute of Standards and Technology (NIST) organized and led a Measurement and Evaluation for Prognostics and Health Management for Manufacturing Operations (ME4PHM) workshop at the 2019 Annual Conference of the Prognostics and Health Management Society held on September 23rd, 2019 in Scottsdale, Arizona. This event featured panel presentations and discussions from industry, government, and academic participants who are focused in advancing monitoring, diagnostic, and prognostic (collectively known as prognostic and health management (PHM)) capabilities within manufacturing operations. The participants represented a diverse cross-section of technology developers, integrators, end-users/manufacturers (from small to large), and researchers. These contributors discussed 1) what works well, 2) common challenges that need to be addressed, 3) where the community’s priorities should be focused, and 4) how PHM technological adoption can be sped in a cost-effective manner. This report summarizes the workshop and offers lessons learned regarding the current state of PHM. Based upon the discussions, recommended next steps to advance this technological domain are also presented

Analysing Systems Interdependencies Using a Digital Twin

This work provides a first step towards next-generation systems engineering by demonstrating the feasibility of using a digital twin to generate new insight into systems relationships and interdependencies. This step required substantial interdisciplinary work and industry collaboration in order to examine the potential to combine a set of relevant analytical methods (e.g. BIM query, network analyses and multi-modelling). We assembled an experienced team (Imperial College London, University of Sheffield, Newcastle University), and worked closely with and used empirical data from a major project (Thames Tideway Tunnel). This first step delivers fundamental theoretical understanding that will support the use of the digital twin for systems analyses, and a practical contribution to the identification, prioritisation and management of interdependencies. The long-term ambition is to build the tools that decision makers need in order to understand infrastructure system interdependencies within and across project boundaries