Papers by Dimitris Kiritsis
Proceedings of the 1st International Conference on Internet of Things and Machine Learning
As IoT envisions a future world where a tremendous amount of sensor data will become available, t... more As IoT envisions a future world where a tremendous amount of sensor data will become available, the significance of extracting valuable knowledge out of those data is increasing day by day. IoT analytics are considered a powerful tool towards demystifying user behavior, providing market insights and intelligence in Industry 4.0 as well as discovering useful patterns in everyday phenomena. At the same time, a shift is observed to Service-Oriented-Infrastructure. In this work, a Knowledge as a Service (KnaaS) framework is proposed along with its prototype implementation architecture aiming at providing a conceptual reference architecture for the knowledge discovery in the future IoT. The discussion and analysis show that the proposed framework is in accordance with the best practices in knowledge discovery and IoT consisting a reasonable solution in offering knowledge as a service in the upcoming IoT era.
IFIP Advances in Information and Communication Technology
Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for ... more Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for identifying the dynamics of virtual model evolution, promoting the understanding of interrelationships between virtual models and enhancing the decision-making based on DT. The CT ensures that assets of Internet of Things (IoT) systems are well-managed and concerns beyond technical stakeholders are addressed during IoT system development. In this paper, a Knowledge Graph (KG) centric framework is proposed to develop CT. Based on the framework, a future tool-chain is proposed to develop the CT for the initiatives of H2020 project FACTLOG. Based on the comparison between DT and CT, we infer the CT is a more comprehensive approach to support IoT-based systems development than DT.
Applied Sciences
Supply chain agility and resilience are key factors for the success of manufacturing companies in... more Supply chain agility and resilience are key factors for the success of manufacturing companies in their attempt to respond to dynamic changes. The circular economy, the need for optimized material flows, ad-hoc responses and personalization are some of the trends that require supply chains to become “cognitive”, i.e., able to predict trends and flexible enough in dynamic environments, ensuring optimized operational performance. Digital twins (DTs) is a promising technology, and a lot of work is done on the factory level. In this paper, the concept of cognitive digital twins (CDTs) and how they can be deployed in connected and agile supply chains is elaborated. The need for CDTs in the supply chain as well as the main CDT enablers and how they can be deployed under an operational model in agile networks is described. More emphasis is given on the modelling, cognition and governance aspects as well as on how a supply chain can be configured as a network of connected CDTs. Finally, a d...
IEEE Transactions on Engineering Management
Applied Sciences, 2021
Supply chain agility and resilience are key factors for the success of manufacturing companies in... more Supply chain agility and resilience are key factors for the success of manufacturing companies in their attempt to respond to dynamic changes. The circular economy, the need for optimized material flows, ad-hoc responses and personalization are some of the trends that require supply chains to become “cognitive”, i.e., able to predict trends and flexible enough in dynamic environments, ensuring optimized operational performance. Digital twins (DTs) is a promising technology, and a lot of work is done on the factory level. In this paper, the concept of cognitive digital twins (CDTs) and how they can be deployed in connected and agile supply chains is elaborated. The need for CDTs in the supply chain as well as the main CDT enablers and how they can be deployed under an operational model in agile networks is described. More emphasis is given on the modelling, cognition and governance aspects as well as on how a supply chain can be configured as a network of connected CDTs. Finally, a d...
Applied Sciences
The goal of this paper is to further elaborate a new concept for value creation by decision suppo... more The goal of this paper is to further elaborate a new concept for value creation by decision support services in industrial service ecosystems using digital twins and to apply it to an extended case study. The aim of the original model was to design and integrate an architecture of digital twins derived from business needs that leveraged the potential of the synergies in the ecosystem. The conceptual framework presented in this paper extends the semantic ontology model for integrating the digital twins. For the original model, technical modeling approaches were developed and integrated into an ecosystem perspective based on a modeling of the ecosystem and the actors’ decision jobs. In a service ecosystem comprising several enterprises and a multitude of actors, decision making is based on the interlinkage of the digital twins of the equipment and the processes, which is achieved by the semantic ontology model further elaborated in this paper. The implementation of the digital twin ar...
Maintenance is a key operation function within manufacturing enterprises related to all of their ... more Maintenance is a key operation function within manufacturing enterprises related to all of their processes and focuses not only on avoiding the equipment breakdown but also on improving business performance. In the last years, due to the evolution of technology, products and machines have become more and more complex. Consequently, the costs of time-based (planned) maintenance have increased and predictive maintenance has evolved as a novel lever for maintenance management. To this end, the emergence of the Internet of Things (IoT) can enhance the condition monitoring capabilities by paving the way for extensive use of physical and virtual sensors generating a multitude of data. In this way, predictive maintenance can significantly evolve in the frame of Industry 4.0. Industry 4.0 indicates the flexibility that exists in value-creating networks which enables machines and plants to adapt their behaviour to changing orders and operating conditions through self-optimization and reconfi...
Closed-Loop Lifecycle Management (CL2M) is an integral part of the circular economy. Managing the... more Closed-Loop Lifecycle Management (CL2M) is an integral part of the circular economy. Managing the CL2M enables manufacturers and associated digital factories to connect in-service issues back to process conditions and product information at manufacturing and other stages of the life cycle with the aim of having Zero Defect Manufacturing (ZDM). ZDM can be implemented through two approaches: product-oriented and process-oriented ZDM. Product-oriented ZDM studies defects in the actual parts., Process-oriented ZDM studies defects in the manufacturing equipment that have led, or might lead to product defects this is implemented through Predictive Maintenance. The Industrial Internet of Things (IIoT) and associated computing continuum Cloud and Edge Technologies and Industrial AI (Artificial Intelligence) provide valuable data for Predictive Maintenance and product-oriented ZDM. Associated to that, ontologies and associated semantic technologies such as Knowledge Graphs are rapidly becomi...
IFIP Advances in Information and Communication Technology
Digital Twins (DT) are proposed in industries to support the entire lifecycle of services with di... more Digital Twins (DT) are proposed in industries to support the entire lifecycle of services with different perspectives. Lack of systematic analysis of DT concepts leads to various definitions and services which challenges the DT developers for data integration and integrated service delivery. In this paper, a systems engineering approach is proposed to identify the requirements of DT in order to formalize the DT concepts from a systematic perspective. The conceptual architecture of DT is defined based on ISO standard 42010. Several concepts are captured to recognize DT, to define related terminologies, and to identity concerns and viewpoints in order to provide cues for delivering DT services to industry. This approach is evaluated by multiple industrial use-cases under the Innosuisse IMPULSE project, from which one-use case is selected for further elaboration. It contributes to the development of DT associated to the use-case by addressing the requirements of DT using a semi-formal approach.
Advances in Production Management Systems. Smart Manufacturing for Industry 4.0
The current industrial revolution is said to be driven by the digitization that exploits connecte... more The current industrial revolution is said to be driven by the digitization that exploits connected information across all aspects of manufacturing. Standards have been recognized as an important enabler. Ontology-based information standard may provide benefits not offered by current information standards. Although there have been ontologies developed in the industrial manufacturing domain, they have been fragmented and inconsistent, and little has received a standard status. With successes in developing coherent ontologies in the biological, biomedical, and financial domains, an effort called Industrial Ontologies Foundry (IOF) has been formed to pursue the same goal for the industrial manufacturing domain. However, developing a coherent ontology covering the entire industrial manufacturing domain has been known to be a mountainous challenge because of the multidisciplinary nature of manufacturing. To manage the scope and expectations, the IOF community kicked-off its effort with a proof-of-concept (POC) project. This paper describes the developments within the project. It also provides a brief update on the IOF organizational set up.
Engineering Assets and Public Infrastructures in the Age of Digitalization
IEEE Systems Journal
Model-based systems engineering (MBSE) provides an important capability for managing the complexi... more Model-based systems engineering (MBSE) provides an important capability for managing the complexities of system development. MBSE empowers the formalism of system architectures for supporting model-based requirement elicitation, specification, design, development, testing, fielding, etc. However, the modeling languages and techniques are heterogeneous, even within the same enterprise system, which leads to difficulties for data interoperability. The discrepancies among data structures and language syntaxes make information exchange among MBSE models more difficult, resulting in considerable information deviations when connecting data flows across the enterprise. Therefore, this article presents an ontology based upon graphs, objects, points, properties, roles, and relationships with extensions (GOPPRRE), providing metamodels that support the various MBSE formalisms across lifecycle stages. In particular, knowledge graph models are developed to support unified model representations to further implement ontological data integration based on GOPPRRE throughout the entire lifecycle. The applicability of the MBSE formalism is verified using quantitative and qualitative approaches. Moreover, the GOPPRRE ontologies are used to create the MBSE formalisms in a domain-specific modeling tool, MetaGraph, for evaluating its availability. The results demonstrate that the proposed ontology supports the formal structures and descriptive logic of the systems engineering lifecycle.
Proceedings of the 4th International Conference on the Industry 4.0 Model for Advanced Manufacturing
Within the context of market globalisation, the quality of products has become a key factor for s... more Within the context of market globalisation, the quality of products has become a key factor for success in manufacturing industry. The growing unpredictability of demand necessitates continuous adjustments in production targets. Addressing customer needs and customer satisfaction are the most important factors for successful businesses. Being consistent in meeting their needs, the existing manufacturing systems have to be adaptable while maximising the quality of their products. Guided by this challenge, in this paper we provide a holistic framework and ad-hoc strategies applicable both to new and existing manufacturing lines to achieve zero-defects in manufacturing via a novel ZDM platform that integrates state of the art ICT technologies, AI models and inspection tools which elevate manufacturing plants to a superior level of competitiveness and sustainability. The proposed approach and results in this article are based on the development and implementation in a large collaborative EU-funded H2020 research project entitled Z - Fact0r, i.e. Zero-defect manufacturing strategies towards on-line production management for European factories.
Lecture Notes in Mechanical Engineering
Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for ... more Cognitive Twins (CT) are proposed as Digital Twins (DT) with augmented semantic capabilities for identifying the dynamics of virtual model evolution, promoting the understanding of interrelationships between virtual models and enhancing the decision-making based on DT. The CT ensures that assets of Internet of Things (IoT) systems are well-managed and concerns beyond technical stakeholders are addressed during IoT system development. In this paper, a Knowledge Graph (KG) centric framework is proposed to develop CT. Based on the framework, a future tool-chain is proposed to develop the CT for the initiatives of H2020 project FACTLOG. Based on the comparison between DT and CT, we infer the CT is a more comprehensive approach to support IoTbased systems development than DT.
IFIP Advances in Information and Communication Technology
The latest developments in Model-Based Systems Engineering (MBSE) and Product Life-Cycle Manageme... more The latest developments in Model-Based Systems Engineering (MBSE) and Product Life-Cycle Management (PLM) are playing a role in the evolution of the aeronautical industry. Despite the reluctance of this domain to accept the introduction of technology leaps in the production process - mostly due to safety reasons - aircraft manufacturers are slowly moving to a new digital factory concept. The deployment of a PLM Tool for Aircraft Ground Functional testing with Eco-design criteria can be leveraged to improve both sustainability of the assembly line and efficiency of the Ground System Tests process end to end, however, heterogeneous data interoperability represents one of the major challenges in this framework. The ontology-based solution proposed in this work addresses this challenge, thus, shows how semantics can be exploited to streamline the data pipeline throughout a PLM digital platform.
Proceedings of the 6th International Conference on Computer Supported Education, 2014
Uploads
Papers by Dimitris Kiritsis