Dimitris Kiritsis

École Polytechnique Fédérale de Lausanne | EPFL · Institute of Mechanical Engineering

Cognitive Digital twins (CDT) are Digital Twins with cognition capabilities and ensure a proper monitoring and optimization of a specific asset’s behaviour. In the context of supply chains, there are different entities involved from assets, processes, up to organizations, which can be modelled as CDTs that collaborate each other, share and process...

Data interoperability is a fundamental dimension in enterprise interoperability. The interoperability of data is concerned with exchanging information coming from heterogeneous sources among different partners. Under the Industry 4.0 context, Internet of Things (IoT) technology has been widely implemented in manufacturing factories which enables th...

Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data-driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing chatter detection approaches are based on external sensors, such as accelerometers and microphones, which require installation of ex...

In a real production line, rush orders arise frequently, and they must be produced more quickly than standard production runs. Rush orders may require setup changes to process the order and to resume normal production once the order is completed. Increased setup times are qualitatively understood to decrease production efficiency and to increase th...

Code generation is an effective way to drive the complex system development in model-based systems engineering. Currently, different code generators are developed for different modeling languages to deal with the development of systems with multi-domain. There are a lack of unified code generation approaches for multi-domain heterogeneous models. I...

The development of an aircraft industrial system faces the challenge of integrative requirements validation with de-correlated modelling languages and distributed proprietary formats. This paper specifies an ontology-centric industrial requirements validation based on a cognitive digital twin approach, aiming at addressing the potentials of utilizi...

Advanced technologies in modern industry collect massive volumes of data from a plethora of sources, such as processes, machines, components, and documents. This also applies to predictive maintenance. To provide access to these data in a standard and structured way, researchers and practitioners need to design and develop a semantic model of maint...

Gas path fault diagnosis of a gas turbine is a complex task involving field data analysis and knowledge-based reasoning. In this paper, a data-knowledge hybrid driven method for gas path fault diagnosis is proposed by integrating a physical model-based gas path analysis (GPA) method with a fault diagnosis ontology model. Firstly, a physical model-b...

Recently, products and services have become joint commodities, in contrast to the traditional focus on products alone. Thus, modern industrial companies need to manage product-service systems (PSSs) as part of a competitive strategy. PSSs are comprised of complex, related products and services; stakeholders; processes; and environments. It is there...

Aircraft assembly is a complex process associated with different stakeholders, which strongly impacts the R&D cost for the entire aircraft lifecycle management. Traditional aircraft assembly process is designed based on a document-centric approach which cannot provide graphical notations for engineers to understand the entire assembly process. More...

Digital Twin is one of the fundamental enabling technologies for Industry 4.0 as it allows the convergence between a physical system and its digital representation. A proper modelling method is the prerequisite for successful digital twin implementation. The manufacturing process determines critically the quality of the manufactured products. The i...

The Prognostic and Health Management (PHM) system of an aircraft has complex structures and diverse functions. It is highly coupled with other systems, such as the avionics system and flight management system. The Model-based Systems Engineering (MBSE) method is effective to support the design and verification of the aircraft PHM system. As a power...

The development of an aircraft industrial system is a complex process which faces the challenge of digital discontinuity in multidisciplinary engineering due to various interfaces between different digital tools, leading to extra development time and costs. This paper proposes an ontology-based system, aiming at functionality integration and design...

Despite the high number of investments for data-based models in the expansion of Industry 4.0, too little effort has been made to ensure the maintenance of those models. In a data-streaming environment, data-based models are subject to concept drifts. A concept drift is a change in data distribution which will, at some point, decrease the accuracy...

Currently, the fundamental tenets of systems engineering are supported by a model-based approach to minimize risks and avoid design changes in late development stages. The models are used to formalize, analyze, design, optimize, and verify system development and artifacts, helping developers integrate engineering development across domains. Althoug...

With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is challenging to implement complexity management, interface definition, and service integration...

Digital Twin technology has been widely applied in various industry domains. Modern industrial systems are highly complex consisting of multiple interrelated systems, subsystems and components. During the lifecycle of an industrial system, multiple digital twin models might be created related to different domains and lifecycle phases. The integrati...

2 The Prognostic and Health Management (PHM) system of an aircraft has complex structures 3 and diverse functions. It is highly coupled with other systems, such as avionics system and 4 flight management system. The model-based systems engineering (MBSE) method is effective 5 to support the design and verification of PHM systems of an aircraft. As...

Production scheduling enables a production system to allocate resources for the efficient and low-cost production. However, pure mathematical methods are typically utilized for production scheduling, which are not understandable and practical for different domain engineers. Moreover, heterogeneous information during production scheduling may result...

An attempt is made to translate five generic key performance indicators (KPIs) into a continuous real-time cost function in a batch order-based manufacturing environment. The challenge of controlling and optimizing resource utilization, production efficiency, product-process quality, environmental impact, and inventory was specified by microelectro...

With the rising complexity of modern products and a trend from single products to Systems of Systems (SoS) where the produced system consists of multiple subsystems and the integration of multiple domains is a mandatory step, new approaches for development are demanded. This chapter explores how Model-Based Systems Engineering (MBSE) can benefit fr...

The development of an aircraft industrial system is a complex process which faces the challenge of digital discontinuity in multidisciplinary engineering due to various interfaces between different digital tools, leading to extra development time and costs. This paper proposes an ontology-based system, aiming at functionality integration and design...

Model-based systems engineering (MBSE) is considered an important approach for understanding multidomain fields and is widely used in complex systems such as aerospace. In this article, a detailed survey of MBSE literature was conducted from its commencement to the present trends through bibliometric analysis. Some bibliometric tools were used to i...

As a key enabling technology of Industry 4.0, Digital Twin (DT) has been widely applied to various industrial domains covering different lifecycle phases of products and systems. To fully realize the Industry 4.0 vision, it is necessary to integrate multiple relevant DTs of a system according to a specific mission. This requires integrating all ava...

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 potenti...

Actionable Cognitive Twins are the next generation Digital Twins enhanced with cognitive capabilities through a knowledge graph and artificial intelligence models that provide insights and decision-making options to the users. The knowledge graph describes the domain-specific knowledge regarding entities and interrelationships related to a manufact...

Contemporary Industries are generating a huge amount of data coming from a high variety of sources, such as machine controllers, corporate systems, sensors, operators etc. Therefore, the need for the utilization of the information generated, also known as Big Data, has emerged. Although data importance is well known, very often in manufacturing ind...

This paper introduces the background, concept and definition of the Industry Commons. It initiates a discussion on the positioning of the Industry Commons Ecosystem (ICE) with respect to current research directions in advanced manufacturing and production systems that shape advances in engineering and technology, novel business models and innovatio...

For manufacturing companies, quality management is a key feature for increasing the competitiveness , productivity, profitability, and sustainability of their systems. Quality improvement (QI) methods aim to achieve high-quality parts without reducing performance. The Industry 4.0 framework brought technological developments that cannot be used by...

Ontologies provide an opportunity to tackle the interoperability challenge in digital manufacturing. Although ontologies have been used in numerous industrial projects, the problem of semantic interoperability in the industry is still unresolved. One reason for the lack of success of ontologies in the industry is that most industrial ontologies hav...

With the continuous improvement of system scale and complexity, model-based system engineering (MBSE) is of great importance in the practice of system engineering (SE). MBSE has been widely concerned in industry, especially in the field of complex equipment. At the same time, in academia, research articles about MBSE come into being and grow rapidl...

Virtual metrology (VM) involves estimating a product’s quality directly from production process data without physically measuring it. This enables the product quality of each unit of production to be monitored in real time, while preserving the process efficiency. Initially developed for the semiconductor industry, VM has recently been examined for...

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 heterogene...

Contemporary manufacturing companies pay a lot of attention to product quality as this aspect affects directly their competitiveness, productivity and the reputation of the company. Traditional quality improvement methods such as Six Sigma, Lean etc. seems unable to cope with the market’s quality standards. Contemporary technological advancements a...

Digital twin (DT) provides a solution for supporting the interconnection between the physical world and the virtual world. When implementing DT integration, it is challenging to implement interface definition, information and service integration across DTs. This paper proposes a semantic modeling approach with a High-Level Architecture (HLA) to sup...

Property verification in Model-based systems engineering (MBSE) supports the formalization of model properties and evaluates the constraints of model properties to check whether the developed models are valid and correct to reduce the design error and risks. However, there is a lack of an integrated method which property verification enables to be...

Model-based systems engineering enables to verify the system performances using system behavior models, which can identify the fault design that do not meet the stakeholders' requirements as early as possible, thus reducing R&D cost and error risks. Currently, different domain engineers make use of different modeling languages to create their own b...

Defects are unavoidable during manufacturing processes, and a tremendous amount of research aimed at improving defect prevention has been conducted by scholars. Zero Defect Manufacturing (ZDM) seeks to eliminate defects in production. In addition, technological advancements now allow the repair of defective products. This creates the need to re-sch...

During the early phase of an aircraft program, industrial architects need to evaluate different industrial scenarios and perform trade-offs to optimize the future industrial architecture according to different key performance indicators. Expert knowledge accumulated during previous programs provides a foundation for the new one. It is a challenging...

With the increasing complexity of engineered systems, systems of systems (SoSs) have been widely used to manage complexity across systems in order to achieve additional desired capabilities. When developing an SoS based on existing systems, digital twins (DTs) provide a solution for supporting integrated modeling, simulation, and decision-making of...

Since the complex engineered system is involved in multidisciplinary , co-simulation is the key technique to the performance analysis in the life cycle. However, the co-simulation is hindered by the challenge of integrating heterogeneous subsystems and ununified environments. In this paper, a Cognitive Twin (CT) to support the co-simulation of the...

In the fact of increasing complexity of aircraft development programs, development processes of aircraft and their subsystems are continuously becoming complicated which leads to the growing risks of development cost across the entire lifecycle. In this paper, we propose a model-based systems engineering approach to support process modeling of airc...

The quality of a product is highly dependent on manufacturing processes. The recent development of industrial information technologies, such as Cyber-Physical Production Systems, Industrial Internet of Things, and Big Manufacturing Data Analytics has empowered the digitalization of manufacturing processes and promoted the concept of Digital Twin (D...

Digital twin (DT) provides a solution for supporting the interconnec-tion between the physical world and the virtual world. When implementing DT integration, it is challenging to implement interface definition, information and service integration across DTs. This paper proposes a semantic modeling approach with a High-Level Architecture (HLA) to su...

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 fle...

Nowadays, the manufacturing industry is constantly changing. Production systems must operate in a highly dynamic environment where unexpected events could occur and create disruption, making rescheduling inevitable for manufacturing companies. Rescheduling models are fundamental to the robustness of production processes. This paper proposes a model...

Actionable Cognitive Twins are the next generation Digital Twins enhanced with cognitive capabilities through a knowledge graph and artificial intelligence models that provide insights and decision-making options to the users. The knowledge graph describes the domain-specific knowledge regarding entities and interrelationships related to a manufact...

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...

Rush orders are common events in enterprises that are utilizing make-to-order production strategy. They have multiple negative impacts to the production system such as higher product defect rate which corresponds to product quality drop, not meeting the due dates and cause customers’ dissatisfaction, higher production costs, waste of materials and...

Predictive maintenance is a subbranch of Zero Defect Manufacturing concept. The goal is to achieve higher quality at the final product with the most optimum and efficient way. Predictive maintenance may be applied with various alternative ways for achieving the same goal. The current paper investigates and identifies the key control parameters for...

Cyber-physical systems (CPS) integrate heterogeneous systems and process sensor data using digital services. As the complexity of CPS increases, it becomes more challenging to efficiently formalize the integrated multi-domain views with flexible automated verification across the entire lifecycle. This paper illustrates a model-based systems enginee...

The paper introduces a Smart Innovation Environment for the devel-opment of Digital Twins and experimentation related to digital transformation projects, thus consolidating the "Digital Engineer" skill profile (with a business-oriented facet labelled as "Digital Innovator"). In the Internet of Things (IoT) era, this profile implies not only the abi...

Zero Defect Manufacturing concept imposes that any event in the production should have a counter-action in order to mitigate it. This approach creates the need for more frequent rescheduling of the shop floor to accommodate corrective actions. This paper focuses on the improvement of the quality in the flexible job-shop scheduling problem. As state...

This position paper introduces a Smart Innovation Environment for experimentation related to digital transformation projects, for the consolidation of a proposed “Digital Engineer” skill profile (with a business-oriented facet labelled as “Digital Innovator”). In the Internet of Things era, this profile implies the ability to perform both digital d...

Model-based systems engineering (MBSE) provides an important capability for managing the complexities of system development. MBSE empowers the formalisms of system architectures for supporting model-based requirement elicitation, specification, design, development, testing, fielding, etc. However, the modeling languages and techniques are quite het...

During the entire lifecycle of system development, various digital twins could be developed to support different systems engineering activities, such as verification and validation. The increasing complexity of digital twins leads to a challenge to manage the consistency, changes and traceability across the entire lifecycle. In this paper, a semant...

In contemporary manufacturing systems, re-scheduling of the production has become an unavoidable and critical phenomenon. There are many types of unexpected events, which can disrupt the normal operation of manufacturing systems. Therefore, the current research work focuses on identifying the critical reaction time for such events in order to keep...

Kick-off meeting plan EPFL-09.2020 ict4sm.epfl.ch/