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Advances in Systems Engineering Interoperability: Engineering Design and Operation

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 15335

Special Issue Editors


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Guest Editor
Department of Computer Science and Engineering, Carlos III University of Madrid, 28903 Madrid, Spain
Interests: interoperability; software engineering; systems engineering; knowledge engineering; model-based systems engineering; service-oriented computing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Bioengineering and Aerospace Engineering, Universidad Carlos III, Av. de la Universidad 30, 28911 Leganés, Madrid, Spain
Interests: model-based systems engineering; reuse; simulation; air navigation; 4D trajectory management; machine learning; avionics systems

Special Issue Information

Dear Colleagues,

The development and operation of software-intensive complex systems is becoming more challenging than ever. The implicit need for the continuous delivery of new products and services (cyber-physical systems) in a timely and cost-effective manner is a cornerstone for the realization of Industry 4.0, especially in the case of safety-critical systems equipped with non-deterministic functions. The digitalization of engineering (DE) is also gaining momentum in the systems and software engineering discipline, with the aim of shifting the paradigm to the design and operation of these complex systems incorporating multiple engineering disciplines. In this context, interoperability emerges as a key enabler to build collaborative engineering environments in which people, processes, methods, and tools are perfectly synchronized to build complex systems making use of methods and techniques such as digital twins, simulation, model-based systems engineering, service-oriented computing, etc. The need of communicating and exchanging data, information, and knowledge between organizations, tools, and people is also increasing. To enable this, it is necessary to establish new mechanisms that can support engineers to easily represent and organize domain knowledge, integrate and exchange data, expose and consume functionalities, and manage the engineering process under a standardized and interoperable environment. This Special Issue aims to bring together research works and real-world use cases, scenarios, and approaches focused on the improvement of the software and systems engineering process through interoperable mechanisms applied to the design and operation of software-intensive systems.

Dr. José María Alvarez Rodríguez
Dr. Javier García-Heras Carretero
Guest Editors

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Keywords

  • interoperability in the engineering design process
  • interoperability in the operation environment
  • engineering methods and interoperability
  • tools and platforms for interoperability
  • data, information, and knowledge representation and exchange
  • functionality and service representation and invocation
  • languages and standards for content- and context-based interoperability in the engineering domain
  • applications and real-world use cases of interoperability in the engineering lifecycle

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Published Papers (5 papers)

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Research

14 pages, 515 KiB  
Article
Towards a Method to Enable the Selection of Physical Models within the Systems Engineering Process: A Case Study with Simulink Models
by Eduardo Cibrián, Jose María Álvarez-Rodríguez, Roy Mendieta and Juan Llorens
Appl. Sci. 2023, 13(21), 11999; https://doi.org/10.3390/app132111999 - 3 Nov 2023
Viewed by 1073
Abstract
The use of different techniques and tools is a common practice to cover all stages in the development life-cycle of systems generating a significant number of work products. These artefacts are frequently encoded using diverse formats, and often require access through non-standard protocols [...] Read more.
The use of different techniques and tools is a common practice to cover all stages in the development life-cycle of systems generating a significant number of work products. These artefacts are frequently encoded using diverse formats, and often require access through non-standard protocols and formats. In this context, Model-Based Systems Engineering (MBSE) emerges as a methodology to shift the paradigm of Systems Engineering practice from a document-oriented environment to a model-intensive environment. To achieve this major goal, a formalised application of modelling is employed throughout the life-cycle of systems to generate various system artefacts represented as models, such as requirements, logical models, and multi-physics models. However, the mere use of models does not guarantee one of the main challenges in the Systems Engineering discipline, namely, the reuse of system artefacts. Considering the fact that models are becoming the main type of system artefact, it is necessary to provide the capability to properly and efficiently represent and retrieve the generated models. In light of this, traditional information retrieval techniques have been widely studied to match existing software assets according to a set of capabilities or restrictions. However, there is much more at stake than the simple retrieval of models or even any piece of knowledge. An environment for model reuse must provide the proper mechanisms to (1) represent any piece of data, information, or knowledge under a common and shared data model, and (2) provide advanced retrieval mechanisms to elevate the meaning of information resources from text-based descriptions to concept-based ones. This need has led to novel methods using word embeddings and vector-based representations to semantically encode information. Such methods are applied to encode the information of physical models while preserving their underlying semantics. In this study, a text corpus from MATLAB Simulink models was preprocessed using Natural Language Processing (NLP) techniques and trained to generate word vector representations. Then, the presented method was validated using a testbed of MATLAB Simulink physical models in which verbalisations of models are transformed into vectors. The effectiveness of the proposed solution was assessed through a use case study. Evaluation of the results demonstrates a precision value of 0.925, a recall value of 0.865, and an F1 score of 0.884. Full article
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15 pages, 2032 KiB  
Article
UML Profile for Messaging Patterns in Service-Oriented Architecture, Microservices, and Internet of Things
by Tomasz Górski
Appl. Sci. 2022, 12(24), 12790; https://doi.org/10.3390/app122412790 - 13 Dec 2022
Cited by 16 | Viewed by 5092
Abstract
The exchange of information among information technology (IT) systems is inevitable. Service fulfillment often involves sending and receiving messages. The article presents a set of messaging patterns for service-oriented architecture, microservices, and messaging protocols for the Internet of Things. The paper describes selected [...] Read more.
The exchange of information among information technology (IT) systems is inevitable. Service fulfillment often involves sending and receiving messages. The article presents a set of messaging patterns for service-oriented architecture, microservices, and messaging protocols for the Internet of Things. The paper describes selected patterns that are the result of current research work. In addition, patterns introduced in open-source frameworks such as ZeroMQ have also been included. Moreover, the set includes Enterprise Integration Patterns. All considered messaging patterns have been described using the stereotype extensibility mechanism of the Unified Modeling Language (UML), and their complete set has been included in the new UML Profile for Messaging Patterns. The paper also shows the manner of integration flow modeling. In the illustrative examples, both the integration flow modeling diagram and the profile have been used to describe the communication in the context of the Integrated services view of the 1+5 architectural views model. The profile has been designed in the visual paradigm tool and revealed in a public repository for the community. Full article
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21 pages, 17902 KiB  
Article
Time-Optimal Trajectory Planning of Six-Axis Manipulators Based on the Improved Direct Collocation Method with FMU
by Ziyao Xiong, Jianwan Ding and Liping Chen
Appl. Sci. 2022, 12(13), 6741; https://doi.org/10.3390/app12136741 - 3 Jul 2022
Cited by 4 | Viewed by 2007
Abstract
The trajectory planning method with dynamics is the key to improving the motion performance of manipulators. The optimal control method (OCM) is a key technology to solve optimal problems with dynamics. There are direct and indirect methods in OCM; indirect methods are difficult [...] Read more.
The trajectory planning method with dynamics is the key to improving the motion performance of manipulators. The optimal control method (OCM) is a key technology to solve optimal problems with dynamics. There are direct and indirect methods in OCM; indirect methods are difficult to apply to engineering applications, and so direct methods are widely applied instead. The direct collocation method (DCM) is a technology in OCM to transform an optimal control problem (OCP) to a nonlinear problem (NLP), so that plenty of solvers can be used directly. However, the general DCM, for which it has been found that the explicit form of the right-hand-side (RHS) functions of state equations of the complex system in the OCP is hard to derive, is limited to solving the OCP of three-axis manipulators. This paper proposes an improved DCM to solve the OCP of six-axis manipulators, which can find the solution of the time-optimal trajectory for the motion of six-axis manipulators based on the improved DCM. The proposed method derives the RHS equations implicitly by introducing a Functional Mock-up Unit (FMU), which simplifies the representation of the RHS equations as a black-box model, so that the DCM can be applied to the OCP of six-axis manipulators. A simulation case of a three-axis manipulator accomplished in a related study works as a reference compared with our improved method to verify the solution consistence between the DCM using the explicit RHS equations or using the implicit RHS equations, and the loss of computational efficiency is acceptable. In the meantime, a simulation solution and an experiment of six-axis manipulators, which is a novel advancement, are presented to validate the proposed method. Full article
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35 pages, 5073 KiB  
Article
SCM-IoT: An Aproach for Internet of Things Services Integration and Coordination
by Isaac Machorro-Cano, José Oscar Olmedo-Aguirre, Giner Alor-Hernández, Lisbeth Rodríguez-Mazahua, José Luis Sánchez-Cervantes and Asdrúbal López-Chau
Appl. Sci. 2022, 12(6), 3133; https://doi.org/10.3390/app12063133 - 18 Mar 2022
Cited by 3 | Viewed by 2871
Abstract
Today, new applications demand an internet of things (IoT) infrastructure with greater intelligence in our daily use devices. Among the salient features that characterize intelligent IoT systems are interoperability and dynamism. While service-oriented architectures (SOA) offer a well-developed and standardized architecture and protocols [...] Read more.
Today, new applications demand an internet of things (IoT) infrastructure with greater intelligence in our daily use devices. Among the salient features that characterize intelligent IoT systems are interoperability and dynamism. While service-oriented architectures (SOA) offer a well-developed and standardized architecture and protocols for interoperability, answering whether SOA offers enough dynamism to merge IoT with artificial intelligence (AI) is still in its beginnings. This paper proposes an SOA model, called SCM-IoT (service composition model for IoT), for incorporating AI into IoT systems, addressing their coordination by a mediator offering services for storage, production, discovery, and notification of relevant data for client applications. The model allows IoT systems to be incrementally developed from three perspectives: a conceptual model, platform-independent computational model, and platform-dependent computational model. Finally, as a case of study, a domotic IoT system application is developed in SCM-IoT to analyze the characteristics and benefits of the proposed approach. Full article
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16 pages, 1319 KiB  
Article
Service Interface Translation. An Interoperability Approach
by Cristina Paniagua
Appl. Sci. 2021, 11(24), 11643; https://doi.org/10.3390/app112411643 - 8 Dec 2021
Cited by 3 | Viewed by 2069
Abstract
Interoperability plays an important role in Industry 4.0. Interoperability in the engineering process allows the automation of the engineering phase, reducing the human effort involved and the associated engineering costs. It improves the quality of the engineering process and its overall efficiency. Nevertheless, [...] Read more.
Interoperability plays an important role in Industry 4.0. Interoperability in the engineering process allows the automation of the engineering phase, reducing the human effort involved and the associated engineering costs. It improves the quality of the engineering process and its overall efficiency. Nevertheless, the diversity of available standards, devices, and systems leads to great levels of heterogeneity and makes it difficult to achieve the aforementioned interoperability. As the lack of interoperability increases, a generic solution to the problem is increasingly demanded by the industry. This paper approaches the interoperability problem from a service interface perspective. A novel approach is presented to address service interface heterogeneity. The proposed solution is based on service interface translation, which is achieved via the generation of service interfaces. A new system, the consumer interface generator system, has been designed and implemented to generate interface instances to solve the interoperability mismatches between service consumers and providers at runtime. In this paper, the autonomous consumer interface generation process, the system architecture, and the generated interface instance are described. The proposed approach has been validated through practical experimentation, including the implementation of a system prototype and a testbed. Full article
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