Development of a low powered wireless iot sensor network based on mbse

Nowadays, the trend in System Engineering (SE) is shifting more and more in the domains of Wireless Sensor Networks (WSN) and Internet of Things (IoT) and will reach new height in demand. The complexity of those systems which are fundamentally different from those of the last decades in their own areas and are furthermore growing. To fulfil all requirements in those fields, a wider range of functionalities and components are needed, especially for IoT systems. In the interdisciplinary development, many conflicts occur. Thus, the complexity of the product demands a change of the development process itself. Most approaches lack in aspects of transparency, traceability and continuous development in general. Therefore, a neutral systematic approach is needed, which model-based systems engineering (MBSE) could provide. This paper applied MBSE in the domain of IoT in WSN development. Although MBSE emerged from system engineering/development, it essentially allows any developer in any discipline to understand relations between different system components in the central system model. The stages of this research are not fully developed yet but a high potential is expected. This holistic central system model is described by MBSE with tool, modelling language and method. The most promising modelling language for an interdisciplinary work in a real industrial content is SysML, which will be applied throughout the modelling tool following the RFLP principle of the V-model. These endeavours will then represent our result to show a more transparent continuous traceable solution in comparison with the existing application

Model Based System Engineering for the development of System on Chip

Abstract. Model Based System Engineering (MBSE) has been utilized in auto manufacturing industries, airplane manufacturing and maintenance, and factory process automation industries. These are some of the complex fields. As SoC design is a complex process and requires years of work, MBSE can reduce time, complexity, reuse, and maintenance costs. It seems a fruitful idea/decision to take MBSE into use in SoC design depending on the previously mentioned elements. System on Chip (SoC) is obtaining the interest of many big companies. Therefore, MBSE will represent a huge competitive advantage once it is taken fully into the systems engineering roles of SoC. The existence of geographically dispersed teams, complexity of systems, interdisciplinarity, personalized system description, and their integration can be enabled by MBSE. As an emerging paradigm for the systems of the 21st century, MBSE paved the way for creating successful systems (for the companies) that are end to end connected. This research focuses on making use of MBSE in SoC. The thesis will show how SoC processes can be implemented in one complete model with top to bottom approach. Firstly, the traditional systems engineering approach has been explained with its tools and examples. Secondly, the need for taking up MBSE by the systems engineers is expressed. This contains the applications, use in modern systems, and benefits of MBSE. Moreover, MBSE methodology tools, languages, and their use in SoC is illustrated with examples. As SoC development is a huge and complex process; therefore, a small component of the chip has been taken in consideration for the purpose of understanding and making of the thesis. MBSE is a model-based approach hence a language needs to be present to produce these models and that language is SysML and OPD/OPL. SysML language and MagicDraw tool is used for expressing the architecture of the system. MagicDraw supports several external evaluators for evaluation of expressions and MATLAB is one of them. With MagicDraw we can do simulations, input parameters, and analyze data by processing on it using algorithms developed in MATLAB

Operation Principles of the Industrial Facility Infrastructures Using Building Information Modeling (BIM) Technology in Conjunction with Model-Based System Engineering (MBSE)

The current industrial facility market necessitates the digitization of both production and infrastructure to ensure compatibility. This digitization is presently accomplished using Building Information Modeling and digital twin technologies, as well as their integrated usage, which enhances convergence and adds further value to facility assets. However, these technologies primarily focus on the physical components of industrial facilities, neglecting processes, requirements, and functions. To address these gaps, the inclusion of the Model-Based System Engineering approach, a proven benchmark in systems engineering, is essential. This inclusion is the main objective of this research. This article outlines methods and principles for integrating Model-Based System Engineering into the informational modeling of existing industrial facilities to address current market gaps. It offers practical steps for such integration and compares it to other methods, positioning Model-Based System Engineering as a pivotal tool for enhancing the value of industrial facility digital assets. The main findings include the proposal of BIM and MBSE integration, which aims to create a competitive advantage for industrial facilities by improving customer service and operational efficiency, requiring collaboration from various stakeholders

A Building Information Modeling (BIM)-centric Digital Ecosystem for Smart Airport Life Cycle Management

An increasing number of new airport infrastructure construction and improvement projects are being delivered in today\u27s modern world. However, value creation is a recurring issue due to inefficiencies in managing capital expenditures (CapEx) and operating expenses (OpEx), while trying to optimize project constraints of scope, time, cost, quality, and resources. In this new era of smart infrastructure, digitalization transforms the way projects are planned and delivered. Building Information Modeling (BIM) is a key digital process technique that has become an imperative for today\u27s Architecture, Engineering, Construction and Operations (AECO) sector. This research suggests a BIM-centric digital ecosystem by detailing technical and strategic aspects of Airport BIM implementation and digital technology integration from a life cycle perspective. This research provides a novel approach for consistent and continuous use of digital information between business and functional levels of an airport by developing a digital platform solution that will enable seamless flow of information across functions. Accordingly, this study targets to achieve three objectives: 1- To provide a scalable know-how of BIM-enabled digital transformation; 2- To guide airport owners and major stakeholders towards converging information siloes for airport life cycle data management by an Airport BIM Framework; 3- To develop a BIM-based digital platform architecture towards realization of an airport digital twin for airport infrastructure life cycle management. Airport infrastructures can be considered as a System of Systems (SoS). As such, Model Based Systems Engineering (MBSE) with Systems Modeling Language (SysML) is selected as the key methodology towards designing a digital ecosystem. Applying MBSE principles leads to forming an integrating framework for managing the digital ecosystem. Furthermore, this research adopts convergent parallel mixed methods to collect and analyze multiple forms of data. Data collection tools include extensive literature and industry review; an online questionnaire; semi-structured interviews with airport owner parties; focus group discussions; first-hand observations; and document reviews. Data analysis stage includes multiple explanatory case study analyses, thematic analysis, project mapping, percent coverage analysis for coded themes to achieve Objective 1; thematic analysis, cluster analysis, framework analysis, and non-parametric statistical analysis for Objective 2; and qualitative content analysis, non-parametric statistical analysis to accomplish Objective 3. This research presents a novel roadmap toward facilitation of smart airports with alignment and integration of disruptive technologies with business and operational aspects of airports. Multiple comprehensive case study analyses on international large-hub airports and triangulation of organization-level and project-level results systematically generate scalable technical and strategic guidelines for BIM implementation. The proposed platform architecture will incentivize major stakeholders for value-creation, data sharing, and control throughout a project life cycle. Introducing scalability and minimizing complexity for end-users through a digital platform approach will lead to a more connected environment. Consequently, a digital ecosystem enables sophisticated interaction between people, places, and assets. Model-driven approach provides an effective strategy for enhanced decision-making that helps optimization of project resources and allows fast adaptation to emerging business and operational demands. Accordingly, airport sustainability measures -economic vitality, operational efficiency, natural resources, and social responsibility- will improve due to higher levels of efficiency in CapEx and OpEx. Changes in business models for large capital investments and introducing sustainability to supply chains are among the anticipated broader impacts of this study

ARCHITECTURE FOR A CBM+ AND PHM CENTRIC DIGITAL TWIN FOR WARFARE SYSTEMS

The Department of the Navy’s continued progression from time-based maintenance into condition-based maintenance plus (CBM+) shows the importance of increasing operational availability (Ao) across fleet weapon systems. This capstone uses the concept of digital efficiency from a digital twin (DT) combined with a three-dimensional (3D) direct metal laser melting printer as the physical host on board a surface vessel. The DT provides an agnostic conduit for combining model-based systems engineering with a digital analysis for real-time prognostic health monitoring while improving predictive maintenance. With the DT at the forefront of prioritized research and development, the 3D printer combines the value of additive manufacturing with complex systems in dynamic shipboard environments. To demonstrate that the DT possesses parallel abilities for improving both the physical host’s Ao and end-goal mission, this capstone develops a DT architecture and a high-level model. The model focuses on specific printer components (deionized [DI] water level, DI water conductivity, air filters, and laser motor drive system) to demonstrate the DT’s inherent effectiveness towards CBM+. To embody the system of systems analysis for printer suitability and performance, more components should be evaluated and combined with the ship’s environment data. Additionally, this capstone recommends the use of DTs as a nexus into more complex weapon systems while using a deeper level of design of experiment.Outstanding ThesisCivilian, Department of the NavyCommander, United States NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

Semantic-Driven Architecture for Autonomic Management of Cyber-Physical Systems (CPS) for Industry 4.0

International audienceToday we are living a new industrial revolution, which has its origin in the vertiginous deployment of ICT technologies that have been pervasively deployed at all levels of the modern society. This new industrial revolution, known as Industry 4.0, evolves within the context of a totally connected Cyber-Physic world in which organizations face immeasurable challenges related to the proper exploitation of ICT technologies to create and innovate in order to develop the intelligent products and services of tomorrow's society. This paper introduces a semantic-driven architecture intended to design, develop and manage Industry 4.0 systems by incrementally integrating monitoring, analysis, planning and management capabilities within autonomic processes able to coordinate and orchestrate Cyber-Physical Systems (CPS). This approach is also intended to cope with the integrability and interoperability challenges of the heterogeneous actors of the Internet of Everything (people, things, data and services) involved in the CPS of the Industry 4.0

Towards a method to quantitatively measure toolchain interoperability in the engineering lifecycle: A case study of digital hardware design

The engineering lifecycle of cyber-physical systems is becoming more challenging than ever. Multiple engineering disciplines must be orchestrated to produce both a virtual and physical version of the system. Each engineering discipline makes use of their own methods and tools generating different types of work products that must be consistently linked together and reused throughout the lifecycle. Requirements, logical/descriptive and physical/analytical models, 3D designs, test case descriptions, product lines, ontologies, evidence argumentations, and many other work products are continuously being produced and integrated to implement the technical engineering and technical management processes established in standards such as the ISO/IEC/IEEE 15288:2015 "Systems and software engineering-System life cycle processes". Toolchains are then created as a set of collaborative tools to provide an executable version of the required technical processes. In this engineering environment, there is a need for technical interoperability enabling tools to easily exchange data and invoke operations among them under different protocols, formats, and schemas. However, this automation of tasks and lifecycle processes does not come free of charge. Although enterprise integration patterns, shared and standardized data schemas and business process management tools are being used to implement toolchains, the reality shows that in many cases, the integration of tools within a toolchain is implemented through point-to-point connectors or applying some architectural style such as a communication bus to ease data exchange and to invoke operations. In this context, the ability to measure the current and expected degree of interoperability becomes relevant: 1) to understand the implications of defining a toolchain (need of different protocols, formats, schemas and tool interconnections) and 2) to measure the effort to implement the desired toolchain. To improve the management of the engineering lifecycle, a method is defined: 1) to measure the degree of interoperability within a technical engineering process implemented with a toolchain and 2) to estimate the effort to transition from an existing toolchain to another. A case study in the field of digital hardware design comprising 6 different technical engineering processes and 7 domain engineering tools is conducted to demonstrate and validate the proposed method.The work leading to these results has received funding from the H2020-ECSEL Joint Undertaking (JU) under grant agreement No 826452-“Arrowhead Tools for Engineering of Digitalisation Solutions” and from specific national programs and/or funding authorities. Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2023)

Activating supply chain business models' value potentials through Systems Engineering

New business opportunities, driven by smart digitalization technology and initiatives such as Industry 4.0, significantly change business models and their innovation rate. The complexity of methodologies developed in recent decades for balancing exploration and exploitation activities of digital transformation has risen. Still, the desired integration levels across organizational levels were often not reached. Systems thinking promises to holistically consider interdisciplinary relationships and objectives of various stakeholders across supply chain ecosystems. Systems theory-based concepts can simultaneously improve value identification and aligned transformation among supply networks' organizational and technical domains. Hence, the study proposes synthesizing management science concepts such as strategic alignment with enterprise architecture concepts and artificial intelligence (AI)-driven business process optimization to increase innovation productivity and master the increasing rate of business dynamics at the same time. Based on a critical review, the study explores concepts for innovation, transformation, and alignment in the context of Industry 4.0. The essence has been compiled into a systems engineering-driven framework for agile value generation on operational processes and high-order capability levels. The approach improves visibility for orchestrating sustainable value flows and transformation activities by considering the ambidexterity of exploring and exploiting activities and the viability of supply chain systems and sub-systems. Finally, the study demonstrates the need to harmonize these concepts into a concise methodology and taxonomy for digital supply chain engineering.OA-hybri

A DIGITAL TWIN MODEL-BASED SYSTEM ENGINEERING APPROACH TO FAILURE ANALYSIS FOR AN ENGINE SYSTEM

In every portion of a product’s life cycle, system failures can occur. The DOD and defense contractors use failure analysis methods such as Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA), which have successfully reduced maintenance downtime and lowered life cycle costs as a result of reducing failures during system operations. However, challenges can hinder the effectiveness of failure analysis and have not been fully addressed due to limitations of current failure analysis and root cause analysis methods. This thesis addresses two of the challenges: (1) incorrectly classified system failures and (2) lack of failure traceability in the system life cycle. A methodology is proposed that incorporates some elements of both FMEA and FTA into a digital twin (DT) by employing the MBSE tool Magic Systems of Systems Architecture (MSOSA) to aid in failure analysis. An MBSE model simulation using an example of an engine is presented to demonstrate the efficacy of the methodology. The results are shown in terms of system operational availability. This research concludes that the approach has potential in emulating the real system’s behavior and can offer a more accurate estimated result. However, due to semantic errors in modeling in MSOSA, the model was unable to generate accurate results as intended. The model’s semantic errors must be addressed before it can be validated by comparing the results from MBSE model and the corresponding real-world system.Civilian, ST Engineering Land Systems Ltd, SingaporeApproved for public release. Distribution is unlimited