Leveraging Circular Economy through a Methodology for Smart Service Systems Engineering

Product Service Systems (PSS) and Smart Services are powerful means for deploying Circular Economy (CE) goals in industrial practices, through dematerialization, extension of product lifetime and efficiency increase by digitization. Within this article, approaches from PSS design, Smart Service design and Model-based Systems Engineering (MBSE) are combined to form a Methodology for Smart Service Architecture Definition (MESSIAH). First, analyses of present system modelling procedures and systems modelling notations in terms of their suitability for Smart Service development are presented. The results indicate that current notations and tools do not entirely fit the requirements of Smart Service development, but that they can be adapted in order to do so. The developed methodology includes a modelling language system, the MESSIAH Blueprinting framework, a systematic procedure and MESSIAH CE, which is specifically designed for addressing CE strategies and practices. The methodology was validated on the example of a Smart Sustainable Street Light System for Cycling Security (SHEILA). MESSIAH proved useful to help Smart Service design teams develop service-driven and robust Smart Services. By applying MESSIAH CE, a sustainable Smart Service, which addresses CE goals, has been developed

Analysis of potential errors in technical products by combining knowledge graphs with MBSE approach

Technical products are developed to meet the demands of stakeholders. Therefore, the product's functions and associated properties are important. Various influencing factors e.g., external disturbances can have an impact on the input flows of the products or its characteristics and thus on the functions. If this leads to deviations between the required and as-is functions, these deviations are called errors. It is therefore important to analyze errors in product development and implement measures to increase the robustness of the product. Model-Based Systems Engineering (MBSE) supports the development of complex systems. However, MBSE alone has limited ability to identify in-depth errors. This requires knowledge of possible errors from previous products in specific contexts. For this purpose, the method proposed in this paper facilitates identifying errors in the concept phase by combining MBSE approaches with reusable knowledge (i.e., knowledge graph). The approach is presented using an application example for a mobile robot

Digital Twin: towards the integration between System Design and RAMS assessment through the Model–Based Systems Engineering

The design of a safety-critical system requires an effective prediction of its reliability, availability, maintainability and safety (RAMS). Anticipating the RAMS analysis at the concept design helps the designer in the trade-off of the system architecture and technologies, reduces cost of product development and the time to market. This action is rather difficult, because the RAMS analysis deals with the hazard assessment of system components, whose abstraction at concept level is never simple. Therefore, to integrate the system design and RAMS assessment, a clear path to follow is required. The paper investigates how the Model Based Systems Engineering (MBSE) supports this task and drives the system reliability allocation, through the functional and dysfunctional analyses. The implementation of the proposed approach needs to set up the tool chain. In the industrial context it must be compatible with practices, standards and tools currently used in product development. Defining a suitable process of integration of tools used for the System Design and the Safety Engineering is a need of industry. Therefore, this task is also discussed, in this paper, dealing with some examples of industrial test case

Multi Domain Design: Integration and Reuse

Design of mechatronic systems is becoming increasingly complex. Companies must continuously reduce time-to-market while increasing the quality, diversity, and functionality of their products. As a result, more and more specialists from various domains are needed to develop such products. To reduce time-to-market, many companies look to reducing the time it takes to design a product. Many focus on the reuse of design objects, leading to libraries of templates and standard components to speed up their design process. However, these reusable design objects are developed and maintained in the specialists’ domains, resulting in communication and integration issues between these domains. This paper discusses these issues and proposes a combined approach for model reuse, design integration, and communication between the designers, design tools, and models involved. A case study at a multi-national company successfully demonstrated that the approach leads to a faster and more consistent design process

A Knowledge-Based Engineering System Framework for the Development of Electric Machines

The new concept industry 4.0 is a great opportunity to improve the competitiveness in a global market for small-medium size electric machinery companies. The demand for electric motors have increased in the last decade especially due to applications that try to make a full transition from fuel to electricity. These applications encounter the need for tailor-made motors that must meet demanding requirements. Therefore, it is mandatory small-medium companies adopt new technologies offering customized products fulfilling the customers’ requirements according to their investment capacity. Furthermore, simplify their development process as well as to reduce computational time to achieve a feasible design in shorter periods. In addition, find ways to retain know-how that is typically kept within each designer either to retrieve it or transfer it to new designers. To support the aforementioned issue, a knowledge-based engineering (KBE) system framework for the development of electric machines is devised. The framework is encapsulated in the so-called KBV2-model comprising the standardized macro-level framework for electrical machine and the knowledge base generation process. This thesis describes this model and the integration of KBE applications with current industrial technologies such as Model-Based Systems Engineering (MBSE), Product Lifecycle Management (PLM), multiphysics and analytical design tools. This architecture provides capability to manage and automate tasks in the development process of electric machines. The author of this work has opted to develop KBE applications following the minimum viable product principle. The KBE system framework herein presented is formalized through the experience and analysis of the development and implementation of the KBE applications. From which a guideline is provided following a sequential process in order to achieve a viable KBE system. To substantiate the process a KBE system is created that supports the development of electric motors for the elevator system industry