A Functional Reasoning Framework and Dependency Modeling Scheme for Mechatronics Conceptual Design Support

RÉSUMÉ La conception mécatronique est un processus de design pluridisciplinaire, il repose sur l'intégration synergique des domaines d’ingénierie mécanique, électrique, contrôle et logiciel pour concevoir des produits qui surpassent les autres produits en termes d'efficacité, de précision, de coût et de fiabilité. Toutefois, cela a un coût, la conception de systèmes multidisciplinaire est une tâche ardue qui exige beaucoup de coordination et de coopération entre les ingénieurs concepteurs. Beaucoup de ces difficultés ont été reportées dans les domaines académique et industriel. Il en ressort que la communication technique entre les concepteurs appartenant à diverses disciplines d’ingénierie se fait très difficilement et ce en raison de l'absence d'un langage commun pour représenter les différents concepts. Ceci entraîne des difficultés majeures à transférer les modèles et les informations pertinentes entre les domaines ce qui entrave la possibilité d’appliquer un processus de développement intégré (concurrent). Pourtant, d’une part, un processus de conception intégré et dynamique doit être suivi pour réduire le temps de conception du projet et ainsi réduire les couts et supporter l'innovation. D’autre part, la conception multidisciplinaire se traduit par l’introduction d’un grand nombre de dépendances durant la conception, rendant ainsi les activités de conception difficile à synchroniser entravant le processus intégré. En raison de l'absence d'outil de support informatique pour le design conceptuel, et l'importance de considérer les dépendances le plus tôt possible dans le processus de conception, un cadre de raisonnement fonctionnel en conjonction avec un système de modélisation des dépendances (liées au produit) ont été développés dans ce mémoire de maîtrise. Le cadre de raisonnement fonctionnel a été réalisé par la personnalisation du langage SysML (Systems Modeling Language), et par le développement d’un module d’extension (plug-in) dans l'outil de modélisation MagicDraw (No Magic, Inc.). Le plug-in intègre un système expert à base de règles (CLIPS : C Language Integrated Production System - NASA) qui permet d’encapsuler les connaissances d'ingénierie sous la forme de règles pour analyser et effectuer des tâches sur des diagrammes fonctionnels. Une nouvelle approche d'acquisition et une représentation schématique de dépendances ont été proposées. La notion de "méta-dépendances» a été introduite pour modéliser les dépendances qui sont partagées par un grand nombre d'éléments dans un même système.----------ABSTRACT Mechatronics is a multidisciplinary design process that relies on the synergic integration of mechanical, electrical, control, and software engineering to deliver products that outperform their competitors in terms of efficiency, precision, cost and reliability. However, this comes at a cost, designing multi-disciplinary systems is a challenging task that requires a lot of coordination and cooperation between designers. Several challenges are reported by both academic and industry-related literature. One of the most important is the tedious communication between engineering designers from various disciplines due to a lack of a common language to represent concepts. This leads to difficulties in transferring models and pertinent information between domains. To succeed in nowadays competitive markets, a concurrent and dynamic design process should be followed to reduce the project lead-time and spark innovation. However, such a process results in many dependencies as a consequence of multi-disciplinary design and it is often difficult to streamline the design activities. Due to the lack of existing computational support tools for conceptual design of mechatronics and the importance of taking dependencies (product related) into account as early as possible in the design process, a functional reasoning framework as well as a dependency modeling scheme were developed in this master thesis. The functional reasoning framework was realised by customizing the SysML (Systems Modeling Language) language and developing a plug-in in the modeling tool MagicDraw (No Magic, Inc.). The plug-in integrates the rule-based expert system CLIPS (C Language Integrated Production System - NASA) that allows encapsulating engineering knowledge in the form of rules to analyze and perform tasks on functional diagrams. A new acquisition method and representation scheme of dependencies was proposed in this master thesis. The concept of “meta-dependency” was introduced to model dependencies shared by a large number of elements in a same mechatronic system or sub-system. It allows engineering designers to efficiently and abstractly capture dependencies early in the deign process and reduces the number of relationships to be built manually between dependent elements in the system

Life Cycle of Multi Technology Machine Tools – Modularization and Integral Design

AbstractFor reasons of high flexibility but still maximum productivity, machine tools integrating various production technologies have recently received particular attention. Combining and integrating multiple manufacturing techniques into one single system in early stages of the product emergence process is challenging. To keep the effort for implementation to a minimum, an initiation already in the concept phase is being actively pursued. Design guidelines are currently investigated based on the examination of different technology combinations.This approach focuses on systematic conceptual design for such hybrid machine technologies. Product architectures are used to describe the modularity and create a specific delimitation for standardization. Reference product architectures for Multi Technology Machine Tools (MTMT) carry high potential for saving expenses in product development. The main emphasis is on technology and system integration. A technological similarity assessment of the single processes involved forms the basis of this approach to assure potential for synergies. Monetary aspects in early stages of product development are considered. Based on the analysis a generic system model is connected with general product architectures for MTMT.The method introduced is validated by a Multi-Technology Machining Centre with two simultaneously usable workspaces integrating a milling spindle and two laser processing units. The research undertaken is part of the Cluster of Excellence “Integrative Production Technology for High-Wage Countries” and has been funded by German Research Foundation (DFG)

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

A Smart Products Lifecycle Management (sPLM) Framework - Modeling for Conceptualization, Interoperability, and Modularity

Autonomy and intelligence have been built into many of today’s mechatronic products, taking advantage of low-cost sensors and advanced data analytics technologies. Design of product intelligence (enabled by analytics capabilities) is no longer a trivial or additional option for the product development. The objective of this research is aimed at addressing the challenges raised by the new data-driven design paradigm for smart products development, in which the product itself and the smartness require to be carefully co-constructed. A smart product can be seen as specific compositions and configurations of its physical components to form the body, its analytics models to implement the intelligence, evolving along its lifecycle stages. Based on this view, the contribution of this research is to expand the “Product Lifecycle Management (PLM)” concept traditionally for physical products to data-based products. As a result, a Smart Products Lifecycle Management (sPLM) framework is conceptualized based on a high-dimensional Smart Product Hypercube (sPH) representation and decomposition. First, the sPLM addresses the interoperability issues by developing a Smart Component data model to uniformly represent and compose physical component models created by engineers and analytics models created by data scientists. Second, the sPLM implements an NPD3 process model that incorporates formal data analytics process into the new product development (NPD) process model, in order to support the transdisciplinary information flows and team interactions between engineers and data scientists. Third, the sPLM addresses the issues related to product definition, modular design, product configuration, and lifecycle management of analytics models, by adapting the theoretical frameworks and methods for traditional product design and development. An sPLM proof-of-concept platform had been implemented for validation of the concepts and methodologies developed throughout the research work. The sPLM platform provides a shared data repository to manage the product-, process-, and configuration-related knowledge for smart products development. It also provides a collaborative environment to facilitate transdisciplinary collaboration between product engineers and data scientists

Permanently updated 3D‑model of actual geometries of research environments

This report describes the approach to create permanently updated 3D models of research aircraft and laboratory facilities. Therefore, optical metrology scans the research environment in its raw or as-delivered condition. The result is a virtual model of the actual geometry and, in comparison to reference data (e.g. CAD-data), the smallest inaccuracies can be identi- fied and analyzed. The exact position of non-rigid components, like riser ducts, electronics or isolation, can be determined in the models. Further changes to the layout of these facilities are permanently digitized and added to the virtual model of the environment. This can be a new recording of the entire facility or of individual areas that are affected by the changes. The individual, newly recorded models are then integrated into the existing model. This creates an always up-to-date 3D model of the research environment, which is added to its digital twin and can be observed there. In combination with CAD data, future conversion and installation measures are planned in advance and analyzed virtually in relation to the up-to-date geometry and installation space data. In addition, the virtual models of the aircraft cabins can be used to support the lengthy approval and certification process at an early stage

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools