A Review on Application of Model Based Systems Engineering to Manufacturing and Production Engineering Systems

Increasing complexity in today’s manufacturing and production industry due to the need for higher flexibility and competitiveness is leading to inconsistencies in the iterative exchange loops of the system design process. To address these complexities and inconsistencies, an ongoing industry trend for organizations to make a transition from document-centric principles and applications to being model-centric is observed. In this paper, a literature review is presented highlighting the current need for an industry-wide transition from document-centric systems engineering to Model-Based Systems Engineering (MBSE). Further, investigating the tools and languages used by the researchers for facilitating the transition to and the integration of MBSE approach, we identify the most commonly used tools and languages to highlight the applicability of MBSE in the manufacturing and production industry

Cyber-Physical Manufacturing Metrology Model (CPM3) for Sculptured Surfaces - Turbine Blade Application

Cyber-Physical Manufacturing (CPM) and digital manufacturing represent the key elements for implementation of Industry 4.0 framework. Worldwide, Industry 4.0 becomes national research strategy in the field of engineering for the following ten years. The International Conference USA-EU-Far East-Serbia Manufacturing Summit was held from 31st May to 2nd June 2016 in Belgrade, Serbia. The result of the conference was the development of Industry 4.0 Model for Serbia as a framework for New Industrial Policy - Horizon 2020/2030. Implementation of CPM in manufacturing systems generates " smart factory". Products, resources, and processes within smart factory are realized and controlled through CPM model. This leads to significant advantages with respect to high product/process quality, real-time applications, savings in resources consumption, as well as, lower costs in comparison with classical manufacturing systems. Smart factory is designed in accordance with sustainable and service-oriented best business practices/models. It is based on optimization, flexibility, self-adaptability and learning, fault tolerance, and risk management. Complete manufacturing digitalization and digital factory are the key elements of Industry 4.0 Program. In collaborative research, which we carry out in the field of quality control and manufacturing metrology at University of Belgrade, Faculty of Mechanical Engineering in Serbia and at Department of Mechanical Engineering, University of Texas, Austin in USA, three research areas are defined: (a) Digital manufacturing - towards Cloud Manufacturing Systems (as a basis for CPS), in which quality and metrology represent integral parts of process optimization based on Taguchi model, and (sic) Cyber-Physical Quality Model (CPQM) - our approach, in which we have developed and tested intelligent model for prismatic parts inspection planning on CMM (Coordinate Measuring Machine). The third research area directs our efforts to the development of framework for Cyber-Physical Manufacturing Metrology Model (CPM3). CPM3 framework will be based on integration of digital product metrology information through metrology features recognition, and generation of global/local inspection plan for free-form surfaces; we will illustrate our approach using turbine blade example. This paper will present recent results of our research on CPM3

Approach to Adapt a Legacy Manufacturing System Into the IoT Paradigm

This work has been supported by Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, by Uninova-CTS research unit and by national funds through FCT -Fundação para a Ciência e a Tecnologia within the research unit CTS - Centro de Tecnologia e Sistemas (project UID/EEA/00066/2013). The authors would like to thank all the institutions.Enterprises are adopting the Internet of Things paradigm as a strategy to improve competitiveness. But enterprises also need to rely on their legacy systems, which are of vital importance to them and normally difficult to reconfigure or modify, their mere replacement being usually not affordable. These systems constitute, therefore, barriers to agility and competitiveness, raising the need to develop cost-effective ways for IoT adaptation. An approach for adapting legacy manufacturing systems into the IoT realm is proposed in this research. The methodology is twofold: an adaptation board is firstly designed to provide IoT connectivity, allowing to remotely invoke the “legacy” functionality as services. Then, the board itself can leverage the legacy system by developing additional functionalities inside it, as the update process is usually triggered by the need of new functionality from these systems. An experiment, which consists of adapting to IoT a small distribution line that is controlled by an aged Programmable Logic Controller, is developed to illustrate how straightforward, affordable and cost effective the adaptation approach is, allowing to holistically achieve a new system with more sophisticated functionality.publishersversionpublishe

A Systematic Mapping Study on Modeling for Industry 4.0

International audienceIndustry 4.0 is a vision of manufacturing in which smart, interconnected production systems optimize the complete value-added chain to reduce cost and time-to-market. At the core of Industry 4.0 is the smart factory of the future, whose successful deployment requires solving challenges from many domains. Model-based systems engineering (MBSE) is a key enabler for such complex systems of systems as can be seen by the increased number of related publications in key conferences and journals. This paper aims to characterize the state of the art of MBSE for the smart factory through a systematic mapping study on this topic. Adopting a detailed search strategy, 1466 papers were initially identified. Of these, 222 papers were selected and categorized using a particular classification scheme. Hence, we present the concerns addressed by the modeling community for Industry 4.0, how these are investigated, where these are published, and by whom. The resulting research landscape can help to understand, guide, and compare research in this field. In particular, this paper identifies the Industry 4.0 challenges addressed by the modeling community, but also the challenges that seem to be less investigated

A survey on the model-centered approaches to conceptual modeling of IoT systems

Internet of Things (IoT) is a system of connected objects, entities, devices, and components which share and transfer data over a network. Many papers are published on the topic of conceptual models in the IoT context, but it is difficult to assess the current status of the conceptual modeling approaches and methods for IoT systems. This paper presents an overview of the state of the art as well as discusses fundamental concepts, challenges and current research gaps with potential future agenda for conceptual modeling of IoT. Search facilities in the selected online repositories were used to identify the most relevant papers. The primary results were scanned and papers were selected according to the inclusion/exclusion criteria. Selected papers were assessed to extract data for the defined attributes. This paper confirms that there is a large body of research related to modeling of IoT systems. However, the results show that there is a lack of commonly agreed approaches and supporting formal methods for conceptual modeling of IoT systems. On the other hand, recent studies that apply model-based or model-driven development principles that use ontology or metamodel based approaches are promising due to systematic use of models as the primary means of a development process enabling for the dissemination of the methods further to the emerging fields such as smart cities, factories, transportation, hospitals, healthcare, hospitality and tourism, etc