DSL-based Interoperability and Integration in the Smart Manufacturing Digital Thread

In the industry 4.0 ecosystem, a Digital Thread connects the data and processes for smarter manufacturing. It provides an end to end integration of the various digital entities thus fostering interoperability, with the aim to design and deliver complex and heterogeneous interconnected systems. We develop a service oriented domain specific Digital Thread platform in a Smart Manufacturing research and prototyping context. We address the principles, architecture and individual aspects of a growing Digital Thread platform. It conforms to the best practices of coordination languages, integration and interoperability of external services from various platforms, and provides orchestration in a formal methods based, low-code and graphical model driven fashion. We chose the Cinco products DIME and Pyrus as the underlying IT platforms for our Digital Thread solution to serve the needs of the applications addressed: manufacturing analytics and predictive maintenance are in fact core capabilities for the success of smart manufacturing operations. In this regard, we extend the capabilities of these two platforms in the vertical domains of data persistence, IoT connectivity and analytics, to support the basic operations of smart manufacturing. External native DSLs provide the data and capability integrations through families of SIBs. The small examples constitute blueprints for the methodology, addressing the knowledge, terminology and concerns of domain stakeholders. Over time, we expect reuse to increase, reducing the new integration and development effort to a progressively smaller portion of the models and code needed for at least the most standard application

The Qualitative background of why a DSL knowledge based platform is needed in the context of Sustainability

With reference to Smart Manufacturing and Industry 4.0 in general, a Digital Thread connects the data and processes for smarter products, smarter production, and smarter integrated ecosystems. While the tangible goods (products and production lines) are understood as needing a Digital Twin as an executable model, i.e. an in-silico entity on which to virtually explore design, production, quality, and lifetime maintenance, the immaterial goods like software and analytics artefacts are not yet treated on par. For the new Digital Thread paradigm to enter the mainstream, models need to be coupled with AI, ML and Data Analytics capabilities, to provide an integrated platform for automatic transformations, generations, and analyses that take advantage of the formalized knowledge about the immaterial and material entities. The formalized knowledge needs to include a variety of models together with Domain Specific Languages that use semantic types at their core. The objective of this overall work is to develop a service-oriented Domain Specific Language (DSL) platform for knowledge management (KM-DSL) especially concerning sustainability and risk management, and then apply it in the context of the Digital Thread platform and demonstrators currently under development in the research group. The KM-DSL is the basis for the design of the smart and aligned processes and workflows that will describe and characterize the collaboration of humans and machines in the future advanced production environments. This paper will examine two strands of that work looking at business logic and understanding along with knowledge harvesting that concentrate on two case studies that will underpin future research to create the aforementioned DSL platform for knowledge management

Innovative Digital Manufacturing Curriculum for Industry 4.0

Manufacturing companies across all major industries are facing serious challenges trying to competitively design and manage modern products, which are becoming increasingly complex multi-domain systems or “systems of systems”. Model-based systems driven product development (or SDPD, for Systems Driven Product Development) has been proposed as a solution based on driving the product lifecycle from the systems requirements and tracing back performance to stakeholders’ needs through a RFLP (Requirement, Functional, Logical, Physical) traceability process. The SDPD framework integrates system behavioral modeling with downstream product design and manufacturing process practices to support the verification/validation of the systems behavior as products progress through all phases of the lifecycle, as well as the optimization of trade-offs decisions by maintaining the cross-product digital twin and thread for global decision optimization in an efficient and effective way. We have developed an innovative digital manufacturing curriculum (designed around the SDPD paradigm) that is based on the digitalization of the SE (Systems Engineering) process through the integration of modelling and simulation continuum, in the form of Model-based Systems Engineering (MBSE), with Product lifecycle management (PLM). At the core of this curriculum is a shift of focus from theory to implementation and practice, through an applied synthesis of engineering fundamentals and systems engineering, that is driven by a state-of-the-art digital innovation platform for product (or system) development consisting of integrated software (digital) tools spanning the complete lifecycle. The curriculum consists of three key components, namely, modelling and simulation continuum, traceability, and digital thread. The curriculum provides a foundation for implementing the digital twin and supports the training of the next generation of engineers for Industry 4.0. The digital manufacturing (or SDPD) framework is applied in the design and optimization of an electric skateboard. The implementation demonstrates: 1) The benefits of digitalization/model-based engineering when developing complex multi-domain products or systems; 2) The ability of students to effectively complete a real-life modern product development within the time line of one semester; 3) The provision of MBSE curriculum for Engineering Education 4.0, characterized by key, integrated skills for the digital enterprise and Industry 4.0

Trends in model-based definition based assembly information in high-value manufacturing

3D modelling is in use for the last many decades at various stages of the product lifecycle i.e., design, analysis, manufacturing, and inspection. In the modern era of Industry 4.0 where the high-value manufacturing industry is aiming at the digital thread, Model-Based Definition (MBD) has been considered as the heart of this transformation. However, MBD needs to be realized throughout the product lifecycle to get full advantage. In literature, considerable work has been found focusing on a shift from traditional 2D drawings to MBD. The majority of this work concentrates on design, manufacturing, and inspection stages, whereas, there is a lack of work in the area of MBD based assembly information. This paper focuses on the current state of knowledge in MBD based assembly information, trends, challenges, and future research directions

The potential of additive manufacturing in the smart factory industrial 4.0: A review

Additive manufacturing (AM) or three-dimensional (3D) printing has introduced a novel production method in design, manufacturing, and distribution to end-users. This technology has provided great freedom in design for creating complex components, highly customizable products, and efficient waste minimization. The last industrial revolution, namely industry 4.0, employs the integration of smart manufacturing systems and developed information technologies. Accordingly, AM plays a principal role in industry 4.0 thanks to numerous benefits, such as time and material saving, rapid prototyping, high efficiency, and decentralized production methods. This review paper is to organize a comprehensive study on AM technology and present the latest achievements and industrial applications. Besides that, this paper investigates the sustainability dimensions of the AM process and the added values in economic, social, and environment sections. Finally, the paper concludes by pointing out the future trend of AM in technology, applications, and materials aspects that have the potential to come up with new ideas for the future of AM explorations

Shipbuilding 4.0 Index Approaching Supply Chain

The shipbuilding industry shows a special interest in adapting to the changes proposed by the industry 4.0. This article bets on the development of an index that indicates the current situation considering that supply chain is a key factor in any type of change, and at the same time it serves as a control tool in the implementation of improvements. The proposed indices provide a first definition of the paradigm or paradigms that best fit the supply chain in order to improve its sustainability and a second definition, regarding the key enabling technologies for Industry 4.0. The values obtained put shipbuilding on the road to industry 4.0 while suggesting categorized planning of technologies