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demonstrates the main components of the Snoopy tool (Snoopy is an open application designed in C++ with installation packages that don't need external dependencies and is available for Windows, Mac OS X, and Linux. It can be obtained free of charge for academic use and is not necessary a specifically hardware configuration, website: https://www-dssz.informatik.tu-cottbus.de/DSSZ/Software/Snoopy (accessed on 20 November 2021)). Circles graph the places of PN, and rectangles represent transitions. In the proposal of this work, places represent passive components, intermediate spaces that allocate the result of message exchange and communication between agents, and transitions represent active components.
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Manufacturing systems need to meet Industry 4.0 (I4.0) guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based...
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Citations
... Fleischmann et al. report that a subjectoriented modeling language, Parallel Activity Specification Schema, is suitable for designing I4C, especially for implementations with OPC UA [42]. Another I4C design framework based on multiple agents with different tasks and optimization has been proposed by Veiga et al. [43,44]. These modeling framework studies explore the design purposes and implementation of I4C. ...
As key components of smart factories, intelligent production machines are gradually becoming a major capital asset of companies in the market, offering connectivity, interoperability, and services. However, due to commercial and technological constraints, production machines rarely provide enough information for customers to develop data-driven applications. Therefore, this research proposes that intelligence should be built into them to assist in production control and to allow relevant data to be collected and made available for future use. In order to realize this proposal, in this paper, an operational paradigm for such systems is first outlined. Then, the states of workpieces in a production environment are classified, and the methods of generation, operation, and transfer of instances described. The next step is to build an intelligent product-driven manufacturing system using Data Distribution Service (DDS). Intelligent workpieces and machines collaborate to complete production tasks in such a system. In the course of this collaborative process, an intelligent workpiece continuously collects relevant data and packages it together for the customer on its transformation into a final product. The feasibility of this intelligent product-driven manufacturing system is examined by upgrading a classic manufacturing factory. In addition, the study explores the system architecture, the implementation of a classic system upgrade, the production data collection, and the intellectualization of data assets. In conclusion, this study’s results will help machine builders expand their business models providing customers with production machines that carry data for advanced data-driven applications.
