Collaborative Technological Process Planning with 5G Mobile Networks and Digital Tools: Manufacturing Environments Perspective Technological process planning (TPP) requires an adaptation to the newest industrial trends, such as virtual reality (VR), mobile communication networks (e.g. Fifth Generation (5G) networks), Internet of Things (IoT), etc., to satisfy the frequently changing product demands in different manufacturing environments. TPP also uses the best practices, knowledge of experts and various digital tools (DTs), which have been implemented as software or hardware digital solutions, helping to achieve the anticipated production aims in the digital era. The DTs have been developed in parallel to the latest industrial trends. This paper presents the general notion of a collaborative technological process planning approach (CTPPA), taking into account the capabilities of the latest developments in mobile communication techniques such as 5G mobile networks. It also discusses the levels of communication within a manufacturing environment and several scenarios of the CTPPA, by considering TPP performance. Finally, it presents how the new 5G technology and new DTs can enhance TPP in the near future. It also demonstrates how faster data transfer can change the functionalities of existing DTs and redefine TPP methodologies.

Smart manufacturing and DVSM based on an Ontological approach Abstract   Smart manufacturing is characterized as transparent shop floor production, rapid and intelligent responses to dynamic changes, and a utilization of highperformance intercooperation networks. Smart manufacturing and a global appetite for personalized products have transitioned industry from mass production into the age of mass customization. Increased autonomy is slowly changing customer expectations as well, enabling customers to modify a product design not only during an order, but sometimes even long after placing an order. In this context, this paper fills a gap by presenting a datacentric infrastructure to enable interaction with a xe2x80x9cglobal, virtual data space,xe2x80x9d which overcomes the problems with traditional direct access methods such as interoperability and compatibility. Using a CyberPhysical System (CPS), resource monitoring on the shopfloor as well as multiple parities beyond the enterprise boundary will be interconnected through this datacentric infrastructure. A semantic knowledge management system, which encompasses product lifecycle knowledge and manufacturing process ontology, is developed as the data schema in the datacentric infrastructure. In comparison to relational databases which are effective at handling paper forms and tabular structure, the flexible schema of graph databases enable these to handle dynamic and uncertain variables. These capabilities are deemed critical for a platform supporting realtime information exchange between customer, manufacturer and collaborators. One advantage of such a system allowing for realtime information exchange is that it enables last minute order changes by the customer, allowing for product design changes even after production has started on the order. The other advantage is that it allows manufacturing managers to monitor the productivity of customerdirected, dynamic manufacturing processes by utilizing Dynamic Value Stream Mapping (DVSM) methods.