The Digital Product Passport (DPP) is a data set that contains information about the product throughout all stages of its lifecycle. Recently, a wide variety of activities are being undertaken to introduce DPP to the industry. However, putting the DPP into practice is still challenging. In this paper, we propose a method to integrate production data acquired from existing manufacturing systems into elements within the DPP submodel, following the required structure of the AAS. We also validate the feasibility of the proposed method and provide a use case of DPP in a real-world environment. The proposed approach provides the benefit of easily creating and managing DPP without the need to modify existing systems. Additionally, it facilitates flexible updates to the information contained within the DPP.

As the digital transformation of the manufacturing industry accelerates, the importance of data integration in manufacturing processes is increasingly emphasized. However, the use of heterogeneous equipment and diverse solutions in building processes hinders smooth data exchange, resulting in compatibility issues among equipment, systems, and data. To address these challenges, the Reference Architecture Model Industry 4.0 (RAMI 4.0) has been proposed as a reference model for Industry 4.0, utilizing the Asset Administration Shell (AAS) to ensure both vertical and horizontal interoperability. In this study, a robot manipulator was modeled using AAS, and the OPC UA protocol was applied to the modeled process elements. Additionally, a digital twin of the robot manipulator was built using MoveIt2 from higher-level systems, allowing for parameter-based control. This facilitates scenario-based integration with heterogeneous equipment such as PLCs, enabling the design of a flexible robot production system that can adapt to the tasks of heterogeneous equipment without human intervention.

The Smart Factory Web (SFW) is a platform that connects Smart Factories over a network to enable flexible sharing and management of resources, assets and inventory to maximize production and efficiency. In order to become part of the Smart Factory Web, network participants describe not only their products, but also the factory capabilities to order to improve factory-to-factory collaboration. A Smart Factory Web Portal (SFWP) enables secure data and service integration in cross-site application scenarios as well as `plug & work' functions for devices, machines, and data analytics software by applying industrial standards, Open Platform Communications Unified Architecture (OPC UA), and Automation Markup Language (AutomationML or AML for short). OPC UA serves as a comprehensive and secure communication protocol from the machine level into the cloud. A Cloud Coupler on the shop floor publishes the availability of a factory and selected process data in the SFWP. Customers or even smart machines can use this information to make decisions for placing an order and track their orders in real time. In order to simplify the setup of the connection to the cloud and minimize the commissioning time the cloud coupler also aggregates all OPC UA servers on devices in the factory into a single OPC UA aggregated server address space. In this paper an architecture is proposed which uses cloud coupler and plug and work techniques to make a new or retrofit factory available in a SFW to share capability information towards a new marketplace for manufacturing. It is shown that the integration efforts are decreased but also the use of standards reduces the effort to define interfaces.

Recently, various applications have emerged which utilize wireless sensor network (WSN) consisting of low cost and low power sensors in smart spaces. Here a great deal of research has been carried out on transmitting video over WSN. WSN has limited resources in terms of bandwidth and data processing capability, while video requires bulk data to be transmitted. In this paper we propose a two-stage Quality of Service (QoS) guaranteeing scheme for video transmission over WSN, called the Multi-Channel Multi-Path (MCMP) scheme. It selects the best paths from the source camera to the gateway based on hop-count, aggregated path energy, BER, and end-to-end delay. A failure recovery scheme is also provided to cope with link failure. Computer simulation reveals that the proposed scheme significantly outperforms the existing scheme in terms of channel utilization and delay.