Industrial Internet of Things practitioners are adopting the concept of digital twins at an accelerating pace. The features of digital twins range from simulation and analysis to real-time sensor data and system integration. Implementation examples of modeling-oriented twins are becoming commonplace in academic literature, but information management-focused twins that combine multiple systems are scarce. This study presents, analyzes, and draws recommendations from building a multi-component digital twin as an industry-university collaboration project and related smaller works. The objective of the studied project was to create a prototype implementation of an industrial digital twin for an overhead crane called “Ilmatar”, serving machine designers and maintainers in their daily tasks. Additionally, related cases focus on enhancing operation. This paper describes two tools, three frameworks, and eight proof-of-concept prototypes related to digital twin development. The experiences show that good-quality Application Programming Interfaces (APIs) are significant enablers for the development of digital twins. Hence, we recommend that traditional industrial companies start building their API portfolios. The experiences in digital twin application development led to the discovery of a novel API-based business network framework that helps organize digital twin data supply chains.

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Industrial Cyber-Physical Systems consist of multiple machines working together and demand efficient and flexible communication methods to function as intended. The protocols used in industrial operations and web applications are often contradictory in regards to the latency and security characteristics. Due to these differences, the intersection of operation and information technologies is a challenging area. But the rewards in smoother information flow are also high, providing a fruitful area for development. This paper introduces a general wrapper application to enable the use of the industrial OPC UA server through an interface implemented with web technology GraphQL. The results demonstrate sufficient performance for the middleware to be used in an overhead crane control application, bringing the agility of web development to industrial environments.

Data collection in an industrial environment enables several benefits: processes and machinery can be monitored; the performance can be optimized; and the machinery can be proactively maintained. To collect data from machines or production lines, numerous sensors are required, which necessitates a management system. The management of constrained IoT devices such as sensor nodes is extensively studied. However, the previous studies focused only on the remote software updating or configuration of sensor nodes. This paper presents a holistic Open Sensor Manager (OSEMA), which addresses also generating software for different sensor models based on the configuration. In addition, it offers a user-friendly web interface, as well as a REST API (Representational State Transfer Application Programming Interface) for the management. The manager is built with the Django web framework, and sensor nodes rely on ESP32-based microcontrollers. OSEMA enables secure remote software updates of sensor nodes via encryption and hash-based message authentication code. The collected data can be transmitted using the Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT). The use of OSEMA is demonstrated in an industrial domain with applications estimating the usage roughness of an overhead crane and tracking its location. OSEMA enables retrofitting different sensors to existing machinery and processes, allowing additional data collection.

Industry 4.0 is moving forward under technology upgrades, utilizing information technology to improve the intelligence of the industry, whereas Industry 5.0 is value-driven, aiming to focus on essential societal needs, values, and responsibility. The manufacturing industry is currently moving towards the integration of productivity enhancements and sustainable human employment. Such a transformation has deeply changed the human–machine interaction (HMI), among which digital twin (DT) and extended reality (XR) are two cutting-edge technologies. A manufacturing DT offers an opportunity to simulate, monitor, and optimize the machine. In the meantime, XR empowers HMI in the industrial field. This paper presents an XR application framework for DT-based services within a manufacturing context. This work aims to develop a technological framework to improve the efficiency of the XR application development and the usability of the XR-based HMI systems. We first introduce four layers of the framework, including the perception layer with the physical machine and its ROS-based simulation model, the machine communication layer, the network layer containing three kinds of communication middleware, and the Unity-based service layer creating XR-based digital applications. Subsequently, we conduct the responsiveness test for the framework and describe several XR industrial applications for a DT-based smart crane. Finally, we highlight the research challenges and potential issues that should be further addressed by analyzing the performance of the whole framework.

Digital twin documents are expected to form a global network of digital twins, a “Digital Twin Web”, that allows the discovery and linking of digital twins with an approach similar to the World Wide Web. Digital twin documents can be used to describe various aspects of machines and their twins, such as physical properties, nameplate information, and communication interfaces. Digital twin is also one of the core concepts of the fourth industrial revolution, aiming to make factories more efficient through optimized control methods and seamless information flow, rendering them “smart factories”. In this paper, we investigate how to utilize digital twin documents in smart factory communication. We implemented a proof-of-concept simulation model of a smart factory that allowed simulating three different control methods: centralized client-server, decentralized client-server, and decentralized peer-to-peer. Digital twin documents were used to store the necessary information for these control methods. We used Twinbase, an open-source server software, to host the digital twin documents. Our analysis showed that decentralized peer-to-peer control was most suitable for a smart factory because it allowed implementing the most advanced cooperation between machines while still being scalable. The utilization of Twinbase allowed straightforward removal, addition, and modification of entities in the factory.

Digital twins (DTs) and eXtended Reality (XR) are two core technological enablers for engineering in the Metaverse that can accelerate the human-centric Industry 5.0 transformation. The digital twin technology provides a digital representation of a physical asset with data linkages for inspection, monitoring, and prediction of complex processes or systems, while eXtended reality offers real-and-virtual combined environments for human users to interact with machines. However, the synergies between digital twins and eXtended reality remain understudied. This work addresses this research gap by introducing a novel method “TwinXR” that leverages ontology-based descriptions of Digital twins, i.e., digital twin documents, in industrial eXtended reality applications. To ease the use of the TwinXR method, we publish a Unity package that allows data flow and conversion between eXtended reality applications and digital twin documents on the server. Finally, the work applies the TwinXR method in two industrial eXtended reality applications involving overhead cranes and a robot arm to demonstrate the use and indicate the validity of the method. We conclude that the TwinXR method is a promising way to advance the synergies between digital twins and eXtended reality: For eXtended reality, TwinXR enables efficient and scalable eXtended reality development; For digital twins, TwinXR unlocks and demonstrates the potential of digital twins for data interchange and system interoperation. Future work includes introducing more detailed principles of Semantic Web and Knowledge Graph, as well as developing factory-level TwinXR-compatible applications.

Industry 4.0 and Cyber-physical systems require easy access to shop-floor data, which allows the monitoring and optimization of the manufacturing process. To achieve this, several papers have proposed various ways to make OPC UA (Open Platform Communications Unified Architecture), a standard protocol for industrial communication, RESTful (Representational State Transfer). As an alternative to REST, GraphQL has recently gained popularity amongst web developers. This paper compares the characteristics of the REST and GraphQL interfaces for OPC UA and conducts measurements on reading and writing data. The measurements show that GraphQL offers better performance than REST when multiple values are read or written, whereas REST is faster with single values. However, using OPC UA directly outperforms both REST and GraphQL interfaces. As a conclusion, this paper recommends using a GraphQL interface alongside an OPC UA server in smart factories to simultaneously yield easy data access, the best performance, and maximum interoperability.