Currently, Open Platform Communication Unified Architecture (OPC UA) is nominated as a reference standard to meet all Industry 4.0 demands with one protocol, enabling an efficient communication between devices in industrial systems. Recently, OPC UA has been extended by a publish/subscribe pattern to support multicast communication since there is a need for an efficient data aggregation and distribution to cope with the increasing number of controllers, sensors, and measured values in industries. Message Queuing Telemetry Transport (MQTT) is the most widely used publish/subscribe communication protocol and is based on a central broker for message exchange. In this paper, the communication latency of OPC UA end devices exchanging data over MQTT as a broker-based middleware is investigated and compared to the client/server-based communication. In particular, we analyze the use case of one-to-many communication for a crane model from the material handling domain. We provide a prototype implementation of the OPC UA MQTT extension and our evaluation results show the reduced traffic overhead and communication latency compared to client/server-based communication.

Indoor positioning enables mobile machines to perform tasks (semi-)automatically, such as following an operator. However, the usefulness and safety of these applications depends on the reliability of the estimated operator localization. Thus, quantifying the accuracy of positioning at runtime is critical for the application in real-world industrial contexts. In this paper, we present a method that produces an estimate of the current positioning error for each user stride. To accomplish this, we construct a virtual stride vector from Ultra-Wideband (UWB) position measurements. The virtual vectors are then compared to stride vectors from a foot-mounted Inertial Measurement Unit (IMU). Using these independent measurements, we estimate the current reliability of the UWB measurements. Positioning errors are mitigated through loosely coupled filtering of both vector types. We evaluate our method in three environments, showing that it improves positioning accuracy, especially in challenging conditions with obstructed line of sight and sparse UWB infrastructure. Additionally, we demonstrate the mitigation of simulated spoofing attacks on UWB positioning. Our findings indicate that positioning quality can be judged at runtime by comparing user strides reconstructed from UWB and IMU measurements. Our method is independent of situation- or environment-specific parameter tuning, and as such represents a promising approach for detecting both known and unknown positioning error states.

The ability to locate assets and humans will lead to many services such as location based services especially in the material handling domain. The development of Industrial Internet of Things (IIoT) necessitates precise positioning, especially for moving objects in industrial environment. This way, automation processes with less human errors, and more safe environments are feasible. In order to achieve a wide reaching penetration of new control and tracking schemes in the Material Handling Domain (MHD), localization of assets needs to be realized in a cost efficient way with sufficient quality of positioning. The cost and quality of localization need to be weighted against each other and depend on the use case. We investigate variations of a indoor localization system, this is done through acquiring raw measurements from an Ultra Wide-Band (UWB) ranging system and comparing various processing approaches to achieve accurate positioning. We then compare the computational cost and quality of positioning of these approaches. Three multilateration algorithms are compared: gradient descent, least square, and recursive least square. Additionally, we investigate the impact of anchor node placement and additional filtering through a Kalman filter. We show that the maximum positioning error is mitigated by up to 30 % and the mean error by up to 4 % when using additional Kalman filtering of multilateration position estimates at comparably low additional computation cost. Our results suggest there are significant differences of localization quality and computational cost between the examined multilateration methods with no clear correlation of computational cost and positioning quality. We also show that the positioning quality and filtering improvement strongly depends on the UWB anchor height.

Current control processes in the material handling domain are generally not automated but require manual human intervention. However, the ongoing development towards the Industry 4.0 involves new models and concepts and hence more and more automated control functions will become necessary. That is, devices such as cranes in the material handling domain will become smarter and will also be networked to a larger extent. However, it will be required that control messages passed to the cranes through a network, possibly shared with other traffic, are guaranteed to arrive in time. In this paper, we present an OPC UA-based model of an overhead travelling crane as part of a material handling scenario. The crane can be controlled by a crane remote controller, which we model as well. We use time-sensitive networking technology to ensure deterministic communication between the crane remote controller and the crane. To demonstrate the crane movement, we illustrate it in a simulation before we prove the deterministic communication in a real testbed.