Advances in digital monitoring, control and management of factory operations are creating increasing demand for reliable wireless communications. The availability and quality of wireless communications in factories can vary abruptly in time and space, presenting challenges for reliable factory operations. This paper presents a method for dynamic allocation of wireless links during an assembly process in a factory that considers both the quality of the wireless links and the time-varying needs of the operators. The method is a particular form of process-aware wireless-link control (PAWLC) with time-share of links using state information available from a process controller. The method allocates to each operator a primary link for normal use and a secondary link of higher quality that may be used only when it is not being used as a primary link by another operator. Previous analysis of a basic model with just two operators showed that assembly process completion times can be largely reduced by this method. This paper describes an extended method that can be used with multiple operators. A theoretical method is presented for computing estimates of completion time based on available link quality. Numerical simulation of a dynamic assembly process model with five operators and five links of different quality shows that completion times can be reduced by up to 78%. Analysis of link usage shows that the usage of low-quality links is reduced and the total link usage is lower with PAWLC, meaning more efficient use of wireless resources.

This paper explores the integration of Smart Resource Flow (SRF) wireless platform with the EmKoI4.0 Orchestrator to enhance industrial network management in Industry 4.0 environments. We examine how the EmKoI Orchestrator, which utilizes Asset Administration Shell for dynamic reconfiguration of 5G Non-Public Networks, can function as an SRF Service Manager to optimize wireless resource allocation. The integration leverages the Central Coordination Point framework specified in IEC 62657-4 for industrial wireless coexistence management. Our approach establishes a multi-layered coordination mechanism where the SRF Field Manager handles localized resource allocation while the EmKoI4.0 Orchestrator provides high-level network adaptation based on application requirements, regulatory constraints, and environmental factors. The paper presents the theoretical framework for this integration and outlines an evaluation plan to assess performance improvements in practical industrial scenarios.

In recent years, automated transportation systems have been used in factories to improve manufacturing efficiency. Trackless automated transportation systems require stable wireless communication for control and monitoring. In this system, equipment must move throughout a large factory area. In cases where outside building area is covered by a public 5G network and inside building area is covered by a non-public 5G network, a system is required to continue wireless communication seamlessly between the non-public 5G network and the public 5G network. We have developed the Smart Resource Flow (SRF) wireless platform to bundle and manage multiple wireless networks. We evaluated the impact of the SRF wireless platform on communication interruption when switching between public and non-public networks. From this evaluation, we confirmed that the communication interruption time was reduced from 9.75 s to 0.14 s by applying the SRF wireless platform.

A measurement method of Power Delay Profile (PDP) using both in-band and out-of-band spectrums for high time-resolution under system operation is proposed for local 5G in this paper. We have proposed the PDP passive measurement method using a receiver antenna for reference near a transmitter equipment under system operation without using any special transmitting (Tx) signal. In this former method, no special Tx signal is necessary. However, there is one disadvantage of limited time-resolution decided by system bandwidth in the former method. We propose one approach using both in-band and out-of-band spectrums for high time-resolution in this paper. An availability of this method is confirmed by a simulation at first. We have also applied this method to PDP measurement for bandwidth-limited RU (Radio Unit) of local 5G system in German factory. Finally, we can confirm an availability of this proposed method.

Private 5G has high expectations from the manufacturing field, and in addition to various evaluation experiments, it has begun to be introduced to production lines. However, many communications used in production lines have strict requirements for latency, and the expansion of its use in applications that require low latency remains an issue for the future. We are proceeding with the evaluation of upstream communication delay, which is important at manufacturing sites and challenging to optimize. In this paper, we introduce a visualization method of Time Division Duplex (TDD) slot utilization and conduct communication evaluation experiments. As a result, we report that the characteristics of the TDD slot utilization differ depending on the base station.

Automated storage systems are used to manage and plan the optimal flow of packages for rapid transportation. Access points (APs) for communicating with the systems are installed and shared with other systems, and their locations cannot be changed for individual systems. To ensure the stable wireless communications for shuttles in the automated storage system, it is necessary to pay attention to changes in the wireless environment due to the layout of APs and surrounding objects. Therefore, we analyze whether the shuttles can communicate to the existed AP with the changes by a ray-trace simulation. The result shows the pallets could be placed at a part of the loading area while maintaining the throughput performance, and placement at the other part affects the shuttle's communication.

Two types of channel model measurement methods are shown in this paper. Type 1 channel model is defined as a relation between distance and path loss for line design and Type2 is defined as a power delay profile (PDP) for MIMO design, respectively. Several measurement methods have been applied for these two channel models. These conventional measurement methods are suitable to implement before starting the system operation using the special transmitter signals. However, these methods are not suitable to use under operational system because it is not available to use these special signals. Therefore, we propose a new measurement method for the mentioned channel models under system operation. We set one receiver antenna for reference near transmitter equipment and a ratio of receiver spectrum and reference spectrum is applied for these measurements. In this proposed method, the special transmitting signal is unnecessary. We have applied this method to local 5G system under operation in Germany. A measurement of type 1 channel model is performed for both line of sight (LOS) and non-line of sight (NLOS) conditions. Especially a gradient linear approximation of the obtained measurement data at LOS condition is near to the gradient of Friis transmission equation. Furthermore, a measurement of type 2 channel model is performed and some obvious multipath signals are obtained.

Robotic automation is becoming prevalent in the manufacturing industry, improving productivity and saving labor. Mobile robotic systems such as Automated Guided Vehicles (AGVs) play critical roles in transport and storage of parts and products. Maintaining reliable wireless communications between AGVs and their control system is essential for high productivity, but often difficult in physically complex wireless environments of storage systems. Specifically, signal loss due to shadowing can trigger operational delays due to the need to check the status of storage operations. On the other, avoiding signal loss requires using more wireless resources. So, it is important to analyze and evaluate the wireless resources required to guarantee efficient operation. However, it is difficult to combine existing simulators for wireless systems and factory systems to analyze inter-dependencies of these systems. This paper presents a method for building a simulation model of a 3D storage system with wireless communication based on multi-layer system analysis. The method is applied to the evaluation of the storage performance and wireless channel usage of a 4-level storage system, including a comparison of the effects of fixed and adaptive rate control. Simulation results shown that adaptive rate control based on learning a spatial map of link quality can achieve reliable storage with up to 50 % reduction in channel load ratio compared to the use of fixed rates. The results demonstrate the usefulness of this type of model for evaluating performance in factory sites with complex wireless environments.

This paper reports the estimation of the radiation characteristics of the harmonics from the K-band wireless power transmission (WPT) system for coexistence consideration with other wireless systems. The transmitting antenna of the WPT system consists of proposed high-gain antennas using higher mode to reduce the number of the RF circuits. The effective isotropic radiated power (EIRP) at the harmonic frequencies of the WPT system were calculated by the simulated gain of the array antenna and the output power from the circuit. The calculation results revealed that the radiation pattern and EIRP at the unknown harmonic frequencies of the WPT system.

The demand for remote management of multiple transport vehicles is growing in factories for labor-saving. To realize the remote management, it is necessary to keep throughput over several dozen Mbps via wireless communication. In this paper, to confirm whether required throughput can be obtained with Local 5G system, we verify whether throughput can be controlled by configuring Guaranteed Flow Bit Rate (GFBR) and Maximum Flow Bit Rate (MFBR). Evaluation results show that throughput can improve by increasing GFBR, but throughput cannot achieve GFBR. The cause is thought that wireless quality is assumed larger than actual value. And evaluation results also show that MFBR limits throughput as configured.

A multi-sensor monitoring system has been developed for real-time monitoring and analysis of indoor wireless communication environments. The system uses commodity hardware and open-source software platforms, which are low cost and suitable for open and cooperative development. It is shown that analysis of time series data of Wi-Fi signal strength obtained from multiple sensors in different rooms can be used to detect predictability relations between signals at different positions.

Automated Guided Vehicles (AGVs) are becoming popular at many manufacturing facilities. To ensure mobility and flexibility, AGVs are often controlled by wireless communication, eliminating the constraints of physical cables. These AGVs require multiple Access Points (APs) to ensure uninterrupted coverage across the site. As AGVs move, they need to switch between these APs seamlessly. A primary challenge is that the communication downtime during this link-switching process must be minimal for effective AGV monitoring and control. Current AP selection strategies based on observed Received Signal Strength Indicator (RSSI) often fail in manufacturing environments due to RSSI’s inherent instability. This paper introduces a new AP selection technique for AGVs navigating these sites. Our approach harnesses the distinct movement patterns of AGVs and uses machine learning techniques to learn location-, trajectory-, and orientation-specific RSSI from the APs. Real-world factory data from our unique dataset revealed that our method extends the potential communication duration per route by 1.34 times compared to the prevalent signal strength-based switching methods commonly implemented in current drivers provided by chipset vendors or open-source Wi-Fi drivers. These results indicate that the automatic evaluation and tuning of the wireless environment using the proposed method is beneficial in reducing the time and effort required to investigate the detailed propagation paths needed to adapt AGV to existing APs.

Wireless communication of Automated Guided Vehicle (AGV) is a key feature of modern factories that contribute to achievement of higher productivity. The quality of a wireless link between an AGV and an Access Point (AP) may change drastically during the movement of an AGV. Recently, it has become feasible to use two wireless interfaces devices that can link to different access points to increase robustness of wireless access. Therefore, methods are needed to efficiently coordinate the use of the two interfaces. In this paper, a method is proposed for cross-layer control which splits data flow over two-links based on lower layer information about the estimated flow rate of each link. The method is evaluated by simulation using a flow-level simulation model. Evaluation is done for a particular test scenario of an AGV trip in a factory requiring multiple handovers between APs while transmitting video camera data on an uplink using IEEE 802.11. Simulation results verify that the proposed method is effective in reducing latency of data transmissions to below 100ms and improving stability over the whole range of AGV movement. There results shows that proposed method is effective when the update interval of split ratio is short enough to match the changes of the AP link flow rates due to the movement of AGV.

In today's logistics sites, there is a rising trend in employing advanced equipment such as stacker cranes and conveyor robots equipped with wireless LAN devices to reduce labor costs and enhance operational efficiency. However, high-rise warehouses present distinctive challenges to wireless LAN communication due to the arrangement of metal pillars in vertical, horizontal, and diagonal patterns. This structural complexity engenders convoluted radio propagation paths, resulting in unexpected signal attenuation. This paper addresses a data-driven approach to applying propagation models to such environments. Specifically, we measure the direction of arrival and received signal strength indicator (RSSI) at each polarization of a 5-GHz wireless LAN. Subsequently, we expand the propagation model based on the radio characteristics of the high-rise warehouse by analyzing the acquired data. The analysis revealed that nonlinear attenuation, which does not show linear proportionality to distance, is locally intensified by reflected waves emanating from the surrounding metal band. Furthermore, the difference from the simulation results indicates that the accuracy can be improved by considering the leakage power of cross-polarized. By using the extended model to calculate the leakage power of cross-polarized waves at the transmitting and receiving antennas, we successfully enhance the accuracy of transmission rate estimation of wireless LANs from 11% (using the original model) to 87% in the best-case scenario.

A distributed network monitoring system has been designed and implemented for smart monitoring of complex indoor wireless environments to support management of wireless communications. In particular, it makes possible real-time monitoring and analysis in smart factories using commodity hardware and open-source software. The system collects data from distributed wireless receivers, aggregates the data in spatial cells and time bins, and computes space-time wireless metric data frames. A prototype monitoring system was implemented with two types of wireless interface sensors, packet-capture and spectral sensors, and automatic online data collection, indexing, aggregation and analysis. The prototype system reports wireless quality metrics with one-meter spatial resolution and periodic update times of 1 to 10 seconds.

In recent days, various types of wireless communication-based equipment such as Automated Guided Vehicles (AGVs), stacker cranes, and mobile robots have been used to enhance productivity and factory automation. Wireless communication networks are promising for a flexible factory where frequent reconfigurations occur, whereas communication quality, reliability and roaming of wireless links may be the issues for their utilization. This paper shows the experimental results of the function that monitors the communication quality of multiple Access Points (APs) and reduces the communication disconnection time by communicating with appropriate APs through multiple interfaces in a real logistics area. As a result, the packet loss ratio was improved by 21.94% and the average delay time was reduced by about 50-60ms.

Recently, the demand for utilizing wireless communication such as Wi-Fi is growing in manufacturing sites because Internet of Things (IoT) and wireless robots are becoming important for improving productivity with factory automation. On the other hand, when too many wireless tools are introduced, communication performance is degraded due to mutual interferences, resulting in less productivity. Thus, for improving productivity, it is important to know how many wireless tools can be stably introduced. To accommodate this demand, we investigate the capacity of radio communication (denoted by wireless capacity) required for wireless tools in manufacturing sites. In this paper, we show a simple but practical calculation method and results obtained by using captured data in a factory.

In recent years, demands for wireless sensing and flexibility of manufacturing environment and systems are increasing and driving an increase in volume and variety of wireless devices in factories. Especially, detection of status and anomaly of systems using sensors is getting a lot of attention in the manufacturing field. In this paper, we introduce two examples in which the state of a manufacturing machine, specifically the wear state of blades in a milling machine, is diagnosed using sensing data which can be collected via a wireless network. It is shown that the volume of data required for reliable diagnosis can be reduced to minimize use of wireless resources by pre-preprocessing of data before sending.

Flexible Factory Partner Alliance (FFPA) has defined the technical specifications for Smart Resource Flow (SRF) Wireless Platform which ensures stable communications in an environment where various wireless systems coexist. SRF Wireless Platform is based on the Smart Resource Flow approach proposed by National Institute of Information and Communications Technology (NICT), which is a multi-layer whole-system engineering approach to managing manufacturing resources to achieve optimal system performance. Authors have been taking part in FFPA activities and also have been doing research and development on wireless systems based on SRF Wireless Platform. In this paper, authors propose radio resource control technologies for SRF Wireless Platform. The results of evaluation tests clarify effectiveness of the technologies for practical use.