Factory Automation Applications Research Articles

Real-Time Monitoring With Timing Side Information

Real-time monitoring plays a pivotal role in the Industrial Internet of Things (IIoT) with potential applications in factory automation, automated driving, and telesurgery, thereby attracting considerable recent attention in anticipation of the development of the sixth-generation (6G) of wireless networks. In this paper, we present a paradigm-shift data compression method that makes use of timing side information (TSI) obtained by observing two synchronized clocks at a remote sensor and a monitor. In particular, the TSI is found to allow the transmitter to send fewer bits consumed in characterizing the changing or holding time of a piecewise-constant stochastic process. We borrow the idea of source coding with side information to reveal the performance limits of both TSI-based lossless and lossy compression, and to develop practical low-complexity source coding schemes. To further reduce the implementation complexity and the hardware cost, we also present a real-time monitoring scheme where the sensor does not necessarily measure the state transition time. A statistical signal processing algorithm is adopted to estimate the changing time accurately. Our theoretical and numerical results show that the compression gain owing to the TSI is quite substantial, especially when the communication latency and the delay jitter are limited.

Low-Light Images In-the-Wild: A Novel Visibility Perception-Guided Blind Quality Indicator

Owing to the increasing deployment of CMOS camera modules, it is inevitable to take photographs under weak illumination. Therefore, low-light imaging quality is one of the most important factors affecting user experience as well as the product values of consumer electronics, automobile, surveillance, factory automation, and other industrial applications. Inspired by human vision, this article jointly considers visibility perception, luminosity cognition, and color sensation, and presents a new visibility perception-guided blind quality indicator for low-light images in-the-wild. To excavate effective descriptors for authentic distortions under weak illumination, we utilize maximum ignorable visible difference to characterize the reduced visibility, and employ the luminance statistical properties and color sensation characteristics to represent brightness and colorfulness distortions. Extensive experimental results on the benchmark dataset verify that the proposed blind quality indicator outperforms nine representative methods including general-purpose and distortion-specific methods.

Implementation of Robots Integration in Scaled Laboratory Environment for Factory Automation

Robotic systems for research and development of factory automation are complex and unavailable for broad deployment in robotic laboratory settings. The usual robotic factory automation setup consists of series of sensors, robotic arms and mobile robots integrated and orchestrated by a central information system. Cloud-based integration has been gaining traction in recent years. In order to build such a system in a laboratory environment, there are several practical challenges that have to be resolved to come to a point when such a system can become operational. In this paper, we present the development of one such system composed of (i) a cloud-based system built on top of open platform for innovation in logistics, (ii) a prototyped mobile robot with a forklift to manipulate pallets in a “factory” floor, and (iii) industrial robot ABB IRB 140 with a customized gripper and various sensors. A mobile robot is designed as an autonomous four Mecanum wheels system with on-board LiDAR and RGB-D sensor for simultaneous localization and mapping. The paper shows a use case of the overall system and highlights the advantages of having a laboratory setting with real robots for the research of factory automation in a laboratory environment. Moreover, the proposed solution could be scaled and replicated in real factory automation applications.

Ultra-Reliable and Low-Latency Wireless Communications in the High SNR Regime: A Cross-Layer Tradeoff

Ultra-Reliable and Low-Latency Communications (URLLC) has attracted considerable attention because of its potential applications in factory automation, automated driving, and telesurgery anticipated for the era of the sixth-Generation (6G) networks. In URLLC with random channel gains and a hard delay constraint, the scheduling of backlogged queues and finite blocklength coding in the physical layer will make it very challenging to specify its performance limits. In this paper, we focus our attention on the asymptotic cross-layer analysis of URLLC when the Signal-to-Noise Ratio (SNR) is sufficiently high. More specifically, we find that a fundamental tradeoff exists among the service capability, latency, and error probability in the high SNR regime, which is characterized by a gain conservation equation. The main result of this work reveals that the sum of our defined service rate gain, real-time gain, and reliability gain is equal to one under the optimal policy. Numerical simulations are also exploited to validate that the derived gain conservation equation holds even with bounded random arrival.

Wavelet neural learning-based type-2 fuzzy PID controller for speed regulation in BLDC motor

In brushless direct current (BLDC) motors, speed control is a prominent operation based on which these motors are widely used in higher-end industrial applications including robotics, aeronautics, disk drives, factory automation, consumer electronics, transport and military applications. A novel wavelet neural learning (WNL)-based type-2 fuzzy system controller is devised in this paper to accomplish effective speed control of the BLDC motor with the set specifications. The performance characteristics of the BLDC motor are simulated and analysed based on the wavelet neural learning-based type-2 fuzzy proportional–integral–derivative (PID) controller. This work employs wavelet neural learning to provide inputs to the constructed new type-2 fuzzy PID controller model, and this drives the BLDC motor mechanism. The gain values of the PID controller are tuned with the developed WNL-based type-2 fuzzy system to carry out most operational speed regulation process for the motor mechanism. The developed speed controller model for the BLDC motor is tested for its superiority by performing step variations of the input signal and also for load disturbances. In WNL, to derive the output a wavelet function is applied and this drives the operation of the type-2 fuzzy system PID controller and attains better gain values for speed control operation. The classic slime mould algorithm is used in this contribution to tune the weight coefficients during wavelet neural learning process and due to which the delayed convergence is controlled. Results attained during the simulation process prove the effectiveness and superiority of the proposed speed controller for the design specifications of the BLDC motor in comparison with the earlier literature contributions made.

Magnetic Sensor Based on Giant Magneto-Impedance in Commercial Inductors

Magnetic sensors have various applications in navigation, power distribution, robotics, factory automation, and medical diagnosis. The development of highly sensitive magnetic sensors usually requires complicated and costly fabrication process. Herein, we report giant magneto-impedance of 41036% in the commercially available ferrite core inductors. A magnetic field detection limit of 10 nT at 1 Hz has been obtained by directly measuring the impedance of the as-obtained inductor without any optimization. With a 100 pF capacitor in series connection with the inductor where lower impedance facilitates the measurement process, a limit of detection of 625 pT at 1 Hz has been obtained in the series <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RLC</i> resonator. These results can be understood in terms of the magnetic field-dependent self-resonance in the inductors which act as lumped <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RLC</i> resonators. Compared with the traditional electromagnetic induction sensing mode, the magneto-impedance sensing mode shows 5000 folds improvement in the magnetic field detection capability.

Link scheduling algorithm for industrial wireless networks applied to factory automation

Industrial Wireless Networks are an alternative to wired networks for process automation and factory automation. In this type of network, the network manager is responsible for creating and maintaining the network. One of the tasks of the network manager is the scheduling process. It is desirable that this process be carried out as fast as possible. In factory automation applications, this process becomes even more critical as cycle times are much shorter and the network topology changes more often compared to process automation applications. Therefore, one metric that should be considered when evaluating scheduling algorithms is the expected execution time under certain network conditions. This paper proposes a method that perform a pre-scheduling before the network start operating, in order to reduce the processing time. When new devices join to the network they receive pre-scheduled timeslots, making the search for available slots faster. We also compared the method proposed with scheduling algorithms applied in Industrial Wireless Networks and results show that the technique of pre-scheduling may be appropriate when it is necessary to execute the scheduling process in a fast manner.

5G Ultra-Reliable Low-Latency Communications in Factory Automation Leveraging Licensed and Unlicensed Bands

Factory automation (FA) applies ultra-reliable low latency communications (URLLC) to support closed-loop control systems with millisecond cycle times. Presently, many of these applications rely on maintenance-prone wireline bus systems since existing wireless technologies cannot meet the stringent latency and outage requirements. The cellular standards body, the Third Generation Partnership Project (3GPP), aims to change this predicament by incorporating support for FA and URLLC into the fifth generation (5G) communication networks. We investigate how combining operation in the unlicensed and licensed band can appropriately balance the technical, regulatory and economic constraints to enable large-scale deployments of bandwidth-hungry FA applications. We present 5G physical layer/MAC layer (PHY/MAC) designs, which carry the bulk of traffic in the cost-effective unlicensed band but switch to the licensed band within the available latency budget to circumvent unlicensed-band interference. We discuss design trade-offs between licensed band occupation, link outage and transmission power level.

A Pragmatic Relay Placement Approach in 3-D Space and Q-Learning-Based Transmission Scheme for Reliable Factory Automation Applications

The biggest challenge in adopting industrial wireless sensor networks (IWSNs) for factory automation applications is to provide low latency and highly reliable communication in harsh factory environments. IEEE 802.15.4e low latency deterministic network (LLDN) mode attempts to address this requirement at the medium access control (MAC) layer. However, the measures offered by this mode are inadequate considering realistic factory environments, suffering from noise, interference, multipath fading, and resulting in frequent packet losses. Cooperative diversity using relay nodes and incorporation of forward error correction (FEC) techniques are the two conventional ways to enhance communication reliability. However, the challenge lies in the placement of relay nodes considering a realistic three-dimensional (3-D) factory space and satisfying various physical, performance, and energy-related constraints. Moreover, the versatile and dynamic behavior of factory environment demand that the solutions offered to enhance communication reliability must be generic and adaptive, thereby eliminating the need for unnecessary redesigns. This paper proposes a twofold solution to enhance the communication reliability offered by 802.15.4e LLDN. First, an efficient and pragmatic relay-placement strategy based on rainbow product ranking algorithm for a 3-D factory space. Second, an adaptive transmission scheme (ATS) inspired from reinforcement learning (RL) technique called Q-learning is proposed, which incorporates cooperative diversity and Reed Solomon (RS) block codes. The effectiveness of the proposed solution is established and demonstrated using a real-world case study.

A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots.

Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability to navigate in an unknown environment and reach mobile targets with minimal or no prior infrastructure deployment. This research investigates and proposes a novel approach of dynamic target localisation using a single RF emitter, which will be used as the basis of allowing autonomous robots to navigate towards and reach a target. Through the use of multiple directional antennae, Received Signal Strength (RSS) is compared to determine the most probable direction of the targeted emitter, which is combined with the distance estimates to improve the localisation performance. The accuracy of the position estimate is further improved using a particle filter to mitigate the fluctuating nature of real-time RSS data. Based on the direction information, a motion control algorithm is proposed, using Simultaneous Localisation and Mapping (SLAM) and A* path planning to enable navigation through unknown complex environments. A number of navigation scenarios were developed in the context of factory automation applications to demonstrate and evaluate the functionality and performance of the proposed system.

A Priority-Aware Multichannel Adaptive Framework for the IEEE 802.15.4e-LLDN

The low-latency deterministic network (LLDN) protocol defined in the IEEE 802.15.4e amendment is intended for factory automation applications that require very low latency and large networks, such as automotive manufacturing. However, LLDN does not provide priority support to properly deal with real-time traffic or dynamic channel configuration capabilities to cope with unreliable channels. Moreover, it offers a limited scalability, as the cycle time grows linearly with the number of network nodes. This paper proposes the priority-aware multi-channel adaptive (PriMulA) framework, which introduces in the LLDN priority-aware scheduling, multichannel communication, adaptive channel selection, and channel blacklisting. PriMulA supports a higher number of network nodes than the LLDN protocol while keeping short cycle times. In addition, PriMuLA avoids deadline miss and improves the network reliability. It maintains the interoperability with LLDN standard nodes and can be implemented on commercial off-the-shelf devices. This paper presents the framework, a schedulability analysis, comparative simulations, and a proof-of-concept implementation.

Wireless Communication for Factory Automation: an opportunity for LTE and 5G systems

The evolution of wireless communication from 4G toward 5G is driven by application demands and business models envisioned for 2020 and beyond. This requires network support for novel use cases in addition to classical mobile broadband services. Wireless factory automation is an application area with highly demanding communication requirements. We classify these requirements and identify the opportunities for the current LTE air interface for factory automation applications. Moreover, we give an outlook on the relevant design considerations to be addressed by 5G communication systems.

Polling in the frequency domain: a new MAC protocol for industrial wireless network for factory automation

Wireless technologies are becoming more and more attractive for industrial communication. In the field of factory automation, the high communication requirements in terms of predictability, reliability and real-time make the adoption of wireless technologies challenging, due to the inefficiency of the wireless physical layer and deterministic medium access control MAC protocols. In this paper, a frequency domain polling MAC protocol FDP-MAC is proposed, which takes advantage of the orthogonal frequency-division multiplexing OFDM technology to achieve simultaneously polling. In the FDP-MAC, a dynamic time division multiple access TDMA scheduling and a downlink acknowledgements aggregation method are also presented to improve the communication efficiency further. We validate the effectiveness of FDP-MAC through simulations, and results indicate that FDP-MAC can meet typical factory automation applications' communication requirements.

Automated Bin-Picking with Active Vision

In this research, an automated robotic bin-picking system employing active vision for picking up randomly distributed plumbing parts is presented. This system employs an actively-controlled single eye-in-hand system to observe structured light projected onto a set of plumbing parts in a bin. By using image processing and iterative closest point (ICP) algorithms, a single plumbing part that could possibly be taken from the bin is detected. Specifically, by projecting stationary structured light patterns onto the set of plumbing objects, the features on the surfaces of plumbing parts can be reconstructed by actively moving the eye-in-hand camera while performing visual tracking of those features. An effective 3D segmentation technique is employed to extract the point cloud of a single plumbing part that can possibly be grasped successfully. Once the object point cloud is obtained, one needs to determine the coordinate transformation from the end-effector to the selected plumbing part for grasping motion. With the point cloud matching result based on utilizing the ICP algorithm, the position and orientation of the selected plumbing part can be correctly estimated if the deviation of the object point cloud from the model point cloud is small. The control command can thus be given to the robotic manipulator to accomplish the automated bin-picking task. To effectively expand the allowed deviation of the object point cloud, an approximate pose estimation algorithm is employed before performing the ICP algorithm. The proposed approach can virtually estimate any pose of the plumbing part and has been successfully experimented with an industrial manipulator equipped with eye-in-hand single-camera vision and a LCD projector fixed in the work space demonstrating the feasibility and effectiveness. The proposed automated bin-picking system appears to be cost-effective and have great potentials in industrial factory automation applications.

Switched Ethernet-Based Real-Time Networked Control System with Multiple-Client–Server Architecture

This paper experimentally verifies that a multiple-client-server architecture based on switched Ethernet can be used as a real-time communication standard for possible applications in factory automation, by observing the effects of packet delays, network congestion, and packet loss on the performance of a networked control system (NCS). The NCS experimental setup used in this research involves real-time feedback control of multiple plants connected to one or more controllers over the network. A multiclient-multiserver (MC-MS) architecture on a local area network (LAN) was developed using user datagram protocol as the communication protocol. In the single-client-single-server (SC-SS) system, as the Ethernet link utilization increased over 82%, the average packet delays and steady-state error of a dc motor speed-control system increased by 2231% and 304%, respectively. As the link utilization increased beyond the threshold, employing an additional server in the NCS reduced average packet delays and also overcame the negative effects of Ethernet's flow control mechanism. The MC-MS architecture is tested with artificially generated random packet loss. The standard deviation of steady-state error (SSE) at 80% utilization with packet loss is found to be 70.2% less than SC-SS and 200% less than multiclient-single-server architecture. The MC-MS architecture remained stable till 70% of control or measurement packet loss.

Designing High Performance Factory Automation Applications on Top of DDS

DDS is a recent specification aimed at providing high-performance publisher/subscriber middleware solutions. Despite being a very powerful flexible technology, it may prove complex to use, especially for the inexperienced. This work provides some guidelines for connecting software components that represent a new generation of automation devices (such as PLCs, IPCs and robots) using Data Distribution Service (DDS) as a virtual software bus. More specifically, it presents the design of a DDS-based component, the so-called Automation Component, and discusses how to map different traffic patterns using DDS entities exploiting the wealth of QoS management mechanisms provided by the DDS specification. A case study demonstrates the creation of factory automation applications out of software components that encapsulate independent stations.

Scalable Offline Optimization of Industrial Wireless Sensor Networks

Sensor networks are increasingly used to control and monitor industrial and manufacturing processes. In this paper, we consider the problem of optimizing a cost function for wireless sensor networks of this kind under energy consumption constraints. We focus, in particular, on the problem of coverage optimization through scheduling. Following existing approaches, we use a mixed integer linear program formulation. We show how to use partitioning techniques to decompose the problem into separate subproblems, solved individually, overcoming the exponential complexity typical of integer linear programming, while minimizing the loss in optimality. In addition, we evaluate the achieved degree of optimality by computing relatively tight bounds with respect to the optimal solution. Finally, we employ simple but effective heuristics to further improve our solution. The results show that our procedure is very efficient and scalable, and is able to find solutions that are very close to optimal. These characteristics make our approach a perfect fit for large and fixed deployments of wireless sensors, typical in factory automation and industrial applications. To show the generality of the approach, we apply our methodology to three different models of varying complexity.

Dual Speed Control Scheme of Servo Drive System for a Nonlinear Friction Compensation

Servo motor drive systems with ball-screw and timing-belt are widely used in a numerical control, robot, factory automation and industrial applications. Most of the servo motor and drive system transfer the motor torque to loads via mechanical connections. However, the nonlinear friction of coupled mechanical devices reduces the performance of a servo drive. Especially, in a low speed range, tracking errors are serious due to the break-away friction and Stribeck effects. In this paper, a new dual speed controller is proposed for the compensation of nonlinear friction torque. The proposed dual speed controller has an outer speed controller and an inner friction torque compensator. The friction torque compensator adds additional torque corresponding to a nonlinear friction of mechanical devices, so the actual speed quickly tracks the reference value. Since the proposed nonlinear friction torque compensator uses the actual speed information without any motor parameters and mathematical model, the proposed compensator has a very simple structure and high stability. The proposed control scheme is verified by computer simulation and experimental results.

Motion Stereo including Tracking Stability Analysis for 3-D Cable Reconstruction

We propose a novel approach to the three-dimensional reconstruction of flexible cables for applications in factory automation, such as cable handling and connecter insertion using robotic arms avoiding conflicts among multiple cables. The approach is based on motion stereo with a single vision sensor. To solve the stereo correspondence problem efficiently and effectively, feature-point projection with slit beams and a feature tracking algorithm based on a robust image-matching method is applied. In addition, we define the tracking stability of the feature points in order to reject defective stereo correspondences. Experiments using these methods demonstrate that an arched cable shape can be reconstructed to an accuracy of 1.5%.

My view... It's that deja vu feeling all over again [fieldbus standards

If you thought the arguments over plant floor communications were resolved by the ratification of an international fieldbus standard back in 2000, think again. The emergence of industrial Ethernet as the future physical and transport medium of choice puts the whole issue back in the melting pot. Today there is widespread recognition of Profibus as the clear leader for factory automation applications in Europe, but less widely appreciated is the fact that Interbus runs a surprisingly close second, that DeviceNet rides the manufacturing roost in North America, that Modbus, without the benefit of inclusion in either or any IEC standard, is still the protocol of choice for a large proportion of industrial automation applications or that, in Asia, CC-Link, hardly mentioned in Europe or North America, leads the field, again without benefit of an IEC accolade. Move the spotlight to the process automation sector and, if anything, the picture becomes even more confused. True, there are only two serious contenders: Profibus and Foundation Fieldbus (FF), but they can&apos;t even agree between themselves what actually constitutes a process application.