Automatic Equipment Research Articles

3D Search Based Hybrid Optimal Trajectory Planning for Autonomous LHD in Turning Maneuvers

Load-haul-dump (LHD) is the main equipment for mining and transportation in underground metal mines. Autonomous driving represents an essential role in the daily operation of LHD. Nowadays, LHD autonomous driving is based on the human driver’s artificial teaching. However, it is not easy to obtain high quality teaching information for all the underground roadways in a mine, which not only affects the commissioning and deployment time of autonomous driving systems for LHD vehicles, but also not conducive to the full play of automation equipment performance, and finally impacts the production efficiency. Planning a high-quality target reference trajectory for LHD in the underground roadway is an effective way to overcome the above issues. This paper proposes an optimal trajectory planning method for LHD in turning maneuvers. This planning method is based on longitudinal and lateral decomposing, integrated sampling method, and optimization method. The contribution of this work lies in the 3D key factors search strategy design, the key parameters value range exploration and the reasonable key factor initial values design, which can improve the online execution ability of the algorithm and reduce the driving time of the LHD. The 3D key factors refer to the terminal state of the trajectory, which are longitudinal driving distance, the lateral driving distance, and travel time. The proposed method is simple and easy to implement. The initial values of the key factors are given, and the effectiveness of the proposed method is proved. The feasibility and effectiveness of the proposed method are verified by the comparative analysis of a series of examples.

Prediction of Conductor Ratio for Tubular Linear Induction Motors using Finite Element Method and Response Surface Methodology

In many countries, the demand for motors has rapidly increased. For equipment automation and energy reduction, motors are efficient machines and play an important role in alleviating the current energy crisis. However, rotary machines have been studied instead of linear machines. Furthermore, tubular linear induction motors (TLIMs) have been developed for use in industry, but the characteristics of these machines have not been analyzed. In this study, using the finite element methodology (FEM), a TLIM was examined using the ratio of conductor thickness and back iron. The design of experiment (DOE) and response surface methodology were used to obtain this result. The TLIM is modeled to obtain thrust force in the steady state. Furthermore, conductor and back iron thickness are efficiently assigned using the DOE. The central composite design introduced in this study is used in various DOE methods. As a result, the conductor and back iron thickness ratio is obtained at an optimum value. This ratio can be used to design the TLIM for low voltages.

A Smart Alcoholmeter Sensor Based on Deep Learning Visual Perception.

Process automation, in general, enables the enhancement of productivity, product quality, and consistency alongside other production metrics. Liquor production on an industrial scale also follows the automation trend. However, small and medium producers lag with equipment modernization due to the high costs of industrial equipment. One of the important sensors in automation equipment for distilleries is the alcohol concentration sensor used for fraction separation, process automation, and supervision. This paper proposes a novel low-cost approach to alcohol concentration sensing by employing deep learning on the visual perception of traditional alcoholmeter. For purposes of the training model, dataset acquisition apparatus is developed and a large dataset of labeled images of alcoholmeter readings is acquired. The problem of reading alcohol concentration from an alcoholometer image is treated as a regression and classification problem. Performances of both regression and classification models were investigated with Resnet18 as an architecture of choice. Both models achieved satisfying performance metrics demonstrating the feasibility of the proposed approaches. The proposed system implemented on Raspberry Pi with a camera can be integrated into new distillation equipment. Additionally, it can be used for retrofitting existing equipment due to its non-invasive nature of reading. The scope of use can be further expanded to the reading of other types of analog instruments simply by retraining the model.

CFD-Based Fire Risk Assessment and Control at the Historic Dong Wind and Rain Bridges in the Western Hunan Region: The Case of Huilong Bridge

The Dong wind and rain bridges in western Hunan are among the most extraordinary historical buildings that express the unique culture of the Dong people, and are an unparalleled display of history, culture, aesthetics and architectural skills, but they are exposed to various disasters. However, fire poses a serious challenge to historical wind and rain bridges. This study investigated the fire risk of wind and rain bridges in terms of building materials, structural forms, fire habits, and fire loads. Fire dynamics simulator software and SketchUp modeling software were used to visualize and numerically simulate fire conditions. The survey results indicated that the fire load of the Huilong bridge was 1,794,561 MJ. After a fire, the central pavilion underwent a flashover at 200 s. By 600 s, the maximum temperature of the bridge was 1200 °C, and the entire bridge was in flashover condition. Furthermore, targeted fire-mitigation strategies were proposed according to the architectural characteristics and cultural environment of the wind and rain bridges in terms of the following four components: automatic fire-extinguishing equipment, fireproof coatings, suspended ceiling, and skylights. The effectiveness of the fire-resistance performance of the strategies was also evaluated. The fireproof coating measures were the most effective, and the bridge sections delayed reaching the flashover state by 40–80 s. The reported results can help reduce the fire-related risks of wind and rain bridges and protect our historical heritage more effectively and efficiently. Furthermore, this study can serve as a reference for other historic wooden structures to develop appropriate mitigation strategies.

Design of a Spiral Double-Cutting Machine for an Automotive Bowden Cable Assembly Line

The manufacture of automotive components requires innovative technologies and equipment. Due to the competitiveness in the sector, the implementation of automatic and robotic equipment has been vital in its development to produce the largest number of products in the shortest amount of time. Automation leads to a significant reduction in defects and enables mass production and standardization of the final product. This work was based on the need of an automotive components’ company to increase the rate of spiral cable cutting, used as protection for Bowden (control) cables. Currently, this component, used in automotive systems, is processed with simple cutting machines and cleaning machines. Based on the design science research (DSR) methodology, this work aims to develop a machine capable of performing the cutting and cleaning of two spiral cables simultaneously and automatically. The development of this machine was based on existing machines, and the biggest challenge was the implementation of a double-cutting system. The designed machine met the initial requirements, such as enabling the simultaneous cut of two spirals, being fully automatic, doubling the output over the current solution, and fully complying with the current legislation.

Оценивание электромагнитной обстановки для аппаратуры автоматики и телемеханики на электрифицированных участках железных дорог

Unstable operation of rail chain equipment and locomotive equipment of automatic locomotive signaling causes false switching of traffic lights that negatively affects the capacity of railway sections and train traffic safety. Such failures in automatic locomotive signaling operation impacts negatively on locomotive crew mentality. At increased intensity of the failures, it is allowed to turn off automatic locomotive signaling equipment as faulty one that significantly worsens train traffic safety. On electrified railways, the main cause of failures in this equipment operation is the interfering effect of traction currents.
 Traction current most strongly interferes with the operation of these devices at this current inequality in rail lines at those places where rail chain equipment is connected or under receiving locomotive coils of automatic locomotive signaling. The interfering activity occurs while an asymmetry (difference in values) of longitudinal and/or transverse resistances of a rail line due to the deterioration of the state of rail butt connectors, throttle jumpers and/or the breakdown of spark arresters in the circuits of connection to rails of grounding circuits of various structures. It is difficult to control the state of electrically conductive elements in rail lines because of their multiplicity and also as their electrical resistance in a tolerance area has milliohm order. It causes the necessity to work out better ways on electro-magnetic situation check and approaches to define the condition of indicated elements such as numerous grounding circuits. It’s time-consuming task but must be carried out with the fulfillment of all requirements for operation in high-voltage lines. This article presents some results on the development of methods for controlling electrically conductive and insulating elements in rail chains and that are more suitable for performing maintenance work of equipment of rail chain and locomotive automatic signaling.

Discussion on the Application of PLC Control System in Electrical Automation Equipment

Discussion on the Application of PLC Control System in Electrical Automation Equipment

Research on Automatic Welding Technology of Vertical Fillet Weld

In this paper, the key automatic welding technology of one-time forming the opposite fillet weld is deeply studied. With the help of the gas electric vertical welding technology and its innovation, it was successfully applied to the test and exploration of the one-time forming technology of automatic welding and equipment of the vertical fillet weld. Major breakthroughs have been made in tackling the key automatic welding technologies of one-time forming vertical fillet welds, filling the gap in this technology in the welding field and accumulating valuable experience for further research and progress of this technology.

A Case Study on First Time Quality Feature Investigation for an Automotive Paint Shop

In today’s highly automated automotive paint shops, production equipment such as robots and conveyors controlled by various sensors and programmable logic controllers (PLCs) are widely used to coat vehicle bodies-in-white. A high-volume automotive paint line typically consists of miles of conveyor lines and dozens of sealing and painting robots equipped with hundreds of sensors and PLCs. It takes a body-in-white several hours to travel on conveyor tracks to complete the painting process. Throughout this process, thousands of process variables are monitored and collected from sensors and devices that control the automatic equipment. When a vehicle is painted, process variables and associated outcomes are collected in a centralized database called the Painted Surface Performance Management (PSPM) system. This database contains a complete history of each painted vehicle and its corresponding quality inspection results. In this work, machine learning (ML) models are used to select a list of the most important features that may affect the outcomes of the painted vehicles. However, this list needs to go through additional steps of feature investigations to validate true causal relationships between the selected features and the target variables. Once this step is completed, the selected features can then be used to target operational first time quality (FTQ) of products through use of such ML models to predict FTQ outcomes. An automotive paint shop data from 2020 to early 2021 was used to conduct a case study to demonstrate the process of feature investigation. Observations and recommendations from the ML model analysis are summarized for improvement.

Case Studies of Robots and Automation as Health/Safety Interventions in Small Manufacturing Enterprises.

This paper reviews the experiences of 63 case studies of small businesses (< 250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (n = 17), computer numerical control (CNC) machining (n = 29), or other programmable automation systems (n = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were: CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: Snack Foods; Photographic Film, Paper, Plate, and Chemical; Machine Shops; Leather Good and Allied Products; Plastic Products; and Iron and Steel Forging. This review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors and improved process productivity in most cases.

FOM 데이터 파일 세트의 공정별 단가 데이터와 장비 절삭 공구 수명 간의 상관관계 분석을 통한 제조원가 절감 알고리즘에 대한 연구

It have been composed only introducing automatic equipment without analyzing manufacturing process in many smart factories; hence, productivity does not improve significantly. In this study, production data obtained from a computerized NC machining center were analyzed based on the operation and tool costs for each process to reduce the tool management cost of the cutting process for the die manufacturing, which is weak in cost analysis. Tool cost of the minimum cost required for each process was then modeled using linear programming. We derived a modeling logic that could manage the life of the medium cutting process using the programming method and achieved a cost reduction of up to 12% compared to the operation cost by linking tool cost to the manufacturing per process cost. The proposed algorithm can be applied to field equipment as a manual cost item one of the items of the FOM which manufacturing optimization system.

E-Commerce Sorting Equipment and System Based on Cloud Computing

In order to solve the problems of order reduction and customer churn caused by sorting delays, the author proposes a method for e-commerce sorting equipment based on cloud computing. This method mainly adopts double-layer sorting equipment; compared with single-layer automatic sorting equipment, double-layer sorting equipment has the characteristics of higher efficiency and smaller floor space. The sorting method adopts the “group sorting” method, which can effectively improve the sorting efficiency of the sorting equipment. The algorithm method adopts the mathematical model based on cloud computing for calculation. Experimental Results. The author adopts the cloud computing-based “composition sorting” double-layer sorting equipment; compared with the traditional single-layer sorting equipment, the throughput of the single-layer sorting strategy is 0.72 pieces/s when the conveying speed of the conveyor belt is the same, the throughput of the two-layer same-direction strategy is 1.46 pieces/s, the throughput of the balanced load strategy is 1.97 pieces/s, and the throughput of the group sorting load strategy is 2.57 pieces/s. This method can effectively solve the problems of order reduction and customer churn caused by sorting delays.

Technology and Application of Digital Nondestructive Prescreening Based on Automated Storage

This project around “DR digital imaging non-destructive prediction based on automatic warehousing screening technology and application” project can be divided into cable full inspection in coil based on DR digital imaging mode of the whole case study, with a small piece of material screening technology research, based on the data acquisition and recognition algorithm used for the detection of automated storage research and pilot test three corpus. The hardware framework structure and software system security access model are designed based on existing warehouse conditions. A non-destructive batch automatic pre-screening equipment is developed for small materials, which has both DR and CT functions. Cold cathode pulse ray source for needle tip pulse discharge is improved. A set of non-destructive pre-screening equipment for the whole length of the cable is developed and arranged on the warehouse automatic tray wire rack. Through the multiangle scan imaging of two ray sources, the application of image recognition is expanded, and the automatic size labeling problem warning is realized. The non-destructive pre-screening of the whole length of the cable is implemented synchronously during the process of unloading the cable from the warehouse. The insulation layer scars of the wire diameter and thickness are compared and checked, and the quality problems are visually reflected, and the detection report is automatically generated.

Automatic monitoring system of power equipment based on Internet of Things technology

Abstract With the rapid development of the social economy, the power industry is also developing rapidly, the electricity load is increasing, and the power grid structure is becoming increasingly complex, people put forward higher requirements for improving the reliability of power supply, the emergence of Internet of Things technology can meet people’s urgent needs in a timely manner. How to use the advanced Internet of Things technology to realize the automation of power equipment is an inevitable trend in the development of power systems, and it is also the technical driving force for the development of power equipment. Due to the problems of information islanding, simplification, and security in traditional power equipment monitoring systems, this paper studies the automation of power equipment monitoring systems based on the Internet of Things. The experimental results show that the introduction of the Internet of Things technology into the automatic monitoring system of power equipment increases the utilization rate of power equipment by 4.33%. In addition, the safety of power grid operation and the monitoring of power equipment are improved. Once the power equipment is abnormal, it will be detected in time to ensure the continuity of the power supply.

Methodology for Large-Scale Camera Positioning to Enable Intelligent Self-Configuration.

The development of a self-configuring method for efficiently locating moving targets indoors could enable extraordinary advances in the control of industrial automatic production equipment. Being interactively connected, cameras that constitute a network represent a promising visual system for wireless positioning, with the ultimate goal of replacing or enhancing conventional sensors. Developing a highly efficient algorithm for collaborating cameras in the network is of particular interest. This paper presents an intelligent positioning system, which is capable of integrating visual information, obtained by large quantities of cameras, through self-configuration. The use of the extended Kalman filter predicts the position, velocity, acceleration and jerk (the third derivative of position) in the moving target. As a result, the camera-network-based visual positioning system is capable of locating a moving target with high precision: relative errors for positional parameters are all smaller than 10%; relative errors for linear velocities (vx, vy) are also kept to an acceptable level, i.e., lower than 20%. This presents the outstanding potential of this visual positioning system to assist in the industry of automation, including wireless intelligent control, high-precision indoor positioning, and navigation.

Design of Payment System for Unmanned Convenience Store

The unattended convenience store system for customers to pay and pick up goods by self-service has disclosed a project to add e-commerce concept to the retail industry. The rise of the Internet has made e-commerce develop rapidly, and the development of network payment and cloud service has escorted e-commerce.But so far, e-commerce is difficult to be applied in the retail field because of people's shopping habits.This project comprehensively considers various factors, uses mechanical and electrical equipment automation, comprehensive deployment of cloud server, and key generation and verification to realize e-commerce concept in retail field.

Development of a fully automated platform for agar-based measurement of viable bacterial growth.

Dynamic in vitro antibacterial studies provide valuable insight on effective dosing strategies prior to translating to in vivo models. Frequent sampling is required to monitor the pharmacodynamics (PD) of these studies, leading to significant work when quantifying the bacterial load of the samples. Spreading a bacterial suspension on agar to allow colony counting is a proven process for measuring very low levels of growth, but commercial automation equipment to handle agar plating and colony counting at scale is not readily available. We describe a process to greatly decrease the hands-on time required for PD assays by utilizing general-purpose liquid handling robots to plate bacteria and a custom-made plate imager to automate colony counting. The platform developed handles the biological assay from beginning to end as well as sample tracking at each step of the process. The process relies heavily on custom automation scheduling software to enable dynamic process decisions and coordinate data flow throughout. Using the described platform, we can efficiently quantify >100 PD samples per day while maintaining the necessary dynamic range of the assay. Alleviating the main bottleneck in the dynamic antibacterial studies has allowed us to accelerate the rate of experiments to provide antibacterial dosing data within shorter timelines.

Design and Motion Analysis of a Magnetic Climbing Robot Applied to Ship Shell Plate

The manufacture, maintenance and inspection of a ship involve a series of works on the ship shell plate, which were always seen as harmful for human operators and time-consuming work. The shipping industry is looking to replace manual work with automation equipment. A magnetic climbing robot that can omnidirectionally move on ship shell plate was presented in this paper. This article summarized the mechanical structure, control system, kinematic model, and autonomy of robot. The mechanical structure of the robot was inspired by bionics and adopted a wheel-leg hybrid locomotion system. In the control system of this robot, industrial control computer (IPC) was adopted as the core controller and brushless direct current servomotor was chosen as the actuating station. Finally, the motion analysis of the designed robot was performed. The results of the analysis show that the magnetic climbing robot adapted to the ship curved shell plate and crossed obstacles.

Container terminal automation: revealing distinctive terminal characteristics and operating parameters

This study focuses on the automation of terminal equipment used to handle containers. A dataset was compiled, which includes 63 fully and semi-automated container terminals in operation around the world, their organizational features, technical dimensions, and the maritime and urban markets they serve. The data analysis focuses on where, when, under which conditions, and to what extent container terminals were automated, and who is responsible for implementing terminal automation. Only 3% of the world’s container terminals were found to be either fully or semi-automated. A survey-based analysis of global terminal operators identifies how they implement their automation and the time necessary for terminal operators to start realizing a return on their investment. The results systematically map global automated terminal characteristics. Acknowledging that not all container terminals are candidates for automation of terminal equipment, this paper contributes to extant literature by presenting a systematic review of all global automated terminals in order to substantiate or refute any perceptions that might exist on their characteristics, for example, in terms of minimum cargo volumes needed for automation. The findings can provide some guidance to market actors considering investments in automation and public and private port authority decision makers that might also commit resources to automation.

A pH Monitoring Algorithm for Orifice Plate Culture Medium

Recently, there has been renewed interest in cell therapy, which plays a key role in the clinical research of genetic diseases, advanced blood disease, and other diseases. It shows considerable clinical application value and is known as “the new pillar of future medicine”. Automatic cell culture and operation technology is the key to ensuring scale, standardization, and stability between batches of therapeutic cells. The pH of the cell culture medium is vital for cell growth. Most cells are suitable for growth at pH 7.2~7.4. A pH of cell culture medium lower than 6.8 or higher than 7.6 is harmful to cells, and cells will degenerate or even die. At present, the monitoring method of cell culture medium pH of automatic cell culture equipment is mainly a visual observation method, which can not accurately or quickly reflect changes in the cell culture medium. To address the issue of monitoring of cell culture fluid pH for automated cell culture equipment and the inability to employ invasive sensors to measure pH during well plate culture, a pH monitoring method for orifice plate culture medium algorithm based on HSV (hue, saturation, value) model is proposed by studying the changes of cell culture medium in the process of cell culture. The research presented here reveals the laws of cell culture fluid pH change and its color moment, and the intelligent monitoring of cell culture fluid pH was successfully achieved. The problem of non-destructive monitoring of the pH of cell culture fluids in well plates is also addressed.