Machining Operations Research Articles

Implementation of Ventilation Panel Installation

Abstract. Electrical panels are an important component in industry, which provides security to electrical installations in various industrial sectors. Large-scale companies dominate this industry to meet the high needs of consumers and maintain the quality and security of electrical installations. Electric panels must be installed carefully, pay attention to the surrounding environment, and play an important role in controlling ventilation to regulate the temperature and air conditions inside the cage. This research uses qualitative methods to understand the process of making ventilation panels. The results cover two types of panels: electric panels and ventilation panels. Electric panels serve as storage for electrical components, protect from the surrounding environment, and facilitate the operation of electrical machines. Meanwhile, ventilation panels are a crucial part of modern farm management, adjusting temperature and humidity to suit the needs of animals. The components in the ventilation panel involve various elements such as MCBs, TORs, contactors, relays, busbars, and others. The process of creating ventilation panels includes steps such as sketching pictures, making electrical panel boxes, assembling components, busbar assembly, wiring, as well as QA and QC stages to ensure panel quality. This process ends with finishing and packing before delivery to the consumer. This research provides an in-depth understanding of the manufacture of ventilation panels, which is essential for modern industry and agriculture inining optimal environmental conditions.

Chatter Identification in Milling of Titanium Alloy Using Machine Learning Approaches with Non-Linear Features of Cutting Force and Vibration Signatures

The generation of chatter during machining operations is extremely detrimental to the cutting tool life and the surface quality of the workpiece. The present study aims to identify chatter conditions during the end milling of Ti6Al4V alloy. Experimental modal analysis is carried out, and stability lobe diagrams (SLDs) are developed to identify machining parameters under stable and chatter conditions. Experiments are conducted to acquire cutting force and vibration signatures corresponding to machining conditions selected from the SLD. Non-linear chatter features, such as Approximate Entropy, Holder Exponent, and Lyapunov Exponent extracted from the sensor signatures, are used to build Machine Learning (ML) models to identify chatter using Decision Trees (DTs), Support Vector Machines (SVMs) and DT-based Ensembles. A feature-level fusion approach is adopted to improve the classification performance of the ML models. The DT-based Adaboost model trained using dominant non-linear features classifies chatter with an accuracy of 96.8%. The non-linear features extracted from the sensor signatures offer a direct indication of the chatter and are found to be effective in identifying the machining chatter with good accuracy.

Design and experiment of an adaptive cruise weeding robot for paddy fields based on improved YOLOv5

Weed control in paddy fields is a critical agronomic practice for enhancing rice yield, in which mechanical weed control is widely used due to its high weed control rate and convenient operation. However, traditional mechanical weed control methods require manual operation, leading to increased operational costs. Therefore, adaptive cruise weeding robots hold significant application promise and market potential. In this paper, an adaptive cruise weeding robot for paddy fields based on improved YOLOv5 is designed to adaptively perform weeding operations. Firstly, a real-time rice seedling recognition method based on MW-YOLOv5s is proposed by establishing a rice seedling dataset under different paddy field environments and growth stages. The model combines the Backbone network structure with MobileViTv3, replacing GIoU_loss with WIoU_loss, which significantly improves the precision and speed of rice seedling recognition. Next, the MW-YOLOv5s was integrated into a paddy weeding machine, and seedling navigation lines were extracted using the least square method. Finally, the control system autonomously operates the weeding machine in real time through feedback control based on the navigation path. The test results showed that the MW-YOLOv5s model exhibits strong recognition performance for rice seedlings under different paddy field backgrounds and growth stages, with a precision of 90.05 % and an mAP of 92.32 %, while the real-time performance reaches 19.51 FPS, which meet the requirements for real-time operation of the weeding machine in paddy fields. The results of the paddy field weed control experiment reveal a weed control rate of 82.4 % and a seedling injury rate of 2.8 %, which meet the agronomic requirements for mechanical weed control in paddy fields. The research findings contribute to the design of intelligent agricultural equipment and promote the practice and application of machine vision in the field of paddy field plant protection.

A dual population collaborative genetic algorithm for solving flexible job shop scheduling problem with AGV

With the increase in labor costs and the development of manufacturing automation technology, automatic guided vehicle (AGV) is widely used in various flexible workshop scenarios. The integrated scheduling of processing machines and AGV is of great significance in real-world workshop production. This article studies the integration problem of flexible job shop scheduling problem (FJSP) and AGV with minimizing the makespan, and proposes a novel mixed integer linear programming (MILP) model and a dual population collaborative genetic algorithm (DCGA). In DCGA, a two-layer encoding strategy based on machine selection and operation sequencing is used. Two decoding methods are designed to determine AGV selection, and each population uses a decoding method. Moreover, a population collaboration operation is designed. The feasibility and effectiveness of the MILP model and DCGA are verified through experimental simulation. Specifically, the DCGA improves 18 current best solutions for benchmarks in the existing studies.

Game of banks - biform game theoretical framework for ATM network cost sharing

Automated teller machines (ATM) play a major role in the world economy as they enable financial transactions and hence good exchanges and consumption. ATM transaction fees are incurred to cover the cost of running the network and these are often settled among the members including banks and cash machine operators. In this paper, we develop a novel biform game theoretic model for members to optimally invest in the ATM network and to share the cost. This biform game includes both a cooperative game theory mechanism for interchange fee sharing and a non-cooperative counterpart to model the fact that members also wish to maximize their utilities. While the proposed coopetition framework is applicable to general ATM networks, we focus the case study on the UK ATM network thanks to the accessibility of the data in addition to the notable stability issues that the network is currently experiencing as has been widely featured by the mainstream media. On the technical side, we prove the existence of a pure Nash equilibrium, which can be computed efficiently. We also show that, under some settings, the Shapley allocation belongs to the core and hence it is not only fair to all members but also leads to a stable ATM network. In addition, we show that the Shapley value allocation dominates the current mechanism in terms of social welfare. Finally, we provide numerical analysis and managerial insights using real data on the complete UK ATM network.

Fabrication Aspects and Performance Characterization of α-Al2O3/AlPO4 Based Sandwich Configuration Flow Channel Inserts and Coatings for High Temperature Liquid Metal Applications

Abstract Liquid metals (LMs) exhibit several key characteristics justifying their utilization as coolants and breeders for nuclear fusion reactors and advanced fission reactors. In fusion reactors, the LMs confront an exorbitantly high flow retarding force, due to the magneto-hydro-dynamics (MHD) effect, imposing significant demands on the pumping power and designs of ancillary coolant systems. Corrosion of structural materials leading to activated corrosion products and coolant chemistry control are some of the vital issues common to both fusion and fission reactors employing liquid lead (Pb) and its alloys. To address these concerns, different technological solutions such as flow channel inserts (FCIs) and high temperature compatible corrosion resistant coatings are being investigated to provide a chemical and/or electrical isolation between the LM and structural material for advanced reactors. In this study, three different prototype geometries (circular, square, and 90 deg bend) of steel-insulator-steel sandwich FCIs are fabricated for fusion reactor applications and an extensive characterization of the electrical insulation is performed over an operating temperature range of 100 °C–600 °C. Welding trials and pneumatic pressure tests up to 10 kg/cm2 (g) are performed on the assemblies to validate the electrical and mechanical integrity over typical fusion reactor operational regime. This paper presents detailed fabrication aspects along with quantitative estimations of insulation filling density, electrical insulation performance and, for the first time, a detailed systematic study of insulation degradation resulting from the combined effects of tungsten inert gas (TIG) welding, exposure to pressure and machining operations on these FCIs. The paper also provides critical details derived from the metallurgical examinations and visual observations from the destructive tests executed on the prototypes. Further, from an implementation perspective toward Lead-cooled Fast Reactors (LFRs), a preliminary feasibility assessment of the α-Al2O3/AlPO4 coating is performed through thin film deposition trials on planar and non-planar substrates followed by mechanical characterizations, such as coating thickness, surface roughness, adhesion strength and microhardness. Metallurgical analyses are presented and discussed to assess Pb ingress after 700 h of continuous exposure to molten Pb alloy at 300 °C–400 °C.

Prediction of cutterhead torque change trend of shield machine based on partial state visible HMM and LSTM

Cutterhead torque is a key parameter to determine the normal operation of shield machine. Accurately predicting the change trend of cutterhead torque can provide decision support for shield operators to control operating parameters. Therefore, a prediction method of cutterhead torque change trend based on partial state visible Hidden Markov Model (HMM) and Long Short-Term Memory (LSTM) network is proposed in this paper. First, the Spearman correlation coefficient is introduced to analyze the correlation of the tunneling parameters, and the historical tunneling data of the cutter torque, pitch angle and related parameters are obtained to establish a database. Secondly, the pitch angle prediction model is established based on LSTM network, and the predicted pitch angle is used as the observation sequence, and the implicit relationship between cutterhead torque and pitch angle is mined through HMM to obtain the probability matrix. Finally, the cutterhead torque prediction model is established, and the pitch angle sequence is used as input to output the corresponding cutterhead torque change trend. The results show that the method can accurately predict the dynamic change trend of the cutterhead torque in the case of less known parameter states, and the effectiveness of the method are verified in this paper.

Machining of a functional hip prosthesis cone in TI-6AL-4V ELI titanium alloy produced by electron beam melting

Digital manufacturing using 3D models and innovative fabrication methods present challenges for functional areas of medical devices. The advantages arising from 3D manufacturing processes like electron beam melting (EBM) play a major role in producing medical devices as, for example, orthopaedic implants. However, surfaces with functional demands for surface roughness and dimensional accuracy require machining operations to achieve the necessary standards. This study aimed to manufacture a functional cone of the modular component of the hip prosthesis through turning and to assess if an EBM-obtained component could offer better machinability as compared to wrought titanium and ensure functionality. To achieve this, the variances in cutting forces and surface roughness of the resulting surface were analysed during the turning tests. The results show that the EBM test samples had higher roughness (Ra) values, yet it was possible to achieve Ra = 0.4 μm for f = 0.1 mm/rev. and approximately 20% lower resulting cutting forces, for example, for f = 0.1 mm/rev, 122N compared to 101N. Using the Kienzle-Victor model, the specific cutting force of titanium EBM was determined to be 1775 N/mm2. The impact of the shell geometry of the EBM test samples had no significant effect on the results. This allows for the exploration of its potential in component design, as it provides an economic advantage in manufacturing. In conclusion, the cutting forces and surface roughness showed similar or superior machinability compared to that of wrought titanium. The EBM technology enables the production of intricate forms and facilitates finishing operations in functional zones.

Data model-based toolpath generation techniques for CNC milling machines

Introduction: With the development of computer technology and data modeling, the use of point cloud models to generate tool paths is particularly important for improving productivity and accuracy.Methods: This study proposes a new method that first preprocesses the point cloud data using four-point denoising and octree methods to improve processing efficiency. Subsequently, roughing tool paths were analyzed using the layer slicing method and finishing paths using the residual height method.Results and Discussion: The experimental results show that the layer slicing method has a minimum error close to 10% on the roughing path generation and the computation time is reduced to 35 s, while the residual height method has an error rate of 10.17% on the finishing path and the computation time is only 11.82 s, which reflects a high trajectory smoothness and accuracy. The above results show that the study not only optimizes the tool path generation process and improves the machining efficiency and accuracy, but also demonstrates the potential application of point cloud models in the machining of complex parts.Conclusion: The novel tool roughing and finishing methods provide more reliable path planning for actual machining operations, and future research will be devoted to further improving the performance of the data processing algorithms and exploring more efficient path planning strategies to facilitate automated production.

The Effect of Different Orchard Ground Conditions on the Performance of A Mechanical Hazelnut Harvesting Machine

In this study, the values of harvesting efficiency, field productivity, kernel productivity, kernel losses, and foreign material separation efficiency of hazelnut harvesting machine with mechanical harvesting unit were determined under different orchard ground conditions (ground preparation before harvesting (OG1) and without ground preparation (OG2)). Also, it was observed how these conditions affect the operation of the hazelnut harvesting machine. For this purpose, the harvesting efficiency, field productivity, kernel productivity and kernel losses of the hazelnut harvesting machine in OG1 and OG2 plots at 265.50 kg ha-1 orchard yield, 1600 mm working width and 1.60 m s-1 working velocity in two different orchard grounds were 96.05%, 90.15%; 8.624 h ha-1, 9.839 h ha-1; 0.116 ha h-1, 0.102 ha h-1; 778.72 kg h-1, 739.76 kg h-1; 3.95%, 9.85%, respectively. The hazelnut harvesting machine with a mechanical harvesting unit can work independently from the ground conditions and we can say that it is an alternative to other hazelnut harvesting machines. The data obtained from the study will help the decision-making process for the best selection and use by providing the necessary technical information about the functional aspects of the machine. Complete mechanization of hazelnut harvesting will lead to a decrease in labor requirements, thus increasing product profitability through a decrease in production cost. The presence of machines with high-performance characteristics in hazelnut harvesting mechanization will shorten the time the product stays on the ground and increase the quality of the harvested product.

Experimental Analysis of Surface Roughness of Steel by Considering Variable Cutting Parameters for Turning

This paper presents results of experiment conducted in order to analysis of surface roughness of steel by considering variables cutting parameters for turning. Surface roughness measurement is a critical aspect of quality control in manufacturing processes, particularly in the context of lathe and milling machine operations. This abstract provides an overview of the methods, tools, and significance of surface roughness measurement in turning processes. It explores the key techniques, such as stylus profilometry and optical interferometry that are commonly employed for assessing surface roughness. The abstract also highlights the importance of surface roughness measurement in ensuring product quality, functionality, and performance. Furthermore, it emphasizes the relevance of this research in optimizing machining processes, enhancing product aesthetics, and reducing material waste. This investigation contributes to the field of precision manufacturing by presenting an in-depth analysis of surface roughness measurement in lathe machine applications, offering valuable insights for industry professionals and researchers alike.

Commissioning and operation of the transverse collimation system at the RCS of CSNS

In high-intensity proton synchrotrons, controlling beam loss during machine operation is crucial to prevent radiation damage. Uncontrolled beam loss poses a significant challenge in achieving higher beam intensity and power in these synchrotrons. The beam collimation system plays a vital role in removing halo particles and localizing beam loss, serving as a critical tool for controlling uncontrolled beam loss in high-intensity proton accelerators. To address the issue of uncontrolled beam loss, a two-stage transverse collimation system was designed at the rapid cycling synchrotron (RCS) of China Spallation Neutron Source (CSNS). However, during the beam commissioning, it was found that the collimation efficiency was compromised due to the small ratio of the physical acceptance to the collimator acceptance and insufficient phase advances between the primary and secondary collimators. To address this issue, the designed two-stage collimator was modified to a one-stage collimator. Through optimization of the collimation system, the beam loss was effectively localized within the collimator area. As a result, CSNS achieved the design power of 100 kW with minimal uncontrolled beam loss.

Online Detection and Classification of Interturn and Groundwall Insulation Aging Based on Broadband Common-Mode Impedance Spectrum

Online condition monitoring for stator insulation is important for reliable operation of electrical machines. Recent studies show that the method based on common-mode (CM) impedance spectrum is effective in online monitoring of the overall insulation ageing condition. However, it is difficult to detect the inter-turn ageing condition since the groundwall insulation ageing has the similar impact on the monitoring results. In this paper, the relationship between the change in the common-mode impedance spectrum and the stator winding insulation ageing is studied based on the per-turn-unit broadband CM stator winding model. The dataset of impedance spectrum for different insulation ageing conditions is built using this model. Multiple points in the impedance spectrum are used to detect the change in the inter-turn and groundwall insulation parameters separately. The online experiment results prove the validity of the proposed method. The proposed method can detect the insulation ageing condition with the error about 6%. There is no other method which can quantify the ageing degree of inter-turn insulation in the presence of groundwall insulation ageing. Compared with the black-box data-driven methods, the proposed method is based on a model with clear physical meaning, which makes the results more reliable.

Design of an Integrated Magnetorheological Fluid Brake Axial Flux Permanent Magnet Machine

This paper presents the design and performance of an integrated magnetorheological fluid brake axial flux permanent magnet (IMRFB-AFPM) machine with two switchable operation modes: rotation and brake modes while the machine has two kinds of windings: armature winding in axial stators and braking winding in radial stator. In rotation mode, this machine is equal to a conventional AFPM machine with high torque density. When switching to brake mode, MR fluid is excited by braking winding and applies large damping stress to the rotor to brake it. This paper illustrates the machine topology, operation principles, and design flow of the proposed machine. Then, this paper analyzes the torque generation mechanism in two modes and applies parameters optimization to improve the torque capability of each mode. Due to the independence of the magnetic flux path, the parameters optimization is divided into two parts: AFPM part and IMRFB part. After the optimization process, the electromagnetic performances of the optimal IMRFB-AFPM machine are analyzed by finite element (FE) analysis. Finally, a prototype machine with the optimal geometric parameters is manufactured and verified experimentally. The experiment results agree well with FE analysis results, validating the feasibility and practicability of the proposed design.

Design Principle Considering Structural Mutual Effects of Double-Stator V-Shape-PM Vernier Machines for Electric Ship Propulsion

This paper proposes the design principle considering structural mutual effects of double-stator V-shape permanent-magnet (DS-V-PM) vernier machines for electric ship propulsion (ESP). Due to the flux concentration effect of the V-PM configuration, the double stators can be divided as a major and a minor stator, considering the different torque generation capability. Cooperation mutual effects between the double stators, V-PM arrangement and vernier machine topology are specifically included in the machine design principle exploration. To illustrate the design principle, first, a unified design principle is deduced, fit for general PM vernier machines. Then, a multi-step optimization strategy with auxiliary of sizing equations is presented, focusing on the parameter cooperation with flux modulation effect. Furthermore, through electromagnetic performance comparison, specific mutual effects of the DS configuration, DS angle shift, V-PMs and barrier structure are clearly summarized. Based on the DS machine design, the multi-mode operation for ESP system is introduced and analyzed. The normal/faulty cruise mode and charging mode are included to realize bi-directional operation. Prototype experiments are carried out for verification of the proposed machine design and operating strategy.

Building a knowledge base for autonomous control of unmanned vehicles

This article presents an approach to building and using a knowledge base for autonomous control of unmanned vehicles (UV). Agriculture is presented as a subject area which features and limitations must be considered. The lack of a sufficient number and level of qualifications of machine operator leads to equipment downtime, a decrease in crop yields and the efficiency of using chemical fertilizers. The use of UV makes it possible to reduce the influence of these factors and the harmful effects on people working in agriculture. The article focuses on taking into account the features and limitations of the subject area when constructing the trajectory of unmanned vehicles and controlling processing facilities. An approach is proposed that consists of separate stages of designing a knowledge base schema, automating the process of filling the knowledge base and organizing the logical inference function. For each stage, developed models and algorithms are presented that help to form and use a knowledge base when solving the problem of autonomous control of unmanned vehicles. The article contains examples and illustrations designed to increase the clarity of the proposed approach.

Сравнительный анализ принципов проектирования электрогидравлических рулевых машин скоростных судов

The composition and control principles of steering electro-hydraulic machines of a simple and follower type, intended for rudder shifting of small and high-speed vessels are considered. An analysis of the functioning of existing steering gears for the specified group of vessels was carried out. Deficiencies in the work associated with the element base and composition of the control and electric drive systems of the analyzed steering machines have been formed. The features of the operation of hydraulic systems with drive electric motors of pumps made on direct current, revealed as a result of experiments, are shown. Variants of technical solutions for improving the energy performance of the electric drive are proposed. A comparative analysis of the operation of steering machines with AC and DC drives has been carried out. An assessment of steering machines operation in normal and emergency modes is given. Structural diagrams of control systems of simple and follow-up action are proposed, taking into account the operating features identified during the analysis and the requirements of the Russian classification society. The possibility of implementing an SM electric drive built using a frequency converter – asynchronous motor system powered by an alternating current network and an emergency source has been shown. Options for the implementation of electric drives for pumps of hydraulic stations with a high-voltage battery are proposed. The possibility of creating domestic installations for steering and other ship mechanisms, according to the proposed structural diagrams of control systems for hydraulic stations for high-speed ships, is shown. Recommendations are given for the construction of steering gears for high-speed vessels with a total displacement of up to 100 tons using domestic electrical equipment.

Tool‐tip vibration prediction based on a novel convolutional enhanced transformer

AbstractSuperior surface finish remains a fundamental criterion in precision machining operations, and tool‐tip vibration is an important factor that significantly influences the quality of the machined surface. Physics‐based models heavily rely on assumptions for model simplification when applied to complex high‐end systems. However, these assumptions may come at the cost of compromising the model's accuracy. In contrast, data‐driven techniques have emerged as an attractive alternative for tasks such as prediction and complex system analysis. To exploit the advantages of data‐driven models, this study introduces a novel convolutional enhanced transformer model for tool‐tip vibration prediction, referred to as CeT‐TV. The effectiveness of this model is demonstrated through its successful application in ultra‐precision fly‐cutting (UPFC) operations. Two distinct variants of the model, namely, guided and nonguided CeT‐TV, were developed and rigorously tested on a data set custom‐tailored for UPFC applications. The results reveal that the guided CeT‐TV model exhibits outstanding performance, characterized by the lowest mean absolute error and root mean square error values. Additionally, the model demonstrates excellent agreement between the predicted values and the actual measurements, thus underlining its efficiency and potential for predicting the tool‐tip vibration in the context of UPFC.

Effect of Hygrothermal Conditioning on the Machining Behavior of Biocomposites

Abstract This work aims to study the cutting behavior of biocomposites under different controlled hygrothermal conditions. This investigation choice is motivated by the fact that natural plant fibers such as flax are characterized by their hydrophilicity which makes them able to absorb water from a humid environment. This absorption ability is intensified by increasing the conditioning temperature. The moisture diffusion process affects considerably the mechanical properties of the resulting composite, which causes many issues during the machining operations. In this paper, moisture diffusion, chip form, cutting and thrust forces, and scanning electron microscope (SEM) observations are considered to explore the cutting behavior of flax fiber-reinforced polylactic acid (PLA) depending on the hygrothermal conditioning time. Results reveal that moisture content in the biocomposite is significantly influenced by the conditioning temperature and the fiber orientation. Moisture content and fiber orientation affect both the curling behavior of the removed chip as well as the tool/chip interaction in terms of friction. The machinability of flax fiber-reinforced PLA biocomposites depending on hygrothermal conditioning time is then investigated using SEM analysis in addition to analytical modeling. An analysis of variance is used finally to quantify the observed results.

Multi-objective elitist spotted hyena resource optimized flexible job shop scheduling

The job shop scheduling problem (JSSP) has drained a lot of consideration since it is one of the most important optimization problems in the manufacturing domain. The scheduling method is crucial for optimizing the objective of minimizing makespan among thousands of jobs, but evaluating machine capacity for achieving this goal remains challenging despite the development of various population-based optimization algorithms for job shop scheduling problems. To improve the efficiency of Job shop scheduling, a novel Multi-objective Elitist Spotted Hyena Monotonic Scheduling (MESHS) technique is introduced. The proposed MESHS technique includes two major processes: machine selection and operation sequences. The number of jobs is considered for solving the scheduling problem. First, the machine selection is performed by applying the Multi-objective Elitist Spotted Hyena optimization technique. The optimization technique selects the optimal machines parallelly based on multiple objective functions such as energy consumption, CPU utilization, and job completion time. The fitness of every machine is calculated based on these multiple objective functions using Levenberg–Marquardt method. Then the Elitist strategy is applied to select the optimal machine based on fitness. After the machine selection, the rate-monotonic preemptive scheduling is modeled to provide a robust operation sequence by assigning high-priority jobs to the optimal machines. As a result, efficient job scheduling is achieved with minimum time. Finally, the experimental valuation is carried out using a benchmark OR-Library dataset with different factors such as job shop scheduling efficiency, job scheduling time, makespan, and memory consumption concerning a number of jobs.