Speed Machining Research Articles

Development of intelligent traction machine for tensioning and paying off construction of transmission lines

Monitoring the traction force and speed of the traction machine is crucial for timely discovering construction problems and avoiding accidents during the construction process of tension wire laying. The existing monitoring methods have low accuracy, are susceptible to environmental interference, and cannot achieve real-time monitoring. Therefore, this article has developed an intelligent traction machine suitable for tension line construction.The design scheme includes three modules: data acquisition and processing, data transmission, and software design. The data acquisition and processing module is responsible for real-time monitoring of traction force and traction speed, and converting the monitored data into digital signals through pressure sensors and speed sensors, and then processing them through a microcontroller. The data transmission module transmits monitoring data to the construction site terminal equipment and remote command center through LoRa wireless transmission technology, displays monitoring data on the terminal equipment, and realizes warning and control functions. At present, the intelligent traction machine has been applied in the tension wire laying construction of a 750 kV transmission line project in Guangdong, China and has achieved good results. Through continuous optimization and improvement, intelligent traction machines have practical conditions and broad application prospects.

Real-Time Prediction of the Yarn Break Position Using Vibration Measurement.

Warping is a crucial process that connects two main stages of production: yarn manufacturing and fabric creation. Two interrelated parameters affect the efficiency of this technological process: warping speed and the ability to swiftly detect the yarn breaks caused by various defects. The faster a break is detected and the warping machine stopped, the higher the machine's working speed can be. Since the beginning of such devices, various types of yarn break detectors have been proposed, primarily based on different mechanical solutions. To enhance the break detection process, a solution involving the use of an accelerometer to measure yarn vibrations and thereby detect whether the moving yarn has broken is proposed. Based on the detection of a threshold value of 22 m/s2, the warping machine could be stopped within 2.752 to 2.808 ms, which is 50 times faster than in the traditional mechanical detectors under investigation. Furthermore, through a precise analysis of yarn vibration patterns, it became possible to determine the distance from the sensor at which the break occurred. This analysis was conducted using the proprietary MRSCEK coefficient, which aggregates data obtained from six standard coefficients: mean, root mean square, standard deviation, crest factor, energy, and kurtosis. This information could potentially lead to the development of automated systems for removing breaks without human intervention in the future. Research efforts focused on analyzing the vibration signals received from yarns made with different linear densities. The results showed that such a system could effectively replace commonly used mechanical yarn break detectors and operate much faster.

Research on muck conditioning for EPB shield tunnelling in composite formation

Compared with simple formations, EPB (earth pressure balance) shield tunnelling in composite formations encounters severe problems with muck conditioning and require improved muck conditioning technology to fulfil expectations for continuous and efficient excavation. In the Nanchang Metro Line 4 Project, a water-rich sand-argillaceous siltstone composite formation is encountered. With a high moisture content and complex composite formation ratio, it is quite difficult to determine the optimum muck conditioning scheme, and thus, muck spewing accidents frequently occur during the tunnelling process. In this study, laboratory muck conditioning tests are conducted for five ratios of stratum, from a full section water-rich sand formation to a water-rich sand-argillaceous siltstone composite formation. The muck conditioner ratio for EPB shield tunnelling in such composite formations is dynamically optimized based on an analysis of propulsion speed, penetration rate, thrust force and torque of the shield machine in the field. The following muck conditioning scheme is obtained: (1) For the full-section water-rich sand layer, foam and bentonite slurry should have similar proportions, namely, the foam injection ratio is 10–15% and the bentonite slurry injection ratio is 10%. (2) As the argillaceous siltstone content increases from 10 to 90%, the foam injection rate gradually increases from 20 to 50%, and the bentonite slurry injection rate gradually decreases from 20% to 0. (3) If the argillaceous siltstone content is 10%, then CMC polymer with an injection ratio of 1% is required. Once the argillaceous siltstone content exceeds 70%, it is necessary to add mudstone dispersant solution (1:5) with a volume ratio of 2 to 3%. According to the analysis of the field tunnelling parameters, including penetration rate, total shield thrust and cutterhead torque, the optimization of the muck conditioning scheme proposed based on laboratory tests is proved effective and deserves further application.

An Experimental Study Based on the Surface Microstructure of Bionic Marine Animals

Masked jet electrolytic machining has the advantages of high machining efficiency and good surface morphology, giving it important applications in fields such as bionic marine animal manufacturing. The factors affecting the electrolytic machining speed are deduced; a modeling simulation is carried out by COMSOL software; the electrolyte potential map and current density line map inside the microgroove are analyzed; and measurements of the actual machined microgroove are made by a scanning microscope to carry out the experiments of electrolytic characteristics and morphology of the microgroove under different pulse voltages, machining gaps, and machining times. Experiments show that the pulse voltage plays a dominant role in processing, and when the pulse voltage is increased from 50 V to 125 V, the microgroove width increases by an average of 7.7%, and the depth increases by an average of 28.8%, which significantly improves the surface microstructure of the bionic marine animal.

Development of Remote-Controlled Self-Propelled Flax Windrow Turner

The paper highlights efforts by major global engineering companies to develop agricultural robotic systems, with a particular focus on universal unmanned mobile energy vehicles designed to perform technological operations autonomously. Analysis of current machinery for harvesting and preparing flax straw indicates a lack of sufficient automation and robotization in these processes. Among the operations involved in flax harvesting, turning is defined as the least energy-intensive. In this regard, research has begun on the development of a remotely controlled, self-propelled flax windrow turner, with potential for further adaptation to autonomous operation. (Research purpose) The study aims to substantiate the optimal operating modes and develop a power electrical circuit for a remotely controlled, self-propelled flax windrow turner equipped with an electric drive. (Materials and methods) The study provides a theoretical basis for the conveyor's linear speed in relation to the rectilinear motion of the flax turner. (Results and discussions) The study identified the following operating modes for the flax windrow turner: the conveyor's angular velocity was determined to be 4.63 radians per second, with a machine speed of 2.78 meters per second. Considering the machine's weight, 7.00-12 F-42-1 drive wheels were selected, with tires that offer excellent road traction and maneuverability. The drive wheels had a load index of 133, an outer diameter of 660 millimeters, and a profile width of no more than 195 millimeters without load. Additionally, a power electrical circuit was designed for a remotely controlled self-propelled flax windrow turner. (Conclusions) The study determined the operating modes for an electrified radio-controlled, self-propelled flax windrow turner and proposed a powered electrical circuit for designing the units and assemblies of machinery used in flax straw harvesting.

Evaluating the Performance of the Carrot Slicer Machine

The study was carried out to evaluate the performance of the carrot slicer machine. An experiment was conducted with a multi-factor factorial design under a randomized complete block design. Using the Statistix 8 software, the experiments' collected data were statistically examined. The analysis of variance indicated that the effects of machine speed and feed rate on throughput capacity, efficiency, and percentage loss of the machine were significant at the 5% probability level. The results of the least significance difference pairwise comparison tests revealed that the treatment combination means did not differ significantly from one another at the 5% level. The key physical properties of the carrot including moisture content, angle of repose, bulk density, porosity, coefficient of friction, geometric mean diameter, arithmetic mean diameter, equivalent mean diameter, sphericity, surface area and aspect ratio were obtained as 84.3%, 39.4°, 469.5 kg m-3, 59.8%, 0.78, 47.8 mm, 62.18 mm, 83.7 mm, 0.55, 57.67 cm2, and 0.27, correspondingly. The results showed that the maximum throughput capacity of 621.4 kg h-1 was recorded at 550 rpm machine speed while the minimum throughput capacity of 511.6 kg h-1 was recorded at 350 rpm machine speed. It has been found that the maximum machine efficiency was 96.03% at 550 rpm machine speed whereas the minimum machine efficiency was 92.5% at 350 rpm machine speed. The investigation results revealed that the minimum percentage loss was 4.2% at 550 rpm machine speed whereas the maximum percentage loss was 7.8% at 350 rpm machine speed. The test results suggested that the carrot slicer machine was found to be very effective for processing the vegetable root crop of carrots for end users.

Manufacturing and evaluating a machine for cutting and raking alfalfa and barley harvest into rows

A machine was manufactured to belt -rake the fodder harvest with a moving finger bar . The harvest collecting machine was installed with a two-wheeled sickle mower, thus the machine group becomes a four-wheeled vehicle that performs two functions at the same time (cutting and harvesting the harvest). The study aims to reduce the effort, time, and fuel consumption required to cut the fodder crop and assemble it into rows in preparation for its subsequent transportation or treatment with silage making machines or hay. A two-factor factorial experiment with a completely randomized block design was conducted to evaluate the combined instrument. The forward speed of the compound machine has three levels: 1.19, 2.67, and 3.42 km/h, and the type of crop has two levels: barley and alfalfa. The results showed a direct relationship between the forward speed and the productivity of the machine, as it reached 0.215 ha/h with the third speed. The efficiency of harvesting and collecting the harvest reached 100% in the barley crop for all forward speeds, while the third speed failed to rake the alfalfa harvest. The cutting efficiency of the sickle mower was not affected, which was 99% when the combined machine was connected to it in cutting barley and jet crops, and the level of cutting height remained stable, as the cutting deviation reached only 1 cm, while the combine machine affected the increase in the slip rate of the combined machine

Genetic algorithm‐based approach for torque control and increased efficiency across an optimised speed range in switched reluctance drives

AbstractThis paper presents a novel genetic algorithm (GA) design for current profiling in switched reluctance machines that eliminates torque ripple (TR) while inherently guaranteeing minimal RMS currents across the machines speed range. Minimising RMS current provides an increase to machine efficiency and the elimination of TR is required for potential SRM applications such as traction vehicles. This paper proposes a novel method for intentional greater‐than‐two‐phase overlap in the algorithm design. This allows any SRM configuration capable of three or more phase conduction to utilise its full speed range with zero torque ripple, in the case where it is limited using two‐phase torque sharing. An optimal set of current profiles is created using the algorithm across the full speed range of an exemplary 8/6 SRM and these are analysed. A current profiling‐based control scheme using these results is then proposed and simulated for the 8/6 SRM. This is then compared to classical and recently published SRM control methods to highlight the merits of the overall GA design and its resultant control scheme.

Efficiency Analysis and Optimization of Two-Speed-Region Operation of Permanent Magnet Synchronous Motor Taking into Account Iron Loss Based on Linear Non-Equilibrium Thermodynamics

In this article, the linear non-equilibrium thermodynamic approach is used to mathematically describe the energy regularities of an interior permanent magnet synchronous motor (IPMSM), taking into account iron loss. The IPMSM is considered a linear power converter (PC) that is multiple-linearized at operating points with a given angular velocity and load torque. A universal description of such a PC by a system of dimensionless parameters and characteristics made it possible to analyze the perfection of energy conversion in the object. For IPMSM, taking into account iron loss, a mathematical model of the corresponding PC has been built, and an algorithm and research program have been developed, which is valid in a wide range of machine speed regulations. This allows you to choose the optimal points of PC operation according to the maximum efficiency criteria and obtain the efficiency maps for IPMSM in different speed regions. The results of the studies demonstrate the effectiveness of the proposed method for determining the references of the d and q components of the armature current for both the loss-minimization strategy at the constant torque range of motor speed and the flux-weakening strategy in the constant power range.

Investigation of electrochemical micromachining on magnesium alloy using hollow tool electrode

This study investigates the application of Electrochemical Micromachining (ECMM) on magnesium alloy AZ31 using a hollow tool electrode. Magnesium alloys, particularly AZ31, are valued for their lightweight properties and strength-to-weight ratio but pose challenges in precision machining due to their high reactivity and susceptibility to corrosion. Utilizing a hollow tool electrode in ECMM offers potential advantages in precision and control, crucial for micro-scale manufacturing applications. This research focuses on studying the effect of process parameters such as electrolyte composition, voltage, and duty cycle to achieve high-quality micro holes. Experimental results demonstrate the effects of these parameters on machining speed and overcut. Findings indicate that the use of a hollow tool electrode significantly improves the hole geometry and surface integrity of the machined features, making ECMM a viable technique for the micromachining of magnesium alloys. The experimental outcome shows that the maximum MS of 0.439 μm/s was noted with 156 OC. The machining was enhanced by 12 % when compared to traditional submerged machining with a solid tool.

Classification of Mental Health Care Using the ELM, MLP, and CatBoost Stacking Framework

Mental health significantly impacts overall well-being, yet the increasing prevalence of mental health issues presents challenges in their effective classification and treatment. Traditional methods often fail to accurately handle complex, non-linear data, compromising the timeliness and appropriateness of interventions. This study introduces an innovative mental health classification framework, ELM-MLP-CatBoost Stacking, to address these deficiencies. The primary objective is to enhance classification accuracy by integrating three advanced computational techniques: the speed of the Extreme Learning Machine (ELM), the flexibility of the Multi-Layer Perceptron (MLP) for modeling non-linear data, and the predictive refinement of CatBoost as a meta-model. Our methodology involves a stacking approach where ELM and MLP models serve as base learners with CatBoost integrating their outputs to optimize final predictions. Experimental results demonstrate that the ELM-MLP-CatBoost Stacking framework substantially outperforms traditional models, achieving a notable accuracy of 92.76%, an improvement over the MLP’s 92.64% and the ELM’s 69.59%. This framework enhances the reliability and efficiency of mental health condition classifications and paves the way for further research into advanced diagnostic tools. The novelty of this research lies in the synergistic combination of these models, setting a new standard for accuracy and reliability in mental health diagnostics and establishing a robust foundation for future advancements in the field.

Analyzing the performance of metaheuristic algorithms in speed control of brushless DC motor: Implementation and statistical comparison.

A brushless DC (BLDC) motor is likewise called an electrically commutated motor; because of its long help life, high productivity, smaller size, and higher power output, it has numerous modern applications. These motors require precise rotor orientation for longevity, as they utilize a magnet at the shaft end, detected by sensors to maintain speed control for stability. In modern apparatuses, the corresponding, primary, and subsidiary (proportional-integral) regulator is broadly utilized in controlling the speed of modern machines; however, an ideal and effective controlling strategy is constantly invited. BLDC motor is a complex system having nonlinearity in its dynamic responses which makes primary controllers in efficient. Therefore, this paper implements metaheuristic optimization techniques such as Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Accelerated Particle Swarm Optimization (APSO), Levy Flight Trajectory-Based Whale Optimization Algorithm (LFWOA); moreover, a chaotic map and weight factor are also being applied to modify LFWOA (i.e., CMLFWOA) for optimizing the PI controller to control the speed of BLDC motor. Model of the brushless DC motor using a sensorless control strategy incorporated metaheuristic algorithms is simulated on MATLAB (Matrix Laboratory)/Simulink. The Integral Square Error (ISE) criteria is used to determine the efficiency of the algorithms-based controller. In the latter part of this article after implementing these mentioned techniques a comparative analysis of their results is presented through statistical tests using SPSS (Statistical Package for Social Sciences) software. The results of statistical and analytical tests show the significant supremacy of WOA on others.

Region-Based Approach for Machining Time Improvement in Robot Surface Finishing

Traditionally, in robotic surface finishing, the entire workpiece is processed at a uniform speed, predetermined by the operator, which does not account for variations in the machinability across different regions of the workpiece. This conventional approach often leads to inefficiencies, especially given the diverse geometrical characteristics of workpieces that could potentially allow for different machining speeds. Our study introduces a region-based approach, which improves surface finishing machining time by allowing variable speeds and directions tailored to each region’s specific characteristics. This method leverages a task-oriented strategy integrating robot kinematics and workpiece surface geometry, subdivided by the clustering algorithm. Subsequently, methods for optimization algorithms were developed to calculate each region’s optimal machining speeds and directions. The efficacy of this approach was validated through numerical results on two distinct workpieces, demonstrating significant improvements in machining times. The region-based approach yielded up to a 37% reduction in machining time compared to traditional single-direction machining. Further enhancements were achieved by optimizing the workpiece positioning, which, in our case, added up to an additional 16% improvement from the initial position. Validation processes were conducted to ensure the collaborative robot’s joint velocities remained within safe operational limits while executing the region-based surface finishing strategy.

Wear Behavior of TiAlN/DLC Coating on Tools in Milling Copper–Beryllium Alloy AMPCOLOY® 83

In recent years, the exponential growth of the machining industry and its needs has driven the development of new manufacturing technologies, more advanced cutting tool types, and new types of coatings to extend tool lifespan. New coating solutions have been studied and implemented for machining tools, which provide a low friction coefficient and lubrication, thus increasing tool lifespan. Following this line of reasoning, it is relevant to develop scientific work aimed at studying the behavior of cutting tools coated with thin films that promote low friction and high lubrication, as is the case with DLC (diamond-like carbon) coatings. These coatings promote good resistance to oxidation and allow high machining speeds, properties also exhibited by TiAlN (titanium aluminum nitride) coatings. In fact, there is a gap in the literature studying the performance of cemented carbide tools provided with multilayered coatings in milling operations of Cu–Be alloys, commonly used in inserts of plastic injection molds. This study’s objective was to investigate the effect of a multilayer coating (TiAlN/DLC) on end-milling tools to analyze their cutting performance when milling a Cu–Be alloy known commercially as AMPCOLOY®83. The quality of the machined surface was evaluated, and the wear of the cutting tool was studied. A comparative analysis of milling parameters with respect to their effect on the condition of the surface after machining and the resulting wear on the tools, using coated and uncoated tools and different machining parameters, allowed us to verify a better quality of the machined surface and wear quantified in approximately half when used coated tools.

Modified Arithmetic Optimization Algorithm (MAOA) based torque ripple minimization for a sensorless BLDC motor

ABSTRACT Permanent magnet brushless DC (PM BLDC) motor drives outperform the induction motor drives in terms of performance and improved efficiency. Recent advancements in power electronics technology have improved the application of BLDC drives in a variety of home applications. However, the BLDC motor drives suffer from torque ripple, which causes machine vibration, speed oscillations, and acoustic noise, limiting the application range. In this prelude, an optimization tuning algorithm, namely Modified Arithmetic Optimization Algorithm (MAOA) is suggested in this paper for torque ripple minimization in a sensorless BLDC drive. In this paper, the cuk converter topology with PAM scheme is proposed for the sensorless BLDC drive, and MAOA algorithm is used to improve the gain of the controller. A MATLAB Simulink model is used to validate the results of MAOA tuned BLDC drive.

Effect of lubricant inertia on textured journal bearing implementing mass conserving (JFO) boundary conditions

PurposeCavitation plays a significant role in the performance of textured journal bearings. Furthermore, because of the usage of low-viscosity lubricants and the high working speed of machines, it is pertinent to consider the lubricant inertia while analyzing the operating characteristics of bearings. This paper aims to investigate the influence of lubricant inertia in the case of a spherically textured journal bearing, considering both protrusion and dimple texturing and implementing the mass-conserving (JFO) boundary conditions.Design/methodology/approachA novel modified Reynolds equation has been developed to accommodate the effects of lubricant inertia and cavitation. The cavitation is treated by using mass-conserving (Jakobsson−Floberg−Olsson [JFO]) boundary conditions. The governing equation is solved by the Gauss−Seidel method with successive over-relaxation. To enhance computational efficiency and expedite the convergence process, the progressive mesh densification (PMD) method has been integrated into the solution process.FindingsThe current study indicates that the JFO boundary conditions result in higher load-carrying capacity and lesser friction variables for heavily loaded bearings, whereas the flow coefficient is reduced due to the application of JFO boundary conditions. The lubricant inertia effect enhances the flow coefficients for lightly loaded and protrusion-textured bearings.Originality/valueIt is crucial to understand the combined effects of lubricant inertia and cavitation for the effective design of textured journal bearings. The findings from this work will help in designing textured journal bearings more effectively and accurately, particularly when low-viscosity oil is used.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0276/

Experimental Study on Performance of Cotton Small Arch Shed Recovery Machine

Most of the small-arch-shed-recycling machines in China use manual disassembly and manual recycling, with low recycling efficiency and low mechanization. Therefore, this paper designs a small recovery machine for arch sheds, greatly improving the efficiency of the recycling of arch sheds, which can realize the lifting and collection of the arch shed rod and orderly recycling of the shed film. By performing univariate experimental studies in the field, on the basis of field experiments, we carried out an experimental analysis with machine speed and different soil moisture contents as the influencing factors and took the removal rate of the shed rod, the removal rate of the shed film, and the damage rate of seedlings as the test indexes. The test results show that the optimal parameter combination is a travel speed of 1.1 m/s, at which the operation effect is the best. The results show that under the optimal operation effect, the removal rate of the shed rod was 95.72%, the removal rate of the shed film was 98.63%, the seedling injury rate was only 2.11%, and the removal rate of the shed rod was only 4.01%, which met the requirements of the recovery operation of the arch shed and means that this approach is conducive to the recycling of the arch shed materials and the realization of sustainable development. In actual operation, the parameters should be adjusted according to the actual situation in the field to meet the different recovery needs of arch sheds.

Research on “Playing Football” Type Roof Control in Fully-Mechanized Mining Face with a Super-Large Mining Height under the Background of 5G+ Big Data

With the increase of mining height at the working face, the influence range of roof fractures in the goaf increases, the advanced supporting pressure on the coal wall increases, ground pressure becomes more intense, and roof support becomes more difficult. Based on the analysis of ground pressure behavior in the first mining and caving stage, the normal mining stage, and the final mining breakthrough stage of the fully-mechanized mining face near 12,404, the relationship between conveyor current and coal speed is studied and compared. Based on the intelligent control system of the fully-mechanized mining face with a super-high mining height of 12,404 and the structure of the football team, the “playing football” roof control mode of the fully-mechanized mining face with super-high mining height under the background of 5G+ big data is put forward. The conclusions are as follows: In 12,404, the ground pressure was first mined. During normal mining, when the roof with a buried depth of more than 200 m is broken, the speed of the coal machine is kept within 12 m/min, and the full guard defends and controls the roof, pulling the lead frame through the area with severe ground pressure. When the roof is good, it is necessary to speed up the coal cutting and get rid of the pressure. When it is less than 200 m, it will overcome the local weighting, and show an offensive trend to speed up and increase production. In the final mining breakthrough stage, the speed of the coal machine should be controlled within 8 m/min, with attention to defense, guarding against roof leakage, and reducing waste rock.

Maximizing efficiency in C45 steel machining: an integrated AI-based approach to coated insert optimization

AbstractMachining involves the subtraction of the material from the sample workpiece to achieve the desired shape or surface. This versatile method is capable of producing a wide range of parts, varying from simple to intricate profiles. Coating materials are increasingly being utilized in tool inserts in the production industry owing to their superior thermal properties and wear resistance. The shielding of hard coatings, with thicknesses of only a few microns, enhances performance and durability. In this study, machining of C45 steel using distinct coated inserts was explored. The experimental trials employed PVD and CVD methods for coated tungsten carbide (WC) tools/inserts and PVD-coated cermet tools/inserts with different machining parameters. Performance metrics, such as the surface finish and reliability of the tool, were considered for the evaluation. The average tool life variation between the PVD-coated cermet and PVD-coated WC was 178.86%, and 30.11% between the PVD-coated cermet and CVD-coated WC at 1 mm DOC. ANOVA was performed using Response Surface Methodology to explore the influence of input parameters on output. The results indicate that the depth of machining and spindle speed significantly influence Ra, whereas spindle speed and type of tool insert have a considerable impact on the life span of the tool. The developed mathematical model for the prediction of tool life and Ra indicates its potential for performance forecasting during C45 steel machining. Grey relation analysis was employed to optimize the process parameters. Optimal results were achieved with a spindle speed of 400 m/min, 0.5 mm depth of cut, and cermet tool inserts. PVD-coated WC inserts performed better. ANFIS was applied for the prediction and optimization of the machining parameters.

Simulation of pulse width modulation strategies: validation based on sound quality evaluations

Though the noise emitted by an electrical machine is less loud than the one from a combustion engine, the existing literature shows it is not always more pleasant. This is because of its strong tonal content, due to deterministic excitations (e.g. electromagnetic slotting and switching effects, mechanical gear mesh effects). The main source of magnetic noise is the radiation of the stator submitted to electromagnetic forces, which are harmonic by nature. Their highest frequency components are generated by the Pulse Width Modulation (PWM) technique designed to vary the supply frequency and operating speed of the electric machine. Several PWM strategies exist, leading to specific harmonic spectra. A temporal simulation model has been developed to auralize the corresponding electromagnetic noise emitted by the machine, considering its mechanical and electrical parameters. A testbench has been adapted to test the relevance of the model, both from an electrical and acoustic point of view. The simulation model and the testbench can be used to generate virtual and real sound stimuli to be assessed in a jury testing. The subjective evaluations allow to assess the relevance of the auralization model, but also to identify the least annoying strategies.