Milling Operations Research Articles

Investigations on the Surface Integrity and Wear Mechanisms of TiAlYN-Coated Tools in Inconel 718 Milling Operations.

Inconel 718 is a Ni superalloy with superior mechanical properties, even at high temperatures. However, due to its high hardness and low thermal conductivity, it is considered a difficult-to-machine material. This material is widely used in applications that require good dimensional stability, making the milling process the most used in machining this alloy. The wear resulting from this process and the quality of the machined surface are still challenging factors when it comes to Inconel 718. TiAlN-based coating has been used on cutting tools with Yttrium as a doping element to improve the process performance. Based on this, this work evaluated the machined surface integrity and wear resistance of cutting tools coated using Physical Vapor Deposition (PVD) HiPIMS with TiAlYN in the end milling of Inconel 718, varying the process parameters such as cutting speed (vc), feed per tooth (fz), and cutting length (Lcut). It was verified that the Lcut is the parameter that exerts the most significant influence since, even at small distances, Inconel 718 already generates high tool wear (TW). Furthermore, the main wear mechanisms were abrasive and adhesive wear, with the development of a built-up edge (BUE) under a125 m/min feed rate (f) and a Lcut = 15 m. Chipping, cracking, and delamination of the coating were also observed, indicating a lack of adhesion between the coating and the substrate, suggesting the need for a good interlayer or the adjustment of the PVD parameters.

Hybrid model development and nonlinear model predictive control implementation for continuous dry granulation process

This study focuses on the development of a hybrid model to integrate roll compaction and ribbon milling operations to design and control a continuous dry granulation process. The proposed hybrid model has three features: (1) it compensates for underestimated roll gap measurements with knurled rolls, (2) it represents the bimodal size distribution of granules using five fitting parameters of the bimodal Weibull distribution instead of only using specific size percentiles, and (3) it considers the impact of rotor-screen gaps on granules. Furthermore, the hybrid model facilitates the implementation of nonlinear model predictive control in a roller compactor Alexanderwerk WP120. Compared to widely applied open-loop operations in the pharmaceutical industry, nonlinear model predictive control demonstrates better performance, indicated by lower integral absolute errors in controlling mass throughput and ribbon solid fraction, in which real-time measurements can be obtained using a near-infrared sensor and a novel spectra selection approach.

Optimizing milling parameters based on full factorial experiment and backpropagation artificial neural network of lamina milling temperature prediction model.

Milling operations of laminae in spinal surgery generate high temperatures, which can lead to thermal injury and osteonecrosis and affect the biomechanical effects of implants, ultimately leading to surgical failure. In this paper, a backpropagation artificial neural network (Bp-ANN) temperature prediction model was developed based on full factorial experimental data of laminae milling to optimize the milling motion parameters and to improve the safety of robot-assisted spine surgery. A full factorial experiment design were used to analyze the parameters affecting the milling temperature of laminae. The experimental matrixes were established by collecting the corresponding cutter temperature Tc and bone surface temperature Tb for the milling depth, feed speed and different bone densities. The Bp-ANN lamina milling temperature prediction model was constructed from experiment data. Increasing milling depth increases bone surface and cutter temperature. Increasing feed speed had little effect on cutter temperature, but decreased bone surface temperature. Increasing bone density of laminae increased cutter temperature. The Bp-ANN temperature prediction model had best training results in the 10th epoch, and there is no overfitting (training set R= 0.99661, validation set R= 0.85003, testing set R= 0.90421, all temperature data set R= 0.93807). The goodness of fit R of Bp-ANN was close to 1, indicating that the predicted temperature was in good agreement with the experiment measurements. This study can help spinal surgery-assisted robot to select appropriate motion parameters at different density bones to improve lamina milling safety.

Optimization of the face milling operations by the criterion of the maximal productivity rate

Optimization of the face milling operations by the criterion of the maximal productivity rate

ПОЧВООБРАБАТЫВАЮЩИЕ ФРЕЗЫ ДЛЯ ОСНОВНОЙ ОБРАБОТКИ ПОЧВЫ И ВОССТАНОВЛЕНИЯ ЗАДЕРНЕННЫХ УГОДИЙ

Milling is one of the most effective methods of processing of heavy over-compacted soils, recultivation of blackened lands and development of virgin and fallow lands. As a result of intensive loosening and mixing of the soil, the mineralization process accelerates. When choosing the type of milling unit and its operating modes, the depth of the humus horizon, the type and density of the soil, the thickness of the sod, the presence of shrubs, stones, stumps, hummocks, the microrelief of the soil, the contamination with rhizomatous and other weeds are taken into account. (Research purpose) The research purpose is analyzing the used tillage cutters for basic tillage and the returning of blackened lands into circulation. (Materials and methods) Considered the design features of tillage cutters used in basic tillage and in blackened areas. Systematized data about them. (Results and discussion) It was determined that various designs of cutters make it possible to effectively grind blackened and compacted soil, destroy above-ground vegetation, and level the surface soil layer. It was found that effective processing of blackened lands includes grinding the sod and embedding it in the soil to a depth of 20-25 centimeters, creating a loose homogeneous fertile soil layer. (Conclusions) Milling allows high-quality processing of heavy, including blackened soils. The technological operation of milling provides shredding of weeds, uniform processing of fields and leveling of the surface layer, increasing the air permeability and infiltration properties of soils, reducing the time to prepare for pre-sowing treatment by combining several technological operations when using combined cutters.

Determining the impact of noise exposure of mining enterprises’ workers

This study investigated one of the main harmful factors at work, namely the impact of noise exposure on employees. The study was conducted in several stages. At the first stage, an on-site measurement was carried out using a calibrated sound level meter and a special smartphone application in the immediate vicinity of the ore grinding mill. It was found that the noise level is not constant. At the second stage, a mathematical dependence of the noise measurement results on the mill operating time was obtained to compare the measurement accuracy of the sound level meter and the app. As a result, it was determined that the application has sufficient accuracy compared to the calibrated instrument. The third stage resulted in the calculation of the risk of hearing loss for employees from noise exposure at workplaces based on the measurements of the calibrated sound level meter. The calculations showed that the level of this risk is high. At the fourth stage, personal protective equipment was selected using the relevant guidelines from NIOSH and EU-OSHA, as well as considering the results of field measurements, the maximum permissible noise level established by state sanitary standards, and the level of hearing loss risk.

Thyristor-based control for high-power and high-voltage synchronous electric drives in ball mill operations

This paper introduces technical solutions for the gradual initiation of potent and high-voltage synchronous motors, with the aim of advancing energy efficiency, resource utilization, and prolonging the operational lifespan of electric drives. A thyristor-based voltage converter device, comprising a cluster of thyristors, has been developed and tested in an experimental setup. The findings demonstrate a substantial reduction in the stator winding start-up current of synchronous motors when launched with the thyristor initiation device, decreasing from 5 to 8 times to 2 to 3 times.

Machining-Induced Distortion during Peripheral Milling of High Strength Aluminum Parts

In the aerospace and automotive industries aluminum sheet metal components are often produced by forming and post-machining. Due to the change in the complex stress state during manufacturing, part distortion is a major challenge. The overall objective of this work is to streamline the process chain to minimize production costs. For this, a determination of the material properties and analysis of the machining process parameters and their influence on the resulting distortion are required.First, tensile tests of the aluminum alloy EN AW-7075-T651 were performed. Subsequently, a series of machining tests were conducted to examine the effect of the machining process on the resulting part distortion. This paper presents machining-induced part distortion depending on the variation of the process parameters for down milling operations of thick aluminum plate material. It was found that the radial depth of cut and the cutting speed have a high impact on the resulting distortion, while the feed rate has a small influence.

Study on the dynamic characteristics of planetary gear transmission mechanism of metal cold rolling mill

Using the parametric modelling feature in Solidworks software, a three-dimensional solid model of a planetary gearbox with linear reciprocating motion of the output shaft was constructed. By conducting theoretical calculations related to the kinematics of the transmission system and combining Adams virtual prototyping simulation technology, a dynamic simulation model of the planetary gear transmission mechanism was established to analyse the motion laws and dynamic characteristics. The simulation results were compared and analysed against the theoretical calculation results, and they showed good agreement and consistency. The study also investigated the impact of counterweights on the inertia forces and moments of the output shaft in the transmission mechanism. The results indicated that adding counterweights effectively reduced the inertia impact caused by inertia forces at the start and end positions of the stroke, as well as the inertia torque caused by changes in angular acceleration during the startup and stopping phases, thereby enhancing the smooth operation of the mechanism. Additionally, different thicknesses of counterweights had varying effects on balancing the inertia forces and moments of the output shaft. The study aimed to find the optimal thickness of counterweights to achieve the best balance effect. Furthermore, the study examined the influence of different speeds of the driving gear on the inertia forces of the output shaft. The results showed that at a driving gear speed of 1500 rpm, the horizontal thrust generated by the output shaft was 63566 N, which could provide the required thrust for the rolling mill operation, and the inertia forces of the output shaft tended to stabilize.

Improving Hot Rolling Mill Operations through Lean Manufacturing and Optimization Techniques

Improving Hot Rolling Mill Operations through Lean Manufacturing and Optimization Techniques

Integrating Cloud Computing, Bayesian Optimization, and Neural-Additive Modeling for Enhanced CAM Systems in 5-Axis Milling

This publication introduces the development and application of an advanced CAD/CAM/CAE system that leverages the computational capabilities of an edge-cloud infrastructure. The developed system consists of containerized technology models for various complex process planning simulation tasks in 5-axis-milling, such as toolpath calculation, cutter-workpiece-engagement, uncut chip geometry or cutting force simulations. Moreover, a Bayesian optimization (BO) algorithm is coupled with the system enabling multi-objective optimizations of the considered machining operations by varying predefined CAM-parameters. The result of the optimization consists of a set of Pareto-efficient solutions. Each solution realizes a different tradeoff between the technological objectives of the process planner. Since mastering the complexity of the design space is a major challenge in today’s CAM programming workflow, a Neural-Additive Model (NAM) is coupled with the system improving guided search through the configuration/result space. This reduces the convergence time to an optimal CAM parameter set. The coupling of the cloud computing, multi-objective optimization and artificial intelligence method with a CAM-kernel is demonstrated based on the process design of 5-axis milling operations for a blade-integrated disk (blisk).

Energy and exergy analysis at the la joya sugar mill in Champotón, Campeche, Mexico

An energy and exergistic analysis was carried out on the bagacera boiler of the sugar mill "La Joya" located in Champotón, Campeche, making the following assumptions: the process develops in a permanent state, the mass that flows through the control volume does not suffer variations with respect to time, there are no work interactions of the system with the environment, changes in kinetic energy and potential energy are considered negligible, thermodynamic data were provided by the mill's operation and control center. It was found that by increasing the mass flow of feed water (mwater) and decreasing the temperature of the dead state (T0) there was the least destruction of exergy. Simulations were carried out to determine the energy and exegetical efficiencies of the mill as a whole with the help of the Software Engineering Equation Solver (EES). When modifying m ̇_water, with T0 at 25 ℃, and inlet water (Twater) 90 ℃, an increase was observed both efficiencies; the energetic reached a maximum of 88, and the exergetic of 31; It was also observed that the maximum energy efficiency is obtained with the Twater 45℃. On the contrary, the exergetic efficiency at 15.3. It was concluded that it is more important to increase the mass flow of inlet water to increase global efficiencies in mill facilities than its temperature.

The Effect of MoS2 and MWCNTs Nanomicro Lubrication on the Process of 7050 Aluminum Alloy

Nanofluid Minimum Quantity Lubrication (NMQL) is a resource-saving, environmentally friendly, and efficient green processing technology. Therefore, this study employs Minimum Quantity Lubrication (MQL) technology to conduct milling operations on aerospace 7050 aluminum alloy using soybean oil infused with varying concentrations of MoS2 and MWCNTs nanoparticles. By measuring cutting forces, cutting temperatures, and surface roughness under three different lubrication conditions (dry machining, Minimum Quantity Lubrication, and nanofluid minimum quantity lubrication), the optimal lubricating oil with the best lubrication performance is selected. Under the conditions of hybrid nanofluid minimum quantity lubrication (NMQL), as compared to dry machining and Minimum Quantity Lubrication (MQL) processing, surface roughness was reduced by 48% and 36% respectively, cutting forces were decreased by 35% and 29% respectively, and cutting temperatures were lowered by 44% and 40%, respectively. Under the conditions of hybrid nanofluid minimum quantity lubrication, the optimal parameter combination is cutting speed (Vc) of 199.93 m/min, feed rate (f) of 0.18 mm, cutting depth (ap) of 0.49 mm, and nanofluid mass fraction (wt) of 0.51%. The hybrid nanofluid can significantly enhance heat exchange capacity and lubrication performance, thereby improving machining characteristics.

Effect of Size-Distribution Environment on Breakage Parameters Using Closed-Cycle Grinding Tests.

The so-called population balance model (PBM) is the most widely used approach to describe the grinding process. The analysis of the grinding data is carried out using-among others-the one-size fraction BII method. According to the BII method, the breakage parameters can be determined when a narrow particle size fraction is used as feed material to the mill. However, it is commonly accepted that these parameters are influenced by changing the particle size distribution in the mill. Thus, this study examines the breakage parameters through kinetic testing in different natural-size distribution environments generated by closed-cycle grinding tests that simulate industrial milling conditions. The differentiation of the milling environments was accomplished using various reference sieves in the closed-cycle tests. The experimentally determined breakage parameters were back-calculated and then used to simulate the closed-cycle tests using the MODSIMTM software. Additionally, the energy efficiency was evaluated based on the specific surface area of the grinding products and the energy consumption. The results of the kinetic tests showed that the breakage rate of the coarse particles increases as the aperture size of the reference sieve decreases, and consequently, the content of fines in the mill increases. The back-calculated breakage parameters can be reliably used to simulate closed-cycle circuits, thus helping control industrial milling operations.

The Situation of Women in Iraq during the Mamluk Rule

This article discusses the situation of women in Iraq during the Mamluk rule (1749-1831) and their role in Pashaliq’s life both in the economic and cultural-educational spheres. Certainly, the social life of Iraqi women differed depending on where they lived - in cities, in rural areas, or in deserts, and to what social level they belonged. In rural areas, women, along with men, were actively involved in all kinds of agricultural activities. These were mainly wheat harvesting and cleaning, production of dairy products, care of domestic animals, harvesting and processing of agricultural crops, such as grinding wheat, and maintenance and operation of water mills. In rural areas, women were also actively involved in animal husbandry, taking care of cattle and poultry. At the same time, they performed quite heavy and labor-intensive work, which was expressed by drawing water from wells and rivers and using it for amelioration purposes. Such hard work often evoked compassion and sometimes outcry of foreign travelers towards the plight of rural women in Iraq.

Quantification of elemental sulfur in pulping liquors by thin-layer chromatography

The inorganic sulfur compounds that are used as pulping agents in the production of pulp and paper from wood are converted into a variety of sulfur species during processing. How sulfur is allocated to different streams and products in a pulp mill is relevant for efficient mill operation and to avoid harmful emissions. Pulping liquors are a highly challenging and potentially destructive sample matrix. We describe a thin-layer chromatographic method for the direct quantification of elemental sulfur in pulping liquors. The liquors are spotted (not sprayed!) directly onto the plate without prior purification, extraction, or workup. Sulfur is then eluted with cyclo-hexane and detected by densitometry at 285 nm or fluorescence quenching close to the solvent front. The method was validated for a calibrated range from 60 to 2000 ng sulfur on plate. The limit of detection was determined at 20 ng; measurement uncertainty was about 20%. With this method, 27–54 mg/L elemental sulfur were found in Kraft pulping liquors, which corresponds to 0.24–0.48% of the total sulfur in these samples.

Biogas Production from Palm Oil Mill Effluent at Low pH

The palm oil industry in Malaysia has aided our economy, but with any thriving industry comes the baggage of industrial waste. This paper focuses on palm oil mill effluent (POME), a waste product formed by palm oil milling operations. The objective of this paper is to evaluate the ability of POME to generate biogas through acid and heat pre-treatment methods. The feasibility of producing biogas at pH levels lower than 5 was investigated. The inoculum is effective microbe 1 (EM1), and the substrate is a liquid POME. Hydrochloric and phosphoric acid were used in this study, and the effect of low initial pH on biogas generation was investigated. The results show that POME alone produced the highest biogas volume (20.1 Nml). However, POME incubated with activated EM1 inoculant at low pH (3.74) generated consistent biogas during 57.75 hours of digestion. In conclusion, the EM1 is a good source of inoculum for POME treatment at low pH, with no pre-treatment required. The pre-treatment methods proposed in this study could have opened new doors for bio-renewable energy research, particularly in agricultural biomass, since substrate pre-treatment can enhance biogas production.

State-of-the-art review of applications of image processing techniques for tool condition monitoring on conventional machining processes

AbstractIn conventional machining, one of the main tasks is to ensure that the required dimensional accuracy and the desired surface quality of a part or product meet the customer needs. The successful accomplishment of these parameters in milling, turning, milling, drilling, grinding and other conventional machining operations directly depends on the current level of tool wear and cutting edge conditions. One of the proven non-contact methods of tool condition monitoring (TCM) is measuring systems based on image processing technologies that allow assessing the current state of the machined surface and the quantitative indicators of tool wear. This review article discusses image processing for tool monitoring in the conventional machining domain. For the first time, a comprehensive review of the application of image processing techniques for tool condition monitoring in conventional machining processes is provided for both direct and indirect measurement methods. Here we consider both applications of image processing in conventional machining processes, for the analysis of the tool cutting edge and for the control of surface images after machining. It also discusses the predominance, limitations and perspectives on the application of imaging systems as a tool for controlling machining processes. The perspectives and trends in the development of image processing in Industry 4.0, namely artificial intelligence, smart manufacturing, the internet of things and big data, were also elaborated and analysed.

OPTIMIZATION EXPERIMENTAL STUDY OF MACHINING ENERGY CONSUMPTION OF ZIG-ZAG MILLING CUTTING PATH USING RSM.

Machining operations in CNC milling which remove the work material require power and energy to activate the machine components such as spindle motor, table and tool movement in order to withstand the high friction and load between tool and work material. Energy consumption during cutting operation is greatly influenced by the machining condition and parameters. This experimental research aims to investigate how energy responds to changes in the machining parameters such as depth of cut, spindle speed, and feed rate during face milling operation of CNC machine. The high-speed steel (HSS) tool with a 10mm diameter was used to face mill the 40mm x 40mm of Aluminum 6061. The design of experiment technique using Response Surface Methodology (RSM) is utilized to optimize the experimental work. Power usage and machining time were recorded for each machining process, which is then used to determine the machining energy consumption. The interaction between machining parameter and energy is comprehensively visualized using surface and contour plot. Additionally, the ANOVA analysis investigates the feed rate as the most influential parameter to the machining energy. Finally, the regression equation of machining energy is generated with reliability (R) value of 0.88 which can be used as an energy prediction model.

Stress-based approach for predicting and improving large-scale HIG mill performance

As a fine and ultrafine grinding technology, the High Intensity Grinding (HIG) Mill is relatively new and there is opportunity to improve its performance by adjusting operational conditions. A laboratory HIG5 mill is commonly used for HIG mill sizing and scale up, however the clear correlation between the operational variables of laboratory mill to their production level is somewhat lacking. This paper presents a stress-based approach for predicting and improving large-scale HIG mill performance. A total of 27 experimental tests were performed with a HIG5 mill over a range of operational variable set points, including media density, media filling level, feed solid content, mill speed and flow rate. The influence of the variables on product size, mill operating power and specific grinding energy was characterized via multivariable linear regression modelling. Based on theoretical stress analysis and empirical calibration with available survey data, the model derived from laboratory testing was calibrated to predict the operation of the commercial HIG1600 mill. An approach was proposed for determining the effect of operational variables using a HIG5 that can be directly applied to reduce energy consumption at a given mill feed rate and product size target for the production scale mill. Results demonstrated that the stress-based approach integrated with laboratory testing can be used for predicting and improving large-scale HIG mill performance.