Multi-Objective Optimization for an Industrial Grinding and Classification Process Based on PBM and RSM

The grinding and classification process is one of the key sub-processes in mineral processing, which influences the final process indexes significantly and determines energy and ball consumption of the whole plant. Therefore, optimal control of the process has been very important in practice. In order to stabilize the grinding index and improve grinding capacity in the process,a process model based on population balance model(PBM) is calibrated in this study. The correlation between the mill power and the operating variables in the grinding process is modelled by using the response surface method(RSM), which solves the problem where the traditional power modeling method relies on some unobservable mechanism-related parameters. On this basis, a multi-objective optimization model is established to maximize the useful power of the grinding circuit to improve the throughput of the grinding operation and improve the fraction of –0.074 mm particles in the hydrocyclone overflow to smooth the subsequent flotation operation. The elite non-dominated sorting genetic algorithm-II(NSGA-II) is then employed to solve the multi-objective optimization problem. Finally, subjective and objective weighting methods and integrated multi-attribute decision-making methods are used to select the optimal solution on the Pareto optimal solution set. The results demonstrate that the throughput of the mill and the fraction of –0.074 mm particles in the overflow of the cyclone are increased by 3.83 t/h and 2.53%, respectively.

Data driven particle size estimation of hematite grinding process using stochastic configuration network with robust technique

As a production quality index of hematite grinding process,particle size(PS)is hard to be measured in real time.To achieve the PS estimation,this paper proposes a novel data driven model of PS using stochastic configuration network(SCN)with robust technique,namely,robust SCN(RSCN).Firstly,this paper proves the universal approximation property of RSCN with weighted least squares technique.Secondly,three robust algorithms are presented by employing M-estimation with Huber loss function,M-estimation with interquartile range(IQR)and nonparametric kernel density estimation(NKDE)function respectively to set the penalty weight.Comparison experiments are first carried out based on the UCI standard data sets to verify the effectiveness of these methods,and then the data-driven PS model based on the robust algorithms are established and verified.Experimental results show that the RSCN has an excellent performance for the PS estimation.

Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process

Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization. Since the MPC does not handle disturbances directly by controller design, it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties. In this paper, an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation. The improved DOB is based on the optimal achievable H 2 performance and can deal with disturbance observation for the nonminimum-phase delay systems. In this DOB-MPC advanced feedback control, the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level. The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system. The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties. Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Multiparameter Optimization and Controlling for Cylindrical Grinding Process

This paper bursts the bondage of conventional no-burn thought, presents an optimum strategy permitting burn appear in grinding roughing stage, but the burning layer can be summed on the following finishing stage. On the base of the basic grinding models, the objective function and constrained functions for the multiparameter optimum grinding models had been built in this paper. By the computer simulation, the nonlinear optimum grinding control parameters had been obtained, and the truth grinding process had been controlled by these parameters. The results of simulation and the experiments proved the exactitude of the optimum models and the feasibility of the optimum strategy. This paper had also created the precondition for the grinding automation, virtual grinding and intelligent grinding system for cylindrical grinding process.

Effects of the grinding process on the preparation and qualities of CWS

Two different grinding processes were examined to determine the effect grinding has on the quality of a CWS. A series of slurries was prepared from Australian (Au) and Chinese (YZ) coals. Both types of coal were ground by a Chinese (CUMT) and an Australian (JK) grinding process. The performance tests of the prepared CWS showed that fluidity of all slurries was acceptable. The concentration of the CWS from YZ coal ground by the CUMT grinding process was higher than when the JK grinding process was used. The highest concentration was 70.14% in this case. The concentration of the CWS prepared from Au coal by the JK grinding process was higher than when the CUMT grinding process was used. The highest con- centration in this case was 70.97%. These differences are caused by the particle size distribution devel- oped during the different grinding processes.

Method for grinding and delaminating muscovite

A method of dry grinding muscovite based on the use of knife-mills is reported.It was possible to produce mica with a particle size below 100 and 45μm.After grinding,the samples were submitted to sonication treatment,which promoted delamination of the material.The particle size distribution shows that sonicated mica has more particles in the size range 10-50μm than does non-sonicated mica have. This also indicates a decrease in the average particle size.Characterization of the treated muscovite by scanning electron microscopy revealed a highly delaminated material with a plate-like structure.The products were characterized by chemical analysis and X-ray diffraction,too.This mica has already been used for the synthesis of pearlescent pigments.

Disturbance rejection control for Raymond mill grinding system based on disturbance observer

In the Raymond mill grinding processes,high-accuracy control for the current of Raymond mill is vital to enhance the product quality and production efficiency as well as cut down the consumption of spare parts.However,strong external disturbances,such as variations of ore hardness and ore size,always exist.It is not easy to make the current of Raymond mill constant due to these strong disturbances.Several control strategies have been proposed to control the grinding processes.However,most of them(such as PID and MPC)reject disturbances merely through feedback regulation and do not deal with the disturbances directly,which may lead to poor control performance when strong disturbances occur.To improve disturbance rejection performance,a control scheme based on PI and disturbance observer is proposed in this work.The scheme combines a feedforward compensation part based on disturbance observer and a feedback regulation part using PI.The test results illustrate that the proposed method can obtain remarkable superiority in disturbance rejection compared with PI method in the Raymond mill grinding processes.

Dynamic modeling and analysis of the closed-circuit grinding-classification process

Mathematical models of the grinding process are the basis of analysis, simulation and control. Most existent models in- cluding theoretical models and identification models are, however, inconvenient for direct analysis. In addition, many models pay much attention to the local details in the closed-circuit grinding process while overlooking the systematic behavior of the process as a whole. From the systematic perspective, the dynamic behavior of the whole closed-circuit grinding-classification process is consid- ered and a first-order transfer function model describing the dynamic relation between the raw material and the product is established. The model proves that the time constant of the closed-circuit process is lager than that of the open-circuit process and reveals how physical parameters affect the process dynamic behavior. These are very helpful to understand, design and control the closed-circuit grinding-classification process.

Experimental Determination of Optimum Exchanged Diameter in Surface Grinding Process

This paper presents an experimental study that helps to determine the optimum exchanged diameter in surface grinding. In the paper, the cost of a surface grinding process was analysed. In the cost structure, the effects of the cost parameters such as machine tool hourly rate, grinding wheel cost were taken into account. Also, process parameters including the initial grinding wheel diameter, the wheel life, the dressing regime and so on were investigated. Based on the cost structure, the set up and the procedure of the experiment for finding the optimum diameter was pointed out. From experimental results, the optimum exchanged grinding wheel diameter was found. Grinding with the optimum exchanged diameter, both the grinding cost and grinding time can be reduced significantly.

Cost Optimization of Surface Grinding Process

This paper introduces a new study on cost optimization of surface grinding. In the study, the effects of grinding parameters including the dressing regime parameters, the wheel life and the initial grinding wheel diameter on the exchanged grinding wheel diameter which were investigated. In addition, the influence of cost parameters including the machine tool hourly rate and the grinding wheel cost were taken into account. In order to find the optimum exchanged grinding wheel diameter, a cost optimization problem was built. From the results of the optimization problem, a model for determination of the optimum exchanged grinding wheel diameter was found. By using the optimum diameter, both the grinding cost and grinding time can be reduced significantly.

Profit Optimization of External Cylindrical Grinding

This article presents a study on profit optimization of external cylindrical grinding. In the optimization problem, the influences of several grinding process parameters such as the initial grinding wheel diameter, the wheel life, the total dressing depth as well as the effect of many cost components were investigated. A model for determination of optimum exchanged grinding wheel diameter was proposed. With this optimum diameter, a new and effective way of using the grinding wheel was proposed.

Effectuate Application of Optimum Methods in Grinding Process

Random error of grinding process is central factor th at give an effect on grinding quality all through. Optimum methods are usually a pplied on grinding process for higher productivity and preferable grinding quali ty. But the grinding quality can’t be reliably controlled now and then while opt imal solution of grinding processing parameters have been applied in production, because of two involved aspects which are availability of established empirical formulas and reliability of setting up optimum mathematical model. That is to s ay, there is particular application of optimum methods in grinding process. This paper discussed that how to confirm conditions of grinding test which be po int to grinding peculiarity when test design and regression analysis are used to setting up some empirical formulas. In order to reduce effect of random errors on precision of the empirical formulas and enable them to be applied widely, a m ethod that a lot of random error can be sufficiently contained in grinding test was suggested. And then, A means to ameliorate restriction formulas of grinding quality is expounded based on marked level of the empirical formulas and improve d reliability of optimum mathematical model is given, which offer an effectual w ay for solving grinding quality out of control as a result of random error and w orkable optimal solution of grinding processing parameters can be applied in the production really. Finally, an example is presented.

Relationship between subsurface damage and surface roughness of ground optical materials

A theoretical model of relationship between subsurface damage and surface roughness was established to realize rapid and non-destructive measurement of subsurface damage of ground optical materials.Postulated condition of the model was that subsurface damage depth and peak-to-valley surface roughness are equal to depth of radial and lateral cracks in brittle surface induced by small-radius(radius≤200 μm)spherical indenter,respectively.And contribution of elastic stress field to the radial cracks propagation was also considered in the loading cycle.Subsurface damage depth of ground BK7 glasses was measured by magnetorheological finishing spot technique to validate theoretical ratio of subsurface damage to surface roughness.The results show that the ratio is directly proportional to load of abrasive grains and hardness of optical materials,while inversely proportional to granularity of abrasive grains and fracture toughness of optical materials.Moreover,the influence of the load and fracture toughness on the ratio is more significant than the granularity and hardness,respectively.The measured ratios of 80 grit and 120 grit fixed abrasive grinding of BK7 glasses are 5.8 and 5.4,respectively.

Clinical Data-Driven Finite Element Analysis of the Kinetics of Chewing Cycles in Order to Optimize Occlusal Reconstructions Dedicated to Professor Karl Stark Pister for his 95th birthday

The occlusal design plays a decisive role in the fabrication of dental restorations.Dentists and dental technicians depend on mechanical simulations of mandibular movement that are as accurate as possible,in particular,to produce interference-free yet chewing-efficient dental restorations.For this,kinetic data must be available,i.e.,movements and deformations under the influence of forces and stresses.In the present study,so-called functional data were collected from healthy volunteers to provide consistent information for proper kinetics.For the latter purpose,biting and chewing forces,electrical muscle activity and jaw movements were registered synchronously,and individual magnetic resonance tomograms(MRI)were prepared.The acquired data were then added to a large complex finite element model of the complete masticatory system using the functional information obtained and individual anatomical geometries so that the kinetics of the chewing process and teeth grinding could be realistically simulated.This allows developing algorithms that optimize computer-aided manufacturing of dental prostheses close to occlusion.In this way,a failure-free function of the dental prosthesis can be guaranteed and its damage during usage can be reduced or prevented even including endosseous implants.

Intelligent optimal control system for ball mill grinding process

Operation aim of ball mill grinding process is to control grinding particle size and circulation load to ball mill into their objective limits respectively, while guaranteeing producing safely and stably. The grinding process is essentially a multi-input multi-output system （MIMO） with large inertia, strong coupling and uncertainty characteristics. Furthermore, being unable to monitor the particle size online in most of concentrator plants, it is difficult to realize the optimal control by adopting traditional control methods based on mathematical models. In this paper, an intelligent optimal control method with two-layer hierarchical construction is presented. Based on fuzzy and rule-based reasoning （RBR） algorithms, the intelligent optimal setting layer generates the loops setpoints of the basic control layer, and the latter can track their setpoints with decentralized PID algorithms. With the distributed control system （DCS） platform, the proposed control method has been built and implemented in a concentration plant in Gansu province, China. The industrial application indicates the validation and effectiveness of the proposed method.

Numerical simulation of particle motion at cucumber straw grinding process based on EDEM

Simulation of straw grinding process based on discrete element method(DEM)was proposed.According to the force analysis and kinematics analysis,the differential equation of straw particle motion on hammers was deduced,and the formation mechanism of the material circulation layer was obtained.Geometric model of grinder,particle model and contact model were established by EDEM software.The influence of hammer number,hammer thickness and gap of the hammer-sieve on particle grinding number and power consumption were obtained by single factor simulation test.The grinding process is divided into three stages.The hammer smashing plays a dominant role in 0-0.25 s.While the hammer smashing particle number increases slowly and then decreases to the lowest level in 0.25-0.60 s,the tooth plate smashing particle number increases rapidly and dominates,and then forming a material circulation layer.The hammer and tooth plate smashing particle number is basically stable in 0.60-2.00 s,and the tooth plate smashing occupies the dominant position.With the increase of the number and thickness of hammers,the power consumption of crusher tends to increase,and with the increase of the gap between hammers and sieves,the power consumption of crusher decreases first and then increases.The results can provide guidance for the development of high-efficiency and energy-saving grinding equipment for cucumber straw.

Subsurface damage pattern and formation mechanism of monocrystalline β-Ga_(2)O_(3) in grinding process

Monocrystalline beta-phase gallium oxide (β-Ga_(2)O_(3)) is a promising ultrawide bandgap semiconductor material. However, the deformation mechanism in ultraprecision machining has not yet been revealed. The aim of this study is to investigate the damage pattern and formation mechanism of monocrystalline β-Ga_(2)O_(3)in different grinding processes. Transmission electron microscopy was used to observe the subsurface damage in rough, fine, and ultrafine grinding processes. Nanocrystals and stacking faults existed in all three processes, dislocations and twins were observed in the rough and fine grinding processes, cracks were also observed in the rough grinding process, and amorphous phase were only present in the ultrafine grinding process. The subsurface damage thickness of the samples decreased with the reduction in the grit radius and the grit depth of cut. Subsurface damage models for grinding process were established on the basis of the grinding principle, revealing the mechanism of the mechanical effect of grits on the damage pattern. The formation of nanocrystals and amorphous phase was related to the grinding conditions and material characteristics. It is important to investigate the ultraprecision grinding process of monocrystalline β-Ga_(2)O_(3). The results in this work are supposed to provide guidance for the damage control of monocrystalline β-Ga_(2)O_(3)grinding process.