Mill Characteristics Research Articles

Preparation of avocado leaf simplicia macro/nano particles by using high energy ball mill

Taguchi method was used to examine high energy ball mill characteristics when producing micro/nano-particles of Simplicia powder using Orthogonal Array (OA) L25. Two factors and five levels were selected for the smallest diameter. The average fineness of the powder produced by high energy ball mill was calculated using the ASTM E11 standard Retsch vibrating sieve machine. The smoothest’s fineness value was obtained at a working time of 30 minutes and a shaft rotation speed of 578 rpm with a powder fineness of 181μm. The coarsest fineness value was obtained at 10 minutes of working time and 488 rpm rotating speed with 336μm powder fineness. Obtained the smallest particle diameter has the potential for better absorption of nutrients into the body.

Experimental Analysis of Semi-autogenous Grinding Mill Characteristics Under Different Working Conditions

In the present work, vibration, acoustic and thermal signals were correlated to the semi-autogenous grinding mill working parameters such as total power and inlet water flow rate, and then these parameters were monitored using vibration, acoustic and thermal analyses. Next, the influential controlling parameters were obtained to monitor the mill conditions via SPSS software and afterward by exploiting neural network method, the modified controlling parameters were acquired for the development of mill performance. It was found that the mill vibration and the bearing temperature increased with motors power. Also, the results revealed that the mill noise reduced with the increase in water flow rate. Finally, an analytical relationship between the controlling parameters and the noise as a measurable parameter was proposed.

English

Maize is the most widely consumed staple food by the Kenyan population. Its wide consumption and centralized processing make it an appropriate fortification vehicle to supply essential micronutrients to the population. The legislation was enacted in 2012 that makes it mandatory for all commercial maize mills in Kenya to fortify the maize flour with specified micronutrients as a public health effort to reduce the prevalence of micronutrient deficiencies. However, there is limited information on the current status of maize milling and implementation of the flour fortification programme by these mills. A cross-sectional study was therefore carried out to characterize the commercial maize mills and determine the status of flour fortification in Kenya. Questionnaires were used to collect data. Information was obtained from 22 large-scale, 25 medium-scale and 31 small-scale mills. These mills had an installed capacity of 6084 metric tons/day of flour using roller and hammer mills. While all the large-scale mills implemented the recommended statutory flour fortification programs, only 45.8% of the medium and 24.1% of small-scale mills did so. There was evidence of weak quality management systems for fortified maize flour and most companies did not have trained mill operators. Regulatory monitoring was mainly done by the Kenya Bureau of Standards and the Ministry of Health. There is a need to enhance industry capacity in food fortification practices and fortification compliance. Key words: Fortification, maize flour, maize mills, mill characteristics.

Use of Single Crystal Masks for Improved Mill Characteristics in High Current Xenon Plasma FIB instrumentation

Journal Article Use of Single Crystal Masks for Improved Mill Characteristics in High Current Xenon Plasma FIB instrumentation Get access Srinivas Subramaniam, Srinivas Subramaniam Intel Corporation, Hillsboro, OR, U.S.A Search for other works by this author on: Oxford Academic Google Scholar Linda Smath, Linda Smath Intel Corporation, Hillsboro, OR, U.S.A Search for other works by this author on: Oxford Academic Google Scholar Adriane Brown, Adriane Brown Intel Corporation, Hillsboro, OR, U.S.A Search for other works by this author on: Oxford Academic Google Scholar Kevin Johnson Kevin Johnson Intel Corporation, Hillsboro, OR, U.S.A Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 22, Issue S3, 1 July 2016, Pages 152–153, https://doi.org/10.1017/S1431927616001616 Published: 25 July 2016

Influence of Silanized-Silica and Carbon Black on the Cure and Mechanical Properties of Natural Rubber/Recycled Chloroprene Rubber (NR/rCR) Blends

The loadings effect of carbon black and silanized-silica filled 75/25 phr/phr of natural rubber/recycled chloroprene rubber (NR/rCR) blends were compared with the unfilled NR/rCR blends. Different filler loading between in the range of 10- 40 phr was used. The rubber blends were prepared by using a laboratory two-roll mill and rheometric characteristics were studied using the Monsanto moving die rheometer (MDR 2000) at 150 °C. The addition of CB and silanized-silica showed different trend in scorch and cure time but showed similar trend in torques. The incorporation of both fillers caused higher tensile strength than that unfilled rubber blends. By comparison, the silanized-silica filled NR/rCR blends showed higher tensile strength than CB filled NR/rCR blends. Morphological characterization as observed from SEM justified these results.

Calculation of grain mill characteristics for mobile compound feeds aggregates

Components of calculation of a two-rolling grain mill as more effective replacement assembly for mobile compound feeds aggregates instead of grain crushers are examined.

OPTIMAL DESIGN OF A FUZZY LOGIC CONTROLLER FOR CONTROL OF A CEMENT MILL PROCESS BY A GENETIC ALGORITHM

The knowledge base of a fuzzy logic controller (FLC) encapsulates expert knowledge and consists of database (membership functions) and rule base of the controller. Optimization of both of these knowledge base components is critical to the performance of the controller and has traditionally been achieved through a process of trial and error. Such an approach is convenient for FLCs having low numbers of input variables; however for greater numbers of inputs, more formal methods of knowledge base optimization are required. Genetic algorithms (GAs) provide such a method to optimize the FLC parameters to be globally optimum. The FLC is optimized by GA for varying nonlinearity and set point in the plant. The proposed control algorithm was studied on the cement mill simulation model and with a real cement mill model using MATLAB and Simulink environments. Parameters of the simulation model were set up based on the actual cement mill characteristics. The performance of the proposed control technique is compared with various other control techniques. The results of the control study indicate that the proposed algorithm can fully prevent the mill from plugging and can control the cement mill circuit more effectively.

Geographic Information System-Based Spatial Analysis of Sawmill Wood Procurement

Abstract In the sawmill sector of the forest products industry, the clustering of mills and wide variation in forest stocking and ownership result in sawlog markets that are complex and spatially differentiated. Despite the inherent spatial attributes of markets for stumpage and logs, few studies have used geospatial methods to examine wood procurement in detail across political boundaries. This article provides a visual representation of wood procurement pressure across the Northern Forest region of the northeastern United States based on a spatial analysis of woodshed maps provided by 273 sawmills in the United States and Canada. The analysis also includes the predicted woodsheds of 280 nonrespondent mills, which were modeled based on mill characteristics and location. In general, maps emphasize the magnitude of softwood procurement on industrial and investment-oriented forestlands in northern Maine, but also highlight distinct spatial procurement patterns in New York, Vermont, and New Hampshire. Sensitivity analyses of woodshed boundary uncertainty suggest that procurement pressure in existing hotspots will intensify if procurement range is restricted by high transportation costs. The methods used to visualize resource procurement in this study have the potential to benefit a broad range of stakeholders including industry, policymakers, and landowners.

Population Balance Model-Based Hybrid Neural Network for a Pharmaceutical Milling Process

Population balances are generally used to predict the particle size distribution resulting from the processing of a particulate material in a milling unit. The key component of such a model is the breakage function. In this work we present an approach to model breakage functions that has utility for situations in which determination of the breakage function from first principles is difficult. Traditionally, heuristic models have been used in those situations but the unstructured nature of such models limits their applicability and reliability. To address this gap, we propose a semi-empirical hybrid model that integrates first principles knowledge with a data-driven methodology that takes into account the material properties, mill characteristics, and operating conditions. The hybrid model combines a discrete form of population balance model with a neural network model that predicts the milled particle size distribution given material and mill information. We demonstrate the usefulness of this approach for compacted API ribbons milled in a lab scale Quadra conical mill for different materials and mill conditions. Comparisons are also given to the predictions obtained via a purely neural network model and a population balance model with a linear breakage kernel.

GA Optimized Knowledge Base of FLC for Complex Industrial Process

The Knowledge Base of a Fuzzy Logic Controller (FLC) encapsulates expert knowledge and consists of the Data Base (membership functions) and Rule-Base of the controller. Optimization of these Knowledge Base components is critical to the performance of the controller and has traditionally been achieved through a process of trial and error. Such an approach is convenient for FLCs having low numbers of input variables. However for greater number of inputs, more formal methods of Knowledge Base optimization are required. Genetic Algorithms (GAs) provide such a method to optimize the FLC parameters. An intelligent multi input multi output (MIMO) control for the cement milling circuit is presented. The FLC is optimized by GA for varying nonlinearity in the plant. The proposed control algorithm was tested with the cement mill simulation model within MATLAB SIMULINK environment. Parameters of the simulation model were set up based on the actual cement mill characteristics. The performances of the proposed control technique are compared with various other control techniques.

Evolutionary Design of Intelligent Controller for a Cement Mill Process

The Knowledge Base of a Fuzzy Logic Controller (FLC) encapsulates expert knowledge and consists of the Data Base (membership functions) and Rule-Base of the controller. Optimization of these Knowledge Base components is critical to the performance of the controller and has traditionally been achieved through a process of trial and error. Such an approach is convenient for FLCs having low numbers of input variables however for greater number of inputs, more formal methods of Knowledge Base optimization are required. Genetic Algorithms (GAs) provide such a method to optimize the FLC parameters. An intelligent multi input multi output (MIMO) control for the cement milling circuit is presented. The FLC is optimized by GA for varying nonlinearity in the plant. The proposed control algorithm was tested on the cement mill simulation model within MATLABTM SimulinkTM environment. Parameters of the simulation model were set up based on the actual cement mill characteristics. The performances of the proposed control technique are compared with various control technique. The results of the control study indicate that the proposed algorithm can prevent the mill from plugging and control the cement mill circuit effectively compared to the other control technique.

Land Cover, Land Use, and Mill Characteristics as Predictors of Wood Procurement Range

Urbanization of forestland has the potential to reduce the timberland base indefinitely. Wood-using industry located in areas with declining timberlands may be forced to expand the range of procurement operations to meet production requirements. This article examines 11 different land use and land cover variables as predictors of woodshed area for sawmills in the northeastern United States. Based on woodshed maps provided by 175 sawmills in seven states, geospatial analysis and multiple regression are used to test the hypothesis that mills in areas with higher proportions of nontimber land have larger woodsheds. Results indicate that mill characteristics, not landscape variables, are the strongest predictors of woodshed area. Although some cover types, including farmland and open water, are associated with larger woodsheds, none of the measures of urbanization used in this study are significant predictors of woodshed area. If urbanization is leading to a reduced flow of sawlogs, the explanation for the lack of observed effects of urban cover on woodshed area may be tied to the flow of sawlogs from terminal harvests, prior relocation of sawmills out of urbanizing areas, or the implementation of alternative procurement and production strategies that help sawmills remain competitive as local wood supplies tighten.

Mill selection and process optimization using a physical grinding model

A comminution result is determined by the number of stress events and the stress intensity. Against that, the comminution behavior of a mill is characterized by the frequency of stress events and the stress energy acting at each stress event. The product of stress number and stress energy is proportional to the specific energy input. The proportionality factor is the energy transfer factor which describes the percentage of energy which is used for stressing the product particles. Using the characteristic numbers based on a few tests, the operating parameters can be optimized. By comparing the mill characteristics with the breakage characteristics of the feed material, the performance of different mills and different operating states can be evaluated.

Tracer studies and breakage testing in pilot-scale stirred mills

A tracer technique is used to provide parameters that describe mixing and breakage in stirred mills. The results are also used to test the accuracy of mixing and breakage models. Tracer studies have been undertaken using a 39-litre vertical Sala agitated mill and a 4-litre horizontal Netzsch mill. The experimental residence time distribution (RTD) of the mills is analysed both in terms of a single mean residence time and a non-linear least squares fit to an optimal number of perf ect mixers of unequal size in series. Results show a strong dependence of RTD on flow rate, minimal dependence on stirrer speed, and support the concept that the RTD's of liquid tracers and solid tracers subject to breakage are similar. A very accurate match to the experimental RTD curves car be achieved with the multiple uneven mixers in series model. Size distribution results from solid tracer tests are used to determine the breakage characteristics of the pilot-scale Sala mill. The population balance model for a single perfect mixer with steady state hold-up is used as the basis for solution of a constrained non-linear optimisation inverse problem for mill breakage rate and breakage function. Experimental results indicate that the breakage rate is first order as hypothesised. The population balance model using optimal breakage parameters provides a reasonable fit to experimental data for cumulative passing percentage as a function of particle size for discrete times. Both the breakage rates and cumulative breakage functions are roughly power law dependent on particle size. Analysis of the size distribution of breakage products indicates that the mode of particle breakage, as indicated by the tracer breakage parameters, is a function of time. This demonstrates that the assumption of time independent breakage parameters in the population balance model may not be valid. Accurate determination of breakage parameters is strongly influenced by the transport characteristics of the slurry through the mill. The work shows that particle breakage in pilot-scale stirred mills is a complex function of both particle and specific mill characteristics. Therefore, in order to gain insight into the appropriate physical processes at work in an industrial scale mill, it is important to perform experiments with and analyse a system that matches the real mill as closely as possible.

Survey of receiving‐water environmental impacts associated with discharges from pulp mills: 1. Mill characteristics, receiving‐water chemical profiles and lab toxicity tests

AbstractThis survey examined the relationship between environmental responses at pulp mill sites and the pulping process (kraft vs. sulphite/thermomechanical pulping), effluent treatment (primary vs. secondary treatment), and bleaching technology used by pulp mills. This manuscript is the first in a series of four; it reviews the location and operating characteristics of mills included in the survey and provides background information on water chemistry that is relevant to the other components of the survey. In addition, lab 7‐d toxicity tests of receiving water were conducted using fathead minnows (Pimephales prome‐las) and the cladoceran Cenodaphma dubia with water samples collected upstream (reference) and downstream (plume) of effluent discharges at 11 Canadian pulp and paper mills; these samples were collected at the same time as fish surveys were conducted. Survival of fathead minnow larvae was significantly reduced at four of the 11 downstream sites. Ceriodaphnia reproduction was significantly higher at six of the 11 downstream sites and significantly lower at two downstream sites. There were no significant effects on fathead minnow larva growth or adult Cenodaphma survival at any of the examined downstream sites. Negative effects in the toxicity tests were generally associated with the low dilution discharge of primary treated effluent with a previous history of acute toxicity. Fathead minnow and Cenodaphnia tests were generally correlated with historical data on benthic mac‐roinvertebrate community responses. Neither toxicity test predicted the physiological changes in wild fish that are presented in accompanying papers.

A comparison of adaptive control strategies for hot steel strip rolling mills

Many modeling situations occur in which the plant has uncertain dynamics, nonlinearities, time varying characteristics and noise corrupted input and output measurements. These processes generally require a human operator whose function is to provide intelligent modeling and control. This exact situation occurs in the modeling and control of roll force in a hot steel rolling mill. It is the purpose of this paper to investigate and compare various adaptive control strategies for this problem. The first strategy uses a parameter identification technique to track the parameters in the roll force setup model from one steel run to the next. The next algorithm provides feedback control from run to run by an adaptive controller which uses a linear reinforcement learning scheme to adjust its parameters. The third method accounts for the above complexities by approaching the problem from a behavioral and structural point of view. The behavior of the model is assessed through a performance evaluator and the model is modified structurally and parametrically to improve the performance of the system as the process evolves. The derivation is based on correlation techniques and linear reinforcement learning theory, the latter of which provides memory and intelligence to the algorithm to model the decision process of the human operator. The results of this work serve to reinforce the opinion that the nonlinear mathematical structure of the model should be able to change from one steel run to the next in order to compensate for changes in mill characteristics and in the mill environment. Modeling results are presented from actual mill data and comparisons are made with time invariant models. In addition, the algorithms are general enough so that they may be easily applied to other processes that seem to defy traditional modeling techniques. They are not case dependent.

Instability and failure phenomena in polymer processing with application to elastomer mill behavior

AbstractThe mill behavior of different elastomers is discussed in some detail and contrasted with melt fracture in extrusion. The mill characteristics of elastomers are discussed, with special emphasis on effect of roll speeds and nip and on molecular structure of elastomer. Theories of failure mechanics in polymer processing are contrasted, and a theory of a viscoelastic material that exhibits rupture above a critical recoverable energy is analyzed. Mixing with carbon black is briefly discussed.

Paper and Printing

Abstract Paper must have certain physical properties to be suitable for use with the different printing processes. Technical specifications for paper and paper testing have been developed to secure proper quality for a specific purpose, but it is not possible to standardize paper made by all mills on a few physical and chemical tests. Such factors as appearance, color, feel, finish, formation, or printability are distinctive mill characteristics. The qualities discussed by the author are paper finish, moisture content, and relationship to printing inks.

Application of electric motors for driving tube mills

Tube Mill Characteristics THE greatest problem presented in the application of the electric motor for the individual drive of the tube mill is found in the fairly large torque required to bring it from rest up to its full operating speed. When once up to speed the load is practically constant, and only slight pulsations in the power requirements can be noticed.