Manual Sieving Research Articles

Rancang Bangun Mesin Pengayak Terasi Bubuk Guna Meningkatkan Output Produksi dengan Pendekatan Antropometri

Increased consumer demand makes UMKM H.J Irin experience obstacles that are quite influential on production process activities. In this study, an ergonomic sieving machine design with anthropometric methods was carried out with the aim of helping the sieving process to be faster and increase productivity. Anthropometry is a method used to determine the size that is in accordance with anthropometric data obtained from the measurement of the worker's body. This research uses the time study method by making direct observations recording normal time and standard time. From the results of data processing that has been carried out from the anthropometric results of workers, the dimensions of the machine are obtained at a machine height of 82 cm, a machine width of 50 cm, and a machine reach of 67 cm. The increase that occurs in the sieving process is obtained an increase in productivity that occurs by 1.40%, with details of the productivity of manual sieving tools of 14% and after the design of the machine as much as 15.40%.

Online Monitoring of Iron Ore Pellet Size Distribution Using Lightweight Convolutional Neural Network

An improved U-Net based convolutional neural network (CNN) is proposed in this paper for online size monitoring of iron ore pellets. The proposed CNN model is a lightweight version of U-Net. In the proposed model each convolution block of the encoder subnet consists of a concatenated <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1\times 1$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3\times 3$</tex-math> </inline-formula> filter kernel, a batch normalization layer, and a ReLU nonlinearity. The proposed CNN model efficiently detects the pellets even under variable illumination conditions and images with overlapping pellets. The proposed model is evaluated using images of iron ore pellets acquired at the discharge end of a pelletizer disc. The proposed CNN model performs satisfactorily using <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim$</tex-math> </inline-formula> 39% less learnable parameters, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim$</tex-math> </inline-formula> 16% reduced computational cost than the original U-Net model. The proposed model outperforms the conventional U-Net, different variants of U-Nets, FCN, and SegNet in weighted IoU, BF Score, global accuracy, SSIM, and PSNR. Experimental validation also shows a good agreement between the obtained pellet size distribution and the manual sieving result. This makes the proposed algorithm suitable for online pellet size-distribution measuring instruments. This method provides a more accurate and fast size monitoring system for iron ore pellets, ideal for real-time industrial applications. The image dataset and source codes are available at the below given link. https://github.com/aryadeo/Pellet_Size_Distribution. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Due to the advent of digitalization in industries, several attempts are being made to use innovative industrial monitoring systems in steel manufacturing plants. Most of the pellet plants in steel industries use human supervision for pellet growth monitoring. In this paper, a camera-based pellet size distribution monitoring method is proposed. A novel deep learning-based algorithm is used for the detection of pellets from the captured image followed by computation of pellet size analysis. Due to low computational complexity and better accuracy, the proposed method is suitable for online pellet size distribution system development compared to other previously proposed methods. However, protection from the harsh industrial environment is required for the uninterrupted and continuous operation of the system. As a future scope, the obtained pellet size information can be used as one of the control variables in designing a control system for the automated operation of the pelletizer disc.

The application of dual energy X-ray soil screening in forensic archaeology

The need to forensically search soil for small artefacts at a burial site or traces of evidence in a deposition site is a common task shared by investigators and forensic archaeologists. In forensic casework, the importance of finding small pieces of evidence, such as personal effects or ballistic fragments, cannot be overstated as it can assist in the positive identification of the deceased, give an insight into the manner and cause of death, and identify any perpetrators. The soil search methods known as wet and dry sieving, are cumbersome, time-consuming and have limited success for some soil types. This often leads to the decision not to search, resulting in missed opportunities to identify potential evidence.The primary aim of this study was to investigate if a dual energy X-ray baggage scanner could be used to search for items of potential forensic interest in soil. A trial was conducted using a Smiths Detection ScanTrailer 100100 V-2is mobile X-ray inspection system to establish if it could be used to detect organic, inorganic, and metallic items located within soil. The soil type and natural variables such as water and organic content were adjusted to simulate different environments. The baggage scanner was found to provide a quick and easy way to detect items contained within various soil types, particularly in a sand rich matrix. It is estimated that using this method to search 1 m3 of soil, when broken down into samples that are < 13 cm in depth, would take around one hour to complete, compared with 100 to 150 person-hours by manual sieving. This is believed to be the first use of dual energy X-ray technology for this purpose and shows the potential for further research and use of this method in forensic archaeology.

Investigating the Granulometric Distribution of Fluvial Sediments through the Hybrid Technique: Case Study of the Baganza River (Italy)

Sediment characterization is a key parameter to understand the geomorphological attributes of a catchment (i.e., assessing the variability of the sediment transport capacity and surface roughness of a hydraulic channel). This assessment can be performed in several ways, for instance, through numerous sampling techniques (i.e., pebble count and zig-zag methods). Sediment sampling using manual sieving inside a laboratory is a hectic process as it requires ample time and physical effort, particularly when the scale of interest is at the catchment level. In order to find the granulometric distribution of some sections of the Baganza streambed (northern Italy), in order to carry out analysis at the catchment scale, a hybrid technique (a combination of the conventional and photogrammetric method) is introduced. Different grain size distribution curves (GSDs) obtained from the image processing technique using Digital Gravelometer software and traditional sediment sieve analysis (sieve-by-weight method) were compared. Sediment sampling was limited to sections of the streambed that were visible during lower flows in the dry summer season. Sediment samples including fine soil fraction, were collected up to a depth of 30 cm, although the exposed areas behaved as gravels and cobble bars. The adopted hybrid technique approach for the characterization of fluvial sediments is desirable in order to accommodate the full range of particle sizes inside the riverbed. Digital photography was performed at ten different cross sections, along the longitudinal profile of the 30 km long reach of the Baganza River, to examine the sediment distribution, grading, and representative particle sizes (D10, D50, D90) at each of the respective cross sections. A comparison of the photogrammetric method and traditional sieve analysis revealed strong agreement in coarser segments of the grain size distributions, but it was deficient in the finer part (&lt;2 mm) due to the shielding effect produced by bigger particles. However, the adopted hybrid technique appears to be quite efficient and promising in determining the GSD by reducing the costs and the sediment sample collection time in the field.

Development and performance evaluation of thresher for onion umbels

AbstractThe post‐harvest unit operations of onion umbels are being carried out manually. To mechanize this process, the present study was carried out to develop an onion umbels thresher. The developed machine works on the principle of abrasive and impact actions from rasp bars. Thresher performance was evaluated at different numbers of rasp bars (2, 3, 4, and 8 numbers), feed rates (25 ± 1, 30 ± 1, and 35 ± 1 kg/h), concave clearance (6.5 and 7.5 mm), and peripheral speeds (2.5 and 3.3 m/s). At 35 ± 1 kg/h feed rate, 2 numbers of rasp bars, 7.5 mm concave clearance, and 2.5 m/s peripheral speed recorded higher threshing efficiency (97.82%) and lower seed damage (2.08%). The parameters such as the number of rasp bars on the threshing cylinder, peripheral speeds, concave clearances, and feed rates recorded significant effect (p &lt; 0.01) on threshing efficiency and seed damage.Practical ApplicationsThe manual onion seed extraction process such as beating with sticks, cleaning of threshed onion umbels by manual sieving than further cleaning by dipping in water, sun drying, and packaging is tedious and requires 6–8 days for completing all associated unit operations. Onion umbels are subjected to impact force leading to damage of the seeds, which affects the germination rate and lower vigor index. In this context, mechanization of the onion umbels threshing process is imperative to maintain the quality of the seed.

Actual Issues of Identification and Examination of Chewing Tobacco for Customs Purposes

The article touches upon the issues of identification of non-smoking tobacco products (sucking tobacco - snus and chewing tobacco); definitions of these terms are given in accordance with the current regulatory documents. Under the guise of chewing tobacco, snus is imported into the territory of the Russian Federation, the import of which is prohibited. The article shows the existence of the problem of identification of chewing tobacco in the production of customs examination; using the example of experimental samples, the features of manual and machine sieving and the influence of the composition of fractions of tobacco raw materials and humidity of non-smoking tobacco products on the fractional composition of the product are considered; the presence of shortcomings in the method of determining the fractional composition according to GOST R 58553-2019 is proved.

Error on the Estimation of Sand Size Parameters When Using Small Diameter Sieves and a Solution

Analyses were carried out to determine the main sand size parameters (median grain size D50 and sorting σ) for beach nourishment purposes using the sieving method aboard a dredger. Due to a lack of space and the need to carry and use the material with ease, the sieves are commonly small (10 cm diameter), and the shaking procedure is usually performed by hand. However, the influence of shaking, either mechanically or manually, has not yet been studied with 10 cm diameter sieves. Therefore, 20 samples were taken from inside the hopper of a trailing suction dredger and sieved both manually and mechanically for 10 min. The results showed that manual sieving yielded higher D50 values than the mechanical procedure. The average error arising from using the manual method was 14%, but it can reach 36.5%. The granulometric analysis carried out for different shaking times has shown that this error is &amp;lt; 5% when at least 20 min of shaking is performed. The mechanical procedure gave always finer sand results. In addition, the overfill ratio calculated for both mechanical and manual results reached differences of up to 48%.

PERANCANGAN MESIN PENGAYAK DAUN KERING BAHAN BAKU PUPUK ORGANIK DI CV. GLOBAL BUMI PUTRA DENGAN PENDEKATAN METODE PAHL AND BEITZ

In the current condition of more advanced technology, all activities will be easy with the emergence of various new tools that have more usability than the basic capabilities of the previous tools. The more sophisticated the tool, the lighter the work done during the production process. CV. Global Bumi Putra, one of the organic fertilizer factories in the city of Jember, is still carrying out the sieving process in a traditional way. To increase the yield of dry leaf organic fertilizer, a dry leaf sieving machine was made. The method used to design this machine is the Pahl and Beitz method. There are 4 design stages in this method, namely planning and explaining tasks, designing product concepts, designing product forms, and the final phase of detailed design. From the results of the design using the Pahl and Beitz method, the design of the dry leaf sieving machine with the machine frame uses iron material, in the form of a cube for the outside. AC motor drive with electrical energy sources, transmission using belts and pulleys. Minimum machine design with size P = 2 m, W = 1.5 m, T = 2 m. The sieve on the machine is tubular, the size of the sieve net is 4 cm. The average yield of 2 sacks of chopped leaves using a manual sieve was 5.36 kg in 10.31 minutes. Meanwhile, from the test results of the sieving machine that was made, the average sieve yield of 2 chopped leaf sacks was 5.92 kg in 03.49 minutes.

PENERAPAN TEKNOLOGI TEPAT GUNA SEBAGAI PENINGKATAN KAPASITAS MESIN PENGAYAK PASIR TIPE ROTARY DAN USAHA DUSUN TANGGALAN, KABUPATEN KARANGANYAR

The increasing of infrastructure development causing in increased demand for sand material. On the other hand, the sand still contains many other components such as gravel. The size of good sand according to the Indonesian National Standard (SNI - 03-247-2002) is natural or artificial sand produced by the stone crusher industry with the largest grain size of 5 mm. On the other hand, the lack of infrastructure of the Tanggalan vilage and the small income of the village has resulted in an uneven distribution of the regional economy. Youths and heads of the Tanggalan village see the potential to increase the village's income by making sieving businesses and providing good quality building sand. The manual sieving process takes longer, so it has an impact on the development process as well as from an economic point of view on the long construction costs. So, it is necessary to have a rotary type automatic sieving machine that has a function to separate fine sand grains or according to the criteria requested by consumers with gravel. Rotary type sieving machine with a capacity of 10 m 3 /hour, so it is expected to meet the demand and accelerating development process. In addition, with this tool, hamlet businesses can be formed to increase hamlet income. Key words: Business, Enhancement, National Standard, Rotary, Sand Sieve.

Perancangan Prototype Mesin Pengayak Pasir Semi Otomatis Menggunakan Photovoltaic

The sand sieving system is generally still done manually which requires full human power for the sieving process. This is quite time consuming and the resulting fine sand mass is far from what is required for a construction project. Therefore the author made the idea of ​​​​designing a sand sieving machine that can be applied anywhere. This machine uses a driving system of a Brushless Direct Current electric motor with a capacity of 350W as the driving motor. Brushless Direct Current Motor is used because it has the advantage of a large starting torque, higher speed because it does not use a brush. As a source of electricity, new renewable energy solar panels with a capacity of 400Wp are used which are more environmentally friendly and efficient. This machine works when the solar panels supply a power source to the driving motor and then transmitted by the chain and gear to the sieve tube for the sieving process. This machine has a faster sand sieving process than manual sieving and the type of motor used is more efficient.

Online size distribution measurement of dense iron green pellets using an efficient and multiscale nested U-net method

Accurately measuring the pellet size distribution during the pelletizing process is critical, because the pellet size distribution is a key quality indicator and affects the efficiency of the blast furnace. In this study, a method based on a convolutional neural network is proposed to measure the pellet size distribution in the stable area of a rotary disc. The proposed network only uses simple convolution layers in sequence to realize multiscale performance; furthermore, it uses a bottleneck layer and a concatenate path to improve the computing efficiency and alleviate the vanishing gradient problem, respectively. Various experimental results demonstrate that the proposed network outperforms other comparison methods in segmenting overlapped pellets, especially pellets of different sizes. The pellet size distribution obtained by the proposed method agreed well with the manual sieving results. Moreover, the computing time of the proposed method can meet the requirements of online size distribution measurement.

Size distribution measurement of coal fragments using digital imaging processing

This paper focuses on the size distribution measurement of coal fragments by digital imaging processing. The fast and precise measurement of coal fragments, which is important to understand the crack propagation and energy dissipation process of coal failure, has not been achieved by previous research. In this paper, an image analysis method using MATLAB is proposed to measure fragment size distribution of coal fragments. The acquisition setup, analysis step and coding process for fragment size distribution measurement by digital imaging processing are introduced in detail. The statistical size distribution of coal fragments measured by image processing is compared with the theoretical distribution function and manual sieving results. This paper provides an innovative and efficient method for size distribution measurement in the study of coal failure process.

Light Drone-Based Application to Assess Soil Tillage Quality Parameters.

The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics, such as laser profile meters. The aim of the study was to compare traditional methods of soil roughness and cloddiness assessment (laser profile meter and manual sieving), with light drone RGB 3D imaging techniques for the evaluation of different tillage methods (ploughed, harrowed and grassed). Light drone application was able to replicate the results obtained by the traditional methods, introducing advantages in terms of time, repeatability and analysed surface while reducing the human error during the data collection on the one hand and allowing a labour-intensive field monitoring solution for digital farming on the other. Indeed, the profilometer positioning introduces errors and may lead to false reading due to limited data collection. Future work could be done in order to streamline the data processing operation and so to produce a practical application ready to use and stimulate the adoption of new evaluation indices of soil cloddiness, such as Entropy and the Angular Second Moment (ASM), which seem more suitable than the classic ones to achieved data referred to more extended surfaces.

An image-based method for online measurement of the size distribution of iron green pellets using dual morphological reconstruction and circle-scan

Particle size distribution (PSD) of green pellets is critically important in pelletizing process because it greatly affects the quality of iron ore oxidized pellet as well as the efficiency of blast furnace process. Image-based methods are effective in automatic measurement of PSD, but are limited in their capacity in segmenting overlapped pellets and computation efficiency. To overcome these shortcomings, a novel image segmentation algorithm is proposed in the present work, with which overlapped pellets in the image can be well separated and thus the PSD of iron green pellets can be measured online with good accuracy. The proposed algorithm first identifies the markers of each pellet directly from the greyscale image by a dual morphological reconstruction method, then a circle-scan method is proposed to split the overlapped pellets and measure the diameter of each segmented pellets. The proposed methods were verified by experiments and compared with methods available in literature as well as manual sieving results. It was demonstrated that the proposed algorithm achieves better segmentation performance and has an accuracy of 94.3%. The proposed measuring system has already been tested in a local steel company. Results show that the robustness and computing efficiency of the proposed image-based method is sufficient to satisfy the requirement for online PSD measurement in harsh environment of the pelletizing process.

Measuring the effects of in vitro mastication on bolus granulometry of shredded meat: A proposal for a new methodological procedure

People with poor oral status and/or neuromuscular deficiencies avoid eating meat because of chewing and swallowing difficulties. Consequently, they expose themselves to the risk of malnutrition and sarcopenia or nutrient deficiencies. To develop a new process for meat preparation, it is necessary to understand how meat is broken down during food oral processing to become a swallowable bolus. However, it is unknown whether the initial texture of meat impacts the meat bolus granulometry. As meat particles are fibrous, making the granulometry analysis with sieving methods is difficult. As the approach of meat bolus granulometry is necessary, it is of importance to control the methodological parameters that affect the measures. This study describes a procedure that allows granulometry analysis of shredded meat before and after in vitro mastication.Meat particles were dispersed in glycerol before image analysis. Granulometry curves were then drawn using generalized linear models, particle by particle, or after applying virtual sieves. Artificial meat bolus granulometry was also analyzed by manual sieving and the different methods were compared through several characteristics, including D50. Image analysis in glycerol preserves meat particles and allows particle distribution characterization and shape descriptors analysis. This method is well adapted to shredded meat and could be performed to evaluate the mastication of meat preparations adapted for deficient mastication.

The research of particle sieving under a creative mode of vibration

In order to improve screening performance, a creative vibrating screen with a new mode coupling of translation and swing was proposed which inspired by the manner of manual sieving. A mechanical model of the new motion was established. The discrete element method (DEM) was used to study the particulate systems with the complex particle size distribution considering interactions between particles. This paper simulated the screening process with the new compound trace to calculate screening efficiency in different vibration parameters. Vibration parameters mainly encompass swing angle, swing frequency, translation frequency, translation direction angle, and amplitude. The functional relationships between screening efficiency and vibration parameters were presented based on 3D-DEM simulations. The results show that each vibration parameter has an optimum value in simulations. The relationships and optimal parameters offer insights to vibrating screen design, manufacture and installation. Compared to single translation or swing trace, screening efficiency were improved. The laboratory-scale vibrating screen with transformation parameters was created for validating the screening principle from the simulation data.

Quantitative model prediction of the combined effect of moisture content and temperature on purple mudstone decay in south-western China

Rock decay is mainly the result of the combined effects of moisture content and temperature, but little is known about the quantitative relationship between these variables and the rate of rock decay. In this study we develop quantitative calculation models of rock decay rate under laboratory conditions and validate the efficiency of these models by comparing the predicted rock decay mass and that measured for rock exposed in the field. Rainfall and temperature data in the field were standardised to a dimensionless moisture content and temperature variables, respectively, and then the predicted rock decay mass was calculated by the models. The measured rock decay mass was determined by manual sieving. Based on our previously determined relationship between a single factor (moisture content or temperature) and the rate of rock decay in the laboratory, power function models are developed. Results show that the rock decay mass calculated by the model was comparable with field data, with averaged relative errors of 1.53%, 9.00% and 11.82% for the Tuodian group (J3t), Matoushan group (K2m) and Lufeng group (J1l), respectively, which are mainly due to inaccurate transformation of field rainfall into the rock moisture content and artificial disturbance when the samples were sieved in the field. Our results show that the developed models based on laboratory-derived rates can accurately predict the decay rates of mudstones exposed in the field.

Quality assessment for recycling aggregates from construction and demolition waste: An image-based approach for particle size estimation

The size distribution of aggregates has direct and important effects on fundamental properties of construction materials such as workability, strength and durability. The size distribution of aggregates from construction and demolition waste (C&D) is one of the parameters which determine the degree of recyclability and therefore the quality of such materials. Unfortunately, standard methods like sieving or laser diffraction can be either very time consuming (sieving) or possible only in laboratory conditions (laser diffraction). As an alternative we propose and evaluate the use of image analysis to estimate the size distribution of aggregates from C&D in a fast yet accurate manner. The effectiveness of the procedure was tested on aggregates generated by an existing C&D mechanical treatment plant. Experimental comparison with manual sieving showed agreement in the range 81–85%. The proposed technique demonstrated potential for being used on on-line systems within mechanical treatment plants of C&D.

Packing and permeability properties of E-glass fibre reinforcements functionalised with capsules for self-healing applications

In the framework of the development of capsule-based self-healing composites, this work investigates whether the capsules containing self-healing agents, dispersed on dry glass fibre reinforcements, influence their packing and longitudinal and transverse permeability properties. Solvent-filled urea–formaldehyde capsules have been produced and their morphology and thermal behaviour characterised for self-healing applications. Glass woven 2×2 twill fabrics were functionalised with capsules spread by manual sieving. Packing and permeability measurements were performed as a function of capsule content. Of practical interest for further manufacturing of self-healing composites by vacuum-assisted resin infusion moulding, the presence of capsules in the range of 125–250μm diameter was found to modify the compression response, leading to higher total porosity for a given applied pressure, from 0.5 to 0.55 with capsules at 1bar. The longitudinal permeability was multiplied by a factor of about 6, whereas the transverse permeability was not affected.

Characteristics and efficiency of a new vibrating screen with a swing trace

A new vibration type and motion characteristics were proposed according to the principle of manual sieving. A mechanical model of the new motion was established and the characteristics of the new vibrating screen were analyzed to establish its equation of motion by using the vibration theory, to include as technological parameters, amplitude, movement velocity, and throwing index through theoretical calculation. The efficiency of particle screening was studied at different values of frequency and swing declination angle. The discrete element method (DEM) was used to simulate the screening with the swing trace. The functional relationship between screening efficiency and the parameters was fitted with the least square method. The results show that high frequency and large swing angle are suitable for small particles, while small values are suitable for particles close to the aperture size. Compared to the linear vibration trace, both screening efficiency and processing capacity were effectively improved.