Sorting Machine Research Articles

Tomato Sorting Machine Design

This design is based on the existing fruit sorting mechanism, and the sorting mechanism has been improved by using a spiral roller to design a tomato sorting machine. Based on the size of tomatoes, this tomato sorter can classify tomatoes into three categories to meet the needs of different occasions for different sizes of tomatoes, improve the utilization rate of tomatoes, and also speed up the rate of tomato sorting. The threads on the outer layer of the drum push the tomatoes forward while the drum rotates, and the tomatoes fall through the corresponding drum gaps to complete this sorting stage, with the largest grade going all the way to the end of the drum for grading. And the whole machine is equipped with sponge as a cushioning material in the parts of tomatoes that are easy to be impacted to prevent tomatoes from being damaged and to facilitate storage and sale of tomatoes. The sorter is inexpensive, easy to maintain and suitable for small-scale farmers.

A self-iterative learning with dual attention mechanism fusion method for pumpkin seed quality equipment

To perform fast and accurate classification of pumpkin seeds, three batches of pumpkin seed images were taken. A self-iterative learning large kernel attention-Squeeze and Excitation-Residual Network34 (LKA-SE-ResNet34) model was proposed by adding dual attention mechanism fusion of large kernal attention (LKA) mechanism and Squeeze and Excitation (SE) attention mechanism to each residual module of ResNet34 for recognizing pumpkin seeds. ResNet34 network model was chosen as the basic framework by comparing GoogleNet, AlexNet, EfficientNet, MobileNet, DenseNet, ResNet34 and Residual Network50 (ResNet50) deep learning network models. The comparation result showed that the top two models with the highest accuracy (Acc) are ResNet50 network model and ResNet34 network model among the compared models. The experimental results showed that the self-iterative learning LKA-SE-ResNet34 model outperformed the above-mentioned other network models in pumpkin seed recognition with an accuracy of 91.8%. To further validate the effectiveness of the proposed model for small sample size of data, two-sided images and deformed images of pumpkin seeds were collected and used, and the experimental results still proved that the proposed model had good generalization ability and accuracy, with the accuracies of 93.63% and 94.15% for two sides of pumpkin seeds as well as an accuracy of 99.03% for deformed pumpkin seeds. A set of seed sorting machine and an application (APP) for non-destructive testing of seeds were initially developed.

Research on Non-Destructive Quality Detection of Sunflower Seeds Based on Terahertz Imaging Technology.

The variety and content of high-quality proteins in sunflower seeds are higher than those in other cereals. However, sunflower seeds can suffer from abnormalities, such as breakage and deformity, during planting and harvesting, which hinder the development of the sunflower seed industry. Traditional methods such as manual sensory and machine sorting are highly subjective and cannot detect the internal characteristics of sunflower seeds. The development of spectral imaging technology has facilitated the application of terahertz waves in the quality inspection of sunflower seeds, owing to its advantages of non-destructive penetration and fast imaging. This paper proposes a novel terahertz image classification model, MobileViT-E, which is trained and validated on a self-constructed dataset of sunflower seeds. The results show that the overall recognition accuracy of the proposed model can reach 96.30%, which is 4.85%, 3%, 7.84% and 1.86% higher than those of the ResNet-50, EfficientNeT, MobileOne and MobileViT models, respectively. At the same time, the performance indices such as the recognition accuracy, the recall and the F1-score values are also effectively improved. Therefore, the MobileViT-E model proposed in this study can improve the classification and identification of normal, damaged and deformed sunflower seeds, and provide technical support for the non-destructive detection of sunflower seed quality.

INOVASI TEKNOLOGI MENUJU ZERO WASTE PENANGANAN DARURAT SAMPAH DI KOTA MAGELANG

The problem of domestic waste has become quite serious, considering the volume and rate of accumulation are increasing with the increasing population and economic activities. The Final Waste Disposal Site (TPSA) in Magelang City is currently overloaded because Magelang City only has one Final Waste Disposal Site (TPSA). If strategic and appropriate steps are not taken to reduce the waste entering the Banyu Urip Final Waste Disposal Site (TPSA), then within a maximum of 1-2 years the Banyu Urip Final Waste Disposal Site (TPSA) will not be able to receive waste shipments from Magelang City. The incomplete resolution of waste in Magelang City is due to the unavailability of waste processing technology that produces zero waste and is environmentally friendly. The policy analysis evaluation approach used is the Grid Analysis (Matrix Analysis) method. The results of the study recommend the application of waste processing machine technology by the Environmental Service. This mechanization technology is expected to be able to replace the previous method (open dumping and landfill) with waste mechanization with the advantages of being relatively odorless, relatively no social conflict and saving land. The mechanization technology consists of waste sorting machines, plastic shredding machines, organic waste pulping machines, conveyors and incinerators.

Analysis of Business Process Re-Engineering in the Implementation of Robotic Sorting Machines in the Middle Mile Process at PT Pos Indonesia (Persero)

PT Pos Indonesia faces challenges in improving courier service business processes due to business change trends. This study aims to identify and analyze inefficiencies in the middle mile supply chain business process of PT Pos Indonesia Processing Centre Surabaya and determine the number of robotic mega bots needed to improve efficiency. The research method uses quantitative information, observations, interviews, computer simulations, Value Stream Mapping process flow charts, and Business Process Reengineering concepts. The results showed that the use of mega bot robots had a positive and significant impact on the company's reputation, and the sorting process carried out using robotic mega bots was appropriate because it had a significant impact on the effectiveness and efficiency of business process improvements at PT Pos Indonesia (Persero).

Numerical investigation of the impact of various parameters on blowing accuracy in the XRT intelligent ore sorting machine blowing process

XRT separation equipment is attracting much attention as the mining industry increasingly uses pre-sorting technology. Its sorting accuracy is affected by differences in ore shape and particle size during operation. This paper, in which numerical simulations are conducted to investigate the resistance of ores under various situations, including varying blowing distances, cross-sections, and practical sizes, Additionally, this paper conducts validation tests. The test results indicate that within the 0.1-0.25 m section from the nozzle exit, there is a rapid decrease in velocity, accompanied by a significant change in ore resistance. Beyond the 0.25 m mark, the velocity reduction slows down, while the ore resistance becomes smaller. There exists a notable disparity in the resistance of ores with varying cross-sectional geometries. The size of the jet velocity surface caused by blowing distance significantly influences the resistance of ore with varying particle sizes. Furthermore, the resistance of the ore remains constant subsequent to the impact surface of the ore surpassing the surface of the jet velocity. Consequently, appropriately modifying the blowing distance, inlet pressure, and jet speed in accordance with the cross-sectional area and particle size of the majority of the ores stream can enhance the precision of the sorting process.

Development of novel prototype of orange sorting machine

Orange is one of the most popular fruits in the world. Oranges originate from Southeast Asia, India, and southern China. Nowadays, they are grown in warm regions around the world. Oranges are consumed either fresh or in the form of fruit juice. Depending on the type of orange, when ripe, its surface is orange or green, with a sweet or slightly sour taste. In Vietnam, oranges have significant export value. Therefore, ensuring consistent quality of oranges before export is an important requirement. Currently in Vietnam, this process is done manually or semi-automatically, resulting in low productivity and inadequate output for export purposes. This article introduces a new design of an automatic orange sorting machine. The proposed machine is equipped with functions to classify the size and defects on the orange surface through image processing technique. The experiment results show that the proposed machine works effectively. The size sorting module worked perfectly with absolute accuracy while the image processing module ensures the confidence level of 95%. The proposed machine could replace the manual sorting process with high accuracy.

Building an Educational Automated Mechatronics-Based Sorting System

This paper discusses the development of an automated sorting machine designed as a comprehensive mechatronics educational project. The project integrates mechanical and electrical design, incorporating a robot arm, a microcontroller, sensors, and actuators. The sorting machine uses color identification to sort wooden blocks of three different colors. The blocks are stacked and dropped onto a conveyor belt by a hopper system that employs a solenoid actuator and a servo to release one block at a time at specific intervals. As the belt runs continuously, each block passes under a color sensor, which monitors the color and signals one of three servo-powered mechanical arms to guide the block into the appropriate chute. Each chute is equipped with a capacitive proximity sensor that sends a voltage signal to the robot controller, queuing commands for the robot to pick up the blocks from the bottom of each chute and return them to the hopper to form a continuously running sorting system. This paper details the design and integration of the system’s various elements and the development of the control software. The designed system can drop blocks every 8.05 s, sort each block within 5 s of being sensed, and return them to the sorting system every 12 s. It has a color-sensing accuracy of 97%, with a failure rate of around 7%. The system achieved quick and reliable sorting using various low-cost, accessible, and open-source parts. The project exemplifies a cost-effective solution suitable for mechatronics education, demonstrating the numerous challenges involved in developing automated sorting systems.

Shortwave infrared hyperspectral imaging for the determination of pork adulteration in minced beef and lamb

Meat adulteration raises religious concerns and economic, quality, and safety issues. Therefore, ensuring that no unnecessary meat is added to the labeled primary meat is important. This study used shortwave hyperspectral imaging (SWIR HSI) working at 895–2504 nm to predict the level of pork adulteration in minced beef and lamb samples. Minced beef and lamb meat samples were adulterated with 2%–50% (w/w) minced pork. Unsupervised principal component analysis (PCA) was used to analyze and visualize the spectral data to determine their similarities. Spectral data were used to develop a partial least squares regression (PLSR) model to predict pork adulteration in minced beef and lamb. PLSR, with several spectral preprocessing methods, resulted in R2 0.97 and RMSE 2.47–2.55 for mixed pork and beef (Pork + Beef) model and R2 0.84–0.91 and RMSE 5.07–6.10 for mixed pork and lamb (Pork + Lamb) model. The developed PLSR model was then applied to each pixel in an image to obtain chemical maps to visualize the presence of pork in minced beef and lamb. This study demonstrated the potency of SWIR HSI to be applied in the sorting machine in meat industries to detect adulteration in meat.

Real-Time Solid Waste Sorting Machine Based on Deep Learning

The collection and separation of solid waste represent crucial stages in recycling. However, waste collection currently relies on static trash bins that lack customization to suit specific locations. By integrating artificial intelligence into trash bins, we can enhance their functionality. This study proposes the implementation of a sorting machine as an intelligent alternative to traditional trash bins. This machine autonomously segregates waste without human intervention, utilizing deep learning techniques and an embedded edge device for real-time sorting. Deploying a convolutional neural network model on a Raspberry Pi, the machine achieves solid waste identification and segregation via image recognition. Performance evaluation conducted on both the Stanford dataset and a dataset we created showcases the machine's high accuracy in detection and classification. Moreover, the proposed machine stands out for its simplicity and cost-effectiveness in implementation.

High-throughput G protein-coupled receptor-based autocrine screening for secondary metabolite production in yeast.

Biosensors are valuable tools in accelerating the test phase of the design-build-test-learn cycle of cell factory development, as well as in bioprocess monitoring and control. G protein-coupled receptor (GPCR)-based biosensors enable cells to sense a wide array of molecules and environmental conditions in a specific manner. Due to the extracellular nature of their sensing, GPCR-based biosensors require compartmentalization of distinct genotypes when screening production levels of a strain library to ensure that detected levels originate exclusively from the strain under assessment. Here, we explore the integration of production and sensing modalities into a single Saccharomyces cerevisiae strain and compartmentalization using three different methods: (1) cultivation in microtiter plates, (2) spatial separation on agar plates, and (3) encapsulation in water-in-oil-in-water double emulsion droplets, combined with analysis and sorting via a fluorescence-activated cell sorting machine. Employing tryptamine and serotonin as proof-of-concept target molecules, we optimize biosensing conditions and demonstrate the ability of the autocrine screening method to enrich for high producers, showing the enrichment of a serotonin-producing strain over a nonproducing strain. These findings illustrate a workflow that can be adapted to screening for a wide range of complex chemistry at high throughput using commercially available microfluidic systems.

Study on the distribution of high ash slime in liquid-solid fluidized bed with different heights

ABSTRACT Liquid-solid fluidized bed (LSFB) sorting has been widely used in coarse coal slurry sorting in coal preparation plants in China. In this paper, the vertical distribution of high-ash fine sludge in the LSFB column was studied in depth, and the results showed that in the vertical direction of the column, the gradient of ash change of the + 0.25 mm particles was obviously larger than that of the −0.25 mm particles. For + 0.25 mm particles, the low-density fine coal particles accumulate in the middle and upper parts, while the high-density particles accumulate in the middle and lower parts, and the overflow −0.25 mm particles are basically uniformly distributed in each density class. In the overflow port and the upper part of the column, the ash content of −0.25 mm particle size is obviously higher than that of + 0.25 mm particle size, and the −0.125 mm high ash and fine sludge basically accumulate in the upper part of the LSFB, and eventually enter the overflow to seriously pollute the fine coal. This study is of great significance for the development and application of LSFB sorting machine and the optimization of coarse coal slurry sorting and recovery process.

PYCR1 expresses in cancer-associated fibroblasts and accelerates the progression of C6 glioblastoma.

Cancer-associated fibroblasts (CAFs) play important roles in tumor microenvironments. Pyrroline-5-carboxylate reductase 1 (PYCR1) is a potential cancer therapy target. This study aimed to explore the expression of PYCR1 in glioma-associated CAFs and analyze the effects of PYCR1 expression in CAFs on the proliferation of C6 glioma. A rat glioma model was induced by injecting C6 cells in the right caudate putamen via a microliter syringe. After 14 days, tumor tissues were collected, and the levels of COL1A1 and PYCR1 were measured by immunohistochemistry. The colocalization of fibroblast activation protein α (FAP) and PYCR1 in tissues was measured by double-immunofluorescence. The CAFs were labeled by FAP and isolated from the tumor tissues using a fluorescence-activated cell sorting (FACS) machine. The isolated CAFs were further separated into CAFs with different PYCR1 expressions using the FACS machine. CAFs with different PYCR1 expressions were respectively cocultured with C6 cells or MUVECs for 48h using a Transwell permeable support. The invasion and proliferation of C6 cells were measured using a Transwell assay and colony formation assay, and the angiogenesis of MUVECs was measured using a Tube formation assay. The expression of COL1A1 and PYCR1 proteins in C6 cells and VEGF-A and EGF proteins in MUVECs was measured by western blotting. PYCR1 silencing in C6 cells was induced by PYCR1 siRNA transfection, the effects of which on the proliferation of C6 cells were measured using a wound healing assay, a Transwell assay, and western blotting. The PYCR1 and COL1A1 upregulation co-occurred in the rat glioma, and PYCR1 was expressed in CAFs. The CAF coculture enhanced the invasion and proliferation of C6 cells and the angiogenesis of MUVECs. Meanwhile, the levels of COL1A1 protein in C6 cells, and the levels of VEGF-A and EGF proteins in MUVECs were increased after CAF coculture. Moreover, the effects of CAF coculture were increased with PYCR1 expression in the CAF. Silencing PYCR1 suppressed the migration and invasion of C6 cells, and decreased the levels of COL1A1 and VEGF-A proteins in C6 cells. PYCR1 is expressed in glioma-associated CAFs, and promotes the proliferation of C6 cells and angiogenesis of MUVECs, suggesting that targeting PYCR1 may be a therapeutic strategy for glioma.

Online sorting of surface defective walnuts based on deep learning

To address concerns regarding walnut shell damage and inadequate sorting precision during the mechanized sorting of walnuts, a walnut automatic sorting machine was designed based on deep learning and experimental research. Initially, the rationality of the design was verified through experiment. Then, three deep learning semantic segmentation algorithms, namely PSPnet, U-net, and Deeplabv3+, were selected to train walnut detection models. Results indicated that the U-net algorithm proved to be the most effective, achieving a Mean Intersection over Union of 96.71% and a Mean Pixel Accuracy value of 98.52%. Finally, performance tests were conducted on the prototype machine, yielding results with an average sorting efficiency of 51.70 kg/h, an average loss rate of 6.50%, and an average accuracy of sorting walnuts of 92.98%. The findings can provide insights for future structural improvements and operational parameter optimization of walnut automatic sorting machines.

IoT Based Automated Tomato Sorting Machine

IoT Based Automated Tomato Sorting Machine

Examination of an Image Identification System for Agricultural Machines Based on Machine Vision

As computer and mechanical automation technologies advance, machine vision-based non-destructive testing technology finds use in a multitude of domains. Non-destructive testing technologies can be used on apple sorting equipment to decrease apple damage while simultaneously increasing sorting efficiency. As a result, the apple sorting machine’s image identification system now incorporates machine vision technology. The automatic classification of apple grades is accomplished by gathering, processing, extracting, and computing the contour features of apple photographs using preset sorting levels. The automatic control system then sorts apples of different grades to designated locations, thus achieving the automation of apple sorting. Tests were run on the sorting machine’s image recognition system to confirm the solution’s viability. The outcomes demonstrate that the sorting machine can effectively classify fruit automatically based on their perimeter, which is important for fruit sorting automation.

Sorting plastics waste for a circular economy: Perspectives for lanthanide luminescent markers

Improved sorting of plastic waste will be needed to increase the circularity of the plastics industry, irrespective of innovations in recycling technologies. The variety of recycling processes available in the future will not alleviate the need for sorting. Rather, nuanced sorting will be necessary to distribute waste streams into tailored feedstocks within an ecosystem comprising of various mechanical and chemical processes. A system for marking plastics with codes that are invisible to consumers, but readily apparent to sorting machines is of interest to enable such nuanced sorting. Luminescent lanthanide markers offer a promising solution, adding unique spectral signatures in the visible and near-infrared (NIR) to allow innovative new sorting options. Currently, 21 codes can be created using mixtures of three upconversion markers when excited with a 978 nm laser and measured with >99% accuracy. This range can be expanded with further NIR emitting markers, whose emission can be obtained at the same time as characterizing the NIR reflectance of plastics.

Conveyor Roll Manufacturing Conveyor Roll Manufacturing

Field work practice is a form of educational and vocational implementation that is participated in by students. Practical work aims to prepare students to become productive people and can work directly in their respective fields. Students can also experience the production atmosphere and can help deal with several problems experienced by professional engineering in factories. Conveyor systems can be said to be part of the equipment mechanics that transport materials from one place to another. This system is useful when goods need to be transported and moved from one place to another. Its existence makes the process easier, faster and more comfortable. In various industries, conveyors are very important. This system is designed to withstand heavy workloads and extreme weather conditions. The ability to adjust certain angles to help move materials. Design is divided into two, namely planning and conceptualizing. Planning this research focused on designing the conveyor for the can and plastic bottle waste sorting machine, then the consumer needs for the conveyor for the can and plastic bottle waste sorting machine were arranged as follows: a) The conveyor is easy to operate. b) Does not endanger the operator. c) Easy maintenance. d) Energy efficient conveyor from carrying out practical field work at CV. According to Agung Widodo's source, it can be concluded as follows: Industrial Automation or Industrial Automation is basically technology related to the application of mechanical, electronic and computer-based information systems to operate and control production.

Manufacturing of Roll Conveyors

Field work practice is a form of educational and vocational implementation that is participated in by students. Practical work aims to prepare students to become productive people and can work directly in their respective fields. Students can also experience the production atmosphere and can help deal with several problems experienced by professional engineering in factories. Conveyor systems can be said to be part of the equipment mechanics that transport materials from one place to another. This system is useful when goods need to be transported and moved from one place to another. Its existence makes the process easier, faster and more comfortable. In various industries, conveyors are very important. This system is designed to withstand heavy workloads and extreme weather conditions. The ability to adjust certain angles to help move materials. Design is divided into two, namely planning and conceptualizing. Planning this research focused on designing the conveyor for the can and plastic bottle waste sorting machine, then the consumer needs for the conveyor for the can and plastic bottle waste sorting machine were arranged as follows: a) The conveyor is easy to operate. b) Does not endanger the operator. c) Easy maintenance. d) Energy efficient conveyor from carrying out practical field work at CV. According to Agung Widodo's source, it can be concluded as follows: Industrial Automation or Industrial Automation is basically technology related to the application of mechanical, electronic and computer-based information systems to operate and control production. Key words: conveyor, roll, as roll.

A low-cost wireless extension for object detection and data logging for educational robotics using the ESP-NOW protocol.

In recent years, inexpensive and easy to use robotics platforms have been incorporated into middle school, high school, and college educational curricula and competitions all over the world. Students have access to advanced microprocessors and sensor systems that engage, educate, and encourage their creativity. In this study, the capabilities of the widely available VEX Robotics System are extended using the wireless ESP-NOW protocol to allow for real-time data logging and to extend the computational capabilities of the system. Specifically, this study presents an open source system that interfaces a VEX V5 microprocessor, an OpenMV camera, and a computer. Images from OpenMV are sent to a computer where object detection algorithms can be run and instructions sent to the VEX V5 microprocessor while system data and sensor readings are sent from the VEX V5 microprocessor to the computer. System performance was evaluated as a function of distance between transmitter and receiver, data packet round trip timing, and object detection using YoloV8. Three sample applications are detailed including the evaluation of a vision-based object sorting machine, a drivetrain trajectory analysis, and a proportional-integral-derivative (PID) control algorithm tuning experiment. It was concluded that the system is well suited for real time object detection tasks and could play an important role in improving robotics education.