Sorting Line Research Articles

Approach to Sorting Line Control using PLC and Factory I/O

The article presents the possibility of using a 3D environment to simulate the operation of a manufacturing process and control a virtual object with a PLC. A sample application of the Factory I/O environment compatible with TIA Portal software and the real S7-1214 DC/DC/DC controller is presented. Visualization and program code written in LAD language correlated with the 3D environment were presented. The results showed the importance of a dynamic programming environment that reflects the program code designed to sort virtual production line components. The research showed that working with the code and the virtual object experiences students and is closer to industrial solutions than just laboratory ones.

Machine vision-based detection of forbidden elements in the high-speed automatic scrap sorting line

Highly efficient industrial sorting lines require fast and reliable classification methods. Various types of sensors are used to measure the features of an object to determine which output class it belongs to. One technique involves the use of an RGB camera and a machine learning classifier. The paper is focused on protecting the sorting process against prohibited and dangerous items potentially present in the sorted material that pose a threat to the sorting process or the subsequent metallurgical process. To achieve this, a convolutional neural network classifier was applied under real-life conditions to detect forbidden elements in copper-based metal scrap. A laboratory stand simulating the working conditions in a high-speed scrap sorting line was prepared. Using this custom stand, training and test sets for machine learning were gathered and labeled. An image preprocessing algorithm was designed to increase the robustness of the resulting forbidden element detector system. The performance of multiple neural network architectures and data set augmentations was analyzed. The highest accuracy of 98.03% and F1-score of 97.16% were achieved with a DenseNet-based classifier. The results of this paper show the feasibility of using the presented solution on a high-speed industrial line.

Green business process management in a Polish municipal waste treatment plant-regional case study

Despite COVID-19, the world economy still contributes to the growth of production and consumption worldwide. Waste disposal, recycling management and energy generation are challenges for many companies in developing economies, including Poland. This article aims to assess the operation of a municipal waste treatment plant (MWTP) from the perspective of green business process management (BMP) solutions. The processes implemented in the MWTP were discussed, with specific consideration of the mechanical waste processing (sorting) process, including the reuse and recycling of materials, composting, energy production (anaerobic process), landfill storage and efficiency parameters of the sorting line. A sustainable waste management system was identified; the cost as well as social and environmental perspectives were analyzed. Also, strategic goals and key performance indicators were considered. The performed analysis included costs, environmental criteria and key environmental indicators. This paper has shown the successful implementation of green BPM, with potential cost and material savings results. The findings of this case study are expected to inspire other waste management companies to adopt green BPM. The presented case study might help raise awareness and promote the implementation of green BPM in municipal plants in Eastern and Southern Europe.

Decision-Making Model in Information Technology Management of Logistics Companies

The research is devoted to developing an innovative decision-making model for automating the sorting processes of postal item sorting. In today’s environment of rapid development of logistics services and growing volumes of mail, there is a need to improve existing technologies and methods of managing sorting lines. The main goal of this study is to create an effective model that will ensure the optimisation of sorting terminals with loading points. The purpose of the research is to develop decision-making models for managing postal service lines that implement sorting logic for terminals with loading points. The research methodology is based on a systematic approach that allows us to take into account all aspects of sorting lines. The theories of finite predicate algebra and set algebra were used to create mathematical sorting models. Methods of building decision support systems and modern information technologies ensure the integration of the developed algorithms into real postal systems. The scientific novelty lies in defining and implementing a variant of the decision-making model for an automated sorting line for mail. The model implements the specified sorting logic, which makes it possible to significantly improve the efficiency and accuracy of the processes of loading and sorting mail. Conclusions. A variant of implementing the model of the decision support system for an automated sorting line of mail is proposed. The developed model makes it possible to implement the logic of sorting mail for terminals with defined loading points. This helps to increase the efficiency and reliability of postal services, reducing the likelihood of errors and ensuring timely delivery.

Fuzzy decision-making model for automatic mail sorting line

The object of this research is the implementation of fuzzy control in an automated mail sorting line. To decrease the processing time of postal items, automated sorting lines with conveyor belts are used, which carry out transportation to predefined loading points. The principal limitation of such systems is the decision-making model's inherent ambiguity when implementing the designated sorting logic. To overcome these shortcomings, a fuzzy decision-making model for automated sorting lines has been developed. This model allows implementing the sorting logic of postal items to specified loading points under predefined conditions. For this, the fuzzy classification of objects based on their parameters has been formalized, with loading points determined for each class. The fuzzy inference process stages have been formalized based on the Takagi-Sugeno-Kanga algorithm. The input and output fuzzy linguistic variables have been identified, and a rulebase for fuzzy inference has been formalized for fuzzification. For defuzzification, the center of gravity calculation for singletons has been chosen. Three criteria have been defined to implement the sorting logic, facilitated by the fuzzy inference rulebase. The first criterion sorts items to loading points considering cost evaluation, irrespective of weight and dimensions. The second criterion considers weight evaluation independent of dimensions. The third one takes into account the combined evaluation of weight and dimensions. The developed model was tested using the Matlab environment. The simulation confirmed the model's functionality and the sorting management criteria for postal items to loading points.

Algorithm of accurate cargo movement on a physical model of a sorting conveyor

Relevance. It is justified by the necessity to confirm the operability of the algorithm of accurate movement of the selected wood sorting to the corresponding storage bunker in the technological process of roundwood sorting at winter warehouses of timber processing companies to solve scientific and engineering problems both at present and in the future. Aim. To investigate the process of moving piece load on the physical model of longitudinal chain or belt conveyor, providing scaled reduction of positioning error. When sorting roundwood on chain longitudinal conveyors of considerable length, there is an error of movement of the selected roundwood sort to the place of discharge into the accumulator, which increases in proportion to the length of the sorting line. At present, conveyors of limited length are used. The accumulators are located on both sides of the conveyor. This reduces the transport error. Sometimes the sorting yard does not allow placing a short conveyor on it or there is a considerable amount of assortments. In this case, it is necessary to use a conveyor of considerable length. The paper proposes a new method of sorting roundwood on longitudinal chain conveyors of considerable length. This reduces the tracking error of the movement of the assortment. Optoelectronic sensors of angular displacements of the leading and driven shafts of the belt conveyor are used as sensors of angular displacements of the shaft. Methods. Physical modelling, information-static processing methods. Results and conclusions. The authors have carried out the analysis of the structure of the physical similarity stand of the longitudinal conveyor; sensors of the technological process, namely, angular frequency of rotation; software and hardware means of processing the obtained information to minimize the error of transporting piece cargo on the conveyor belt. The results of the study confirm the possibility of practical application of the device for operation on longitudinal conveyors.

Smart-sight: Video-based waste characterization for RDF-3 production

A material recovery facility (MRF) can transform municipal solid waste (MSW) into a valued commodity called refuse-derived fuel (RDF) as a promising solution to waste-to-energy conversion. The quality of the produced RDF significantly relies on the composition of in-feed waste and waste characterization method applied for auditing purposes, a process that is both time-consuming and fraught with potential hazards. This study focuses to enhance the workflow of the waste characterization process at an MRF. A solution named Smart Sight is proposed to detect and classify waste based on videos recorded after processing MSW through a mechanical sorting line consisting of bag breakers and trommel screens. A comprehensive dataset is created encompassing thirteen mixed waste classes from single and multi-family streams. The dataset is preprocessed with motion compensation techniques and frame differencing methods to extract and refine valuable frames. A one-stage YOLO detector model is then trained over the dataset. The experimental results show that the proposed method works efficiently at detecting and classifying waste objects in indoor MRF environments. Accuracy, precision, recall, and F1 score related to the proposed solution are found to be 0.70, 0.762, 0.69 and 0.72, respectively, with a mAP@0.5 of 0.716. The proposed approach is validated using data collected from local MRF by comparing the estimated waste composition values of the proposed solution with laboratory results obtained through current standardized industrial practices. Comparison reveals that waste characterization estimation obtained is consistent with the laboratory results, inferring that Smart-Sight is a viable tool for estimating waste composition.

Design and Implementation of an Intelligent Log Diameter Grading and Sorting Line Based on Machine Vision

In order to address the challenges posed by elevated manual labor costs and limited automation in traditional log diameter grading and sorting processes, this paper centers on the design and research of an intelligent log diameter grading and sorting line utilizing machine vision. The study focuses on logs with smaller diameters located in Fujian province, China. By analyzing production requirements, the study formulates the structure of the feeding, alignment, detection, and sorting zones to fulfill sorting functions. Using the YOLOv5 model, the system achieves accurate log end face positioning, and the diameter is computed through a designated algorithm. The operational process of the system is examined, and the control logic governing the production line is elucidated. Evaluating the practical performance of the production line, the study assesses the accuracy of diameter recognition, precision in grading, and operational efficiency. The results reveal that the absolute error in diameter detection for the sorting line averages 1.12 mm, with sorting accuracy exceeding 95%. The sorting line can automatically categorize logs with diameters ranging from 60 mm to 300 mm and lengths ranging from 2 m to 6 m, achieving an annual sorting capacity of 120,000 to 130,000 cubic meters. The research findings illustrate that the system fulfills the industry’s demands for log diameter grading and sorting, thereby enhancing economic efficiency for enterprises.

Noise source visualization of conveyor systems on the postal packaging sorting line

Noise source visualization of conveyor systems on the postal packaging sorting line

Development of a Graphic Interface Application for the Vision System of the Fruit Sorting Line

Introduction. At present, an intuitive graphical interface is an indispensable component of modern agricultural-oriented software products. Aim of the Article. The research is aimed at improving the efficiency of sorting apples by developing a graphical control interface for a vision system to recognize various defects and sort apples. Materials and Methods. The authors used methods of analysis, enumeration, comparison and synthesis of modern software solutions. Results. As a result of the research, there was created a graphical application of the software for the control unit of the machine vision system containing all the necessary tools for managing and optimizing costs when sorting apples into three commercial quality classes. Discussion and Conclusion. The graphical interface of the machine vision system was used in the line LSP-4 for sorting and packing apples. It was developed by Scientific and Practical Center NAS of Belarus for Agricultural Mechanization in 2020 and successfully passed state acceptance tests.

An FPGA-Based Hardware Low-Cost, Low-Consumption Target-Recognition and Sorting System

In autonomous driving systems, high-speed and real-time image processing, along with object recognition, are crucial technologies. This paper builds upon the research achievements in industrial item-sorting systems and proposes an object-recognition and sorting system for autonomous driving. In industrial sorting lines, goods-sorting robots often need to work at high speeds to efficiently sort large volumes of items. This poses a challenge to the robot’s real-time vision and sorting capabilities, making it both practical and economically viable to implement a real-time and low-cost sorting system in a real-world industrial sorting line. Existing sorting systems have limitations such as high cost, high computing resource consumption, and high power consumption. These issues mean that existing sorting systems are typically used only in large industrial plants. In this paper, we design a high-speed, low-cost, low-resource-consumption FPGA (Field-Programmable Gate Array)-based item-sorting system that achieves similar performance to current mainstream sorting systems but at a lower cost and consumption. The recognition component employs a morphological-recognition method, which segments the image using a frame difference algorithm and then extracts the color and shape features of the items. To handle sorting, a six-degrees-of-freedom robotic arm is introduced into the sorting segment. The improved cubic B-spline interpolation algorithm is employed to plan the motion trajectory and consequently control the robotic arm to execute the corresponding actions. Through a series of experiments, this system achieves an average recognition delay of 25.26 ms, ensures smooth operation of the gripping motion trajectory, minimizes resource consumption, and reduces implementation costs.

Industrial automation and robotics in AAC industry: Selected models and case studies

AbstractAs the global manufacturing industry entered its fourth revolution (4IR, or Industry 4.0), innovations such as robotics, automation, and artificial intelligence are set to take over and improving the global industries. As the number of active industrial robots worldwide is increasing every day in different applications and industries automation continues to create new types of robots with improved utility and function. In the AAC Industry, these innovations already took place for some time in different process phases and applications such as oiling, autoclaves stacking pins, handling, packing, and so forth. Through this research, advantages commonly attributed to automation and robotics include higher production rates and increased productivity, more efficient use of materials, better product quality, improved safety, shorter workweeks for labor, and reduced factory lead times. Especially reduced scrap and waste through improved accuracy, increased efficiency, and operation around the clock could be emphasized. Based on the accumulated experience of WKB Systems GmbH in the field of the forging industry, selected models, real‐life application case studies, and implementation of different robotics in the AAC industry are discussed in this paper. These examples such as linear robots for autoclaves stacking pins, articulated robots for AAC packing and sorting line, and hybrid systems for handling and packing AAC insulation boards are studied in detail.

Removal of undissolved substances in the dissolution-based recycling of polystyrene waste by applying filtration and centrifugation

Polystyrene (PS) is a versatile polymer typically used in applications such as yogurt cups, packaging trays, disk cases and toys. To increase recycling rates of PS, dissolution recycling is being investigated, which involves the liquefication of the polymer in a suitable solvent, allowing deep cleaning of the polymer from impurities. Quite specific to PS is that polystyrene waste contains both general-purpose polystyrene and high-impact polystyrene (HIPS), which is composed of free PS and polystyrene-grafted polybutadiene particles. In this work the potential of filtration and centrifugation is analyzed with the aim of cleaning the polymer from both, insoluble PB-PS particles and pigments (TiO2, Cr/Sb/Ti oxide and carbon black). The dead-end lab scale filtration were performed at room temperature and at pressures between 1.5 and 30 bar. The pigments were successfully removed, yet, filtration of HIPS solutions results in low fluxes due to extreme membrane fouling caused by the PB-PS particles, which was confirmed by the application of pore-blockage filtration models. Alternatively, centrifugation at 14,052 G-force has shown to be a promising alternative to separate the particles from HIPS, resulting in 100% turbidity reduction. Equally, the separation of pigments was successful, highlighting that TiO2 and Cr/Sb/Ti oxide have shorter sedimentation times compared to carbon black. Finally, the two separation processes are tested on a PS rigid packaging waste sample coming from a sorting line and the results show that centrifugation allows a high turbidity reduction and that a two-step separation process starting with centrifugation for PB-PS particles removal can facilitate further downstream cleaning.

Towards circular plastics: Density and MFR prediction of PE with IR spectroscopic techniques

The high variety of tailor fitted molecular structures of polyethylene (PE) is very beneficial to fulfill requirements of various applications, however it poses a difficulty in the mechanical recycling of post-consumer PE products. To improve the quality of PE recyclates and increase the amounts of recyclates that can be used in new products, separation of PE waste by density and melt flow rate (MFR) during mechanical sorting is essential. Therefore, 25 virgin PE grades were used to manufacture compression molded plates that were then characterized by means of Attenuated Total Reflection - Fourier transformed IR (ATR-FTIR) and near IR (NIR) spectroscopy, NIR hyperspectral imaging and dual-comb spectroscopy. The results were used to build partial least squares regression (PLS) models to predict MFR and density. ATR-FTIR and laboratory NIR spectroscopy provided sufficient information to predict the density value of PE, whereas the MFR assessments was not possible. The PLS model from the industrial NIR data also only allowed the density-based classification of virgin PE grades. The PLS models built from transmission and reflectance dual comb spectroscopy infrared (DCS-IR) of selected samples clearly showed that density and MFR prediction can be carried out with high accuracy. As DCS-IR could be implemented on plastic sorting systems using a conveyor belt, the addition of this sensor in mechanical sorting line would lead to a significantly higher quality of recycled PE with narrow well-defined density and MFR ranges. Such an improvement would immensely support the targeted recycling rates and amount by the European Union and would make a significant step towards circular plastics.

An energy-efficient classification system for peach ripeness using YOLOv4 and flexible piezoelectric sensor

Peach is a kind of popular fruit with significant economic value, but it is commonly sorted through manual labor on sorting lines, which can negatively affect the economic efficiency. To address this issue, this paper proposes a system for classifying different ripeness of peaches based on their visual and tactile characteristics. This system consists of two stages. The first stage utilizes YOLOv4 as the core model for preliminary visual-based classification of fruit ripeness. The second stage proposes a method centered on flexible piezoelectric sensors to more deeply classify the fruit ripeness based on tactile characteristics. The system classifies peaches into five categories (A1, A2, B1, B2, and R), which can be applied to the peach sorting line. The mAP and meanIoU are used as evaluation parameters for the visual part and TPA test is used to validate the accuracy of the tactile part. The results of the experiments show that mAP value reaches 0.9304, meanIoU reaches 0.9454, and the accuracy of the tactile part reaches 92.22%. The results indicate that visual and tactile characteristics can accurately classify peach ripeness using YOLOv4 and flexible piezoelectric sensor. The proposed system completes the entire classification with lower cost and less power consumption, providing potential ways to increase productivity and automate the sorting line.

Assessing the Sorting Efficiency of Plastic Packaging Waste in an Italian Material Recovery Facility: Current and Upgraded Configuration

The first step in reintroducing plastic waste into the recycling cycle is to use material recovery facilities (MRFs). However, while the composition and types of plastic waste are changing over time, the layout of MRFs does not always adapt to this change. In this paper, an existing MRF in Southern Italy was chosen as a reference to evaluate its current performance and to estimate possible improvements in sorting through a specific upgrade. First, an analysis of the amount, composition, and sources (in terms of type of waste and distance from the MRF) of the input waste was conducted. The composition of the input waste was then compared with the amount of selected output waste streams in order to calculate the current sorting efficiency of each stream and compare it with the values obtained from the upgrade. Lastly, the current performance of the plant was compared with a previous assessment of the same MRF in order to highlight possible variation. Results showed how the incoming waste was mainly composed of packaging plastic waste, and that some plastic waste not yet selected by the plant ended up in specific output streams. Therefore, the current performance of the MRF resulted high for PET and PE bottles (80.2% and 92.8%, respectively), in contrast to mixed or flexible packaging, where the efficiency achieved lower values (55–50%). These values were caused by a weakness in the 2D flow sorting line, which the upgrade mostly addressed. The upgraded configuration increased the production of recyclable waste from 34.32% to 50.39%, especially due to the recovery of small flexible packaging films in PE and biopolymers.

Development of a mathematical model of the process of sorting municipal solid waste using elements of similarity of technical systems

The article studies the similarity of ensuring the technical condition of the solid municipal waste sorting line system. The functional dependence of the productivity of the waste sorting line is given, partial expressions and numerical values of the criteria for similarity of the functioning of the sorting process are obtained. A generalized criterion of similarity of the state of the solid municipal waste sorting process is also obtained, the nature of the influence of the parameters of functional dependence on the value of the output characteristic is investigated.

Design of Accurate Association System of QR Code Information for Cigarette Sorting

This study employs the EIQ analysis approach to quantitatively examine the real order data of the cigarette distribution center in an effort to further increase the efficiency of cigarette sorting and distribution. To further increase the accuracy and efficiency of sorting labor, a sorting system based on QR code information and an accurate identification algorithm is proposed with the use of statistical data and the associated planning scheme. According to the system simulation findings, the sorting efficiency of the system’s sorting line is 18570 pieces per hour. However, by adding packing equipment, the efficiency of the system can be raised by 61.55 percent and can reach 30000 pieces per hour. Additionally, it confirms the viability of the system design. The two-dimensional code’ properties determine which global threshold method the binarization algorithm chooses. The two-dimensional code’ coding principle is investigated, and a two-dimensional code decoding algorithm is developed. The results of the experiment indicate that the decoding algorithm can fulfill these requirements.

Methods of Wood Volume Determining and Its Implications for Forest Transport.

Proper measurements are extremely significant for the forest owner, the harvesting company, the hauler, the final buyer, and the wood processing company. The accuracy of round wood volume determination is of fundamental importance in planning and accounting for individual processes related to the wood trade. It is the basis for determining the maximum quantity in single load of wood that allows for using the permissible total gross vehicle weight. The determination of wood load in cubic meters does not allow unequivocally determining its weight, which often leads to overloading of vehicles. This paper presents a comparison of the photo-optical method for determining the volume of wood to be transported with the real measurement and determination of the weight of a load and the total gross vehicle weight (GVW) with the simultaneous application of conversion factors determining the weight of the load from the volume of wood. The measurement included 23 broadleaf round wood piles (193.73 m3) and 14 coniferous round wood piles (149.23 m3). The measurement error for broadleaf wood piles ranges from −47.67% to 63.16%, and from −43.31% to 24.72% for coniferous wood piles. Determination of the volume of a broadleaf wood pile using the iFOVEA method had an average error of 1.34%, while the Timbeter method had an average error of −1.83%. In the coniferous wood pile measurement, the error is −12.82% and 2.41%, respectively. Verification of the volume of the large-sized wood indicated on the delivery note (reference value) on the log sorting line (by laser scanning) showed larger volumes by 0.10 m3 to 2.54 m3, giving a percentage error of 0.35% and 8.62%, respectively. As a consequence of the application of such methods for determining the weight of wood loads, the transport truck sets are often significantly overloaded, which has a significant impact on the accelerated degradation of roads and safety in traffic and timber transportation.

Detection of internal defects in onion bulbs by means of single-point and scanning laser Doppler vibrometry

The number of onion consignments which are rejected or downgraded due to the incidence of internal defects is a continuing problem for wholesalers and growers. Defects may only be up to 4% incidence level, but result in the entire lot being lost for sale. Destructive quality control testing causes waste, so that there is a need for alternative non-invasive assessment. The aim of the current research was to demonstrate whether internal defects could be detected using Laser Doppler vibrometry (LDV). Several trials, with different types of sensors and levels of onion defect severity were conducted. Both scanning and single-point LDV were employed in order to develop a suitable measurement method to evaluate onion defects. It was necessary to measure resonant frequency at the neck or equator of the bulbs in order to segregate neck rot ( Botrytis allii ) or bacterial rot, respectively, but LDV could not differentiate sprouting and double hearted bulbs from sound onions. In conclusion, it was possible to non-destructively identify onion bulbs with only a 5% area affected with neck rot (visible after cutting). It would be necessary to calibrate for different onion cultivars and origins, if the technique is to be implemented on a commercial sorting line. • Laser Doppler vibrometry is capable of non-destructively identifying neck rot in onion. • Non-invasive laser Doppler vibrometry measures internal defects in onion.