Processing Line Research Articles

EROSION OF TUBULAR HEAT EXCHANGERS

This paper presents the results of an erosion study of a tubular heat exchanger operating on a railroad sleepersaturation processing line. The object of the study is a DN 800 oil condenser cooling the creosote oil vaporsflowing through the condenser tubes, fixed in the sieve plate of the upper and lower condenser bottom.Subject to the erosion are the upper part of the tubes and the weld connecting the tubes to the upper sieveplate. This resulted in unsealing of the connection, which led to the contamination of the cooling medium.The key problem, therefore, is to protect the entire condenser bottom from erosion. Since only the centralpart of the surface of the top sieve plate was eroded, the conclusion is that the velocity of the vapor streamover the inlet to the condenser tubes in the central part and beyond is varied. This thesis was confirmed bythe correspondence of the actual eroded area with the cavitation area resulting from a simulated flow inAutodesk CFD 2019 Ultimate software after increasing the height of the upper condenser bottom, placinga stream dispersing element between the liquid vapor inlet to the condenser and the upper sieve plate, andafter applying a protective sieve plate. Flow simulation studies for each of these variants, or a combinationof them, made it possible to evaluate the tested solutions in terms of protection against erosion, includingcavitation erosion, of the upper sieve plate of the condenser.

Abnormal Monitoring Data Detection Based on Matrix Manipulation and the Cuckoo Search Algorithm

Structural health monitoring is an effective method to evaluate the safety status of dams. Measurement error is an important factor which affects the accuracy of monitoring data modeling. Processing the abnormal monitoring data before data analysis is a necessary step to ensure the reliability of the analysis. In this paper, we proposed a method to process the abnormal dam displacement monitoring data on the basis of matrix manipulation and Cuckoo Search algorithm. We first generate a scatter plot of the monitoring data and exported the matrix of the image. The scatter plot of monitoring data includes isolate outliers, clusters of outliers, and clusters of normal points. The gray scales of isolated outliers are reduced using Gaussian blur. Then, the isolated outliers are eliminated using Ostu binarization. We then use the Cuckoo Search algorithm to distinguish the clusters of outliers and clusters of normal points to identify the process line. To evaluate the performance of the proposed data processing method, we also fitted the data processed by the proposed method and by the commonly used 3-σ method using a regression model, respectively. Results indicate that the proposed method has a better performance in abnormal detection compared with the 3-σ method.

On-machine measurement and compensation of thin-walled surface

On-machine measurement technology is considered as a key technology for realizing closed-loop feedback control in intelligent manufacturing due to the reduction of the transfer process. However, the complexity of the machine tool process system introduces some uncertainty into the accuracy of on-machine measurement, which severely limits the application in the actual industrial field. To overcome the shortcomings of the existing uncertainty, an inspection framework for on-machine measurement of thin-walled surface is proposed. Firstly, a low-cost wireless on-machine measurement system based on potential signals is established and integrated into a manufacturing process line for automatic sampling. Then, the similarity of momentum conservation is introduced into sampling planning, and an adaptive sampling model based on momentum conservation and multi-objective particle swarm optimizer is proposed. Finally, a stacked deep learning model under the vertical inspection direction is proposed to improve the inspection accuracy by correcting the sampling data. Compared with existing sampling methods, the proposed model is similar to an attention mechanism that enables adaptive enhancement of profile features. The inspection performance by data correction is improved by about 16.14% in the mean inspection error. Simulations and experiments show that the proposed method has great advantages in terms of efficiency and robustness, which can provide a theoretical reference for adaptive toolpath correction for thin-walled surfaces.

Design of Yellow Peach Quality Identification System Based on PlC and Machine Vision

China is the main producer and exporter of canned fruit, leading the world inhe processing and consumption of canned fruits. Most of the fruit can processing lines are semi-automated, while the fruit quality is mostly identified by naked eye and thus needs to be automatically identified again before the sealing of the cans on the production line for prevention of inferior pulp from entering the canned bottles. Based on this, this paper designs a fruit quality identification system for PLC canned yellow peach production line based on machine vision taking canned yellow peaches as an example, and analyzes the difficulties in identifying the control of sub-packaging. Software programming and hardware design were carried out for the visual inspection of canned yellow peaches, and the simulation and implementation of the system were completed. This system reduces labor costs, improves the production environment, and provides favorable solutions to the construction of semi-automated production workshops that meet the needs of enterprise development. Its promotion is of significant value.

Active Dual Line-Laser Scanning for Depth Imaging of Piled Agricultural Commodities for Itemized Processing Lines.

The accurate depth imaging of piled products provides essential perception for the automated selection of individual objects that require itemized food processing, such as fish, crabs, or fruit. Traditional depth imaging techniques, such as Time-of-Flight and stereoscopy, lack the necessary depth resolution for imaging small items, such as food commodities. Although structured light methods such as laser triangulation have high depth resolution, they depend on conveyor motion for depth scanning. This manuscript introduces an active dual line-laser scanning system for depth imaging static piled items, such as a pile of crabs on a table, eliminating the need for conveyor motion to generate high-resolution 3D images. This advancement benefits robotic perception for loading individual items from a pile for itemized food processing. Leveraging a unique geometrical configuration and laser redundancy, the dual-laser strategy overcomes occlusions while reconstructing a large field of view (FOV) from a long working distance. We achieved a depth reconstruction MSE of 0.3 mm and an STD of 0.5 mm on a symmetrical pyramid stage. The proposed system demonstrates that laser scanners can produce depth maps of complex items, such as piled Chesapeake Blue Crab and White Button mushrooms. This technology enables 3D perception for automated processing lines and offers broad applicability for quality inspection, sorting, and handling of piled products.

Assembly of pig slaughter and processing lines according to foreign patterns. Part 1

Assembly of pig slaughter and processing lines according to foreign patterns. Part 1

Continuous direct compression of a commercially batch-manufactured tablet formulation with two different processing lines

The transfer from batch-based to continuous tablet manufacturing increases the quality and efficiency of processes. Nonetheless, as in the development of a batch process, the continuous process design requires optimization studies to ensure a robust process. In this study, processing of a commercially batch-manufactured tablet product was tested with two continuous direct compression lines while keeping the original formulation composition and tablet quality requirements. Tableting runs were conducted with different values of process parameters. Changes in parameter settings were found to cause differences in tablet properties. Most of these quality properties could be controlled and maintained within the set limits effortlessly already at this stage of studies. However, the API content and content uniformity seemed to require more investigation. The observed content uniformity challenges were traced to individual tablets with a high amount of API. This was suspected to be caused by API micro-agglomerates since tablet weight variability did not explain the issue. This could be solved by adding a mill between two blenders in the process line. Overall, this case study produced promising results with both tested manufacturing lines since many tablet properties complied with the test result limits without optimization of process parameter settings.

A versatile setup for nanosecond laser polishing processes with in situ analysis capabilities.

Laser polishing of material surfaces is a complex process depending on many variable parameters, such as, e.g., the properties of the used laser and optics (wavelength, pulse duration, fluence, and profile), as well as the processing (spot size, feed rate, and line or point overlap), and the thermodynamical properties of the material to be polished (heat capacity, heat conduction, etc.). For the successful laser polishing of any material, a systematic variation of all the process parameters is required to obtain satisfactorily polished surfaces with an appropriate set of parameters for the material of interest. In order to allow systematic studies of laser polishing processes, a new setup employing a highly stable nanosecond laser with an adjustable wavelength has been realized. The sample is located in a small high-vacuum chamber with the capability of introducing additional gases in a controlled manner, and the entire chamber is scanned in the beam to allow laser polishing of selected spots, lines, or larger areas. The setup is fully remote-controlled and allows in situ inspection of the initiated processes by means of a long-range microscope, electrical measurements, reflected laser light from the sample surface, and an analysis of the vacuum within the process chamber. The main properties of the setup will be presented, and some exemplary results on niobium and molybdenum metal samples will be discussed.

Production increase of high-grade crude zinc oxide pellets at Shisaka Smelting Co., Ltd.

Shisaka Smelting Co., Ltd. has recovered crude zinc oxide pellets from an electric arc furnace dust (EAF dust) by the Waelz kiln process since 1977. The EAF dust processing line consists of a reduction roasting process, a Waelz oxide washing process, and a drying/calcination process. In late years, about 90,000 tons of EAF dust is processed annually at Shisaka. The recovered zinc is sold to zinc smelters as crude zinc oxide pellets, and the amount of production of the pellets is about 40,000 tons per year. Two types of zinc oxide pellets are produced, and the product for electro-refinery requires high quality, especially in fluorine reduction. Most of fluorine are distributed to the clinker in a reduction roasting process, and others are distributed to the Waelz oxide. Conventionally, high-grade crude zinc oxide pellets were produced by washing the Waelz oxide and by volatilizing and separating fluorine under high temperature operation in a drying rotary kiln. However, formation of accretion in the kiln and damage of the shell and refractories of the kiln often occurred under the influence of high temperature operation, and stable consecutive operation of the kiln was difficult.To improve this situation, the fluorine input was reduced by compounding management of EAF dust in the reduction roasting process, and the material residence time in the drying rotary kiln was extended by reducing rotary speed. These improvements resulted in stable consecutive operation under low temperature conditions and increased production of high-grade crude zinc oxide pellets. To improve this situation, the fluorine input was reduced by compounding management of EAF dust in the reduction roasting process, and the material residence time in the drying rotary kiln was extended by reducing rotary speed. These improvements resulted in stable consecutive operation under low temperature conditions and increased production of high-grade crude zinc oxide pellets.

워터젯 로봇의 가공 전용 치구 제작 공정 개선 및 평가에 관한 연구

Water-jet robots find application across various domains, including cutting, cleaning, and drilling diverse materials. Recently, they have been integrated into automated process lines for manufacturing automobile interior components. Consequently, with the advancement of water-jet robot processing technology, a dedicated fixture is required to support the product shape for processing complex-shaped automobile interiors. The existing water-jet processing fixtures were produced through a wet lay-up process using glass fiber to reduce manufacturing costs; however, recently, water-jet fixtures employed in automated lines have experienced deformation over prolonged usage, resulting in shape-processing errors and an increased the defect rate. Therefore, this study explores the use of carbon fiber and the VARTM vacuum bagging process to enhance the quality of water-jet dedicated fixtures, refine the manufacturing process, alleviate shape strain, and bolster the structural integrity of the fixtures compared to the conventional wet lay-up method typically employed for composite fixtures. A study was conducted on.

Computational substantiation of technological characteristics of the closure stage of nuclear fuel cycle using code VIZART

There exist different variants of organizing the closure of nuclear fuel cycle (CNFC) depending on fast reactor type, fuel types, station or centralized allocation of closed nuclear fuel cycle stages. One of the ways to verify and estimate engineering solution is mathematical modeling of radiochemical technology which in the end will allow to optimize composite technological process in order to increase effectiveness and reduce cost. In order to calculate the balance of material flows of process circuits and individual production sections in the stationary and dynamic modes, with taking into account the isotopic composition evolution, a software package VIZART (Virtual Plant of Radiochemical Technologies) was developed, allowing the user to assemble the required sequence of operations for any part of the process scheme and perform the calculation of material balance for all flows of the circuit, as well as to optimize the equipment operating modes and provide the necessary data to justify the safety of certain limits and the entire process circuit. The following capabilities of code VIZART for computational substantiation of CNFC technology design and characteristics are considered: material balance calculation, cyclogram creation, determination of the most loaded parts of processing lines, estimation of fissile materials accumulating in devices and intermediate vessels, optimization of productivity of nodes and devices.

Ventilation and air conditioning design approach based on ASHRAE psychrometric chart and Mollier diagram

Society needs long-term sustainability and healthy building projects, and indoor air quality assurance engineering systems play a pivotal role in the energy performance of buildings. Therefore, when designing heating, ventilation, and air conditioning systems, it is crucial to make the most technically sound decisions in terms of energy consumption and assess their impact on the building’s energy performance. This article delves into the design of ventilation and air conditioning systems, presenting a method for evaluating their performance. The foundation of project development is an agreement on the design criteria, which are developed based on a preliminary analysis of the building concept. This agreement ensures cohesive collaboration among all stakeholders: the client, the architect, the system designer, the contractor, and ultimately the personnel responsible for commissioning, operating, and maintaining the systems post-construction. We suggest conducting a comprehensive analysis of the processes occurring within the space without initially linking them to room air exchange. From this analysis, we derive the angular coefficient for the direction of the air condition change on both a psychrometric chart and a Mollier diagram. The process line on the psychrometric chart provides insights into how the performance factor of the air distribution system will influence the desired supply air parameters. We can then evaluate how significantly the gap between the supply air and the exhaust air parameters expands if the room’s air exchange volume is reduced for budgetary reasons. The article showcases this design methodology using a simplified case study.

Pathogenic potential of meat-borne coagulase negative staphylococci strains from slaughterhouse to fork.

This study aimed to determine the prevalence of coagulase-negative staphylococci (CoNS) in meat processing lines for their pathogenic potential associated with biofilm formation, staphylococcal toxin genes, and antibiotic resistance in obtained isolates. Out of 270 samples, 56 isolates were identified as staphylococcal with their species level, and their antimicrobial resistance profiles were also determined with the BD Phoenix™ system. Among these, CoNS were found in 32 isolates, including S. epidermidis (22%), S. warneri (22%), S. cohnii (9%), S. schleiferi (9%), S. capitis (6%), S. haemolyticus (6%), S. lugdunensis (6%), S. chromogenes (6%), S. kloosii (3%), S. sciuri (3%), S. lentus (3%), and S. caprae (3%). Biofilm formation was observed in 78.1% of CoNS isolates, with 56% being strong biofilm producers; and the frequency of the icaA, fnbA, and fnbB genes were 43.7% and 34.3%, and 9.3% in isolates, respectively. Twenty-five (78.1%) of these strains were resistant to at least one antimicrobial agent, 20 (80%) of which exhibited multidrug resistance (MDR). Regarding genotypic analyses, 15.6%, 22.2%, 87.5%, and 9% of isolates, were positive for blaZ, ermC, tetK, and aacA-aphD, respectively. In 8 (25%) of all isolates had one or more staphylococcal toxin genes: the sed gene was the most frequent (12.5%), followed by eta (9.3%), tst-1 (6.25%), and sea (3.1%). In conclusion, this study highlights meat; and meat products might be reservoirs for the biofilm-producing MDR-CoNS, which harbored several toxin genes. Hence, it should not be ignored that CoNS may be related to foodborne outbreaks.

Synergistic control potential of flue gas pollutants under Ultra-Low emission standards in waste incineration plants

As the dominant waste disposal process, incineration is regarded as the main incentive for the “not-in-my-backyard” syndrome, and faces an inescapable pressures of ultra-low emissions (ULE). Establishing precise response relationships between emission factors (EFs) and full-process influencing factors can provide guidance for the synergistic mitigation of flue gas pollutants (FGPs). In this work, the multi-dimensional EFs of FGPs were identified by initially integrating FGPs concentration monitoring data of existing 1,226 processing lines in China, technologies applied and operational experience (OE), local economic and political characteristics. Significant regional imbalance performance was observed, which EFs in the coastal regions were 3.55–92.39 % lower than those of the inland areas. NOx, SO2, HCl were identified as critical components requiring further reduction under the ULE standards, with exceedance rates recorded at 73.07 %, 38.90 %, and 56.69 %, respectively. An indicative value of 20 mg/m3 for PM is recommended for the control of heavy metals of Cd + Tl and Sb + As + Pb + Cr + Co + Cu + Mn + Ni based on the correlation coefficients of r = 0.28 (p < 0.001) and r = 0.20 (p = 0.002), respectively. Waste composition and OE were quantified as the main contributors of EFs’ disparities by the tree-branching controlled variable approach established in this study. Predictive models for FGPs control process and corresponding EFs were constructed. EFs of nine FGPs in 2030 would decrease by 0.97–65.42 %, due to more complex purification processes employed to meet ULE’s limitations, such as the application of five-stage processes growing from 45.60 % to 58.28 %. While regional imbalance in EFs-SO2 and EFs-HCl were extended with increases from 25.83 % to 33.07 % and 9.91 % to 32.32 %, respectively, due to the consistent disparities of OE and growing heterogeneity of control policies. Enhancing interregional empirical exchanges, reducing the regional market monopolies, and formulating technical guidelines would be beneficial to synergize the reduction of FGPs emissions and alleviate regional imbalance.

Colorimetric analysis platform based on thin layer chromatography for monitoring gluten cross-contamination in food industry

Monitoring of the accidental presence of gluten (Glu), resulting from cross-contamination, is imperative in different industries, in particular food industry. The objective of this study was the development of an analytical platform utilizing thin-layer chromatography (TLC) with colorimetric read-out for making binary (yes/no) decisions on surfaces and/or point of these industries. The composition of the extractive phase was optimized with commercial products used in cleaning processing lines. Subsequently, an exploration of TLC separation and detection was undertaken. CN-modified nanosilica plates and 30:70 acetonitrile:water were used to achieve a selective signal for Glu residues. The study of the detection performance showed that both spectroscopic measurement and image analysis were resulted in satisfactory results for quantitate analysis (RSD = 5 %, LOD = 0.12 mg). The practical application of the proposed methodology on surfaces of the food processing lines. This work demonstrated the operational feasibility in detecting gluten cross-contaminations within the food processing industry.

A novel method to build knowledge graph models for the configuration and operation design of smart and connected industrial products

Abstract Smart and connected industrial products (SCIPs), characterized by their capabilities of self-monitoring, environment awareness, machine–machine/machine–human communication and collaboration, intelligent decision-making, etc., have become the fundamental elements for cyber-physical systems, digital twin, industrial internet of things, etc. Configuring the components in SCIPs and modeling their interaction and operation mechanisms are important during SCIPs design. However, existing product design methods were originally developed for none smart and connected products. This could limit the accuracy of SCIP modeling during the design stage and consequently, it may cause more reworks during the implementation stage of the designed SCIPs. In this regard, a SCIP configuration and operation design method is established, including (i) meta knowledge graph (KG)-based configuration of the components in the physical system and status monitoring system of a required SCIP, (ii) event-state swimlane flowchart-based analysis of the dynamic interaction, operation, and data monitoring mechanisms among the components, and (iii) event-state KG based modeling of the overall workflow, monitoring data self-updating and intelligent operation mechanisms of the SCIP. Compared with existing SCIP design methods, the work provides a specific method for not only the configuration of the static components in customized SCIPs, but also the dynamic interaction, data acquisition/storing/transmitting, and intelligent function implementation mechanisms of the configured SCIP using a kind of event-state KG. The event-state KG is both human-readable and computer-programmable, and it can self-update according to predefined reasoning algorithms during the operation of the SCIP. The configuration and operation design modeling of a robot-based grinding processing line is used as a case study.

Chemical conditioning of aerobically digested sludge using polyelectrolytes with different charge densities

This research was carried out to evaluate the effects of different dosages (1.85–4.44 g kg−1 Ts−1) of three cationic polyelectrolytes with charge densities (CD) of 20%, 40%, and 60% on the dewatering properties of an aerobically digested sludge. The sludge was collected from the sludge processing line in a wastewater treatment plant in the city of Mashhad, Iran (MWWTP). To assess the sludge dewatering properties, parameters such as specific resistance to filtration, sludge cluster geometry, filtration rate, and filtrate turbidity and volume were measured. The experimental results were then compared with the effects of a reference polyelectrolyte that was used in the conditioning of the sludge in that treatment plant. The results indicated that the sludge samples treated with the polyelectrolyte of the highest CD matched better dewatering performance than the samples conditioned with the other two polyelectrolytes. This polyelectrolyte (60%CD) presented its best effects at the dosage of 4.07 g kg−1 Ts−1. With this dosage, its performance was similar to the performance of the reference polyelectrolyte at the dosage of 4.44 g kg−1 Ts−1.

Designing an Industrial Product Service System for Robot-Driven Sanding Processing Line: A Reinforcement Learning Based Approach

The Industrial Product Service System (IPS2) is considered a sustainable and efficient business model, which has been gradually popularized in manufacturing fields since it can reduce costs and satisfy customization. However, a comprehensive design method for IPS2 is absent, particularly in terms of requirement perception, resource allocation, and service activity arrangement of specific industrial fields. Meanwhile, the planning and scheduling of multiple parallel service activities throughout the delivery of IPS2 are also in urgent need of resolution. This paper proposes a method containing service order design, service resource configuration, and service flow modeling to establish an IPS2 for robot-driven sanding processing lines. In addition, we adopt the modified Deep Q-network (DQN) to realize a scheduling scheme aimed at minimizing the total tardiness of multiple parallel service flows. Finally, our industrial case study validates the effectiveness of our methods for IPS2 design, demonstrating that the modified deep reinforcement learning algorithm reliably generates robust scheduling schemes.

Si/SiO2 silicon-on-insulator based scaffold for interfacing with cerebral organoids

Cerebral organoids are hSPC derived tissue complexes that self-organize over an extended period and begin to recapitulate certain features of in vivo neurogenesis, and there is a need to develop tools that allow for the physical and electrical interrogation of these cell complexes as they mature. Presented here is a method of manufacturing thin, porous, scalable silicon scaffolds as a structure to support multi-electrode arrays using industry standard semiconductor fabrication techniques. Mechanical tests by nanoindentation demonstrate the scaffold as linearly elastic with an approximated effective stiffness of 51.6 MPa. Biological cell studies indicate that mature Cerebral Organoids are capable of cellular expansion through, and partially absorbing, the scaffold, with 0.125 mm3 ± 0.027 of new tissue generation over a 5-day culture period. The structure is designed for compatibility with front end of line and back end of line semiconductor processes for future integration with metal electrodes, which enables deep tissue access in multi-cellular structures.

Process implications on the stability and reliability of 300 mm FAB MoS2 field-effect transistors

Recent advances in fabricating field-effect transistors with MoS2 and other related two-dimensional (2D) semiconductors have inspired the industry to begin with the integration of these emerging technologies into FAB-compatible process flows. Just like in the lab research on 2D devices performed in the last decade, focus during development is typically put on pure technology-related issues, such as low-temperature growth methods of large-area 2D films on target substrates, damage-free transfer from sacrificial substrates and growth of top-gate oxides. With maturing technology, the problem of stability limitations caused by oxide traps is gradually coming into focus now. Thus, here we report an in-depth analysis of hysteresis and bias-temperature instabilities for MoS2 FETs fabricated using a 300 mm FAB-compatible process. By performing a comprehensive statistical analysis on devices with top gate lengths ranging between 18 nm and 10 μm, we demonstrate that aggressive scaling results in additional stability problems, likely caused by defective edges of the scaled top gates, in particular at higher operation temperatures. These are important insights for understanding and addressing the stability limitations in future nanoscale 2D FETs produced using FAB process lines.