Set Of Technological Parameters Research Articles

Possibility Assessment of Automatic Formation of Technological Processes in Small Batch Production

The work is devoted to urgent problem solution of lack of convenient tools with functional capabilities of the system of route technological process automated design, adapted to small-scale production. The estimation of potential possibility of automatic small-scale production formation by means of estimation of efficiency and expediency technological processes of automation of key stages of design of production technological preparation, such as equipment selection, selection of cutting modes, workpiece, cutting and measuring tools and tooling selection is given. The key stages of technological process development are considered and characterized, such as selection of technological bases, type of workpiece and equipment, formation of route technological process, calculation of cutting modes, selection of allowances and so on. The paper shows both the relevance and necessity of analyzing approaches to automation and their correct adaptation to production needs to achieve maximum efficiency and resource savings for small batch production, and the high relevance for small-batch production of the automatic formation of route technological processes. At the same time, the paper shows the lack of automated systems adapted to the specifics of small-batch production. The existing approaches to the formation of stages are analyzed, as well as the possible methods of automation of stages and the existing limitations of these methods are considered, the efficiency of the considered approaches is evaluated. The methods of automation of separate stages of technological preparation of production are analyzed and the efficiency of the considered approaches is evaluated. The original concept of solving the problem of automation for small-scale production by using a combination of a limited number of standard solutions, represented as a set of technological parameters or knowledge base, with individual solutions, adapted to the specifics of enterprises and industry, is proposed and the potential effectiveness of this approach is shown.

Нейросетевая модель для определения регламентных параметров технологического процесса переработки рудного сырья

Machine learning methods are currently widely used to solve various production problems, the problems of defects diagnosing and predicting for items in mass production, in particular. One of the most important problems is defects diagnosing and predicting, basing on its solution the regulations for the technological processes parameters and raw materials used can be determined, that insures the minimum probability of defects and the highest possible quality of manufactured products. The solution of this urgent problem with the help of a neural network model is shown on the example of the technological process for manufacturing products from fine ore material. The proposed model is based on the neural network trained on the set of historical data including examples of manufacturing products with different sets of technological parameters and raw ore material. The predicted parameter is warping of the product in one of its sections. Designing and training of the proposed neural network structure allowed achieving the coefficient of determination R2 between the predicted and actual warpage values of 92%. The dependences for the warpage value on the most significant parameters of the technological process, including thermophysical and chemical power technological processes of raw materials processing were constructed by conducting computer experiments using the method of partial freezing for input parameters. Due to these dependencies, the regulations for the most significant parameters of the production process are determined, which ensures the product to be without violating the tolerance for the warpage value specified by the design documentation. Thus, a specific example shows the possibility of using neural network modeling to solve the problem of setting regulations for the production process parameters, which compliance ensures the minimum amount of rejects and, accordingly, a higher quality of a production batch.

Design and Manufacturing of Feeding System to Improve Accuracy and Surface Roughness of FDM Products

Fused Deposition Modeling, a great potential technology, has been increasingly applied in various industries as rapid prototyping for testing, casting prototyping and final products manufacturing. This widely usage comes with high products accuracy requirements. Currently, industrial 3D printers are very high in price that open-source low cost printers are the most suitable for hobbyist and researchers in the world. Therefore, research to improve product quality for low-cost 3D printers to serve industrial demand is greatly necessary. Realizing that in FDM technology, the feeding method is one of the important issues that determine the accuracy of printed products. The problem to be studied here is to design and manufacture a filament feeding system for a low-cost 3D printer and find out an optimal set of parameters for the fabricated feeder. This paper analyzes the feeding systems for 3D printers that have been used on the market, thereby offering a design and manufacturing feeder for the low-cost 3D printer. Then, experiments with Polylactic Acid (PLA) filament will be taken to check the accuracy of printed products and figure out the optimal set of technological parameters for the 3D printing process. Thereby improving product quality and shortening printing time. Continue to research and perfect the design can help commercialize low-cost 3D printers and stimulate research as well as 3D printing in industries.

Design and Research Sowing Devices for Aerial Sowing of Forest Seeds with UAVs

Modern unmanned aerial vehicles (UAV) can be effectively used for aerial sowing of forests. A feature of aerial sowing is the possibility of rapid reforestation at low costs, which is extremely important in the current environmental situation. The purpose of this study is to develop a set of sowing devices intended for use with UAVs. For this, the metering devices and seed distribution devices were analyzed, used on the UAV or having prospects for such use. The existing studies of metering devices, implemented by numerical methods, are analyzed. Further, the synthesis of eight different designs of sowing devices in the 3D CAD was carried out and their comparative assessment was completed in terms of mass and a set of technological parameters. Based on its results, a sowing device was selected that is most suitable for a specific given technology. Discrete Element Method (DEM) was used to simulate the workflow: imitation of loading of the sowing device, study of work in various modes, study of the process of impact interaction of seeds with the soil environment. The complex of developed sowing devices can provide sowing of almost any type of forest seeds within the framework of various technologies and soil climatic conditions.

Algebra of Technological Process

A formal apparatus for modeling the structure of the technological process of mechanical processing based on the algebra of design and technological elements is presented. Design and technological element (manufacturing feature) is considered as a set of geometric processing area and the tool trajectory applied to it, set by a set of technological parameters. Algebra includes an addition operation (adding an element to the process structure) and a multiplication operation (merging elements). The set of processing elements forms an associative and generally noncommutative algebraic group. The possibility of using algebra for analysis and synthesis of technological process structures is shown

Algorithms for selecting the operating mode of the technological process of waveguide paths induction brazing

The article presents the development of a method for selecting the operating mode of the induction brazing process based on intelligent methods. The use of intelligent methods is due to the presence of uncertain conditions caused by the complexity of the initial setting of the technological parameters of the induction brazing process, the error of measuring instruments, and the human factor. The use of smart methods will make it possible to reduce the impact of negative factors, remove uncertainty, and adequately perform the initial set of technological parameters for the induction brazing process. Artificial neural networks, the fuzzy controller and the neural fuzzy controller have been chosen as the smart methods in this work. The article gives a brief overview of the above methods, provides a rationale for the choice of intelligent methods, and also compares their effectiveness. Based on the results of the experimental efficiency check, the most suitable method for determining the choice of induction brazing process operation is proposed.

Comparative evaluation of powertrain concepts through an eco-impact optimization framework with real driving data

The assessment of the ecological impact of different powertrain concepts is of increasing relevance considering the enormous efforts necessary to limit the global warming effect due to the man-made climate change. Within this contribution, we adopt existing methods for the optimization of electric and hybrid electric powertrains using a vehicle simulation environment and derive a method to identify the ecological potential of different powertrain concepts for a set of technological parameters in the reference year 2030. By optimizing the parametrization for each powertrain concept and by adapting the respective operating behaviour specifically to minimize the ecological impact, a reliable and unbiased comparison is enabled. We use our optimization environment with the Real Ecological Impact as objective function to compare different powertrain concepts on driving profiles that are based on real driving data recorded in Germany. Despite the fact that all of the considered driving profiles contain trips of similar length, their respective optimized powertrain concepts are different. Plug-In Hybrid vehicles achieve the greatest potential for long-range capable vehicles and are least sensitive to different driving profiles.

Влияние реагентов-флокулянтов на параметры глинистых суспензий

The purpose of the work is to evaluate the effect of flocculant reagents on the rheological and structural-mechanical properties of clay suspensions, and to select their optimal concentration in the drilling mud. Currently, the industry produces a huge number of drilling mud flocculants that differ in their properties and composition. Most flocculants are water-soluble polymers with a large molecular weight, both of natural and artificial origin. The main purpose of such reagents is to separate the solid and liquid phases of the drilling mud during its dewatering and disposal. However, in clay suspensions, the same reagents are used as thickeners. As drilling fluids are complex systems that differ in their component composition, it is not possible to recommend a universal flocculant. During the study, the analysis of the flocculating and thickening capacity of the reagents was performed in two stages. The study defined an optimal concentration of the polymer at which maximum values of the dynamic shear stress were reached. The clay suspensions containing polymer reagents were been experimentally compared. The values of the rheological, structural-mechanical and filtration parameters of the solution were used as the evaluation criteria. The study has established the following. The reagents BEN-EX, BENTOPLUS and DRB-9 can be used to increase the viscosity of the clay solution, provided that the concentration of the additives BENTOPLUS and DRB-9 does not exceed 0.2 kg/m 3 . The SPECFLOC A 7950-20 reagent can be used to increase the viscosity of the clay solution in concentrations up to 0.1 kg/m 3 , while in concentrations of 0.2 and 0.3 kg/m 3 , the additive mainly effects the drilling mud as a flocculant, reducing the static shear stress of the solution and increasing the filtrate output. If the dynamic sheer stress is the only diagnostic variable when drilling with the SPECFLOC № 6919 additive, the latter can be recommended for use. In all other cases, additional research is required. The conducted laboratory studies allow us to obtain drilling fluids with a set of technological parameters that ensure high quality of the prepared drilling fluids.

Using an Adaptive Network-based Fuzzy Inference System to Estimate the Vertical Force in Single Point Incremental Forming

Manufacturing processes are usually complex ones, involving a significant number of parameters. Unconventional manufacturing processes, such as incremental forming is even more complex, and the establishment of some analytical relationships between parameters is difficult, largely due to the nonlinearities in the process. To overcome this drawback, artificial intelligence techniques were used to build empirical models from experimental data sets acquired from the manufacturing processes. The approach proposed in this work used an adaptive network-based fuzzy inference system to extract the value of technological force on Z-axis, which appears during incremental forming, considering a set of technological parameters (diameter of the tool, feed and incremental step) as inputs. Sets of experimental data were generated and processed by means of the proposed system, to make use of the learning ability of it to extract the empirical values of the technological force from rough data.

Determining the influence of the composition of milk from cows of different breeds on quality indicators for the dutch-type cheese

The paper reports a comprehensive study into the impact of feeding rations and breed of cows on the technological properties of milk and quality characteristics of the Dutch type of cheese. Despite the abundance of information on the relationship between domestic animal feeding and technological parameters for the production of cheeses, a possible relationship between particular properties of animal breeds, changes in feed, and a positive influence on the quality of products requires in-depth research. That explains the relevance of studying the influence of an animal breed and the optimization of animal feed on a set of technological parameters and quality indicators for the Dutch type of cheeses. We manufactured the Dutch-type cheese in a series of experiments using milk from cows of different breeds, obtained at different rations of feeding. We compared the chemical composition of milk from three groups of cows ‒ the Ukrainian brown dairy breed, Lebedinskaya breed, and Simmental breed, at different feed. The results obtained demonstrate that the use of alfalfa haylage contributes to an increase in the mass share of a dry fat-free milk residue in milk, improves its suitability for cheese, as compared with milk obtained over a silage-hay period.We have worked out technological modes for producing the hard Dutch-type cheese from milk of three cow breeds at different feeding rations. It is shown that when applying alfalfa haylage to feed animals the duration of basic technological operations shortens. That helps reduce the share of dry substances (including fat) in whey, and increases the output of finished product. The samples of hard Dutch-type cheese, made from milk of all three groups of animals over a haylage-hay period are characterized by a high content of essential amino acids, as well as free amino acids, and soluble non-protein nitrogen. That predetermined their higher degree of ripeness, and the larger point-based assessment, in terms of organoleptic characteristics (by 7‒15 points), compared to the samples of cheese produced from milk received over a silage-hay period. The highest point-based estimate for organoleptic characteristics (99 points) was given to samples of the Dutch-type cheese made from milk of the Ukrainian brown dairy cow, milked over a haylage-hay period.It was established that an animal breed has a significant impact on the suitability of milk for cheese and yield of the finished product. The most significant influence of the optimized feeding was exerted on the organoleptic and sensorial indicators for a Dutch-type cheese. The proof are the indicators for proteolytic activity. There was an increase in the growth of nitrogen within soluble fractions, an accelerated maturation process, as evidenced by the accumulation of low-molecular nitrogenous fractions. The largest total amount of free amino acids was demonstrated by cheese made from milk of the cows that were fed the improved ration using alfalfa haylage.The developed feeding rations, as well as the improved technological parameters for making a Dutch-type cheese, could be recommended as the cost and product quality management methods for producing mass-market and craft cheese.

Effect of Aluminum Particles on the Fracture Toughness of Polyamide-based Parts Obtained by Selective Laser Sintering (SLS)

Numerous additive manufacturing technologies are currently used in industry and research: selective laser sintering, selective laser melting, electron beam melting, fused deposition modelling, laminated object manufacturing and stereolithography. Independently on the type of technology, a set of technological parameters have to be controlled in order to obtain good quality parts that also possesses acceptable mechanical properties. Selective laser sintering (SLS) is a multipurpose additive manufacturing technology that allows fabrication of good resolution parts with adequate mechanical properties. The versatility of the process refers to the limitless geometrical shapes that can be achieved and also to a variety of powders and mixtures that can be used.The uncontrollable process variables occurring along the sinterization process (heat transfer, humidity), together with the multitude of controllable technological factors, including raw materials, lead to inconsistencies in shape, size and mechanical properties of the parts. These inconsistencies appear not only in SLS but in all additive manufacturing technologies.The study proposes to underline the influence of the aluminum mixed polyamide on the fracture toughness and geometrical characteristics of parts manufactured using the same energy density but different orientations in the building environment. The findings can be used for part design and parameter setup, in order to prevent both mechanical and geometrical failures.

Technological and Economic Investigations on the Application of Metal Infiltrated Graphite Electrodes for the Sinking EDM of Cemented Carbides

Cemented carbides are a substantial tool material in various production areas, but to date these are almost impossible to machine by conventional manufacturing processes. Since electric discharge machining (EDM) is a process that benefits from a nearly force free thermal material removal principle, it is distinguished for the machining of cemented carbides. State-of-the-art sinking EDM (SEDM) technology uses tungsten copper alloys as tool electrode materials for this application, but shortage of resources in tungsten production leads to rising prices and increasing manufacturing costs. This leads to great interest for advanced SEDM processes to manufacture cemented carbides. One of the most used material for tool electrodes in standard SEDM applications is conventional graphite, however, the process is far from being economically efficient using graphite compared to using tungsten copper alloys for the machining of cemented carbides. A promising alternative is metal infiltrated graphite, since it shall inherit benefits from both materials without being as cost-intensive as tungsten copper alloys. This research is both about technological and economic investigations using metal infiltrated graphite as tool electrodes for the SEDM processing of cemented carbides. A set of technological parameters is identified that results in higher material removal rates using the alternative material. Compared to the state-of-the-art the relative tool wear is still higher, but the alternative material can be applied with more economic efficiency.

FORMALIZATION TASK OF OPTIMIZING RESERVOIR PRESSURE MAINTENANCE SYSTEM

This article discusses aspects of the development of methods for the automated optimization of reservoir pressure maintenance through the use of models for the variation of performance control devices: throttling valves and characteristic group pumping station (SPS). In the operation of hydraulic systems to maintain reservoir pressure (PAP), there are a number of operational tasks which no systematic approach to the analysis of the state of the hydraulic system may not be adequate to the requirements of good governance. For the most effective management of structurally complex systems requires the use of the model system that mimics the behavior of real or projected hydraulic systems with arbitrary structure and indicators that make up their items. The complex is to be achieved with optimum joint compliance with the terms of minimizing the mean relative deviation from the optimal current pickups - and maximize efficiency system - a need to maximize the efficiency factor - reflecting the joint fulfillment of the conditions of technology and technical optimization. In addition to controlling the flow of fluid parameters, the model allows modifying the properties of the individual elements of the track projected costs and the fluid pressure in the system variable Selecting the optimum condition or just a way to optimize the resources we mean to achieve the goal of optimization: a set of technological parameters, which change in the real system, will change the complex hydraulic regime, in line with its optimal state.

Processing of AlGaAs/GaAs quantum-cascade structures for terahertz laser

We report research results with regard to AlGaAs/GaAs structure processing for THz quantum-cascade lasers (QCLs). We focus on the processes of Ti/Au cladding fabrication for metal–metal waveguides and wafer bonding with indium solder. Particular emphasis is placed on optimization of technological parameters for the said processes that result in working devices. A wide range of technological parameters was studied using test structures and the analysis of their electrical, optical, chemical, and mechanical properties performed by electron microscopic techniques, energy dispersive x-ray spectrometry, secondary ion mass spectroscopy, atomic force microscopy, Fourier-transform infrared spectroscopy, and circular transmission line method. On that basis, a set of technological parameters was selected for the fabrication of devices lasing at a maximum temperature of 130 K from AlGaAs/GaAs structures grown by means of molecular beam epitaxy. Their resulting threshold-current densities were on a level of 1.5 kA/cm2. Furthermore, initial stage research regarding fabrication of Cu-based claddings is reported as these are theoretically more promising than the Au-based ones with regard to low-loss waveguide fabrication for THz QCLs.

Blueshift of bandgap energy and reduction of non-radiative defect density due to precise control of InAs-on-GaSb interface in type-II InAs/GaSb superlattice

We have investigated the influence of As-soak parameters at InAs-on-GaSb interfaces on the structural and optical parameters of InAs/GaSb superlattices (SLs). The lattice-matched SLs were obtained for two sets of technological parameters. For a long As-soak time of 12.0 s and high V/III ratio of 10, the photoluminescence (PL) analysis indicates the presence of a non-radiative recombination channel. For a shorter time of 2.8 s and a reduced V/III ratio of 5.6, the PL excitation power dependence is close to that relevant for a clear excitonic recombination. The spectral blueshift of the bandgap energy of 23 meV was observed for SLs with GaAs-like interface thicknesses of 0.4 ML and 1.0 ML and other fixed parameters.

Features of SiAlON synthesis from kaolin

Under conditions of experimental–industrial synthesis of SiAlON from kaolin with the use of carbothermal reduction the fabrication of single-phase β′-SiAlON with z=2 is limited by a set of technological parameters: temperature and time of treatment, composition and volume of mixture. The introduction of iron additives in mixture is accompanied by the formation of iron silicides. The regions of melt of the highest iron silicides are the zones of SiAlON formation according to the VLS-mechanism. The powders synthesized in the temperature range of 1723–1873 K from the mixtures of kaolin, carbon, silicon carbide, and iron are the composite ones.

Performance-driven scaling of BiCMOS technology

A BiCMOS scaling analysis is carried out to optimize the performance of digital BiCMOS gates while accounting for the conditions that make the direct application of conventional BJT and MOS scaling rules invalid. A simple set of technological parameters that directly affect BJT and MOS device characteristics in the context of BiCMOS is identified. Scaling of the technological parameters leads to scaling of the device parameters which in turn appear in a comprehensive, accurate delay model. The scaling of logic gate delay under various possible scenarios is investigated and a set of optimal scaling rules is proposed that simultaneously scales all components of gate delay. The optimal rules require a linear reduction in horizontal and vertical dimensions, a linear increase in collector doping, and a square root reduction in supply voltage. When 1 mu m, 5 V, 8 GHz technology is scaled to 0.5 mu m, 3.5 V, 18 GHz according to the optimal scaling rules, a 2* improvement in BiCMOS performance is obtained. Despite the supply voltage reduction BiCMOS maintains a performance advantage of 1.5* over CMOS. >