Modular Machine Research Articles

Analysis of Modular Stator PMSM Manufactured Using Oriented Steel

Oriented steel has higher permeability and lower losses in the direction of orientation (the rolling direction) than non-oriented steel. However, in the transverse direction, oriented steel typically has lower permeability and higher losses. The strategic use of oriented steel in a modular Permanent Magnet Synchronous Machine (PMSM) stator can improve machine performance, particularly when compared to a machine designed with non-oriented steel, by increasing both torque and efficiency. Typically, steel manufacturers provide magnetic properties only in the rolling and transverse directions. Furthermore, in modern Finite Element Analysis (FEA) software, the magnetic properties between the rolling and transverse directions are interpolated using an intrinsic mathematical model. However, this interpolation method has proven to be inaccurate; to resolve this issue, an improved model was proposed in the literature. This model requires the magnetic properties of the oriented steel in between the rolling and transverse directions. Therefore, a procedure for extracting the magnetic properties of oriented steel is required. The objective of this work is to propose a method of determining the magnetic properties of oriented steel beyond just the oriented and transverse directions. In this method, flux-injecting probes, also known as sensors, are used to inject and control the flux density in an oriented steel segmented stator in order to extract the properties of the oriented steel. These extracted properties are then used to model an oriented steel modular stator PMSM. The machine’s average torque and core losses are compared with conventional, non-modular, non-oriented steel stator PMSM, and modular, non-oriented steel stator PMSM. It is shown that both the average torque and the core loss of the oriented steel modular stator PMSM have better performance at the selected number of segments than either of the two non-oriented steel stators.

Dimensional-time relationships of the technological process of manufacturing a "ТМЗ—450Д" diesel cylinder

Changes in the dimensions of the main bore of the cylinder of a "ТМЗ-450Д" diesel engine in the technological process of its mechanical and thermal treatment at the Tula Machine-Building Plant are analyzed. The accepted sequence of operations is presented: turning with CNC — aging — boring — aging — honing — aging — honing — honing — honing — aging. An incorrect choice of the cylinder basing scheme was noted during the first operations. A new version of the technological process of mechanical and heat treatments is proposed, including natural aging and the use of double boring on a modular boring machine, which made it possible to reduce the number of honing operations to one, including rough and finish steps. Keywords: shape and size errors, aging, dimensional changes, basing, boring, honing, Abbot diagram. Yamnikovas@mail.ru

Analysis and Synthesis in the Design of Magnetic Switching Electric Machines

A systematic approach to the design of electrical machines is implemented by solving problems of analysis and synthesis in various combinations at different stages and stages of design. The questions of the formulation and implementation of synthesis and analysis problems in the study and design of modular-type magnetically commutated electrical machines are considered. They are aimed at reducing weight, size and cost while improving the performance of these newly designed machines. A complex method of parametric synthesis and an automated program containing a calculated mathematical model of an electric machine has been developed. On the basis of numerical full factorial experiments, the optimization parameter is determined, and a regression analysis is performed with the construction of an optimization model. It allows you to find a narrow range of variation of significant factors, at which the optimization parameter satisfies the specified conditions. On the example of studying an inductor generator of axial-radial configuration, new approaches to the formulation and solution of typical problems of analysis and synthesis of modular-type electrical machines are shown. The use of complex parametric synthesis makes it possible to significantly reduce the masses of the designed modular machines in comparison with drum-type inductor machines of the same power.

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).

The layout method is an effective method for creating a product design

The advantages of creating a product design by the layout method are shown. An example of using the layout method when creating modular machines is given. It is noted that the effectiveness of using the layout method largely depends on the quality of the element base; the characteristics of the element base are given. A methodological approach to the construction of element bases is proposed, including the division of the element base into two parts: the base of the main elements and the base of the auxiliary elements.

Regularities of changing the dimensions of the main bore of the cylinder of TMZ-450D diesel engine during the technological process

The article deals with the problems arising during the mechanical and thermal treatment of the TMZ-450D diesel engine cylinder, which is the base part of the engines of small-sized generators and compressors, which are widely used for mobile units in the oil and gas and mining industries. It was found that the metal in the casting has a non-uniform structure, the density of which ranges from 6.75 to 7.25 g/cm3. Redistribution of dislocations and residual stresses in the casting leads to significant changes in the size and shape of the main bore. In addition to the successive changes in size specified by the technology due to the removal of the designated allowance, the dimensions and shape change arbitrarily, uncontrollably in the course of the technological process. It is shown that artificial aging by a thermal method does not provide the desired dimensional stability; therefore, it is proposed to supplement it with natural aging after rough boring for six months. It was revealed that the use of morally and physically outdated equipment makes it necessary to increase the number of finishing operations of honing and, accordingly, to increase the labor intensity of cylinder manufacturing. The use of a two-position boring machine is substantiated, on which the transitions of semi-finishing and fine boring are combined. This completely eliminates the copying of errors that arose when changing the base on previous operations. The use of a two-position modular boring machine ARS-4/Ts of increased accuracy and rigidity significantly increases the accuracy of the bore hole, which makes it possible to reduce the number of honing operations. A variant of the technological process of mechanical and heat treatment is proposed, including natural aging, the use of double boring on a modular boring machine, which will reduce the number of honing operations to one, including rough and finish transitions.

S3 manufacturing process taxonomy

Abstract In the literature, the design approach has been mainly focused on products, however, manufacturing process awareness lacks structure measurements of the organization resources and their productive capacity to systematize the adoption of newer technologies and automation of production lines. Due to this fact, there is a remaining gap in the adoption of technological resources to automate them. The study of manufacturing processes has made it possible to identify three opportunity areas in any type of organization: i) structured processes, ii) industrial environmental knowledge and iii) technological adoption. This article presents a taxonomy that structure available information in manufacturing processes into five levels to characterize, redesign, or develop them from scratch. To get a better comprehension of the environment, it is possible to enhance awareness of energy consumption, waste management, information flow and emissions control through Sensors, collection, processing, and communication of information through Smart components. The technological adoption goes hand in hand with the sustainable objectives of the organization and dictates the search for alternatives throughout the development or redesign of the manufacturing process to pursue economic, social and environmental objectives. Besides, the taxonomy was used in the characterization and updating of four manufacturing processes for a modular machine. These four case studies allow for better insight into the design process. The changes between the initial and final stages after the update were recorded in the S3 Scorecard to visualize the increase of the characteristics and to chart a route for future technological acquisitions. The proposal has made it possible to locate the characteristics of the manufacturing process at one level and align the objectives of the organization to a technology acquisition plan since manufacturing firms are looking to future-proof their investments by acquiring solutions to comply current regulations while maintaining low-cost operations.

Cutting Tests of the Outer Layer of Material Using Onion as an Example.

This paper describes experimental research on cutting the outer layer of onions in the machine peeling process. The authors’ own globally innovative modular machine construction was used for this purpose. The onion peeling machine was constructed on a real scale. The effectiveness of the machine’s functioning was defined as the ratio of the mass of material correctly removed by the scale blower to the mass of all material leaving the machine on the test bench . In order to carry out the experimental research, a test stand was constructed, a research plan and programme were adopted, and the research methodology was developed. The results obtained during the experimental research and the data obtained from the regression function equations for the developed design of the onion peeling machine were used to build systems of independent variables, for which the dependent variable reached extreme values. The effectiveness of the machine’s operation of modular construction increased with the increase in the depth of the external incisions of the shells , the number of scale-blowing nozzles, and the pressure of the air supply to the scale-blowing unit . Increasing the material feed rate and the distance of the air nozzles from the material to be processed reduced the machine’s efficiency . The tests carried out showed a high level of efficiency on the level of , which is not found in mass-produced machines.

Application Research of Integrated Prefabricated Module Computer Room Solution Based on Computer Communication

Modular machine room is to divide the whole machine room into several independent areas. The scale, power load and configuration of each area are customized according to the requirements [1]. A module is a single, independent, small data center. With the continuous expansion of business demand, independent modules are added, which can be combined flexibly to meet the different requirements of different customers for reliability level, power density and security level, so as to realize the purpose of rapid construction.

Physiology of Cerebellar Reserve: Redundancy and Plasticity of a Modular Machine.

The cerebellum is endowed with the capacity for compensation and restoration after pathological injury, a property known as cerebellar reserve. Such capacity is attributed to two unique morphological and physiological features of the cerebellum. First, mossy fibers that convey peripheral and central information run mediolaterally over a wide area of the cerebellum, resulting in the innervation of multiple microzones, commonly known as cerebellar functional units. Thus, a single microzone receives redundant information that can be used in pathological conditions. Secondly, the circuitry is characterized by a co-operative interplay among various forms of synaptic plasticity. Recent progress in understanding the mechanisms of redundant information and synaptic plasticity has allowed outlining therapeutic strategies potentiating these neural substrates to enhance the cerebellar reserve, taking advantage of the unique physiological properties of the cerebellum which appears as a modular and potentially reconfiguring brain structure.

Conceptual design of controllers for automated modular construction machines

A systematic design approach overcomes the inefficiency associated with the ad hoc development of control strategies, which depends on experience and trial-and-error [1], for automated modular construction machines. Implementation of controllers requires planning at the conceptual design phase. Axiomatic design (AD) has been introduced in developing control solutions. This paper formalizes the conceptual design methodology in building a controller with the use of quality function deployment (QFD) as a design and an analysis tool. The controller design approach using QFD has been applied to the automated steel wall framing machine and to a 2-degree-of-freedom (2 DOF) robotic arm, which can be readily extended to n-DOF robotic manipulators. The analysis and decoupling techniques for controller design presented in this paper differ from those used in traditional AD. QFD for controller design provides continuous transfer functions to represent relationships and mathematical decoupling that is easily implemented in software.

Electromagnetic and Mechanical Analysis of a Modular Outer Rotor Synchronous Reluctance Machine for Light Propulsion Vehicles

This article presents the optimal design from the electromagnetic and structural point of view of a fault-tolerant modular outer rotor synchronous reluctance machine, a not previously constructed topology. Two new topologies with the rotor in modular construction, one with each pole of the rotor considered as a separate module and a segmented one where each rib of a module can be considered as independent, are compared with a classic structure. The electromagnetic analysis is carried out using FLUX 2D software. The main studied parameters are electromagnetic torque, torque ripple content, saliency ratio, and power factor. In order to optimize the power factor of the machine, a cosimulation procedure is carried out for each structure, by employing a MATLAB and FLUX 2D coupling. Based on the obtained performances, the best topology is selected. Furthermore, a mechanical analysis is performed to determine if the new proposed rotor meets the structural integrity at rated speed and to establish the maximum speed value that can be attained such that the structural failure of the rotor is prevented. A modular outer rotor synchronous reluctance machine is designed and built. Experimental results of testing the prototype are given to confirm the validity of the proposed machine.

Research of design an educational modular 5 axis milling machine

Industrial CNC machine tools are supplied as closed architecture systems. Their structure, kinematics and CNC controllers are designed to be used exclusively for their basic purpose, without any possibility of being changed. Reconfiguration is seen as the ability to add or remove modules from the machine, to be equipped with additional degrees of freedom (axes). For the concept to become a reality, it is necessary that the machine tool can be easily assembled and disassembled by an end-user and can adapt to changing projects or machining requirements. The approached of this research was to develop a 5-axis modular machine tool, with technological capabilities similar to industrial ones, at an affordable level of development costs and suitable to be used for teaching CAM techniques for future engineers.

Identifying Mild Hepatic Encephalopathy Based on Multi-Layer Modular Algorithm and Machine Learning.

Hepatic encephalopathy (HE) is a neurocognitive dysfunction based on metabolic disorders caused by severe liver disease, which has a high one-year mortality. Mild hepatic encephalopathy (MHE) has a high risk of converting to overt HE, and thus the accurate identification of MHE from cirrhosis with no HE (noHE) is of great significance in reducing mortality. Previously, most studies focused on studying abnormality in the static brain networks of MHE to find biomarkers. In this study, we aimed to use multi-layer modular algorithm to study abnormality in dynamic graph properties of brain network in MHE patients and construct a machine learning model to identify individual MHE from noHE. Here, a time length of 500-second resting-state functional MRI data were collected from 41 healthy subjects, 32 noHE patients and 30 MHE patients. Multi-layer modular algorithm was performed on dynamic brain functional connectivity graph. The connection-stability score was used to characterize the loyalty in each brain network module. Nodal flexibility, cohesion and disjointness were calculated to describe how the node changes the network affiliation across time. Results show that significant differences between MHE and noHE were found merely in nodal disjointness in higher cognitive network modules (ventral attention, fronto-parietal, default mode networks) and these abnormalities were associated with the decline in patients’ attention and visual memory function evaluated by Digit Symbol Test. Finally, feature extraction from node disjointness with the support vector machine classifier showed an accuracy of 88.71% in discrimination of MHE from noHE, which was verified by different window sizes, modular partition parameters and machine learning parameters. All these results show that abnormal nodal disjointness in higher cognitive networks during brain network evolution can be seemed as a biomarker for identification of MHE, which help us understand the disease mechanism of MHE at a fine scale.

Modular machine learning for Alzheimer's disease classification from retinal vasculature

Alzheimer's disease is the leading cause of dementia. The long progression period in Alzheimer's disease provides a possibility for patients to get early treatment by having routine screenings. However, current clinical diagnostic imaging tools do not meet the specific requirements for screening procedures due to high cost and limited availability. In this work, we took the initiative to evaluate the retina, especially the retinal vasculature, as an alternative for conducting screenings for dementia patients caused by Alzheimer's disease. Highly modular machine learning techniques were employed throughout the whole pipeline. Utilizing data from the UK Biobank, the pipeline achieved an average classification accuracy of 82.44%. Besides the high classification accuracy, we also added a saliency analysis to strengthen this pipeline's interpretability. The saliency analysis indicated that within retinal images, small vessels carry more information for diagnosing Alzheimer's diseases, which aligns with related studies.

МОДУЛЬНАЯ МАШИНА ДЛЯ РОЗОВОДСТВА

The cultivation of oil-bearing roses requires signifi cant labor and energy resources. The research aims to develop a multifunctional farm implement to mechanize technological operations in rose-growing on small and medium-sized farms. The modular farm implement includes a platform-type base module. Depending on the technological operation performed, it incorporates a spraying system, pneumatic pruning system, side panels, or two workplaces for rose pickers. Using computer simulation with a simulation model created using the “Solid Works” software package, the author determined the profi les and the type of materials for the base module production. Graphoanalytical models help establish the parameters of the other modules of the modular machine. The conducted experimental tests proved the constructive strength of the technical solutions and the functional suitability of the modular machine. It was found that in oil-bearing rose plantations, the farm implement performs spraying at the consumption rates of 300…400 l/ha for treatment of the soil surface area under the rose bushes and 1000 l/ha and more for disease and pest control, foliar feeding, and other activities. The variant of the modular machine for selective pruning is ergonomic and effi cient at a maximum cut diameter of up to 25 mm and pressure in the tractor pneumatic system between 0.3…0.73 MPa. The highest eff ect of mechanized oil-bearing rose harvesting with the modular machine could be achieved in well-maintained plantations. The optimal height of the bushes should be 1.5…1.6 m, and the operation should be performed in the period of active fl owering (after 4-5 years of planting or rejuvenation). It is also possible to use the modular machine for transportation purposes. Experimental tests of the developed modular machine for oil-bearing rose production proved the constructive strength of the technical solutions and its functional

Scope and delimitation of game engine simulations for ultra-flexible production environments

Game engines are middleware that allows the integration of multiple resources turning them into assets with graphic information, programmed content and physical simulation parameters. These features meet the requirements for modelling, visualizing, simulating and controlling complex production systems. Therefore, an approach based on game engines to manage the user-perceived complexity was proposed. This paper compares 24 game engines and identifies suitable modelling environments for production based on their technical and market-development features. Then, a modular machine was integrated in two game engines. The results of scopes and limitations regarding functionality, scale, physics simulation accurateness, resource redundancies and visualization are presented.

A Hybrid Modular Cascade Machines System for Electric Vehicles Using Induction Machine and Permanent Magnet Synchronous Machine

Modular Cascade Machines (MCM) system is a multi-machine system for the traction systems of electrified vehicles. Currently, MCM is composed of several machines of the same type, generally, several Permanent Magnet Synchronous Machines (PMSM). This paper proposes a hybrid MCM system, which is composed of a PMSM and an Induction Machine (IM). This combination aims to fully benefit the properties of different machines. This hybrid MCM is compared with other traction systems, namely, PMSM-based MCM and single PMSM drive. For a fair comparison, the design specifications of all the traction systems are optimally sized by a specific sizing method, which can maximize the system high-efficiency area. Then, different traction systems are designed by Finite Element Method (FEM), in order to have accurate material consumptions and efficiency maps. The comparison study shows that the proposed hybrid MCM is competitive for energy saving. Therefore this new drive saves about 5% of energy in comparison with a single PMSM derive. The hybrid MCM energy saving is very close to the one of a PMSM-based MCM. Moreover, the hybrid MCM system reduces the PM volume (reduced by 53%) while increases the usage amount of winding copper, steel and aluminum, due to the existence of IM. Fortunately, the cost estimation proves that the hybrid MCM (not include inverters) has almost the same cost as the single PMSM. Hence the proposed hybrid MCM is a competitive alternative of the single PMSM than the PMSM-based MCM.

A Novel Matrix Transformation for Decoupled Control of Modular Multiphase PMSM Drives

When multiphase drives are used for specific applications, the modular solutions are preferred as they use consolidated power electronics technologies. The literature reports two modeling approaches for multiphase machines having a modular configuration of the stator winding. The first approach is the vector space decomposition (VSD) that models the energy conversion as for an equivalent three-phase machine. The main alternative to the VSD is the multistator (MS) modeling that emphasizes machine modularity in terms of torque production. Both approaches have advantages and disadvantages for multiphase machines with a modular structure. Therefore, this article aims to combine the VSD and MS approaches, defining a new matrix transformation and, hence, developing a new modeling approach for multiphase machines with a modular structure. The proposed transformation allows a decoupled and independent torque control of the sets composing the machine, preserving the torque regulation's modularity. Together with a new vector control scheme, it has been applied to a modular permanent magnet synchronous machine (PMSM) with a nonstandard spatial shift between windings. Experimental results are presented for a nine-phase PMSM prototype with a triple-three-phase stator winding configuration.

Modularity and Convertibility Characteristics of Reconfigurable Manufacturing System : An Approach for Operations Management

Modularity and Convertibility Characteristics of Reconfigurable Manufacturing System : An Approach for Operations Management