Industrial Machine Parts Research Articles

EXPANDING HORIZONS: DIVERSE APPLICATIONS OF RUBBERS AND ELASTOMERS IN EMERGING TECHNOLOGIES

ABSTRACT Rubbers and elastomers have a rich history that spans many eras of human civilization dating back to 1600 AD. Upon their introduction into Europe, they became common materials in shoes and fabrics. With the invention of vulcanization by Charles Goodyear in 1839, rubbers became widely used in many new applications, ranging from tires to industrial machine parts. Today, rubbers and elastomers are essential in the development of innovative, emerging technologies. This review exemplifies how rubbers and elastomers have been used to advance the emerging fields of soft robotics through soft grippers and dielectric elastomer actuators, stretchable and wearable devices through conductive elastomers and smart elastomers used in thermal camouflage and sensors, biomedical applications through tissue scaffolding and stretch-triggered drug delivery, and energy harvesting through piezoelectric elastomers and wave harvesting triboelectric nanogenerators. This review also briefly summarizes other developments in these fields as well as glimpses into other emerging fields that are advancing through the incorporation of rubbers and elastomers.

Grasp and Inspection of Mechanical Parts based on Visual Image Recognition Technology

In the process of industrial production, whether the machine can work stably is an important issue related to production efficiency and production safety. The cleaning of mechanical parts is an important factor affecting the stable operation of mechanical equipment, so the cleaning of mechanical parts is one of the important manufacturing links before assembly and manufacturing. The important value of the application of image recognition technology in the quality inspection of mechanical parts is briefly analyzed, and then the common problems in the quality inspection of mechanical parts are studied, the relevant measures of the application of image recognition technology in the quality inspection of mechanical parts are discussed, and finally the case analysis of the quality inspection of mechanical parts is carried out. The main purpose is to rationally use image recognition technology to complete the quality inspection of mechanical parts, so as to improve the overall level of production automation and give full play to the maximum role of this technology. At present, a variety of mechanical parts classification methods based on deep learning are studied. According to the demand of industrial machine parts, the corresponding machine parts data set is created. According to the production requirements, the SPP structure in the traditional YOLOV5 network is improved, and a new SPC structure is proposed: The YOLOv5 network with SPC structure is characterized by no pooling layer, which improves the accuracy and recall rate compared with the traditional YOLOv5 network. Secondly, the control method of robot grasping mechanical parts is studied. Using the camera to capture the image and the upper computer to calculate the mechanical parts under the camera coordinate system; Through camera calibration and hand-eye calibration, the transformation relationship between the grasping coordinates of mechanical parts in the camera coordinate system and the grasping coordinates of mechanical parts in the robot base coordinate system is obtained. The grasping coordinates and part type information of the mechanical parts in the robot base coordinate system are transmitted from the host computer to the robot through Modbus/TCP communication protocol.

Sintering Behavior, Thermal Expansion, and Environmental Impacts Accompanying Materials of the Al2O3/ZrO2 System Fabricated via Slip Casting.

This work focuses on research on obtaining and characterizing Al2O3/ZrO2 materials formed via slip casting method. The main emphasis in the research was placed on environmental aspects and those related to the practical use of ceramic materials. The goal was to analyze the environmental loads associated with the manufacturing of Al2O3/ZrO2 composites, as well as to determine the coefficient of thermal expansion of the obtained materials, classified as technical ceramics. This parameter is crucial in terms of their practical applications in high-temperature working conditions, e.g., as parts of industrial machines. The study reports on the four series of Al2O3/ZrO2 materials differing in the volume content of ZrO2. The sintering process was preceded by thermogravimetric measurements. The fabricated and sintered materials were characterized by dilatometric study, scanning electron microscopy, X-ray diffraction, and stereological analysis. Further, life cycle assessment was supplied. Based on dilatometric tests, it was observed that Al2O3/ZrO2 composites show a higher coefficient of thermal expansion than that resulting from the content of individual phases. The results of the life cycle analysis showed that the environmental loads (carbon footprint) resulting from the acquisition and processing of raw materials necessary for the production of sinters from Al2O3 and ZrO2 are comparable to those associated with the production of plastic products such as polypropylene or polyvinyl chloride.

Recognition of industrial machine parts based on transfer learning with convolutional neural network.

As the industry gradually enters the stage of unmanned and intelligent, factories in the future need to realize intelligent monitoring and diagnosis and maintenance of parts and components. In order to achieve this goal, it is first necessary to accurately identify and classify the parts in the factory. However, the existing literature rarely studies the classification and identification of parts of the entire factory. Due to the lack of existing data samples, this paper studies the identification and classification of small samples of industrial machine parts. In order to solve this problem, this paper establishes a convolutional neural network model based on the InceptionNet-V3 pretrained model through migration learning. Through experimental design, the influence of data expansion, learning rate and optimizer algorithm on the model effectiveness is studied, and the optimal model was finally determined, and the test accuracy rate reaches 99.74%. By comparing with the accuracy of other classifiers, the experimental results prove that the convolutional neural network model based on transfer learning can effectively solve the problem of recognition and classification of industrial machine parts with small samples and the idea of transfer learning can also be further promoted.

CAOS line camera.

Proposed and demonstrated is the coded access optical sensor (CAOS) line camera, a one-dimensional or line version of the two-dimensional (2D) digital-micromirror-device (DMD)-based CAOS camera. The proposed line camera design includes a precise dual-axis mirror scanning galvo system incorporating feedback control that eliminates the need for mechanical motion of either the camera or the target. CAOS line scan imaging experiments using a white light source with two test targets are conducted and compared with non-scan 2D CAOS imaging. Specifically, a 2D DMD operated as both a full-frame and a line modulator is used to demonstrate both full-frame (${127} \times {45}$127×45 pixels) and line (127 pixels) scan CAOS imaging. Also demonstrated is an increase in field of view (FOV) of the camera unit using the galvo system with FOV increased by factors of 2.87 and 1.67 in the horizontal and vertical directions, respectively. In addition, proposed for future implementation is a CAOS line camera design that allows analog and hybrid analog-digital time-frequency CAOS-mode irradiance coding for realizing improved inter-pixel cross talk. The CAOS line camera versus a 2D image sensor camera is suited for broad-spectrum large area/FOV imaging applications where high linear dynamic range and low contrast recovery are critical challenges, such as in active illumination inspection of archeological and art works and industrial machine parts.

Characterization of a coating 316L applied by plasma transferred arc

Parts of industrial machines and structures are often exposed to the action of aggressive environments, which in a short period of time can provoke the loss of their integrity. It is well known that for extending the service life against erosion and corrosion, protection of the exposed structure zone by coating is frequently used. Various application methods of protective coatings are applied, and the most common are welding and thermal spraying processes. The aim of this study was characterization of coatings made of stainless steel 316L, widely used in chemical and petrochemical industries. The coating was applied on a structural steel S235JR by plasma transferred arc using powder as a filler material. Due to a number of advantages, the plasma transferred arc (PTA) surfacing process has found significant usages in the field of surface protection. This paper presents results of hardness measurements in characteristic zones of the coating and the base material, as well as microstructural characterization of coatings using optical and scanning electron microscopy. Results of EDS analysis of the coating and hardness measurements indicated that a relatively high dilution (26.1 %) of the base material (BM) and the filler material (FM) occurred in a very narrow zone above the fusion line, and thus did not significantly affect the chemical composition of the rest of the coating. Also, erosion resistance tests of coatings were performed by changing the basic functional parameters that is the impact angle and the speed of erodent particles. It was observed that the erosion resistance of the coating material decreases approximately linearly with the increase of the particle speed. Also, with the increase of the impact angle of the erodent (up to 45 ?), the mass loss of the coating material is increased.

Robust active vision industrial CAD parts recognition system

In automated assembly systems the machine parts identification is entirely different from simple object recognition; moreover the ability of humans to differentiate between correct and not correct machine parts is better but it is a difficult task for a machine. In general, with fast moving machine parts on the conveyor manual defect detection by human inspectors is impractical. Also it is expensive, inaccurate, subjective, eye straining and causes other health issues to quality control inspectors. A computer vision-based non-contact inspection technique is developed with image processing methods by considering these problems, for defect detection in industrial machine parts. The present work will help the industrial robot used in assembly process and industrial inspection systems. In this paper features-based industrial object detection techniques are implemented in MATLAB to recognise the presence of the industrial CAD parts in the query image. In the end the actual industrial tool images are also used to show the accuracy and robustness of the proposed machine vision system for industrial manufacturing automation.

India Machinery Stores: a burgeoning success story of an entrepreneur

The case is a gripping story of an entrepreneur dealing in agricultural and industrial machine parts. The case portrays his journey from inception to the burgeoning success. The case entails the challenging business dealership decisions and speckled strategies adopted to capture the market. The diverse policy decisions taken by Mr. Krishna Kumar Agrawal with regards to inventory management, receivables management and other functional areas assisted him to gain strategic competencies which transformed a pioneer into a market leader. Mr. Agrawal was highly socially responsive and the corporate social responsibility activities acted as a contributor in business growth and creating goodwill. The case ends with challenging dilemmas wherein suggestions may be invited from the target audience.

India Machinery Stores: a burgeoning success story of an entrepreneur

The case is a gripping story of an entrepreneur dealing in agricultural and industrial machine parts. The case portrays his journey from inception to the burgeoning success. The case entails the challenging business dealership decisions and speckled strategies adopted to capture the market. The diverse policy decisions taken by Mr. Krishna Kumar Agrawal with regards to inventory management, receivables management and other functional areas assisted him to gain strategic competencies which transformed a pioneer into a market leader. Mr. Agrawal was highly socially responsive and the corporate social responsibility activities acted as a contributor in business growth and creating goodwill. The case ends with challenging dilemmas wherein suggestions may be invited from the target audience.

Frictional property of Ti–B–N coating with preferred grain orientations deposited by arc ion plating under dry condition

It was shown in the previous paper that the low coefficients of friction of TiN coatings with (111) preferred grain orientation were measured under dry condition. In this paper, the new Ti–B–N coatings with (111) preferred grain orientation were developed for the industrial application. The coefficients of friction of the Ti–B–N coatings against steel materials were measured by ball-on-disc friction tester. As a result, it was found that the Ti–B–N coatings were able to maintain the low coefficients of friction over long sliding distance under severe sliding condition in comparison with the TiN coatings. It is understood that the Ti–B–N coatings have the possibility of being applied to the sliding parts of industrial machines under dry condition.

Methods and application of residual stress analysis on thermally sprayed coatings and layer composites

Coating and layer composite manufacturing most commonly involves high temperature gradients and intensive heat transfer between the different composite materials. This can be noticed not only for thermal spraying, but also for other coating techniques. The combination of temperature gradients and materials with different thermophysical properties leads to the formation of thermal stresses in the composite, which are superimposed by stress generating effects during coating solidification, phase transformation or recrystallization. The final state of residual stresses affects the structural and functional properties of the coating as well as the component reliability during operation. Therefore, residual stress analysis is an important tool for the optimization of coatings and layer composite manufacturing processes in order to ensure stability of the processes, adhesion and compatibility of the coating, and finally, the reliability of the components in various technical systems. The most common residual stress measurement techniques are described and compared, with the focus on the incremental hole drilling and milling method. The advantages and disadvantages of the methods are discussed with respect to their application on industrial machine parts. The typical application fields for the different methods are given with respect to the specific measurement principles. The incremental hole drilling method is presented in more detail with application examples that illustrate the suitability of this method for the optimization of thermal spraying processes in industrial layer composite manufacturing by managing the heat and mass transfer in a most appropriate way.

Fast distance measurements by use of dynamic speckles

A technique for fast measurements of the distance to an object's surface based on spatial filtering of dynamic speckle patterns is proposed. Exploitation of two spatial filters (Ronchi rulings) enables measurements to be independent of surface speed. Experimental verification of the technique is demonstrated at speeds of the surface as high as 50 m/s. The technique may find applications in machine-vision systems for acquisition of three-dimensional images and in control systems for on-line monitoring of fast-moving parts of industrial machines.

Metal vapour vacuum arc ion implantation facility in Turkey

A vacuum arc ion source based metal ion implantation facility is built and in operation at TUBITAK (The Scientific and Technical Research Council of Turkey), Izmir, Turkey and a surface modification research and development program is being carried out here. The system is similar to the one in Lawrence Berkeley Laboratory, which was first built and developed by Brown et al. The broad-beam ion source can be repetitively pulsed at rates up to ∼50 pulses per second and the extracted ion beam current can be up to ∼1 A peak or ∼10 mA time averaged. The ion source extraction voltage can be increased up to 110 kV. Additionally, mixed metal and gas ion beams were generated by a magnetic field, which was obtained through a magnet coil located in front of anode plate and by adding gas in the discharge region. This modified system was used to form buried layers of mixed metal–gas species such as Ti+N (on 316 SS and Ti alloy samples) and Zr and W (316 SS and Ti alloy samples, respectively) of which their hardness, coefficient of friction and wear volumes were measured and their RBS results were obtained. The anodic electrochemical tests showed that the corrosion resistance of Ti implanted 304 SS samples was increased with the dose. Micro structures of Ti implanted surfaces of 304 SS samples were examined with SEM before and after the corrosion tests and the results showed that the pittings were formed mostly in the areas where implanted Ti concentration was less. Recently, the system is equipped with TOF for measuring the charge state distribution of ions. R&D work is planned for the purpose of forming tribologically enhanced materials for industrial applications by using ion implantation, PVD coating, plasma nitriding and their combinations. The results showed that the hardness and performance of ion implanted (with various metals and N) PVD coated cutting inserts increased remarkably. The use of ion implantation techniques in modifying the properties of textile and other materials and optimising the performance of textile and other industrial machine parts and tools is also being investigated and some of the results are presented in this work.

Non-destructive crack detection by capturing local flux leakage field

The crack detection in the industrial machine parts is very important. The non-destructive crack detection and evaluation of the these cracks are highly desirable from the viewpoint of safe and economic operation of installed facilities such as industrial factories and power plants. A crack induces local damages in the magnetic flux path in a ferromagnetic material and any change in crack area results in change in the distribution of magnetic flux in the material. In this paper, variation of the magnetic flux distribution in locally magnetised ferromagnetic materials which has discontinuity as a crack, is studied.