Laser cladding and applications

Laser coating is a material placement technique wherein a powder material is melted using a laser to coat a portion of a substrate. In this study, laser cladding and its applications are reviewed. First, background of the technique and its important parameters are highlighted. Then, control of laser cladding procedure is criticized. As an example of the process, laser cladding of titanium alloys is investigated. Finally, applications of laser cladding on gas turbine engines, dies and drilling spindles, tools, turbine blades are highlighted

State of the Art of Laser Hardening and Cladding

In this paper an overview is given about laser surface modification processes, which are developed especially with the aim of hardness improvement for an enhanced fatigue and wear behaviour. The processes can be divided into such with and without filler material and in solid-state and melting processes. Actual work on shock hardening, transformation hardening, remelting, alloying and cladding is reviewed, where the main focus was on scientific work from the 21st century

Comparison of intelligent control methods for the ore jigging process

Efficient control of the process of jigging ore of small and fine grain allows avoiding the loss of valuable material in production residual.  Due to the multi-dimensionality and multi-connectivity of this enrichment process, classical control methods do not allow achieving the maximum technological indicators of enrichment. This paper proposes investigating intelligent algorithms for controlling the jigging process, which determine the key variables - the level of the natural «bed» and the ripple frequency of the jigging machine. Algorithms are developed using fuzzy logic, neural and hybrid networks. The adequacy of intelligent algorithms was evaluated using the following criteria: correlation of expert and model values (R); Root Mean Square Error (RMSE); Mean absolute percentage error (MAPE). To assess the adequacy of the obtained algorithms, a test sample of input variables, different from the training one, was compiled. As a consequence, we determined an algorithm that gives a minimal discrepancy between the calculated and experimental data

Process control for WAAM using computer vision

This study is mainly about the vision system and control algorithm programming for wire arc additive manufacturing (WAAM). Arc additive manufacturing technology is formed by the principle of heat source cladding produced by welders using molten inert gas shielded welding (MIG), tungsten inert gas shielded welding (TIG) and layered plasma welding power supply (PA). It has high deposition efficiency, short manufacturing cycle, low cost, and easy maintenance. Although WAAM has very good uses in various fields, the inability to control the adding process in real time has led to defects in the weld and reduced quality. Therefore, it is necessary to develop the real-time feedback through computer vision and algorithms for WAAM to ensure that the thickness and the width of each layer during the addition process are the same

Variation of Process Parameters Using the Taguchi Method

As of late, RPT has been executed in the industry, especially in the areas of product development. Existing methods give the ability to quickly create a substantial strong part, specifically from three dimensional Computer Aided Design (CAD) information, from a scope of materials, for example, photo curable resin, powders and paper. Much of the time, the final result of a formative cycle is a metallic object with dimensionally steady and of high precision, whether it is a part or a device. Part testimony introduction is vital variable of layered assembling as it impacts fabricate time, bolster structure, dimensional exactness, surface complete and expense of the model. Various layered assembling procedure particular parameters and imperatives must be considered while choosing the part statement introduction. Determination of an ideal part affidavit introduction is a troublesome and prolonged errand as one needs to exchange off among different negating destinations like part surface complete and construct time. It is referred to those process parameters, for example, the air gap between adjoining tracks, raster point, thickness, width of kept layers impact the execution of parts created on a FDM machine. From the outcomes, it is discovered that FDM parameters, i.e. layer thickness, raster edge and air gap altogether influence the versatile execution of the compliant ABS model. The ideal levels of parameters at diverse edge of removal are likewise introduced. Nevertheless, the suitable levels of parameters connected with diverse execution criteria still need further examination. A few studies have been directed to focus the ideal parameters of FDM, and execution criteria frequently utilized incorporate form time, quality, sturdiness and surface trustworthiness of the models, typically for infusion trim and tooling applications

Comparison of different optimization and process control procedures

This paper includes a comparison of different optimization methods, used for optimizing the cutting conditions during milling. It includes also a part of using soft computer techniques in process control procedures. Milling is a cutting procedure dependent of a number of variables. These variables are dependent from each other in consequence, if we change one variable, the others change too. PSO and GA algorithm are applied to the CNC milling program to improve cutting conditions, improve end finishing, reduce tool wear and reduce the stress on the tool, the machine and the machined part. At the end a summary will be given of pasted and future researches.Peer Reviewe

Non-silicon Microfabricated Nanostructured Chemical Sensors For Electric Nose Application

A systematic investigation has been performed for Electric Nose , a system that can identify gas samples and detect their concentrations by combining sensor array and data processing technologies. Non-silicon based microfabricatition has been developed for micro-electro-mechanical-system (MEMS) based gas sensors. Novel sensors have been designed, fabricated and tested. Nanocrystalline semiconductor metal oxide (SMO) materials include SnO2, WO3 and In2O3 have been studied for gas sensing applications. Different doping material such as copper, silver, platinum and indium are studied in order to achieve better selectivity for different targeting toxic gases including hydrogen, carbon monoxide, hydrogen sulfide etc. Fundamental issues like sensitivity, selectivity, stability, temperature influence, humidity influence, thermal characterization, drifting problem etc. of SMO gas sensors have been intensively investigated. A novel approach to improve temperature stability of SMO (including tin oxide) gas sensors by applying a temperature feedback control circuit has been developed. The feedback temperature controller that is compatible with MEMS sensor fabrication has been invented and applied to gas sensor array system. Significant improvement of stability has been achieved compared to SMO gas sensors without temperature compensation under the same ambient conditions. Single walled carbon nanotube (SWNT) has been studied to improve SnO2 gas sensing property in terms of sensitivity, response time and recovery time. Three times of better sensitivity has been achieved experimentally. The feasibility of using TSK Fuzzy neural network algorithm for Electric Nose has been exploited during the research. A training process of using TSK Fuzzy neural network with input/output pairs from individual gas sensor cell has been developed. This will make electric nose smart enough to measure gas concentrations in a gas mixture. The model has been proven valid by gas experimental results conducted

Hydrotreating unit models based on statistical and fuzzy information

This paper presents the results of mathematical models’ development for hydrotreating reactor, stripping соlumn, absorbers and hydrotreating furnace which are basic units of hydrotreating block in catalytic reforming unit. Since these objects of modeling in reforming unit of Atyrau refinery operate in conditions of insufficiency and fuzziness of the initial information, their mathematical models are developed on the basis of a systematic approach, using available information of different nature (experimental-statistical data, fuzzy information from the experts), with appropriate methods of construction for mathematical models. Mathematical models, describing the dependence of the production output from the hydrotreating reactor, columns and furnace, are designed as a nonlinear regression models based on experimental-statistical data. Whereas models, evaluating the quality indicators of generated products from the hydrotreating reactor and columns, i.e., hydrogenation, hydrogen-containing and hydrocarbon-containing gases are built based on fuzzy information from specialists-experts in the form of fuzzy multiple regression equations. We have plotted the graph for the dependence of hydrogenation products output on the temperature in the hydrotreating reactor. To describe the dependence of the optimum temperature value in hydrotreating process on raw material quality, a linguistic model is designed based on compositional rules of inference and fuzzy information. Membership functions of fuzzy parameters are constructed for linguistic models