Evaluation of gas nitriding process with in-process variation of nitriding potential for AISI H13 tool steel

Gas nitriding under controlled nitriding potential represents one of the important factors in enhancing the service life of dies used in the industry for hot aluminum extrusion. In the present study, AISI H13, a typical material used for hot extrusion dies, is gas nitrided using automated two-stage controlled nitriding process. Prior heat treatment on the material was carried out under the same controlled environment as used for hot extrusion dies to avoid any decarburization. The nitrided layer has been characterized using different techniques including optical microscopy, SEM, XRD, EDS, and microhardness analysis. It was found that controlled nitriding with in-process variation of nitriding potential can efficiently be used to control the morphology of compound layer and diffusion zone, effective case depth, case hardness, and quality of nitrided layer at sharp edges for better die performance. All the results were found in close agreement with established specifications required for improved die performance.     

The effects of plasma nitriding process parameters on the wear characteristics of AISI M2 tool steel

The main aim of this work is to evaluate the effects of the plasma nitriding process on AISI M2 tool steel. In previous work, treatment time and temperature were varied to identify the treatment conditions for good wear behaviour. In the present work, the treatment time was fixed while temperature and gas pressure were varied. Samples were characterised by glow discharge optical spectroscopy, scanning electron microscopy, X‐ray diffraction, surface microhardness and wear test. The specimens nitrided at 400 and 900 Pa showed the best wear performance, which is possibly due to reduction of the friction coefficient and the low adhesive wear observed. Samples processed at 200 Pa showed spalling during the wear test, indicating a brittle surface. This revised version was published online in July 2006 with corrections to the Cover Date.     

Genetic algorithm based optimization of the process parameters for gas metal arc welding of AISI 904 L stainless steel

The present study is focused on welding of super austenitic stainless steel sheet using gas metal arc welding process with AISI 904 L super austenitic stainless steel with solid wire of 1.2 mm diameter. Based on the Box — Behnken design technique, the experiments are carried out. The input parameters (gas flow rate, voltage, travel speed and wire feed rate) ranges are selected based on the filler wire thickness and base material thickness and the corresponding output variables such as bead width (BW), bead height (BH) and depth of penetration (DP) are measured using optical microscopy. Based on the experimental data, the mathematical models are developed as per regression analysis using Design Expert 7.1 software. An attempt is made to minimize the bead width and bead height and maximize the depth of penetration using genetic algorithm.     

Improving profile accuracy in SPIF process through statistical optimization of forming parameters

In single-point incremental forming (SPIF) process, a number of parameters are involved and need to be adjusted before the commencement of the forming operation. The inappropriate selection of these parameters could be detrimental to process accuracy. In this paper, the effect of five parameters, namely, sheet thickness, tool radius, step size, wall angle, and pre-straining level of sheet, on the profile accuracy of the produced part of AA1060 with SPIF is experimentally investigated. A response surface method is employed for the experimental design and regression analysis. The experimental results are presented in the form of graphical three-dimensional response surfaces. The results of ANOVA show that the sheet thickness, wall angle, step size, and the interaction between the sheet thickness and wall angle are extremely significant in terms of their effect on profile accuracy. Furthermore, an empirical model is proposed to achieve improved profile accuracy in terms of the optimized parameters.     

Analysis of oil consumption in cylinder of diesel engine for optimization of piston rings

The performance and particulate emission of a diesel engine are affected by the consumption of lubricating oil.Most studies on oil consumption mechanism of the cylinder have been done by using the experimental method,however they are very costly.Therefore,it is very necessary to study oil consumption mechanism of the cylinder and obtain the accurate results by the calculation method.Firstly,four main modes of lubricating oil consumption in cylinder are analyzed and then the oil consumption rate under common working conditions are calculated for the four modes based on an engine.Then,the factors that affect the lubricating oil consumption such as working conditions,the second ring closed gap,the elastic force of the piston rings are also investigated for the four modes.The calculation results show that most of the lubricating oil is consumed by evaporation on the liner surface.Besides,there are three other findings:(1) The oil evaporation from the liner is determined by the working condition of an engine;(2) The increase of the ring closed gap reduces the oil blow through the top ring end gap but increases blow-by;(3) With the increase of the elastic force of the ring,both the left oil film thickness and the oil throw-off at the top ring decrease.The oil scraping of the piston top edge is consequently reduced while the friction loss between the rings and the liner increases.A neural network prediction model of the lubricating oil consumption in cylinder is established based on the BP neural network theory,and then the model is trained and validated.The main piston rings parameters which affect the oil consumption are optimized by using the BP neural network prediction model and the prediction accuracy of this BP neural network is within 8%,which is acceptable for normal engineering applications.The oil consumption is also measured experimentally.The relative errors of the calculated and experimental values are less than 10%,verifying the validity of the simulation results.Applying the established simulation model and the validated BP network model is able to generate numerical results with sufficient accuracy,which significantly reduces experimental work and provides guidance for the optimal design of the piston rings diesel engines.     

Multi-response optimization of Micro-EDM process parameters on AISI304 steel using TOPSIS

The Technique for order preference by similarity to ideal solution (TOPSIS) method of optimization is used to analyze the process parameters of the micro-Electrical discharge machining (micro-EDM) of an AISI 304 steel with multi-performance characteristics. The Taguchi method of experimental design L27 is performed to obtain the optimal parameters for inputs, including feed rate, current, pulse on time, and gap voltage. Several output responses, such as the material removal rate, electrode wear rate, overcut, taper angle, and circularity at entry and exit points, are analyzed for the optimal conditions. Among all the investigated parameters, feed rate exerts a greater influence on the hole quality. ANOVA is employed to identify the contribution of each experiment. The optimal level of parameter setting is maintained at a feed rate of 4 μm/s, a current of 10 A, a pulse on time of 10 μs, and a gap voltage of 10 V. Scanning electron microscope analysis is conducted to examine the hole quality. The experimental results indicate that the optimal level of the process parameter setting over the overall performance of the micro-EDM is improved through TOPSIS.     

Friction and wear processes in piston rings

It has been recognised that a large part of the top piston ring wear of an ic engine takes place in boundary lubrication around top dead centre (tdc) position. A quantitative assessment of the friction behaviour using actual piston ring and cylinder liner under conditions close to tdc has been made. The factors responsible for wear under these conditions have been identified as surface temperature, peak combustion pressure, total energy on the wearing surfaces and other physical properties of the material under sliding     

渗碳钢制轴承套圈渗碳及热处理工艺

通过对某渗碳钢制轴承套圈渗碳工艺的试验研究,达到足够的有效硬化层深度、表面碳含量且渗碳层组织中无粗大网状碳化物等要求,使轴承内、外套圈的工作表面具有高的硬度、耐磨性、高抗疲劳性,而心部具有高的强韧性等性能。     

On the hydrodynamic lubrication analysis of piston rings

A theoretical hydrodynamic lubrication analysis of piston rings is presented. A numerical scheme is developed to solve the Reynolds' equation and the load equilibrium equation simultaneously. The hydrodynamic effects are examined in detail by considering solutions to the problem of lubricating the top compression ring in a two-stroke diesel engine. The minimum film thickness is computed throughout a complete cycle. The pressure profiles and film shapes at different crankshaft angles are presented. In the method proposed, the camtation boundary condition within the lubricated conjunction is included in the analysis.     

F-C201氢压机Ⅱ级活塞、活塞环的改造

将氢压机活塞、活塞环进行改造。活塞环由金属环改为复合型填充PTFE新材料，增加巴氏合金导向环，实际运行表明，运行周期增加数倍。     

活塞式无油润滑压缩机填料环的加工

根据产品的材料、结构及使用要求，介绍了钩形填料环的一种新型而实用的加工工艺，从而提高了产品的合格率及优质品率，满足了其使用要求。     

发动机修理时活塞环的正确选择与更换

发动机是汽车起重机、内燃叉车的核心部件，发动机性能的好坏将直接影响设备的使用和作业效率的提高。气缸活塞环的失效是造成发动机动力性下降的一个主要原因。在修理发动机的过程中，应合理确定活塞环的修理或更换时机，并按工艺要求进行更换。     

Friction characteristics of piston rings in a reciprocating engine

The performance of a reciprocating engine can be improved by reducing the friction between piston rings and cylinder liner, which significantly contributes to the mechanical friction losses of an engine. The friction force of a piston ring pack is calculated, based on hydrodynamic lubrication theory, for the piston rings. Calculations were carried out for three sets of conditions. Oil starvation is taken into consideration in the calculation of oil-film behaviour for a ring pack. The friction characteristics of piston rings are evaluated using the frictional mean effective pressure. The friction force of a piston assembly is measured experimentally by an improved floating liner method. The effects of lubricant viscosity and engine speed on friction characteristics are investigated by both calculation and experiment.     

Concurrent optimization of machining process parameters and tolerance allocation

With the advent use of sophisticated and high-cost machines coupled with higher labor costs, concurrent optimization of machining process parameters and tolerance allocation plays a vital role in producing the parts economically. In this paper, an effort is made to concurrently optimize the manufacturing cost of piston and cylinder components by optimizing the operating parameters of the machining processes. Design of experiments (DoE) is adopted to investigate systematically the machining process parameters that influence product quality. In addition, tolerance plays a vital role in assembly of parts in manufacturing industries. For the selected piston and cylinder component, improvements efforts are made to reduce the total manufacturing cost of the components. By making use of central composite rotatable design method, a module of DoE, a mathematical model is developed for predicting the standard deviation of the tolerance achieved by grinding process. This mathematical model, which gives 93.3% accuracy, is used to calculate the quality loss cost. The intent of concurrent optimization problem is to minimize total manufacturing cost and quality loss function. Genetic algorithm is followed for optimizing the parameters. The results prove that there is a considerable reduction in manufacturing cost without violating the required tolerance, cutting force, and power.     

FEM simulation-based cutting parameters optimization in machining aluminum-silicon piston alloy ZL109 with PCD tool

Journal of Mechanical Science and Technology - The Johnson-Cook (JC) constitutive model was utilized to simulate the processing of Al-Si piston alloy ZL109 to obtain the optimal finishing...     

Development of a special geometry carbide tool for the optimization of vertical turning of martensitic gray cast iron piston rings

The machining process for vertical turning martensitic gray cast iron is of great importance to the automotive industry, mainly in the manufacturing process of piston rings. The aim of this paper is to demonstrate the process of development of coated carbide tools to maximize the productivity of the process, considering the maximum life of the cutting tool and the minimum machining cost per part. Using full-factorial design of experiments, we tested two different geometries: a square tool with special geometry—formed by two edges and two ends simultaneously cutting—and a hexagonal tool. Considering that the special square geometry provided maximum life, full quadratic models for responses of interest were constructed using a central composite design for feed (f) and rotation (n). Applying the generalized reduced gradient algorithm, the proposed optimization goals were achieved with feed f?=?0.37?mm/v and rotation of 264?rpm for the use of the special square tool. Confirmation experiments prove the effectiveness of this solution.     

PID控制参数优化中的改进免疫遗传算法

针对传统的PID控制起参数优化方法的缺点,提出了一种结合精英策略的改进的人工免疫遗传算法(IGAE),该算法的特点是以新的抗体相似度、期望繁殖率以及克隆选择概率的定义方法和计算公式作为优化问题的目标函数,采用IGAE去调整和优化PID控制器的三个增益参数,结合精英选择策略(elitism strategy)以获得性能最优的PID控制器.仿真实验结果表明新的免疫遗传算法具有全局优化的能力,响应速度快、鲁棒性强,对变参数PID控制的参数优化设计是成功和有效的.     

The influence of the nitriding process on the dry wear resistance of 15-5 PH stainless steel

The dry wear resistance of 15-5 PH stainless steel nitrided using various methods was investigated. The methods included gas nitriding in cracked ammonia, plasma or ion nitriding and ion implantation of nitrogen. The dry wear resistance and the topography of the wear surface were studied as a function of load and sliding distance. It was found that the wear resistance of the plasma-nitrided specimens is higher than that of the gas-nitrided specimens. The wear resistance of the ion-implanted specimens was even better. However, because of the very small thickness of the implanted layer, only partial results were obtained.     

The multi-objective optimization of medium-speed WEDM process parameters for machining SKD11 steel by the hybrid method of RSM and NSGA-II

In the medium-speed wire electrical discharge machining (MS-WEDM) process, the extremely high temperature and massive electrical discharges in a fraction of 1 s result in the poor surface quality such as high tensile residual stresses, high surface roughness, white layers, and micro cracks. In this paper, an experimental plan for central composite design (CCD) of processing the tool steel (SKD11) has been conducted according to response surface methodology (RSM). The aim is to develop the mathematical model that can correlate the main process parameters of MS-WEDM with machining performance and to seek the optimal parameters on material removal rate (MRR) and 3D surface quality (Sq) by integrated RSM and Non-dominated Sorting Genetic Algorithm-II (NSGA-II). Then, a set of pareto-optimal solutions is obtained. Moreover, from the confirmation experiment, it has been proved that the optimal process-parameter combinations are suitable on the MRR and the 3D surface texture. Eventually, it has also demonstrated that the method of integrated RSM and NSGA-II is an effective way for multi-objective optimization.