Optimization of lapping process parameters of CP-Ti based on PSO with mutation and BPNN

This work aims to improve the surface quality of commercially pure titanium (CP-Ti) with free alumina lapping fluid and establish the relationship between the main process parameters of lapping and roughness. On this basis, the optimal process parameters were searched by performing particle swarm optimization with mutation. First, free alumina lapping fluid was used to perform an L9(33) orthogonal experiment on CP-Ti to acquire data samples to train the neural network. At the same time, a BP neural network was created to fit the nonlinear functional relation among the lapping pressure P, spindle speed n, slurry flow Q and roughness Ra. Then, the range of the node numbers in the hidden layer of the neural network was determined by empirical formulas and the Kolmogorov theorem. On this basis, particle swarm optimization with mutation was used to search for the optimal process parameter configurations for lapping CP-Ti. The optimal process parameter configurations were used in the neural network to calculate the prediction value. Finally, the accuracy of the prediction was verified experimentally. The optimum process parameter configurations found by particle swarm optimization were as follows: the lapping pressure was 5 kPa, spindle speed was 60 r·min− 1 and slurry flow was 50 ml·min− 1. Then, the configurations were applied to a neural network to simulate prediction: the roughness was 0.1127 µm. The roughness obtained by experiments was 0.1134 µm. The error was 0.62%, which indicates that the well-trained neural network can achieve a good prediction when experimental data are missing. Applying the particle swarm optimization (PSO) algorithm with mutation to a neural network will obtain the optimal process parameter configurations, which can effectively improve the surface quality of CP-Ti lapped with free abrasive.

Repairing Ti-6Al-4V aeronautical components with DED additive manufacturing

Direct Energy Deposition (DED) processes are Additive Manufacturing (AM) processes that provide new perspectives for the manufacturing industry. In particular the area of component repair could highly benefit from these processes. It is consequently necessary to ensure the ability of DED processes, so that the repaired component can provide the same level of service than a new one. This paper focuses on the repair of Ti-6Al-4V parts by powder based LMD AM and investigates its accuracy, repeatability and reliability. At first, an experimental campaign has been carried out to evaluate the characteristics of as-built material. Optimal process parameter selection is made by a porosity and macrostructure analysis. Tensile properties, Low Cycle Fatigue and crack propagation studies have been done on as-built samples (100% AM) and interface samples (50% AM / 50% substrate). The results compare to wrought alloy and validate the relevance of LMD to produce sound repaired parts. In a second section, the paper proposes a semi automatic repair method of Ti-6Al-4V components: the defect geometry and the CAD model of the part to repair are identified from 3D scanning operations. Adapted additive and machining tool paths are then generated on the selected equipment.

Influence of a Zn Interlayer on the Interfacial Microstructures and Mechanical Properties of Arc-Sprayed Al/AZ91D Bimetals Manufactured by the Solid–Liquid Compound Casting Process

A novel technique combining solid–liquid compound casting (SLCC) with arc spraying was designed to manufacture the arc-sprayed Al/AZ91D bimetals with a Zn interlayer. The Al/Mg bimetal was produced by pouring the AZ91D melt into the molds sprayed with Al/Zn double-deck coating, during which the arc-sprayed Zn coating acted as the interlayer. The effect of the Zn interlayer on microstructures, properties, and fracture behaviors of arc-sprayed Al/AZ91D bimetals by SLCC was investigated and discussed in this study. The optimal process parameter was acquired by analyzing the results from different combinations between the arc-spraying time of the Zn coating (10, 18, and 30 s) and the preheat time of the Al/Zn double-deck coating (6 and 12 h). The interfacial microstructures of the arc-sprayed Al/AZ91D bimetals with a Zn interlayer could be approximately divided into two categories: One was mainly composed of (α-Mg + Al5Mg11Zn4) and (α-Al + Mg32(Al, Zn)49) structures, and the other primarily consisted of (α-Mg + Al5Mg11Zn4), (MgZn2 (main) + β-Zn), and (β-Zn (main) + MgZn2) structures. In the interface zone, the (α-Mg + Al5Mg11Zn4) structure was the most abundant structure, and the MgZn2 intermetallic compound had the highest microhardness of 327 HV. When the arc-spraying time of the Zn coating was 30 s and the preheat time of the Al/Zn double-deck coating was 6 h, the shear strength of the arc-sprayed Al/AZ91D bimetal reached 31.73 MPa. Most rupture of the arc-sprayed Al/AZ91D bimetals with a Zn interlayer occurred at the (α-Mg + Al5Mg11Zn4) structure and presented some typical features of brittle fracture.

Multi-Objective Parameter Optimization for Disc Milling Process of Titanium Alloy Blisk Channels

The blisk has been widely used in modern high performance aero-engines of high thrust-weight ratio. Disc milling process provides a reliable way to improve the efficiency of the blisk milling. The process parameters of disc milling have crucial effects on the milling efficiency and physical property of blisk. In this paper, material removal rate, cutter life and thickness of residual stress layer are regarded as optimization targets the key process parameters such as spindle speed, cutting depth and feed speed are optimized. Based on the grey relational analysis, the multi-objective optimization problem is transformed into a single objective optimization problem. At the same time, the problem of non-symmetry influence of key process parameters on optimization targets can be solved. And the influence weight of material removal rate, cutter life and thickness of residual stress layer on the grey relational grade (GRG) are calculated according to principal component analysis. The second order prediction model of GRA is developed by response surface method. On the basis of verifying the accuracy of the model, the influence mechanism of the process parameters coupling on the gray correlation degree is analyzed the optimal process parameter combination is obtained as spindle speed with 81.92 rpm, cutting depth with 5.88 mm and feed rate with 66.0823 mm/min. The experimental research show that the optimal process parameter combination can effectively improve the material removal rate and cutter life and reduce the thickness of residual stress layer.

Experimental Investigation and Optimization of Direct Metal Laser Sintered CL50WS Material Using Desirability Function Approach

The aim of the this study to determine optimal process parameter for the hardness of direct metal laser sintering (DMLS) process as the hardness plays a significant role in to DMLS made components and die or mould. In this manner, research is focused around determining the effect of process parameters like laser power, scanning speed, layer thickness and hatch spacing on the hardness of CL50WS (maraging18Ni300 steel) material. A response surface methodology based numerical model was proposed to predict hardness, and the adequacy of the created model was checked through the analysis of variance technique. Additionally, optimized conditions were set up to maximize the hardness through the desirability function theory.

The Study of Characteristic Impedance of Conductive Transmission Line in FPC(Flexible Printed Circuit Board) Design and Process

To meet the demand of the signal stable at high speed, the key is control precision for the characteristic impedance of FPC. This article is intended to study the strip-line structure for reducing cross-talk (noise) and their theoretical analysis and calculation. By varying effect factor and countermeasure in the production process of FPC, and the optimal process parameter have been obtained. By using the some testing technology, the impedance of strip-line in FPC have been tested.

Process Control of Injection Molding Based on Multiscale Visualization Methodology - A Case Study

Multiscale visualization approaches are proposed to efficiently assist designers not familiar with statistical mathematics in determining the optimal process parameter schemes for achieving desired part quality in injection molding, based on which the parameters’ relative importance to part quality and their influence on either single quality index or comprehensive part quality can be visually described by the map of the sum of squared deviations, response surface diagram and distribution map of comprehensive part quality. The proposed visualization approaches are universal for analyzing the effects of process parameters on the quality of any injection-molded plastic parts although the mobile phone cover is utilized as an example in the presentation of our work.