The Effect of a Hollow Fixture on Energy Dissipation of Ultrasonic Welded Carbon Fiber/Polyamide 66 Composite

In this study, the effect of the fixture configuration on ultrasonic welding of 4-mm-thick carbon-fiber-reinforced polyamide 66 (CF/PA66) composite with 30% mass fiber was evaluated. An analytical model to estimate the energy dissipation in the welding zone of lapped CF/PA66 samples was derived. Calculation analyses showed the energy dissipation at the faying interface of joints made from hollow-fixture ultrasonic welding (HFUSW) was about 25% higher than those made from conventional ultrasonic welding (CUSW) under the given process variables. This was primarily attributed to the almost total reflection at the workpiece-to-fixture interface in HFUSW. Experimental results indicated that the HFUSW joints exhibited a greater peak load and weld area than CUSW joints when the weld time was less than 2.1 s. The optimal weld time for CUSW and HFUSW processes were 2.1 and 1.7 s. When the weld time exceeded the optimal time, the joints occurred with a porous region, which was caused by thermal decomposition of the material, resulting in the decrease in peak load. Experimental and simulation results demonstrated the HFUSW process changed the propagation behavior of the ultrasonic wave and enhanced the energy dissipation at the faying interface. This study enriched the understanding of energy dissipation during ultrasonic welding of polymers.

Optimization of Modular Fixture Layout by Minimizing Work-piece Deformation

Machining fixtures are utilized to locate and restrain a workpiece during different manufacturing processes. The workpiece must be properly located and clamped in order to have it to be manufactured according to the prescribed dimensions and tolerance. The real motive of fixture design is to maximize locating accuracy and workpiece firmness while minimizing deformations. The purpose of this research work is to conduct a multi-objective optimization in order to minimize workpiece deflections due to clamping forces and optimized fixture layout by taking into consideration the boundary conditions and loads applied during a machining process. The locators are employed in a 3-2-1 fixture configuration. Then the empirical relations are used to calculate the machining forces and moments generated during drilling and milling processes and after that the workpiece is loaded to model those cutting forces. ANSYS parametric design language (APDL) code which made use of sub-approximation method is utilized to automatically optimize locator and clamp positions. Afterwards the clamping forces are being optimized using balancing force-moment method. Lastly, the maximum deformation of the workpiece against the optimum clamping forces is found by harmonic analysis.

Modeling and performance analysis of machining fixture for near-net-shaped jet engine blade

PurposeNear-net-shaped processes of jet engine blade have better performance in both reducing the material waste during production and improving work reliability in service, while the geometric features of blade, both sculptured surface and thin-walled shape, make the precise machining of blade challenging and difficult owing to its dynamics behaviors under complex clamping and machining loads. This paper aims to present a fundamental approach on modeling and performance analysis of the blade–fixture system.Design/methodology/approachA computerized framework on the complex blade–fixture dynamic behavior has been developed. Theoretical mechanic analysis on blade fixturing and machining is proposed with an especial emphasis on the boundary conditions of the blade–fixture system. Then the finite element analysis (FEA) method is used to simulate the variation trend of preloads, stiffness and blade distortion. The strong influence of parameters of workpiece–fixture configuration on blade distortion and machining error is investigated.FindingsWith a case of real jet engine blade machining, the experimental results and theoretical predictions suggest good agreement on their variation tendency. The loaded pressure of clamps has a critical influence on the total stiff performance of the blade–fixture system, and the profile error of the blade contributes much to the inconsistency in geometric dimension and surface integrity of blades’ machining. In the end, the results also validate the effectiveness of this methodology to predict and improve the performance of the blade–fixture configuration design.Originality/valueThe adaptive machining of near-net-shaped jet engine blade is a new high-performance manufacturing technology in aerospace production. This study provides a fundamental methodology for the performance analysis of blade-fixture system, to clear the variation law of blade distortion during preloading and machining, which will contribute to minimize the machining error and improve productivity.

Design of Fixture for Pitch Circle Diameter Run-out Check

The design of fixture is an exceptionally mind boggling and natural process, which require learning and knowledge. Fixture configuration assumes an imperative part at the setup arranging stage. Appropriate fixture configuration is urgent for creating item quality in various terms of exactness, surface complete and accuracy of the machined parts. In existing plan the installation set up is done physically, so the point of this undertaking is to supplant with installation to spare time for stacking and emptying of segment. Apparatuses are ordinarily grouped by the kind of machine on which they are utilized. Installations can likewise be recognized by a sub arrangement. For instance, if an installation is intended to be utilized for examination called as inspection apparatus. By using the new designed fixture, run-out checking become easier and process becomes simpler.

SETUP GENERATION USING NEURAL NETWORKS

The article presents an unsupervised learning algorithm that groups technological features in a setup for machining process. Setup generation is one of the most important tasks in automated process planning and in fixture configuration. A setup is created based on approach direction of the features. The algorithm proposed in this work generates a neural network that determines the setup each feature belongs to, and the number of setups generated is minimal. This algorithm, unlike others, is not influenced by the order of the input sequence. Parallel implementation of the algorithm is straightforward and can significantly increase the computational performance.

Variation Analysis of Sheet Metal Assemblies with Fixture Configuration

The dimensional quality of auto-body relates to the whole external appearance and wind noise, the effect of closing the door and even driving smoothness of vehicles. The deviation propagation can be analyzed through the method of influence coefficient (MIC). However, fixture deviation usually impacts on the assembly variation than part variation. A variation analysis modeling with fixture configuration is presented to improve the current variation analysis efficiency of sheet metal parts. The variation change process of part, fixture and assembly was analyzed by researching the locating and assembly process of sheet metal parts. The linear relationships among variations of parts, fixtures and assemblies are established with two locating principles of “N-2-1” and “3-2-1”. Moreover, in accordance with the different release modes of the fixture locating points after the assembly, the assembly variation modeling is established in the two modes of over-constrained release and full release. Finally, a case of sheet metal assembly is illustrated to show the effectiveness of the assembly variation analysis modeling.