نتایج جستجو برای: resource efficiency machining
تعداد نتایج: 596351 فیلتر نتایج به سال:
optimization of machining parameters is very important and the main goal in every machining process. surface finishing prediction is a pre-requirement to establish a center for automatic machining operations. in this research, a neuro-fuzzy approach is used in order to model and predict the surface roughness in dry turning. this approach has both the learning capability of neural network and li...
As an innovative and cost-effective method for carrying out multiple-axis CNC machining, 3 1 2 1 2 -axis CNC machining technique adds an automatic indexing/rotary table with two additional discrete rotations to a regular 3-axis CNC machine, to improve its ability and efficiency for machining complex sculptured parts. In this work, a new tool path generation method to automatically subdivide a c...
This paper presents a methodology to be employed in the whole process design phase including first and second processing. This methodology consists of a set of steps which are characterised by an independent model. This paper’s objective is to analyse the coherence between the different models and the coherence between the model and the objectives of each step. The final stage is to develop the...
Ultrasonic machining (USM) is a mechanical material removal process used to erode holes and cavities in hard or brittle work pieces by using shaped tools, high-frequency and an abrasive slurry. This paper addresses the concept and development of an expert system (ES) for hard and brittle material, such as glass, quartz, diamond, carbides, semi conducting materials, ceramic and graphite which ca...
In 5-axis finish cut of freeform surfaces, drastic change in tool postures is harmful in many aspects. On the premise of no machining interference, it is desirable to generate ‘smooth’ tool-paths with confined posture change between cutter contact (CC) points. In this paper, interference-free tool-paths are first generated based on a heuristic aiming at better machining efficiency. For the prob...
This research proposes an optimized magnetic abrasive machining process that uses an ultra-high-speed system to perform precision machining on a workpiece. The system can process several microns of material, either for machining surface roughness or for machining a workpiece for a precise micro-diameter. The stainless steel workpieces have been machined using an ultra-high-speed magnetic abrasi...
aluminium matrix composites (amcs) materials are continuously displacing traditional engineering materials because of their advantages of high stiffness and strength over homogeneous material formulations. properties of amcs can be tailored to the demands of different industrial applications by suitable combinations of matrix, reinforcement and processing route. presently, several grades of amc...
In the rough-cut stage of sculptured surface machining, using rough-cut models with simple geometric complexity to generate tool paths could effectively reduce the machining time and improve the machining efficiency. In this paper, a 3D rough-cut model generation algorithm for sculptured surface machining is presented. The proposed algorithm is based on offset and multi-resolution mesh. Offsett...
In the finishing process of optical glass, polishing with ceria, silica or zirconia slurry is conventionally adopted. The machining process, however, has problems involving inefficiency and a detrimental impact on the environment. Therefore, it is strongly recommended that the process be replaced with fixed-abrasive machining, but conventional fixed-abrasive tools have problems relating to low ...
Optimization of machining parameters is very important and the main goal in every machining process. Surface finishing prediction is a pre-requirement to establish a center for automatic machining operations. In this research, a neuro-fuzzy approach is used in order to model and predict the surface roughness in dry turning. This approach has both the learning capability of neural network and li...
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