This article proposes an effective methodology to reduce manufacturing time through the creation of quasi-optimal G command sequences, based on initial machining codes derived from CAD/CAM Service-Oriented Architecture (SOA) software The optimization steps involved minimizing travel path time for CNC manufacturing machine milling and drilling Also, identifying the optimal order of operation that enabled the shortest travel path for the cutting tool These steps resulted in consistent enhancements of approximately 1041% and 1658% for milling and drilling machining, respectively Furthermore, high-performing Ant Colony Optimization (ACO) algorithms were used to optimize the travel path time In the context of automatic NC program production, the optimization of the cutting tool’s travel path could be achieved by integrating the ACO algorithm and the Open Architecture Control (OAC) into commercial CAD/CAM In this paper, a new optimized generation of CNC systems, based on combining the Open Architecture Control (OAC) technology supported by the G-code data model and the optimization algorithm are presented

A novel integrating between tool path optimization using an ACO algorithm and interpreter for open architecture CNC system

Today, in most of metal machining process, Computer Numerical Control (CNC) machine tools have been very popular due to their efficiencies and repeatability to achieve high accuracy positioning. One of the factors that govern the productivity is the tool path travel during cutting a work piece. It has been proved that determination of optimal cutting parameters can enhance the machining results to reach high efficiency and minimum the machining cost. In various publication and articles, scientist and researchers adapted several Artificial Intelligence (AI) methods or hybrid method for tool path optimization such as Genetic Algorithms (GA), Artificial Neural Network (ANN), Artificial Immune Systems (AIS), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). This study presents a review of researches in tool path optimization with different types of AI methods that show the capability of using different types of optimization methods in CNC machining process.

Application of Artificial Intelligence Methods of Tool Path Optimization in CNC Machines: A Review

To automatically detect SMT (surface mount technology) electronic modules, algorithms are investigated for geometry and shape features, module matching and detection in PCB (printed-circuit board) components. First, geometry and shape features of SMT electronic modules are presented. Then matching technology and process for SMT electronic modules are studied through optimization searching algorithms, such as similarity based detection and pyramid algorithms. Based on the analysis of major defects, algorithms for detecting major defects in SMT electronic modules are investigated. Finally, the crucial factors affecting inspection precision and speed, i.e., components contour, searching range and minimum similarity, are analyzed. The experimental results show the detection time for Circuit Boards without defect is 0.82s, and for those with one component absent 0.89s, yet for multiple components absent 10.68s. Therefore, it can satisfy the requirements of high reliability, stability, precision, inspection speed and anti-interference for defect detection in SMT electronic module of Circuit Boards.

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Defect Detection of SMT Electronic Modules

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Application of Artificial Intelligence Methods of Tool Path Optimization in CNC Machines

This study is concerned with a precedent-oriented approach to structural designing of configured templates of airplane parts. The specificity of the approach is defined by the use of means for simulating the template from the viewpoint of its computer numerical control programming (CNC-programming). The simulation is implemented with the use of template reflections on a semantic memory that supports pseudo code programming of CNC-processes.

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A Precedent-Oriented Simulation In Designing The Templates Of Airplane Parts.

In CAD/CAM integration system, the problem of the path optimization to be thorough researched Through numerical describe of information elements, by using graph theory of traveling salesman problem，set up the mathematical model of path optimization problem Based on ant colony algorithm and lin-kernighan (LK) algorithm, an intelligence fusion algorithm is put forward With group of holes processing as an example, the group of holes drilling tool path of optimized, and realize the CAD/CAM many features of optimization, which greatly improve the processing precision and efficiency

Application of Intelligence Fusion Algorithm in Path Optimization Problem

The rapid growth of modern technology place greater demand on electronic products’ performance and quality. As for the printed circuit board (PCB) assembly of electronic components through surface mounting technology (SMT), high-pixel charge coupled device (CCD) can only screen local images during image collection because of its limited vision. A rapid image mosaic technology has been proposed to seamlessly stitch the local images with overlapping boundaries. The complete image of PCB assembly has been acquired through rapid area matching method within double Mark points and Mark circle. The experiment results show that this method can greatly reduce the image-mosaic time and fairly improve the real-time performance of modern automatic optical inspection (AOI) equipment. Furthermore, such method avoids the alignment error from the characteristic points for noise jamming or noise shielding, and therefore obtains better robustness.

Study on Image Mosaic and Registration of Electronic Component through Surface Mounting Technology

With the development of digitalized manufacturing (DM), on-machine inspection (OMI) has become the key link of integrated quality system in DM. In DM, The detection and monitoring system chiefly dealing with kinds of parameters in machining process, taking on-line detection, analyzing the process quality information and carrying out corresponding quality assurance, so the quality of product may be assured and DM can be run in good condition. Therefore, the OMI technology of machining center based is researched. The framework of OMI and the hardware structure of special driving card for probe or tool (SDCPT) are described. Computer aided inspection planning (CAIP) is the integration bridge between CAD/CAM and computer aided inspection. A feature-based CAIP system for OMI is proposed to inspect the complicated mechanical parts efficiently during machining or after machining. The CAIP system is designed to produce an inspection process planning directly from CAD model. The prototype CAIP system includes the tolerance feature analysis, accessibility analysis, feature identification, measurement planning, and collision detection. The CAIP system can minimize the number of part setups and probe orientations and the inspection feature sequence.

Shi Gang Wang

Papers

Application of Intelligence Fusion Algorithm in Path Optimization Problem

Study on Image Mosaic and Registration of Electronic Component through Surface Mounting Technology

Study on On-Machine Inspection Technology of Machining Center Based