Optimization of a Sequence for Multi-Cutting Tool Operations in CNC Machines

Optimizing the sequence of operations (SOS) is important factor in improving the productivity of machines and reducing the production cost. However, CNC programing packages are available and have been significantly improved program generation for CNC machines, but in most of these packages the SOS optimization is not considered. This paper, introduce an efficient solution to optimized SOS for multi-cutting tools operations located asymmetrically. A well-known genetic algorithm (GA) is utilized to solve the SOS problem. After optimizing SOS, its related CNC program will be generated. The operation locations are considered as cities of Traveling Salesman Problem (TSP), and the cutting tool is considered as traveling salesman, by this way, TSP methodology can be modified to formulate the SOS problem. GA and the modified TSP can be incorporated into CNC programming packages to optimize the SOS before the program generation

Second Order Sliding Mode Control of the Coupled Tanks System

Four classes of second order sliding mode controllers (2-SMC) have been successfully applied to regulate the liquid level in the second tank of a coupled tanks system. The robustness of these classes of 2-SMC is investigated and their performances are compared with a first order controller to show the merits of these controllers. The effectiveness of these controllers is verified through computer simulations. Comparison between the controllers is based on the time domain performance measures such as rise time, settling time, and the integral absolute error. Results showed that controllers are able to regulate the liquid level with small differences in their performance

Hybrid Integrated System for Air Bending Optimal Design

Genetic algorithm (GA) is widely accepted method for handling optimization problems. GA can find optimal solutions for large and irregular search spaces. However, finding optimal solutions using GA is associated with high computational time when coupled with finite element (FE) code, since FE analysis should be applied to each individual of GA populations. A neural network metamodel (NNM) is introduced to reduce the computational time.GA utilizes the NNMas an approximation tool instead of FE. Application examples results show that the metamodelcan be used efficiently to obtainthe optimal process parameters of metal forming operations with large saving in time

Optimization of the Parameters of RISE Feedback Controller Using Genetic Algorithm

A control methodology based on a nonlinear control algorithm and optimization technique is presented in this paper. A controller called “the robust integral of the sign of the error” (in short, RISE) is applied to control chaotic systems. The optimum RISE controller parameters are obtained via genetic algorithm optimization techniques. RISE control methodology is implemented on two chaotic systems, namely, the Duffing-Holms and Van der Pol systems. Numerical simulations showed the good performance of the optimized RISE controller in tracking task and its ability to ensure robustness with respect to bounded external disturbances

Comparative Study of Non-Productive Tool Path Length for Contour Parallel Machining / Haslina Abdullah...[et al.]

Reduction of machining time is significant for increasing the efficiencies of a machining process. It can be minimized by the rise with the cutting speed or decrease the tool path length. This paper presents an optimization method of non-productive tool path length during contour parallel offset machining by minimizing the tool retraction based on Ant Colony Optimization (ACO). The optimization of the tool retraction is modeled as an application of the Travelling Salesman Problem (TSP). To assess the performance of the proposed method, the length of the non-productive tool path obtained by ACO is compared with traditional computer-aided manufacturing (CAM) software. It can be ascertained that the ACO method generates a non-productive tool path length that is approximately 20% better than the conventional method

Effect of different cooling strategies on surface quality and power consumption in finishing end milling of stainless steel 316

In this paper, an experimental investigation into the machinability of AISI 316 alloy during finishing end milling operation under different cooling conditions and with varying process parameters is presented. Three environmental-friendly cooling strategies were utilized, namely, dry, minimal quantity lubrication (MQL) and MQL with nanoparticles (Al$_{2}$O$_{3}$),and the variable process parameters were cutting speed and feed rate. Power consumption and surface quality were utilized as the machining responses to characterize the process performance. Surface quality was examined by evaluating the final surface roughness and surface integrity of the machined surface. The results revealed a reduction in power consumption when MQL and MQL + Al$_{2}$O$_{3}$ strategies were applied compared to the dry case by averages of 4.7% and 8.6%, respectively. Besides, a considerable reduction in the surface roughness was noticed with average values of 40% and 44% for MQL and MQL + Al$_{2}$O$_{3}$ strategies, respectively, when compared to the dry condition. At the same time, the reduction in generated surface roughness obtained by using MQL + Al$_{2}$O$_{3}$condition was marginal (5.9%) compared with using MQL condition. Moreover, the results showed that the improvement obtained in the surface quality when using MQL and MQL + Al$_{2}$O$_{3}$ coolants increased at higher cutting speed and feed rate, and thus, higher productivity can be achieved without deteriorating final surface quality, compared to dry conditions. From scanning electron microscope (SEM) analysis, debris, furrows, plastic deformation irregular friction marks, and bores were found in the surface texture when machining under dry conditions. A slight smoother surface with a nano-polishing effect was found in the case of MQL + Al$_{2}$O$_{3}$ compared to the MQL and dry cooling strategies. This proves the effectiveness of lubricant with nanoparticles in reducing the friction and thermal damages on the machined surface as the friction marks were still observed when machining with MQL comparable with the case of MQL + Al$_{2}$O$_{3}$

Principles and Characteristics of Different EDM Processes in Machining Tool and Die Steels

Electric discharge machining (EDM) is one of the most efficient manufacturing technologies used in highly accurate processing of all electrically conductive materials irrespective of their mechanical properties. It is a non-contact thermal energy process applied to a wide range of applications, such as in the aerospace, automotive, tools, molds and dies, and surgical implements, especially for the hard-to-cut materials with simple or complex shapes and geometries. Applications to molds, tools, and dies are among the large-scale initial applications of this process. Machining these items is especially difficult as they are made of hard-to-machine materials, they have very complex shapes of high accuracy, and their surface characteristics are sensitive to machining conditions. The review of this kind with an emphasis on tool and die materials is extremely useful to relevant professions, practitioners, and researchers. This review provides an overview of the studies related to EDM with regard to selection of the process, material, and operating parameters, the effect on responses, various process variants, and new techniques adopted to enhance process performance. This paper reviews research studies on the EDM of different grades of tool steel materials. This article (i) pans out the reported literature in a modular manner with a focus on experimental and theoretical studies aimed at improving process performance, including material removal rate, surface quality, and tool wear rate, among others, (ii) examines evaluation models and techniques used to determine process conditions, and (iii) discusses the developments in EDM and outlines the trends for future research. The conclusion section of the article carves out precise highlights and gaps from each section, thus making the article easy to navigate and extremely useful to the related research communit