Simulation of ant colony optimization on hole making performance

Hole making operation one of machining process widely used in industrial industry. One of the main criteria in determining the efficiency of machining performance in hole making operation is shortest machining time. In this paper, simulation approach based on Ant colony optimization (ACO) has been done on hole making operation in order to minimize the machining time. The result based on ACO has been compared with the result obtain based on Genetic Algorithm (GA). Based on the simulation results, the ACO is enhance the performance of hole making process by reducing 13.5% of machining time. The results show that ACO is capable to minimize the machining time of hole making procees

The effects of machining process variables and tooling characterisation on the surface generation: modelling, simulation and application promise

The paper presents a novel approach for modelling and simulation of the surface generation in the machining process. The approach, by integrating dynamic cutting force model, regenerative vibration model, machining system response model and tool profile model, models the complex surface generation process. Matlab Simulink is used to interactively perform the simulation in a user-friendly, effective and efficient manner. The effects of machining variables and tooling characteristics on the surface generation are investigated through simulations. CNC turning trials have been carried out to evaluate and validate the approach and simulations presented. The proposed approach contributes to comprehensive and better understanding of the machining system, and is promising for industrial applications with particular reference to the optimisation of the machining process based on the product/component surface functionality requirements

Manufacturing Process Modeling and Simulation

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 production plans. The casting process was the first one to be analyzed. Casting models were created using CAD software (Catia V5R17) and imported into the casting simulation environment (Magmasoft). Filling and solidifying processes have been simulated using different casting models in order to optimize the final configuration. The machining process was modeled using the machining features concept and it was simulated using Catia’s Advanced Machining environment. Two machining strategies have been analyzed according to positioning strategies. Process engineering software was used to create the process plans and to analyze the resource allocation

A simulated investigation on the machining instability and dynamic surface generation

In this paper, the authors propose the generic concept of machining instability based on the analysis of all kinds of machining instable behaviors and their features. The investigation covers all aspects of the machining process, including the machine tool structural response, cutting process variables, tooling geometry and workpiece material property in a full dynamic scenario. The paper presents a novel approach for coping with the sophisticated machining instability and enabling better understanding of its effect on the surface generation through a combination of the numerical method with the characteristic equations and using block diagrams/functions to represent implicit equations and nonlinear factors. It therefore avoids the lengthy algebraic manipulations in deriving the outcome and the solution scheme is thus simple, robust and intuitive. Several machining case studies and their simulation results demonstrate the proposed approach is feasible for shop floor CNC machining optimisation in particular. The results also indicate the proposed approach is useful to monitor the machining instability and surface topography and to be potentially applied in adaptive control of the instability in real time

機械加工シミュレーションを用いた多軸加工教育の展開

Educational program of multispindle machining has been developed by using of VERICUT CNC simulation. VERICUT simulation demonstrated machining process in workshop practice class of department of mechanical engineering. Students took a view of tool motion and material removal process on screen effectively. Consequently, it was found that VERICUT simulation have a useful role in the education of multispindle machining

Finite element simulation of machining AISI 1045 steel using uncoated carbide tool

In recent years, finite element methods (FEM) have become widely used in research and industrial applications because of the advancements in computational efficiency and speed. FEM is a useful tool for the analysis of metal cutting process where this method provide better prediction of process variables whereas interaction of the tool and the chip can also be examined. Much cutting force models have been developed to predict the machining parameter. Most focus mainly on dry conditions even though coolants are widely used in practical machining. Research for modeling of minimal quantity lubricant (MQL) conditions is scarce and not really established. The use of coolants in machining makes it very difficult to determine the friction coefficient at the tool-chip interface. Hence, a better understanding of friction modeling is required in order to produce more realistic finite element models of machining process. In this study, a rigorous investigation on the role played by the implemented friction model within a 2D simulation was carried out. The simulation tool used for the purpose of this study is DEFORM2D. DEFORM 2D can simulate large deformation accompanied by elastic, plastic, thermal and friction effects. The simulation results on cutting forces and temperature were compared with experimental measurement in order to verify wether it is possible to identify the best friction model and indicate the consistency and accuracy of the results when conducting the comparison. From the result, it shows that friction models affect predicted result for both cutting force and temperature in dry and MQL conditions

Process simulation for 5-axis machining using generalized milling tool geometries

Multi-axis machining (especially 5-axis machining) is widely used in precision machining for automotive, aerospace and die-mold manufacturing. The goal in precision machining is to increase production while meeting high part quality needs which can be achieved through decision of appropriate process parameters considering machine tool constraints (such as power and torque), chatter-free operations and part quality. In order to predict and decide on optimal process parameters, simulation models are used. In the literature, individual tool geometries for multi-axis machining are examined in detailed with different modeling approaches to simulate cutting forces. In this study, a general numerical model for 5-axis machining is proposed covering all possible tool geometries. Tool envelope is extracted from CAD data, and helical flutes points are represented in cylindrical coordinates. Equal parallel slicing method is utilized to find cutter engagement boundaries (CEB) determining cutting region of the tool surface. for each axial level in the tool axis direction. For each level uncut chip thickness value is found and total forces are calculated by summing force values for each point along the cutting flutes. For arbitrary cases forces are simulated and obtained results are experimentally verified

DIFFERENTIAL EVOLUTION FOR OPTIMIZATION OF PID GAIN IN ELECTRICAL DISCHARGE MACHINING CONTROL SYSTEM

ABSTRACT PID controller of servo control system maintains the gap between Electrode and workpiece in Electrical Dis- charge Machining (EDM). Capability of the controller is significant since machining process is a stochastic phenomenon and physical behaviour of the discharge is unpredictable. Therefore, a Proportional Integral Derivative (PID) controller using Differential Evolution (DE) algorithm is designed and applied to an EDM servo actuator system in order to find suitable gain parameters. Simulation results verify the capabilities and effectiveness of the DE algorithm to search the best configuration of PID gain to maintain the electrode position. Keywords: servo control system; electrical discharge machining; proportional integral derivative; con- troller tuning; differential evolution

Intelligent feature based resource selection and process planning

Lien vers la version éditeur: https://www.inderscience.com/books/index.php?action=record&rec_id=755&chapNum=3&journalID=1022&year=2010This paper presents an intelligent knowledge-based integrated manufacturing system using the STEP feature-based modeling and rule based intelligent techniques to generate suitable process plans for prismatic parts. The system carries out several stages of process planning, such as identification of the pairs of feature/tool that satisfy the required conditions, generation of the possible process plans from identified tools/machine pairs, and selection of the most interesting process plans considering the economical or timing indicators. The suitable processes plans are selected according to the acceptable range of quality, time and cost factors. Each process plan is represented in the tree format by the information items corresponding to their CNC Machine, required tools characteristics, times (machining, setup, preparatory) and the required machining sequences. The process simulation module is provided to demonstrate the different sequences of machining. After selection of suitable process plan, the G-code language used by CNC machines is generated automatically. This approach is validated through a case

Simulation study for investment decisions on the EcoBoost camshaft machining line

Design/redesign of manufacturing systems is a complex, risky, and expensive task. Ford Motor Company’s Valencia Engine Plant faces this challenge as it plans to upgrade its machining and assembly lines to introduce the new EcoBoost engines. The research project described in this paper aimed to support the transition process particularly at the camshaft machining line by using simulation modelling techniques. A series of experiments was carried out using the simulation model developed, and recommendations were proposed based on the results of these experiments to support the decision as to where to invest on the line. The outcomes from the research project indicated that investment is required in terms of increasing the capacity of two bottleneck operations through retooling and improving the conveyor routing logic in one key area. Keywords: simulation modelling, closed-loop network, automotive production system