Determination of optimal tool path in drilling operation using Modified Shuffled Frog Leaping Algorithm

Applications like boilerplates, food-industry processing separator, printed circuit boards, drum and trammel screens, etc. consists of a matrix of a large number of holes. The primary issue involved in hole-making operations is a tool travel time. It is often necessary to find the optimal sequence of operations so that the total processing cost of hole-making operations can be minimized. In this work, therefore an attempt is made to reduce the total tool travel of hole-making operations by applying a relatively new optimization algorithm known as modified shuffled frog leaping for determining the optimal sequence of operations. Modification is made in the existing shuffled frog-leaping algorithm by introducing three parameters with their positive values to widen the search capability of existing algorithms. A case study of the printed circuit board is considered in this work to demonstrate the proposed approach. Obtained results of optimization using modified shuffled frog leaping algorithm are compared with those obtained using particle swarm optimization, firefly algorithm and shortest path search algorithm

CNC PCB drilling machine using novel natural approach to euclidean TSP

Nowadays, many industries use the Computerized Numerical Control (CNC) for Printed Circuit Board (PCB) drilling machines in industrial operations. It takes a long time to find optimal tour for large number of nodes (up to thousands). To achieve more effective results, optimization systems approach is required to be equipped in drilling machine. Euclidean Traveling Salesman Problem (TSP) is one of optimization method that gives fast near optimal solution for the drilling machine movement using novel friendly techniques. This paper describes the development of that CNC PCB drilling machine with novel approach to Euclidean TSP. This design can be widely applied to various CNC PCB drilling machines in small and medium scale manufacturing industries

Tool Path Optimization of Drilling Sequence in CNC Machine Using Genetic Algorithm

Drilling is a one of the most common machining process. There are a lot of applications where drilling is used, like drilling of holes in the printed circuit boards. . CNC machines are used today to perform the drilling process. These machines are capital intensive, and their maximum utilization is due to their economic viability. An issue that affects the utilization of these machines is the drilling sequence, because usually there is a number of points that has to be visited. Determination of drilling sequence is similar to the Traveling Salesman Problem (TSP) and exhibits characteristics of an NP-hard problem. In this paper, a program to find the optimum shortest path was built, using Genetic Algorithm and Traveling Salesman Problem to shorten machining time for the drilling of a given group of holes and hence to reduce machining cost and improve CNC machining efficiency without degrading motion accuracy. The results showed the effectiveness of the genetic algorithm, and the machining time is reduced to around 50% in some cases and hence machining power and cost are reduced Keywords: GA, Tool Path Optimization, CNC, Drillin

Optimization of multi-holes drilling path using particle swarm optimization

Multi-hole drilling is a manufacturing process that is commonly used in industries. In this process, the tool movement and switching, on average, take 70% of the total machining time. There are many applications of multi-hole drilling, such as in mould, die-making and printed circuit board (PCB). One way to improve the multi-hole drilling is by optimising the tool path in the process. This research aims to model and optimise multi-hole drilling problems using Particle Swarm Optimisation (PSO) algorithm. The study begins by modelling the multi-hole drilling problems using the Travelling Salesman Problem (TSP) concept. The objective function was set to minimise the total tool path distance. Then, the PSO was formulated to minimise total length in multi-hole drilling. The main issue in this stage was to convert the continuous encoding in PSO to permutation problems as in multi-hole drilling. For this purpose, a topological sorting procedure based on the most prominent particle rule was implemented. The algorithm was tested on 15 test problems where between 10 to 150 holes were randomly generated. The performance of PSO was then compared with other meta-heuristic algorithms, including Genetic Algorithm (GA) and Ant Colony Optimisation (ACO), Whale Optimisation Algorithm (WOA), Ant Lion Optimiser (ALO), Dragonfly Algorithm (DA), Grasshopper Optimisation Algorithm (GOA), Moth Flame Optimisation (MFO) and Sine Cosine Algorithm (SCA). Then, a validation experiment was conducted by implementing the PSO generated tool path against the commercial CAD-CAM path. In this stage, the machining time was measured. The results from the computational experiment indicated that the proposed PSO algorithm came out with the best solution in 10 out of the 15 test problems. In the meantime, the validation experiment result proved that the PSO generated tool path provides faster machining time compared with the commercial CAD-CAM path by 5% on average. The results clearly showed that PSO has a great potential to be applied in the multi-hole drilling process. The findings from this research could benefit the manufacturing industry to improve their productivity using existing resources

Computer Numerical Control-PCB Drilling Machine with Efficient Path Planning – Case Study_2

In Printed Circuit Board (PCB) drilling machines, the location of the drill holes are fed into the machine and the PCB will be drilled at the corresponding coordinates. Some machines do not choose the optimal route when completing their tasks. Hence, this paper proposes an approach, which is based on the Algorithm Shortest Path Search Algorithm (SPSA), for finding the optimal route in PCB holes drilling process. In SPSA, when the robotic arm at the initial position, the algorithm calculates the nearest point to the initial position from all points that the wires starts or ends with. If the nearest point is a start-of-wire point, it will use SPS algorithm 1. If the nearest point is an end-of-wire point, it will use SPS algorithm 2. This process is repeated until drilling all the lines. Then, the robotic arm will drill all the holes according to the proposed Simulated Annealing Algorithm (AS) in order to determine the optimal machining parameters for milling operations. The results of the different optimization algorithms Genetic Algorithm (GA) and AS are compared and conclusions are presented. . The proposed Computer Numerical Control (CNC) machine consists of driver, drill, three stepper motors, cables and microcontroller PIC16f877A to control the movement of the machine. The SPSA algorithm optimizes the use of the motors and other mechanical paths involved in the process while reducing total time taken to traverse all the drill holes. This paper also explains the detailed problem of interest and the mathematical formulation of the problem is defined. Experimental result indicates that the proposed SPSA-based approach is capable to efficiently find the optimal route for PCB holes drilling process

A critical review of multi-hole drilling path optimization

Hole drilling is one of the major basic operations in part manufacturing. It follows without surprise then that the optimization of this process is of great importance when trying to minimize the total financial and environmental cost of part manufacturing. In multi-hole drilling, 70% of the total process time is spent in tool movement and tool switching. Therefore, toolpath optimization in particular has attracted significant attention in cost minimization. This paper critically reviews research publications on drilling path optimization. In particular, this review focuses on three aspects; problem modeling, objective functions, and optimization algorithms. We conclude that most papers being published on hole drilling are simply basic Traveling Salesman Problems (TSP) for which extremely powerful heuristics exist and for which source code is readily available. Therefore, it is remarkable that many researchers continue developing novel metaheuristics for hole drilling without properly situating those approaches in the larger TSP literature. Consequently, more challenging hole drilling applications that are modeled by the Precedence Constrained TSP or hole drilling with sequence dependent drilling times do not receivemuch research focus. Sadly, these many low quality hole drilling research publications drown out the occasional high quality papers that describe specific problematic problem constraints or objective functions. It is our hope through this review paper that researchers' efforts can be refocused on these problem aspects in order to minimize production costs in the general sense

DESIGN AND IMPLEMENTATION OF AN INTELLIGENT HEXAPOD

Robots are used to replace humans in some hazardous duty service like bomb disposal and capture information on places that cannot be reached. However, most of the robots used are wheeled robots. Walking machines have the potential to transverse rough terrain that is impossible for standard wheeled vehicles. The mobility of animals, including many insects is typically superior to current legged robots. However, the reality of current technology often encourages engineers to use different designs for the purposes of reducing the number of actuators or simplifying control problem. Thus, the main aim of this project is to design and implement a hexapod walking robot using servo drive mechanism and light weight material for easier control. The project includes constructing the hardware of the machine which is building the structure using appropriate material. The structure is built in the workshop by hand. All sawing and drilling is done using the equipment available in the workshop in Building 22, UTP. To have a stable and rigid structure, the machine is designed to be at its minimum size. This hexapod is designed to move using tripod gait controlled by 3 servo motors. The whole structure is controlled by microcontroller PIC16F877 programmed using C language. The hexapod is able to be controlled manually to move forward, reverse, turning left and right. The walking can be adjusted in 3 different speeds. This hexapod has the object avoidance intelligence using limit switches. The hexapod is able to reverse and find a new walking path if it encounters objects in front of it. With the wireless camera attached in front of the structure, it is able to be used for remote monitoring and rescue operations. The final design is cost effective, light, robust, has easy control and intelligently applicable

Application of traveling salesman problem in generating a collision-free tool path in drilling

In machining, the tool path is generated according to the workpiece geometry and arrangement of holes. Majority of Computer Aided Manufacturing (CAM) software offer a set of predefined strategies to choose from. These tool paths are mostly far from being the optimum path, specifically for complex geometries with non-flat surfaces. This thesis introduces a new algorithm based on Travelling Salesman Problem (TSP). The proposed local search algorithm generates an optimum collision free tool path in drilling operations. The developed optimization algorithm considers multiple constraints such as location of tool origin and presence of obstacles. Furthermore, a discussion on stopping criteria for the developed algorithm is presented. Obtained results confirm the proposed algorithm is capable of providing optimum collision free path with more than 50% reduction (in given examples) in path length compared to the HSMWorks software

The walking robot project

A walking robot was designed, analyzed, and tested as an intelligent, mobile, and a terrain adaptive system. The robot's design was an application of existing technologies. The design of the six legs modified and combines well understood mechanisms and was optimized for performance, flexibility, and simplicity. The body design incorporated two tripods for walking stability and ease of turning. The electrical hardware design used modularity and distributed processing to drive the motors. The software design used feedback to coordinate the system and simple keystrokes to give commands. The walking machine can be easily adapted to hostile environments such as high radiation zones and alien terrain. The primary goal of the leg design was to create a leg capable of supporting a robot's body and electrical hardware while walking or performing desired tasks, namely those required for planetary exploration. The leg designers intent was to study the maximum amount of flexibility and maneuverability achievable by the simplest and lightest leg design. The main constraints for the leg design were leg kinematics, ease of assembly, degrees of freedom, number of motors, overall size, and weight

Development of an electrochemical micromachining (μECM) machine

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.Electrochemical machining (ECM) and especially electrochemical micromachining (μECM) became an attractive area of research due to the fact that this process does not create any defective layer after machining and that there is a growing demand for better surface integrity on different micro applications such as microfluidics systems and stressfree drilled holes in the automotive and aerospace sectors. Electrochemical machining is considered as a non-conventional machining process based on the phenomenon of electrolysis. This process requires maintaining a small gap - the interelectrode gap (IEG) - between the anode (workpiece) and the cathode (tool-electrode) in order to achieve acceptable machining results (i.e. accuracy, high aspect ratio with appropriate material removal rate and efficiency). This work presents the design of a next generation μECM machine for the automotive, aerospace, medical and metrology sectors. It has 3 axes of motion (X, Y and Z) and a spindle allowing the tool-electrode to rotate during machining. The linear slides for each axis use air bearings with linear DC brushless motors and 2nmresolution encoders for ultra-precise motion. The control system is based on the Power PMAC motion controller from Delta Tau. The electrolyte tank is located at the rear of the machine and allows the electrolyte to be changed quickly. A pulse power supply unit (PSU) and a special control algorithm have been implemented. The pulse power supply provides not only ultra-short pulses (50ns), but also plus and minus biases as well as a polarity switching functionality. It fulfils the requirements of tool preparation with reversed ECM on the machine. Moreover, the PSU is equipped with an ultrafast over current protection which prevents the tool-electrode from being damaged in case of short-circuits. Two different process control algorithms were made: one is fuzzy logic based and the other is adapting the feed rate according to the position and time at which short-circuits were detected. The developed machine is capable of drilling micro holes in hard-to-machine materials but also machine micro-styli and micro-needles for the metrology (micro CMM) and medical sectors. This work also presents drilling trials performed with the machine with an orbiting tool. Machining experiments were also carried out using electrolytes made of a combination of HCl and NaNO aqueous solutions. The developed machine was used to fabricate micro tools out of 170μm WC-Co alloy shafts via micro electrochemical turning and drill deep holes via μECM in disks made of 18NiCr6 alloy. Results suggest that this process can be used for industrial applications for hard-to-machine materials. The author also suggests that the developed machine can be used to manufacture micro-probes and micro-tools for metrology and micro-manufacturing purposes.Brunel University European Commissio