Charged system search algorithm for robotic drill path optimization

Charged System Search Algorithms for Optimal Tuning of PI Controllers

Motion estimation has a critical role to play in the transmission and compression of digital video. As it has a complexity in terms of computation that is inherent it is a big challenge for the implementation of real time codes. Recently there have been studies on block matching algorithms (BMA) for bringing down the complexity in the computation and has also got better attention in many algorithms that are very effective for very large scale integration (VLSI) systems for bringing down the complexity. These BMA algorithms are relatively easy to implement which can give solutions that are suboptimal even if the entire search has not been performed. The entire search is high in terms of cost of computation that prevents it from being applied in the systems of VLSI. A novel and fast motion estimation based algorithm known as charged system search (CSS) and full search algorithm (FSA) for multipliers of low power and for H.264 encoders is proposed. The CSS is used in all fields of optimization and is well suited for most domains and does not require any gradient information. The results have proved that proposed FSA has better performance.

This paper presents a developed meta-heuristic algorithm to optimize the shear walls of tall reinforced concrete buildings. These types of walls are considered as lateral resistant elements. In this paper, Quantum Charged System Search (QCSS) algorithm is presented as a new optimization method and used to improve the convergence capability of the original Charged System Search. The cost of tall building is taken as the objective function. Since the design of the lateral system plays a major role in the performance of the tall buildings, this paper proposes a unique computational technique that, unlike available works, focuses on structural efficiency or architectural design. This technique considers both structural and architectural requirements such as minimum structural costs, torsional effects, flexural and shear resistance, lateral deflection, openings and accessibility. The robustness of the new algorithm is demonstrated by comparing the outcomes of the QCSS with those of its standard algorithm.

A damage-based seismic design procedure for steel frame structures is formulated as an optimization problem, in which minimization of the initial construction cost is treated as the objective of the problem. The performance constraint of the design procedure is to achieve repairable damage state for earthquake demands that are less severe than the design ground motions. The Park-Ang damage index is selected as the seismic damage measure for the quantification of structural damage. The charged system search (CSS) algorithm is employed as the optimization algorithm to search the optimum solutions. To improve the time efficiency of the solution algorithm, two simplifying strategies are adopted: first, SDOF idealization of multi-story building structures capable of estimating the actual seismic response in a very short time; second, fitness approximation decreasing the number of fitness function evaluations. The results from a numerical application of the proposed framework for designing a twelve-story 3D steel frame structure demonstrate its efficiency in solving the present optimization problem.

With the rapid development of information technology, wireless sensor network(WSN) gradually permeates all walks of life. However, WSN is always out of work because of too much energy consumption on certain sensor nodes. This paper presents a new protocol based on parallel charged system search(PCSS) algorithm to balance energy consumption during WSN transmission. Firstly, a novel optimization algorithm named PCSS is presented based on two communication strategies with different conditions. First experiments on 10 benchmark functions in different dimensions demonstrate that the PCSS shows an excellent ability of convergency compared to CSS and PSO and the advantage of PCSS in quickly finding optimum is more obvious with the increasing of dimension. After that, a new clustering model based on PCSS(PCSS-C) is introduced to update cluster heads dynamically according to a designed fitness function, another experimental results illustrate that the proposed protocol is superior to low-energy adaptive clustering hierarchy, LEACH-centralized, and hybrid energy-efficient distributed clustering.

This study aims to improve the performance of the Crayfish Optimization Algorithm (COA), a swarm intelligence algorithm recently introduced in the literature, on various test functions with fixed and variable dimensions. Optimization can be defined as making a system as efficient as possible at the least cost, within certain constraints. Numerous optimization algorithms have been designed in the literature to obtain the best solutions for specific problems. The most critical aspects in solving these problems are modeling the problem correctly, determining the parameters and constraints, and selecting an appropriate meta-heuristic algorithm for solving the objective function. Not every algorithm is suitable for every problem structure. While some algorithms solve fixed-dimension test functions better, others may perform better on variable-dimension test functions. In this study, the COA algorithm's performance was evaluated on 10 test functions previously used in the literature, consisting of three fixed-dimension functions (Schaffer Function, Himmelblau Function, Kowalik Function) and seven variable-dimension functions, including one unimodal (Elliptic Function) and six multimodal functions (Non-Continuous Rastrigin Function, Alpine Function, Levy Function, Weierstrass Function, Michalewicz Function, Dixon & Price Function). The solution values obtained for each of the selected functions were compared with the solutions obtained using the Harris Hawks Optimizer (HHO), the Charged System Search Algorithm (CSS), and the Backtracking Search Optimization Algorithm (BSA).

Charged System Search Algorithm

The estimation of low and high-pass active filter parameters with opposite charged system search algorithm

Purpose The purpose of this paper is to study the movement characteristics of micro drill bit during entry period in printed circuit board (PCB) high-speed drilling and to present an effective method to conduct quantitative analysis of the wandering of drill bit based on high-speed video capturing. Design/methodology/approach Based on the high-speed camera technology, experiments are conducted to get a series of time sequence images and the wandering of micro drill tip and the radial run-out of drill body, and the max-deformation of drill bit are calculated by using a quantitative analysis method. Finally, the movement characteristics of micro drill bit during entry drilling period PCB high-speed drilling are evaluated. Findings With the increasing spindle speed, the radial run-out of drill body decreases gradually, whereas the wandering amplitude of the drill point gradually increases; micro drill bit itself has an ability of positioning deviation correction after contacting the entry sheet; the feed rate within a certain range could slightly worsen the deformation of drill tip at the instant of impingement. Research limitations/implications With the improvement of spindle speed, the camera’s shooting speed needed will increase accordingly, thus, the resolution of the pictures will decline, which always affects the analysis precision. Originality/value A series of effective methods to conduct quantitative analysis of the wandering micro drill bit by using high-speed camera technology is presented; a reference for the optimization of micro-hole drilling is provided.

Automatic optical inspection (AOI) of micro drill bit becomes more and more important with the rapid expanding of printed circuit board (PCB) manufacturing industry. Distinguished from most traditional manual inspection approach, AOI is time-saving, objective and non contact. In this work, a pattern classification method is proposed for the AOI of micro drill bit in PCB manufacturing, in which three features of drill bit blade are extracted for classification. In order to be independent on the clamp that can guarantee the exact position of drill bit blade for photography, and reduce the cost of the AOI system, an image registration method is used to align the drill bit blade, which can also make the feature extraction much easier. The evaluation result indicates that the approach works well for the AOI of micro drill bit. It is real time, more detailed result providing and low requirement on photographic device.

Determination of the optimal path sequence in a multi-hole drilling operation is a challenging task in a manufacturing industry as it facilitates substantial reduction in tool travel distance (path length), machining time and machining cost. It is quite analogous to the travelling salesman problem, which is one of the most fundamental NP-hard optimization problems. In this paper, six well-known metaheuristics, i.e. ant colony optimization, artificial bee colony algorithm, particle swarm optimization, firefly algorithm, differential evolution and teaching learning-based optimization algorithm are applied to determine the optimal path sequences in computer numerically controlled multi-hole drilling operations. Two layouts consisting of four and five concentric circular patterns, and a heat exchanger tube sheet with 2600 holes are considered here as three different test problems. The minimum drill path lengths as estimated using these algorithms are observed to be better than that as determined by the spiral path method. Amongst them, teaching learning-based optimization algorithm performs best with respect to the derived optimal path length, consistency of the solution, convergence speed and computational time. Its distinctiveness over the others is also validated using the paired t-test.

Charged System Search CSS is a new evolutionary algorithm inspired by the interaction between charged particles. This paper presents a modified CSS SACSS algorithm, which highly improves the performance of CSS and applies it to solve the unit commitment UC problem. In order to achieve better performance and higher speed in solving the UC problem, a self-adaptive reformation technique with tree updated schemes has been implemented. The proposed algorithm has been tested on 10, 20, 40 and 100 unit systems for one-day and scheduling horizon. The results are compared with the solutions obtained from other methods such as Lagrangian Relaxation LR, Genetic Algorithm GA, Particle Swarm Optimization PSO, Bacterial Foraging BF and Shuffled Frog Leaping Algorithm SFLA. The results show the high performance and convergence speed of SACSS.

The research object in the work is the printed circuit boards (PCB) Production technological process using the additive technology of photopolymer 3D printing. The existing problem is that the manufacturing process of single-sided and double-sided PCBs, simple in technology, from the third to the fifth accuracy class, requires the use of a large amount of consumables and technological equipment. In turn, this affects the cost of the product. The research subject is models and methods for manufacturing PCB using photopolymer 3D printing. In order to reduce the cost of materials: film or aerosol photoresist, as well as reduce the number of technological operations, applying photoresist and for the manufacture of PCBs stencils, it is proposed to use photopolymer 3D printing technologies for the manufacture of PCBs. The paper analyzes the costs of Plexiwire Resin Basic Orange Transparen photopolymer resin for the manufacture of single-sided PCBs and calculates the cost of the consumable (resin) compared to the costs of dry film photoresist. 60 % cost of consumables (photopolymer resin) compared to dry film photoresist for making single-sided PCBs. The work is aimed at determining the dependence of the geometric dimensions of the PСВs topology and the consumption of photopolymer resin on the technological parameters of photopolymer exposure. A regression correlation model of the dependence of resin consumption on exposure parameters has been developed and correlation coefficients have been calculated. It has been established that with an increase in the exposure time of the photopolymer resin, the consumption of the photopolymer resin increases and the deviation of the geometric dimensions of the PCBs topology increases, which in turn negatively affects the quality of the product. Therefore, using the obtained regression model, it is possible to calculate the influence of parameters on the PCB topology and reduce the deviation of conductor sizes and resin consumption.

There are many complex problems in the optimization of an electronics manufacturing environment, and it is the view of the authors that these problems should not be solved and optimized in isolation, but analysed in the framework of a system. A systems approach offers an overall approach for solving problems, and optimizing the whole of the system as well as discrete subsystems. The research introduced in this paper integrates several techniques, namely: Integrated computer aided manufacturing DEFinition (IDEF), and experimental design and response surface methods for the analysis, control and optimization of electronic manufacturing processes. Electronics manufacturing includes three major processes; Printed Circuit Board (PCB) manufacturing, semiconductor device manufacturing and electronics assembly. This paper describes a novel generic systematic methodology that has been used to create a model to optimize the photolithography process in PCB manufacture. For this, photolithography has been considered as a whole system made up of several sub-systems. This is shown in the process map for PCBs that focuses on photolithography and its subprocesses. A model of the manufacturing process is then given with the results of this being validated using an industrial study. Optimized settings for processing equipment are given resulting in an increase in process yield within industry.

The present paper describes the challenges and preliminary results obtained during the design and implementation of a disassembly system for capacitors placed on printed circuits boards. This research is included in an attempt to reduce the impact of the electronic waste. The proposed architecture includes a six axis multipurpose industrial robot, dedicated sensors and a custom built tool. An originally designed rotary tool, with a specific type of drill bit, was used to dismantle each capacitor on the board. A sensor triggers the tool for the drill rotation when the perforation is accomplished accordingly, so that the friction force is big enough to initiate the dismantling procedure. Using the rotation movement of the drill, at a calculated number of rotations, the capacitors are successfully dismantled from the printed circuits board. An artificial vision system composed from a stereo camera and an image-processing algorithm, provides data with regard to the position of each capacitor on the printed circuit board. A vacuum cleaner was integrated in the scheme to recover the capacitors after dismantling. The scheme design was perpetually optimized using dedicated simulation software. Also, preliminary results obtained on the physical system underline the potential advantages of the proposed approach.