scholarly journals Optimization of friction stud welding process parameters by integrated Grey-Fuzzy logic approach

2018 ◽  
Vol 16 (4) ◽  
Author(s):  
N. Rajesh Jesudoss Hynes ◽  
R. Kumar ◽  
P. Shenbaga Velu ◽  
J. Angela Jennifa Sujana
Keyword(s):  
Fuzzy Logic ◽  
Process Parameters ◽  
Welding Process ◽  
Fuzzy Reasoning ◽  
Optimal Level ◽  
Metal Loss ◽  
Stud Welding ◽  
Fuzzy Logic Approach ◽  
Friction Stud Welding ◽  
Fuzzy Logic Technique

In this work, an integrated grey fuzzy logic technique is employed for solving the multi objective function of friction stud welding machine process parameters. This technique converts the multi-objectives into a grey fuzzy reasoning grade. According to the grey fuzzy reasoning grade, an optimal combination of process parameters is concluded. Here, Taguchi L9 orthogonal array is used to design the experiments. The objective of this work is to maximize impact strength and minimize metal loss during the joining of AA 6063 and AISI 1030 steel. Rotational speed, friction time, and friction pressure are considered as the input process parameters. The outcomes of the confirmation test show that good joining strength is accomplished by the optimal level of process parameters.

A vector-format fuzzy logic approach for online robot motion planning in 3D space and its application to underwater robotic vehicle

Robotica ◽  
2006 ◽  
Vol 25 (3) ◽  
pp. 325-339
Author(s):  
X. J. Wu ◽  
J. Tang ◽  
Q. Li ◽  
K. H. Heng
Keyword(s):  
Fuzzy Logic ◽  
Motion Planning ◽  
Fuzzy Reasoning ◽  
Rule Base ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Fuzzy Variables ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Fuzzy Logic Technique

SUMMARYDue to its inherent advantages such as reasoning in the format of heuristic rules based on human experience and less stringent requirement on environmental description, fuzzy logic is a promising tool for the robot motion planning in 3-dimensional dynamic environment. In general, in the Cartesian space, the variables used in characterizing the motion of a mobile robot, such as position, velocity, and force relative to other objects or coordinate frames, contain both the magnitude and the pointing information. In previous studies, the fuzzy reasoning on the pointing information was often developed based on the decomposition of the pointing vector followed by conventional fuzzy logic technique on individual vector components. Consequently, when multiple pointing variables are involved, the number of fuzzy variables that need to be considered simultaneously becomes large and the rule base may become very complex, which diminishes the advantages of the fuzzy reasoning approach. In this research, we tackle this issue by implementing a new fuzzy reasoning approach based on vector-format fuzzy variables. To achieve this, a set of new membership functions is defined for the vector-format fuzzy variables, followed by the establishment of a series of new vector-based fuzzification, fuzzy inference, and defuzzification procedures. By treating the multidimensional variables as unitary linguistic variables, the number of fuzzy variables in the fuzzy propositions and therefore the scale of the rule base can be reduced considerably. As an application example, the proposed new fuzzy reasoning approach for motion planning is applied to an Underwater Robotics Vehicle (URV) operating in an oceanic environment, where the pointing of the goal and the pointing vectors of the obstacles are treated as vector-type fuzzy variables, which leads to a compact and significantly simplified rule base. The motion planner can successfully guide the URV to move in the complicated dynamic environ-ment in a real-time fashion, which clearly demonstrates the effectiveness and robustness of the new fuzzy logic approach.

Overview of Fuzzy Logic Technique for Modeling Machining Process

2015 ◽  
Vol 815 ◽  
pp. 264-267
Author(s):  
Azizah Mohamad ◽  
Azlan Mohd Zain ◽  
Noordin bin Mohd Yusof
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Prediction Model ◽  
Process Parameters ◽  
Previous Literature ◽  
Machining Process ◽  
Fuzzy Logic Technique

This paper describes an overview of Fuzzy Logic (FL) application for solving machining problems. The developed fuzzy prediction model is an essential operational guideline for machinist in decision making and adjusting process parameters. This paper also discussed the previous literature that applied the FL in modeling machining process.

scholarly journals Optimization and Modeling of Process Parameters in Multi-Hole Simultaneous Drilling Using Taguchi Method and Fuzzy Logic Approach

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 680 ◽  
Author(s):  
Muhammad Aamir ◽  
Shanshan Tu ◽  
Majid Tolouei-Rad ◽  
Khaled Giasin ◽  
Ana Vafadar
Keyword(s):  
Surface Roughness ◽  
Fuzzy Logic ◽  
Taguchi Method ◽  
Process Parameters ◽  
Cutting Speed ◽  
Hole Drilling ◽  
Hole Size ◽  
Drilling Parameters ◽  
Fuzzy Logic Approach ◽  
Logic Approach

In industries such as aerospace and automotive, drilling many holes is commonly required to assemble different structures where machined holes need to comply with tight geometric tolerances. Multi-spindle drilling using a poly-drill head is an industrial hole-making approach that allows drilling several holes simultaneously. Optimizing process parameters also improves machining processes. This work focuses on the optimization of drilling parameters and two drilling processes—namely, one-shot drilling and multi-hole drilling—using the Taguchi method. Analysis of variance and regression analysis was implemented to indicate the significance of drilling parameters and their impact on the measured responses i.e., surface roughness and hole size. From the Taguchi optimization, optimal drilling parameters were found to occur at a low cutting speed and feed rate using a poly-drill head. Furthermore, a fuzzy logic approach was employed to predict the surface roughness and hole size. It was found that the fuzzy measured values were in good agreement with the experimental values; therefore, the developed models can be effectively used to predict the surface roughness and hole size in multi-hole drilling. Moreover, confirmation tests were performed to validate that the Taguchi optimized levels and fuzzy developed models effectively represent the surface roughness and hole size.

scholarly journals Analysis and optimization of ultrasonic copper wires using fuzzy logic approach

2019 ◽  
Vol 28 ◽  
pp. 01019
Author(s):  
Jacek Zawadzki ◽  
Cezary Jędryczka
Keyword(s):  
Fuzzy Logic ◽  
Process Parameters ◽  
Fusion Welding ◽  
Manufacturing Industries ◽  
Additional Material ◽  
Fuzzy Logic Approach ◽  
Logic Approach ◽  
Weld Time ◽  
Peel Stress ◽  
Short Time

Ultrasonic welding has been used in the market over the past thirty years and offer to the manufacturing industries like automotive, aviation, medical and many more due to various hurdles faced by conventional fusion welding or crimp processes. Very short time (less than 1 second) and no additional material during the connection process are very key advantages. Due to this fact this technology can be used for mass production. Plenty of times, the problems faced by industry due to this process are the poor weld quality and strength of the joints surface. In presented study, the process parameters like vibration amplitude, weld pressure and weld time are considered in analysis of the welding of copper wires (Cu- ETP1). Experiment is conducted according to the fractional design with replications to get the responses like tensile shear stress and T-peel stress of the weld. Measured data are utilized next to develop fuzzy logic model between responses and predictors. As a quality is an very important issue in these manufacturing industries, the optimal combinations of studied process parameters are found using fuzzy logic approach.

scholarly journals Fuzzy-Logic-RSSI based approach for cluster heads selection in wireless sensor networks

2020 ◽  
Vol 18 (3) ◽  
pp. 1424
Author(s):  
Azamuddin Abdul Rahman ◽  
Mohd Nizam Mohmad Kahar ◽  
Wan Isni Sofiah Wan Din
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Residual Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Input Parameters ◽  
Fuzzy Logic Approach ◽  
Fuzzy Logic Technique

<span>Wireless Sensor Networks (WSNs) are defined as networks of nodes that work in a cooperative way in order to sense and control the surrounding environment. Several WSNs algorithms have been proposed by utilizing the Fuzzy Logic technique to select the cluster heads (CHs). Each technique employs a different combination of input parameters such as nodes density, communication cost, and residual energy. CHs determination is critical towards this goal, whereas the combination of input parameters is expected to play an important role. Nevertheless, the received signal strength (RSSI) is one of the main criteria which get little attention from researchers on the topic of CHs selection. In this study, an RSSI based scheme was proposed which utilizes Fuzzy Logic approach in order to be combined with residual energy and centrality of the fuzzy descriptor. In order to evaluate the proposed scheme, the performance Multi-Tier Protocol (MAP) and Stable Election Protocol (SEP) were compared. The simulation results show that the proposed approach has significantly prolonged the survival time of the network against SEP and MAP, while effectively decelerating the dead process of sensor nodes.</span>

scholarly journals Process Parameters Optimization of Aa2024 Alloy Friction Stir Welding using Taguchi’s Technique

2019 ◽  
Vol 8 (11) ◽  
pp. 1940-1945
Keyword(s):  
Tensile Strength ◽  
Process Parameters ◽  
Welding Process ◽  
Travel Speed ◽  
Optimal Level ◽  
Parameters Optimization ◽  
Micro Hardness ◽  
Friction Stir ◽  
Taguchi’S Technique ◽  
The Impact

Within this research study, Taguchi system of style of experimental was utilized to assess the impact of some welding process parameters of sound state welding techniques like rotational speed(spinning velocity), travel speed in addition to pin profile on Tensile Strength (UTS), microhardness in addition to effect strength of Friction Stir Welded (FSW) 2024 light weight aluminum alloy joint. An orthogonal array of L9 design was actually employed for experimental trials and also Signal to noise proportion( S/N) values for each process specifications was computed. Based upon the S/N review the optimal level of process specifications was actually decided on as 1120 revoltions per minute, 25 mm/min and also Cylinder pin with Flutes( CWF) for best Tensile Strength and also micro Hardness. The ideal degree of process parameters for Impact toughness was actually pinpointed as 1120rpm,31.5 mm/min and also Tapered Cylindrical pin account( Drawback). Depending on to Analysis of variance (ANOVA), it was seen that the task of spinning, travel velocity and also pin geometry was 37.31, 64.84 and 1.13 per-cent effect on Ultimate tensile strength, 34.16, 51.28 and 0.58 per-cent impact on micro Hardness as well as 50.10, 43.7 and 6.2 percent influence on Influence Toughness of joint respectively. Eventually based upon FSW guidelines a model was actually created for tensile strength, Micro Hardness and Toughness values. The results were confirmed by further experiments, which yield the experimented values as 349.83 MPa for tensile strength, 114.26 Hardness and 7.8kJ Impact strength.

Sign in / Sign up

Export Citation Format

Share Document