Utilization of Soft Computing Techniques in Sputtering Processes: A Review

2013 ◽  
Vol 832 ◽  
pp. 260-265
Author(s):  
Norlina M. Sabri ◽  
Mazidah Puteh ◽  
Mohamad Rusop Mahmood
Keyword(s):  
Soft Computing ◽  
Process Parameters ◽  
Optimization Techniques ◽  
Future Research ◽  
Film Properties ◽  
Reliable Technique ◽  
Computing Technique ◽  
Optimization Of Process Parameters ◽  
Soft Computing Techniques ◽  
Soft Computing Technique

This paper presents an overview of research works on the utilizing of soft computing in the optimization of process parameters and in the prediction of thin film properties in sputtering processes. The papers from this review were obtained from relevant databases and from various scientific journals. The papers collected were published from 2008 to 2012. The focus of the review is to provide an outlook on the utilization of soft computing techniques in sputtering processes. Based on the review, the soft computing techniques which have been applied so far are ANN, GA and Fuzzy Logic. The first finding of this review is that soft computing technique is a promising and more reliable approach to optimize and predict process parameters compared to the traditional methods. The second finding is that the utilizing of soft computing techniques in sputtering processes are still limited and still in exploratory phase as they have not yet been extensively and stably applied. The techniques applied are also limited to ANN, GA and Fuzzy, whereas the exploration into other techniques is also necessary to be conducted in order to seek the most reliable technique and so as to expand the application of soft computing approach. Future research could focus on the exploration of other soft computing techniques for optimization in order to find the best optimization techniques based on the specific processes.

scholarly journals PSO Research on Cutting Parameters in AWJM Process for Aluminum 6061 Alloy

2019 ◽  
Vol 8 (2S3) ◽  
pp. 64-71
Keyword(s):  
Particle Swarm Optimization ◽  
Soft Computing ◽  
Process Parameters ◽  
Particle Swarm ◽  
Machining Process ◽  
Orifice Diameter ◽  
Machining Performance ◽  
Swarm Optimization ◽  
Computing Technique ◽  
Soft Computing Technique

In recent years there is a rapid growth in the improvement of complexity, difficult and harder to machine metals and alloys. AWJM is one of the hybrid, nontraditional machining process in machining several hard-to-cut materials these days. Machining parameters play the lead role in determining the machine economics and quality of machining. In this study Particle Swarm Optimization soft computing technique is executed to estimate the optimal process parameters which leads to a least value of machining performance and compared with the machining performance value of experimental data. The approaches suggested in this study involve three components, viz., experimental observation, multi regression modeling and single objective Particle Swarm Optimization. The consequence of Pressure, Abrasive flow rate, Orifice diameter, Focusing nozzle diameter and Stand off distance AWJM process parameters on MRR and SR of Aluminium 6061 alloy which is machined by AWJM was experimentally performed and analyzed. According to Response Surface Methodology design, different experiments were conducted with the combination of input parameters on this alloy. The outcome of this study revealed that the PSO soft computing technique obtains the optimal solution of AWJM process parameters for Aluminium 6061 alloy.

EARLY QUALITATIVE SOFTWARE RELIABILITY PREDICTION AND RISK MANAGEMENT IN PROCESS CENTRIC DEVELOPMENT THROUGH A SOFT COMPUTING TECHNIQUE

2009 ◽  
Vol 16 (06) ◽  
pp. 521-532 ◽  
Author(s):  
K. KRISHNA MOHAN ◽  
A. K. VERMA ◽  
A. SRIVIDYA
Keyword(s):  
Risk Management ◽  
Soft Computing ◽  
Computing Technique ◽  
Fuzzy Membership Functions ◽  
Soft Computing Techniques ◽  
Management Schemes ◽  
Soft Computing Technique ◽  
Unified Process ◽  
Orthogonal Defect Classification

A unique take on strengthening the role of a prototype of a software system without actually realizing it, would be to arrive at predictions using historical information from similar PoCs or the permeating experience of those involved in projects of comparable nature. Abundance of soft computing techniques should make this crucial bypassing feasible. The purpose of the this work is to demonstrate the same. Validation of this approach could be obtained by comparing the results with the ones obtained on realized prototypes at module level. In a work of the first of its kind involving studies at the PoC level, qualititave predictions for the metric 'number of defects' are obtained using a generic Fuzzy Logic based modeling. A sound mathematical base for the calculation of slopes of various Fuzzy membership functions employed is explained in detail for the case studies considered. This framework is applicable to any of the process oriented developmental systems like rational unified process. Pivotal risk management schemes are put forward. Significance of orthogonal defect classification method is explained in the context of the case study considered earlier.

Type2 Fuzzy Soft Computing Technique for Image Enhancement

2015 ◽  
Vol 4 (3) ◽  
pp. 97
Author(s):  
U. Sesadri ◽  
B. Siva Sankar ◽  
C. Nagaraju
Keyword(s):  
Fuzzy Logic ◽  
Image Enhancement ◽  
Soft Computing ◽  
Second Step ◽  
Fisher Criterion ◽  
Computing Technique ◽  
Soft Computing Techniques ◽  
Soft Computing Technique ◽  
Membership Value ◽  
Fuzzy Logic Technique

<p class="Default">The mainpurpose of Image enhancement is to process an image so that outcome is more appropriate than original image for definite application. The fuzzy logic isone of the soft computing techniques to enhance the images by eliminating uncertainty.In this paper efficient type2 fuzzy logic technique is used to get betterquality image. This method consists of two steps. In the First step fisher criterion function is useful to generate type1 fuzzy membership value. In the second step based on type1 membership value fuzzy rules are derived to enhance the image. The type2 fuzzy method is compared with type1 fuzzy. The table values and graphs provethat the proposed method gives better results compared with fuzzy type1 method.</p>

scholarly journals Prediction of Process Parameters of Ultrasonically Welded PC/ABS Material Using Soft-Computing Techniques

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 33849-33859
Author(s):  
T. Chinnadurai ◽  
Natarajan Prabaharan ◽  
S. Saravanan ◽  
M. Karthigai Pandean ◽  
P. Pandiyan ◽  
...  
Keyword(s):  
Soft Computing ◽  
Process Parameters ◽  
Soft Computing Techniques

scholarly journals A Novel Ten Check Maximum Power Point Tracking Algorithm for a Standalone Solar Photovoltaic System

Electronics ◽  
2018 ◽  
Vol 7 (11) ◽  
pp. 327 ◽  
Author(s):  
Muhammad Afzal Awan ◽  
Tahir Mahmood
Keyword(s):  
Soft Computing ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Flower Pollination Algorithm ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Computing Technique ◽  
Soft Computing Techniques ◽  
Power Point

Optimal energy extraction under partial shading conditions from a photovoltaic (PV) array is particularly challenging. Conventional techniques fail to achieve the global maximum power point (GMPP) under such conditions, while soft computing techniques have provided better results. The main contribution of this paper is to devise an algorithm to track the GMPP accurately and efficiently. For this purpose, a ten check (TC) algorithm was proposed. The effectiveness of this algorithm was tested with different shading patterns. Results were compared with the top conventional algorithm perturb and observe (P&O) and the best soft computing technique flower pollination algorithm (FPA). It was found that the proposed algorithm outperformed them. Analysis demonstrated that the devised algorithm achieved the GMPP efficiently and accurately as compared to the P&O and the FPA algorithms. Simulations were performed in MATLAB/Simulink.

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