Standard Deviation Method Based PSO

2016 ◽  
Vol 7 (2) ◽  
pp. 15-35
Author(s):  
Arindam Majumder ◽  
Abhishek Majumder
Keyword(s):  
Process Parameters ◽  
Performance Index ◽  
Manufacturing Process ◽  
Pso Algorithm ◽  
Optimization Techniques ◽  
Advanced Manufacturing ◽  
Optimization Of Process Parameters ◽  
Optimal Value ◽  
Single Attribute ◽  
Deviation Method

Nowadays, optimization of process parameters in manufacturing process deals with a number of objectives. However, the optimization of such process becomes more complex if selected attributes are conflicting in nature. Therefore, to overcome this problem in this study a SDM based PSO algorithm is proposed for optimizing the manufacturing process having multi attribute. In this proposed approach the SDM is used to convert multi attributes into single attribute, named as multi performance index, while the optimal value of this multi performance index is predicted by PSO. Finally, three instances related to optimization of advanced manufacturing process parameters are solved by the proposed approach and are compared with the results of the other established optimization techniques such as Desirability based RSM, SDM-GA and SDM-CACO. From the comparison it has been revealed that the proposed approach performs better as compare to the existing approaches.

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.

Application of Standard Deviation Method Integrated PSO Approach in Optimization of Manufacturing Process Parameters

2015 ◽  
pp. 536-563 ◽  
Author(s):  
Arindam Majumder ◽  
Abhishek Majumder
Keyword(s):  
Standard Deviation ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Optimization Problems ◽  
Integrated Approach ◽  
Multi Objective ◽  
Research Areas ◽  
Manufacturing Optimization ◽  
Logical Method ◽  
Deviation Method

Multi-objective optimization is one of the most popular research areas in the world of manufacturing. It concerns the manufacturing optimization problems involving more than one optimization simultaneously, but in this present scenario, it is becoming very tough to solve a manufacturing-related multi-objective problem as no logical method has been developed in assignment of response individual weight. Therefore, to tackle this problem, this chapter proposes a new integrated approach by combining Standard Deviation Method with Particle Swarm Optimization. Two examples of optimizing the advanced manufacturing process parameters are performed to test the proposed approach. The examples considered for this approach are also attempted using other established optimization techniques such as Desirability-based RSM and SDM-GA. The results verify the effectiveness of the proposed approach during multi-objective manufacturing process parameter optimization.

Parameters optimization in FSW of polypropylene based on RSM

2015 ◽  
Vol 11 (1) ◽  
pp. 32-42 ◽  
Author(s):  
K Panneerselvam ◽  
Kasirajan Lenin
Keyword(s):  
Process Parameters ◽  
Rotational Speed ◽  
Optimization Techniques ◽  
Parameters Optimization ◽  
Tool Rotational Speed ◽  
Content Type ◽  
Friction Stir ◽  
Optimization Of Process Parameters ◽  
Output Characteristics ◽  
Tool Pin

Purpose – The purpose of this paper is to weld polypropylene (PP) material by friction stir welding (FSW) process. The input process parameters considered were: tool pin profile, feed rate and tool rotational speed and the process output characteristics were tensile strength, Shore-D hardness, Rockwell hardness, Izod strength, Charpy strength and nugget area. Design/methodology/approach – Optimization of process parameters were carried out based on response surface methodology (RSM) and significant parameters were obtained by performing analysis of variance (ANOVA). Findings – The optimized results were the threaded pin profile for feed of 60 mm/min and tool rotational speed of 1,500 rpm. A confirmation test was carried out to verify the optimized results. Originality/value – In this paper, the process parameters were optimized based on RSM. This is newly adopted optimization techniques in the FSW process of PP materials and also it gives better results.

scholarly journals Optimization of advanced manufacturing processes using socio inspired cohort intelligence algorithm

2022 ◽  
Vol 13 ◽  
pp. 6
Author(s):  
Ishaan R. Kale ◽  
Mayur A. Pachpande ◽  
Swapnil P. Naikwadi ◽  
Mayur N. Narkhede
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Harmony Search ◽  
Optimization Techniques ◽  
Technological Advancement ◽  
Machining Processes ◽  
Bee Colony ◽  
Optimization Of Process Parameters ◽  
Advanced Machining ◽  
Linear And Nonlinear Constraints

The demand of Advanced Machining Processes (AMP) is continuously increasing owing to the technological advancement. The problems based on AMP are complex in nature as it consisted of parameters which are interdependent. These problems also consisted of linear and nonlinear constraints. This makes the problem complex which may not be solved using traditional optimization techniques. The optimization of process parameters is indispensable to use AMP's at its aptness and to make it economical to use. This paper states the optimization of process parameters of Ultrasonic machining (USM) and Abrasive water jet machining (AWJM) processes to maximize the Material Removal Rate (MRR) using a socio inspired Cohort Intelligent (CI) algorithm. The constraints involved with these problems are handled using static penalty function approach. The solutions are compared with other contemporary techniques such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Modified Harmony Search (HS_M) and Genetic Algorithm (GA).

scholarly journals Optimization of Process Parameters for Formulation of Fluvastatin Tablet by Using Dry Granulation Method

2020 ◽  
Vol 10 (5-s) ◽  
pp. 97-107
Author(s):  
Nikhil Arun Shete ◽  
Vishwajeet Swami ◽  
Vaibhav Kulkarni ◽  
Gajanan Paratkar ◽  
Rahul Mohan
Keyword(s):  
Process Parameters ◽  
Manufacturing Process ◽  
Quality By Design ◽  
Flow Behavior ◽  
Scale Up ◽  
Dissolution Time ◽  
Optimization Of Process Parameters ◽  
Study Results ◽  
Tablet Dissolution ◽  
Machine Speed

The manufacturing process of the tablet is a very complex process; it can be affected by the several process parameters or variables. The aim of this study was to understand and optimize the process parameters such as mixing, granulation, lubrication and tablets compression processes using quality by design (QbD) approach for a model Anti- Hyperlipidemic drug Fluvastatin sodium. During the processes there are several parameters which may influence or affect product quality. So the main objective of present work was to identify various process parameters and optimize this parameter, for the formulation of good quality product which needs to optimize Blending time, Roller force, Compression force and machine speed. A scale up batch was taken to evaluate and optimize the parameters. Critical quality attributes (CQA) such as flow behavior, granules parameters, Blend uniformity, tablet appearance, effect on tablet quality like physical appearance (surface, weight etc.) and tablet dissolution time as well as drug release.  The test results of following parameters at various in-process phases are complies with the specified limits and finished product sample results were found to be within specified limits. This study results assures the manufacturing process is reproducible, robust and will yield consistent product, which meets specification. Keywords: Process Parameters, Quality by Design, Fluvastatin, Granulation, Blending, Compression etc,. 

scholarly journals Optimization of Process Parameters during Hydroforming of Tank Bottom using NSGA-III Algorithm

2021 ◽  
Author(s):  
Zaifang Zhang ◽  
Feng Xu ◽  
Xiwu Sun
Keyword(s):  
Process Parameters ◽  
Quality Criteria ◽  
Pso Algorithm ◽  
Hydraulic Pressure ◽  
Blank Holder Force ◽  
Technological Parameters ◽  
Blank Holder ◽  
Optimization Of Process Parameters ◽  
Element Simulation ◽  
Thickness Variations

Abstract The hydroforming technology can realize overall forming of large storage tank’s bottom, but the quality is affected by many technological parameters. In view of wrinkling and cracking defects of integral storage tank’s bottom in hydroforming, a multi-objective optimization model is established for process parameters include pre-expansion pressure, hydraulic pressure, blank holder force and fillet radius of blank holder. Based on finite element simulation, the surrogate model between process parameters and quality criteria is established using Kriging technique. NSGA-III is used to determine optimal process parameters when storage tank’s bottom reaches targets include minimum wall thickness variations, minimum fracture trend, minimum flange wrinkle and minimum wrinkle trend. Compared with Particle swarm optimization (PSO) algorithm, NSGA-III algorithm is more suitable to solve this optimization problem. The validity of this method and accuracy of the results are verified by simulation experiments.

Optimization of Process Parameters for Electro-Chemical Machining of EN19

2019 ◽  
pp. 127-142 ◽  
Author(s):  
Divya Zindani ◽  
Nadeem Faisal ◽  
Kaushik Kumar
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Input Parameter ◽  
Electrochemical Machining ◽  
Pso Algorithm ◽  
Machining Process ◽  
Matrix Composites ◽  
Machining Performance ◽  
Electrode Gap ◽  
Optimization Of Process Parameters

Electrochemical machining (ECM) is a non-conventional machining process that is used for machining of hard-to-machine materials. The ECM process is widely used for the machining of metal matrix composites. However, it is very essential to select optimum values of input process parameters to maximize the machining performance. However, the optimization of the output process parameters and hence the machining performance is a difficult task. In this chapter an attempt has been made to carry out single and multiple optimization of the material removal rate (MRR) and the surface roughness (SR) for the ECM process of EN19 using the particle swarm optimization (PSO) technique. The input parameter considered for the optimization are electrolyte concentration (%), voltage (V), feed rate (mm/min), and inter-electrode gap (mm). The optimum value of MRR and SR as found using the PSO algorithm are 0.1847 cm3/min and 25.0612, respectively.

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