Devolpment and Modeling of an Industrial Process Plan, Its Optimization using stochastic search Optimization Technique

2021 ◽  
Vol 15 ◽  
pp. 87-91
Author(s):  
Umer Asgher ◽  
Riaz Ahmad ◽  
Liaqat Ali
Keyword(s):  
Process Planning ◽  
Manufacturing Systems ◽  
Manufacturing Industry ◽  
Optimization Technique ◽  
Industrial Process ◽  
Optimal Solution ◽  
Stochastic Search ◽  
Optimization Techniques ◽  
Process Plan ◽  
Search Optimization

Industrial process planning is principally an association between design and development or final production and has vital function in the manufacturing systems. In this paper the under research industry is security vehicle manufacturing industry in Pakistan. First of all a fundamental process plan is developed and then modeled mathematically using progressive closed loop approach. Mathematically modeled process plan is then optimized in order to find optimal or sub optimal solutions. Research then investigates the capability of an innovative optimization technique called stochastic search in handling optimization of manufacturing process plan. This new technique of stochastic, searches the best approximate process planning solution. Finally the research examines the convergence of optimization techniques to an optimal solution for a manufacturing framework.

scholarly journals Modeling Of Multi-Objective Process Plan, Its Optimization using Linear Modeling Technique

2021 ◽  
Vol 15 ◽  
pp. 110-114
Author(s):  
Umer Asgher ◽  
Riaz Ahmad ◽  
Aamer Ahmad Baqai
Keyword(s):  
Process Planning ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Raw Material ◽  
Reconfigurable Manufacturing ◽  
Linear Modeling ◽  
Process Plan ◽  
Organizational Goals ◽  
Manufacturing Procedure ◽  
Design Requirements

The Process planning is the procedure to opt for and schedule manufacturing procedure so as to attain one or more organizational goals and suit with a set of constraints. More specifically a Process planning in the reconfigurable manufacturing setup engages a sequence of all activities from raw material storage into the finished manufactured yield. In the current study a manufacturing setup of automotive industry is discussed. At the outset of papers, a basic process plan is modeled that includes design requirements after that it is mathematically modeled. Mathematically modeled process plan is then optimized in order to find optimal solution. Research then search the potential of linear programming optimization technique in handling optimization of process plan.

A New Simple Micro-PSO for High Dimensional Optimization Problem

2012 ◽  
Vol 236-237 ◽  
pp. 1195-1200
Author(s):  
Wen Hua Han
Keyword(s):  
Optimization Problem ◽  
Optimization Technique ◽  
Pso Algorithm ◽  
Population Based ◽  
Global Optimum ◽  
Stochastic Search ◽  
High Dimensional ◽  
Swarm Optimization ◽  
Search Optimization ◽  
Dimensional Optimization

The particle swarm optimization (PSO) algorithm is a population-based intelligent stochastic search optimization technique, which has already been widely used to various of fields. In this paper, a simple micro-PSO is proposed for high dimensional optimization problem, which is resulted from being introduced escape boundary and perturbation for global optimum. The advantages of the simple micro-PSO are more simple and easily implemented than the previous micro-PSO. Experiments were conducted using Griewank, Rosenbrock, Ackley, Tablets functions. The experimental results demonstrate that the simple micro-PSO are higher optimization precision and faster convergence rate than PSO and robust for the dimension of the optimization problem.

Economic Dispatch Problems Using Backtracking Search Optimization

2018 ◽  
Vol 7 (2) ◽  
pp. 39-60
Author(s):  
Kuntal Bhattacharjee
Keyword(s):  
Large Scale ◽  
Transmission Loss ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Inequality Constraints ◽  
Optimization Techniques ◽  
Backtracking Search ◽  
Search Optimization ◽  
Set Up ◽  
Optimum Solution

The purpose of this article is to present a backtracking search optimization technique (BSA) to determine the feasible optimum solution of the economic load dispatch (ELD) problems involving different realistic equality and inequality constraints, such as power balance, ramp rate limits, and prohibited operating zone constraints. Effects of valve-point loading, multi-fuel option of large-scale thermal plants, system transmission loss are also taken into consideration for more realistic application. Two effective operations, mutation and crossover, help BSA algorithms to find the global solution for different optimization problems. BSA has the capability to deal with multimodal problems due to its powerful exploration and exploitation capability. BSA is free from sensitive parameter control operations. Simulation results set up the proposed approach in a better stage compared to several other existing optimization techniques in terms quality of solution and computational efficiency. Results also reveal the robustness of the proposed methodology.

Swarm-Based Mean-Variance Mapping Optimization (MVMOS) for Solving Non-Convex Economic Dispatch Problems

2015 ◽  
pp. 211-251 ◽  
Author(s):  
Truong Hoang Khoa ◽  
Pandian Vasant ◽  
Balbir Singh Mahinder Singh ◽  
Vo Ngoc Dieu
Keyword(s):  
Optimization Technique ◽  
Economic Dispatch ◽  
Optimal Solution ◽  
Mapping Function ◽  
Population Based ◽  
Optimization Techniques ◽  
Solution Quality ◽  
Complex Constraints ◽  
Global Optimal ◽  
Mean Variance

The practical Economic Dispatch (ED) problems have non-convex objective functions with complex constraints due to the effects of valve point loadings, multiple fuels, and prohibited zones. This leads to difficulty in finding the global optimal solution of the ED problems. This chapter proposes a new swarm-based Mean-Variance Mapping Optimization (MVMOS) for solving the non-convex ED. The proposed algorithm is a new population-based meta-heuristic optimization technique. Its special feature is a mapping function applied for the mutation. The proposed MVMOS is tested on several test systems and the comparisons of numerical obtained results between MVMOS and other optimization techniques are carried out. The comparisons show that the proposed method is more robust and provides better solution quality than most of the other methods. Therefore, the MVMOS is very favorable for solving non-convex ED problems.

scholarly journals Development of an Evaluating Method for Carbon Emissions of Manufacturing Process Plans

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yanhong Wang ◽  
Hua Zhang ◽  
Zhiqing Zhang ◽  
Jing Wang
Keyword(s):  
Process Planning ◽  
Carbon Emissions ◽  
Manufacturing Process ◽  
Carbon Emission ◽  
Manufacturing Industry ◽  
Evaluation Method ◽  
Energy Utilization ◽  
Carbon Intensity ◽  
Emission Analysis ◽  
Process Plan

Carbon intensity reduction and energy utilization enhancement in manufacturing industry are becoming a timely topic. In a manufacturing system, the process planning is the combination of all production factors which influences the entail carbon emissions during manufacturing. In order to meet the current low carbon manufacturing requirements, a carbon emission evaluation method for the manufacturing process planning is highly desirable to be developed. This work presents a method to evaluate the carbon emissions of a process plan by aggregating the unit process to form a combined model for evaluating carbon emissions. The evaluating results can be used to decrease the resource and energy consumption and pinpoint detailed breakdown of the influences between manufacturing process plan and carbon emissions. Finally, the carbon emission analysis method is applied to a process plan of an axis to examine its feasibility and validity.

scholarly journals Mathematical Research on Optimization Technique for Diet Planning Problem: Case Research Autism Paralympic Athlete

2019 ◽  
Vol 8 (2S3) ◽  
pp. 387-391
Keyword(s):  
Operation Research ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Optimization Techniques ◽  
Planning Problem ◽  
Case Research ◽  
Diet Plan ◽  
Diet Problem ◽  
The Mathematical Model ◽  
The Ideal

This paper demonstrates distinctive methods used in operation research to experience with different diet issues. Every diet problem has its particular cost limitation and objective function. The designation of sufficient menus including the consideration of several types of constraints, for example, the ideal nutritional content, the amount of food to be consumed and others. The mathematical model is constructed to determine a diet plan as an optimal solution which fulfills every requirements and limitations. The application of different optimization techniques and weakness in each method has been reviewed. The use of integer programming and development that can be done also represents in this paper. An optimal and practical solution is acquired to solve the diet problem for autism Paralympic athlete

scholarly journals Classification of research and applications of the computer aided process planning in manufacturing systems

2021 ◽  
Vol 12 (5) ◽  
pp. 1250-1281
Author(s):  
Mohsen Soori ◽  
Mohammed Asmael
Keyword(s):  
Process Planning ◽  
Manufacturing Systems ◽  
Optimization Techniques ◽  
Computer Applications ◽  
Added Value ◽  
Future Research ◽  
Planning Systems ◽  
Computer Aided Process Planning ◽  
Computer Aided ◽  
Part Production

The Computer Aided Process Planning (CAPP) systems are recently developed in manufacturing engineering to provide links between Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) systems. The CAPP systems are developed by considering the different issues of computer applications in production engineering. Optimization techniques can be applied to the CAPP to increase efficiency in part production processes. The energy consumption of part production process can be analyzed and optimized using the CAPP systems in order to increase added value in the part manufacturing process. Also, artificial neural networks as well as cloud manufacturing systems can be applied to the CAPP systems to share advantages of the different CAPP systems in different industry applications. Flexible process planning systems are developed using dynamic CAPP in order to cope with product varieties in process of part production. To develop potential energy saving strategies during product design and process planning stages, the advanced CAPP systems can be used. In this paper, a review of Computer Process Planning systems (CAPP) is presented and future research works are also suggested. It has been observed that the research filed can be moved forward by reviewing and analyzing recent achievements in the published papers.

scholarly journals Multi-criteria Optimization Technique with Complex Pythagorean Fuzzy N-soft Information

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Muhammad Akram ◽  
Faiza Wasim ◽  
José Carlos R. Alcantud ◽  
Ahmad N. Al-Kenani
Keyword(s):  
Decision Making ◽  
Comparative Study ◽  
Manufacturing Industry ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Fuzzy Topsis ◽  
Industrial Robots ◽  
Weighted Averaging ◽  
Topsis Method ◽  
Vikor Method

AbstractThe main objective of this article is to lay the foundations of a novel multi-criteria optimization technique, namely, the complex Pythagorean fuzzy N-soft VIKOR (CPFNS-VIKOR) method that is highly proficient to express a great deal of linguistic imprecision and vagueness inherent in human assessments. This strategy provides a versatile decision-making tool for the ranking-based fuzzy modeling of two-dimensional parameterized data. The CPFNS-VIKOR method integrates the ground-breaking specialities of the VIKOR method with the outstanding parametric structure of the complex Pythagorean fuzzy N-soft model. It is exclusively designed for the specification of a compromise optimal solution having maximum group utility and minimum individual regret of the opponent by analyzing their weighted proximity from ideal solutions. The developed strategy factually permits specific linguistic terms to demystify the individual perspectives of the decision-making experts regarding the efficacy of the alternatives and the priorities of the applicable criteria. We comprehensively assemble these independent appraisals of all the experts using the complex Pythagorean fuzzy N-soft weighted averaging operator. Moreover, we calibrate the ranking measure by utilizing group utility measure and regret measure in order to specify the hierarchical outranking of the feasible alternatives. We demonstrate the systematic methodology and framework of the proposed method with the assistance of an explicative flow chart. We skilfully investigate an empirical analysis related to selection of constructive industrial robots for the modernization of a manufacturing industry which really justifies the remarkable accountability of the proposed strategy. Furthermore, we validate this technique by a comparative study with the existing complex Pythagorean fuzzy TOPSIS (CPF-TOPSIS) method, complex Pythagorean fuzzy VIKOR (CPF-VIKOR) method and Pythagorean fuzzy TOPSIS (PF-TOPSIS) method. The comparative study is exemplified with an illustrative bar chart that visually endorses the rationality of the proposed methodology by interpreting highly compatible and accurate final outcomes. Finally, we holistically analyze the functionality of the developed strategy to enlighten its merits and prominence over other available competent approaches.

scholarly journals Optimization of the Tungsten Inert Gas Process Parameters using Response Surface Methodology

2021 ◽  
Vol 2 ◽  
pp. 26-33
Author(s):  
P. Pondi ◽  
J. Achebo ◽  
A. Ozigagun
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Heat Input ◽  
Manufacturing Industry ◽  
Optimal Solution ◽  
Statistical Design ◽  
Optimization Techniques ◽  
Inert Gas ◽  
Diffusible Hydrogen

Optimization is a very important techniques applied in the manufacturing industry that utilizes mathematical and artificial intelligence methods. The complexity associated with most optimization techniques have resulted to search for new ones. This search has led to the emergence of response surface methodology (RSM). The paper aims to optimize tungsten inert gas process parameters required to eliminate post-weld crack formation and stabilize heat input in mild steel weldment using RSM. The main input variables considered are voltage, current and speed whereas the response parameter is Brinell hardness number (BHN). The statistical design of experiment was done using the central composite design technique. The experiment was implemented 20 times with 5 specimens per experiment. The responses were measured, recorded and optimized using RSM. From the results, it was observed that a voltage of 21.95 V, current of 190.0 A, and welding speed of 5.00 mm/s produced a weld material with the following optimal properties; BHN (200.959 HAZ), heat input (1.69076 kJ/mm), cooling rate (72.07 /s), preheat temperature (150.68 ) and amount of diffusible hydrogen (12.36 mL/100g). The optimal solution was selected by design expert with a desirability value of 95.40 %.

Layer Separation for Optimization of Composite Laminates

2008 ◽  
Author(s):  
Hossein Ghiasi ◽  
Damiano Pasini ◽  
Larry Lessard
Keyword(s):  
Composite Laminates ◽  
Optimization Technique ◽  
Optimal Solution ◽  
Global Optimum ◽  
Important Variable ◽  
Optimization Techniques ◽  
Thin Layers ◽  
Stacking Sequence ◽  
Layer Separation ◽  
Number Of Layers

The excellent mechanical properties of laminated composites cannot be exploited without a careful design of stacking sequence of the layers. An important variable in the search of the optimum stacking sequence is the number of layers. The larger is this number, the harder as well as longer is the search for an optimal solution. To tackle efficiently such a variable-dimensional problem, we introduce here a multi-level optimization technique. The proposed method, called Layer Separation (LS), increases or decreases the number of layers by gradually separating a layer into two, or by merging two layers into one. LS uses different levels of laminate representation ranging from a coarse level parameterization, which corresponds to a small number of thick layers, to a fine level parameterization, which corresponds to a large number of thin layers. A benefit of such differentiation is an increase of the probability of finding the global optimum. In this paper, LS is applied to the design of composite laminates under single and multiple loadings. The results show that LS convergence rate is not inferior to that of other optimization techniques available in the literature. It is faster than an evolutionary algorithm, more efficient than a layerwise method, simple to perform, and it has the advantage of possibility of termination at any point during the optimization process.

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