Manufacturing Optimization through Intelligent Techniques

2006 ◽  
pp. 25-26
Keyword(s):  
Manufacturing Optimization

DARPA DICE Manufacturing Optimization

1992 ◽  
Author(s):  
Linda J. Lapointe ◽  
Thomas Laliberty ◽  
Nancy Toro ◽  
Robert V. Bryant
Keyword(s):  
Manufacturing Optimization

Exergoenvironmental Evaluation for a Coal-Fired Power Plant of Near-Zero Air Pollutant Emission

2017 ◽  
Author(s):  
Xiliang Hong ◽  
Jianhong Chen ◽  
Deren Sheng ◽  
Wei Li
Keyword(s):  
Environmental Impact ◽  
Power Plants ◽  
Air Pollutant ◽  
Pollutant Emission ◽  
Component Level ◽  
Large Space ◽  
Construction Design ◽  
Manufacturing Optimization ◽  
Energy Conversion Systems ◽  
High Benefit

Owing to the growing environmental concerns, super-critical and ultra-supercritical coal-fired power plants dominate the electricity generation with the demand of near-zero air pollutant emission in China. Therefore, it is highly expected to assess the environmental impact and optimize the design at global and local levels. Exergoenvironmental analysis is a valid approach to investigate the formation of environmental impacts (EIs) associated with energy conversion systems at the component level. It generates information crucial for designing systems with a lower overall environmental impact, based on life cycle assessment (LCA) and exergy analysis. A 600 MW supercritical coal-fired system with and without dust, SO2 and NOx mitigation controls was analyzed. Heat transfer in the boiler, condenser (CND), low pressure cylinder (LP), air preheater (APH) show high potential to decrease the environmental impact due to high exergy destructions. The deaerator (DEA), induced draft fan (IDF), forced draft fan (FDF) should be focussed on construction design and manufacturing optimization. Purification units reveal high benefit for reducing EI produced by coal combustion, but there is a large space for the EI saving for it. The specific EI of electricity in China is much greater than European.

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.

Dynamic job sequencing of converging-diverging conveyor system for manufacturing optimization

2021 ◽  
Author(s):  
H.S. Sharath Chandra ◽  
Ajit Hebbale ◽  
T.S. Hemanth ◽  
J. Naveen ◽  
S.J. Niranjana
Keyword(s):  
Conveyor System ◽  
Manufacturing Optimization ◽  
Job Sequencing

Artificial Intelligence Techniques for Modern Energy Applications

2010 ◽  
pp. 1-39 ◽  
Author(s):  
Soteris Kalogirou ◽  
Kostas Metaxiotis ◽  
Adel Mellit
Keyword(s):  
Artificial Intelligence ◽  
Power Systems ◽  
High Speed ◽  
Fault Tolerant ◽  
System Modeling ◽  
Social Psychological ◽  
Energy Applications ◽  
Manufacturing Optimization ◽  
Linear Problems ◽  
Very High

Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and nowadays are very popular. They are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems and once trained can perform prediction and generalization at very high speed. AI-based systems are being developed and deployed worldwide in a wide variety of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. This chapter presents a review of the main AI techniques such as expert systems, artificial neural networks, genetic algorithms, fuzzy logic and hybrid systems, which combine two or more techniques. It also outlines some applications in the energy sector.

Sweep in a Transonic Fan Rotor: Part 1 — 3D Geometry Package

1998 ◽  
Author(s):  
Hazem F. Abdelhamid ◽  
Raymond P. Shreeve
Keyword(s):  
Axial Compressor ◽  
Compressor Blade ◽  
Design Parameters ◽  
Control Points ◽  
Manufacturing Optimization ◽  
3D Geometry ◽  
Blade Shape ◽  
Two Parameters ◽  
Transonic Fan ◽  
Blade Element

A geometry package was developed which uses six Bezier surfaces to describe an axial compressor blade. The blade is defined by 32 control points and two parameters, which determine the leading and trailing edge extensions. The package was used to represent a reference transonic fan rotor to within machining tolerances, and then to introduce forward and backward sweep holding blade-element design parameters fixed. Blade lean and point geometry manipulations were also demonstrated. All geometries produced by the package are machinable without approximation. The Bezier-surface representation was chosen in order to minimize the number of control points required to specify the blade shape and eventually enable aero-structural-manufacturing optimization.

scholarly journals Manufacturing optimization using Tsukamoto fuzzy inference system method: A case study in block paving and solid concrete block industry

2018 ◽  
Vol 204 ◽  
pp. 02002
Author(s):  
M Sayuti ◽  
Juliananda ◽  
Diana Khairani Sofyan
Keyword(s):  
Fuzzy Inference ◽  
Concrete Block ◽  
Optimal Number ◽  
High Demand ◽  
Inference System ◽  
The Third ◽  
Manufacturing Optimization ◽  
System Method ◽  
Real World Problems

Fuzzy method has advantages in solving real-world problems that are mostly non-binary and non-linear, such as calculating the optimization of production quantities. A case study for the application of this method was applied in UD. Setia Kawan Company that run the production of solid concrete and block paving. The problems faced by this company is the high demand for products resulting in short stock and sometimes over stock due to unstable customer ordering and inaccurate management in production planning. From the calculations, the number of solid concrete block produced by the company on the period of October 2016, December 2016 and February 2017 was not optimal. According to Tsukamoto’s FIS, the optimal number of solid concrete block in the third period is 9973, 9562 and 12.087 unit of solid concrete block. While the number of block paving produced by the company on the period of November 2016, December 2016 and January 2017 was also not optimal. According to Tsukamoto’s FIS analysis, the optimal number of block paving in the third period should be 9.116, 10.113 and 7.120 unit of block paving

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