Optimal Tolerance Allocation of Automotive Pneumatic Control Valves Based on Product and Process Simulations

2006 ◽  
Author(s):  
Naesung Lyu ◽  
Amane Shimura ◽  
Kazuhiro Saitou
Keyword(s):  
Product Quality ◽  
Production Cost ◽  
Radial Basis Function Network ◽  
Discrete Event ◽  
Computational Method ◽  
Tolerance Allocation ◽  
Production Volume ◽  
Pneumatic Control ◽  
Multi Objective ◽  
Trade Offs

This paper discusses a computational method for optimally allocating dimensional tolerances for an automotive pneumatic control valve. Due to the large production volume, costly tight tolerances should be allocated only to the dimensions that have high influence to the quality. Given a parametric geometry of a valve, the problem is posed as a multi-objective optimization with respect to product quality and production cost. The product quality is defined as 1) the deviation from the nominal valve design in the linearity of valve stroke and fluidic force, and 2) the difference in fluidic force with and without cavitation. These quality measures are estimated by using Monte Carlo simulation on a Radial-Basis Function Network (RBFN) trained with computational fluid dynamics (CFD) simulation of the valve operation. The production cost is estimated by the tolerance-cost relationship obtained from the discrete event simulations of valve production process. A multi-objective genetic algorithm is utilized to generate Pareto optimal tolerance allocations with respect to these objectives, and alternative tolerance allocations are proposed considering the trade-offs among multiple objectives.

Optimizing Tolerance Allocation Based on Manufacturing Cost and Quality Loss

1994 ◽  
Author(s):  
Mukund Krishnaswami ◽  
R. W. Mayne
Keyword(s):  
Product Quality ◽  
Numerical Optimization ◽  
Quantitative Measure ◽  
Tolerance Allocation ◽  
Manufacturing Cost ◽  
Quality Loss ◽  
Assembly Tolerance ◽  
Trade Offs ◽  
Nonlinear Programming Methods ◽  
Methods Numerical

Abstract This paper describes a procedure for optimizing the allocation of tolerances considering manufacturing cost and product quality in a constrained optimization process. The procedure can utilize various existing models for relating manufacturing costs to part tolerances. It also includes a relationship between part tolerances and assembly tolerance to provide a quantitative measure of product quality using the Taguchi concept of quality loss. The two cost relationships are combined in a formulation which is convenient for solving the optimal tolerance allocation problem by nonlinear programming methods. Numerical optimization can then be directly applied to balance manufacturing cost and product quality allowing trade-offs to be explored.

scholarly journals A Comparison of Genetic Representations and Initialisation Methods for the Multi-objective Shortest Path Problem on Multigraphs

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Lilla Beke ◽  
Michal Weiszer ◽  
Jun Chen
Keyword(s):  
Shortest Path ◽  
Time Budget ◽  
Exact Algorithm ◽  
Simple Graph ◽  
Shortest Path Problem ◽  
Future Application ◽  
Multi Objective ◽  
Trade Offs ◽  
Conflicting Objectives ◽  
Problem Instances

AbstractThis paper compares different solution approaches for the multi-objective shortest path problem (MSPP) on multigraphs. Multigraphs as a modelling tool are able to capture different available trade-offs between objectives for a given section of a route. For this reason, they are increasingly popular in modelling transportation problems with multiple conflicting objectives (e.g., travel time and fuel consumption), such as time-dependent vehicle routing, multi-modal transportation planning, energy-efficient driving, and airport operations. The multigraph MSPP is more complex than the NP-hard simple graph MSPP. Therefore, approximate solution methods are often needed to find a good approximation of the true Pareto front in a given time budget. Evolutionary algorithms have been successfully applied for the simple graph MSPP. However, there has been limited investigation of their applications to the multigraph MSPP. Here, we extend the most popular genetic representations to the multigraph case and compare the achieved solution qualities. Two heuristic initialisation methods are also considered to improve the convergence properties of the algorithms. The comparison is based on a diverse set of problem instances, including both bi-objective and triple objective problems. We found that the metaheuristic approach with heuristic initialisation provides good solutions in shorter running times compared to an exact algorithm. The representations were all found to be competitive. The results are encouraging for future application to the time-constrained multigraph MSPP.

scholarly journals Multi-Objective Optimization of Autonomous Microgrids with Reliability Consideration

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4466
Author(s):  
Maël Riou ◽  
Florian Dupriez-Robin ◽  
Dominique Grondin ◽  
Christophe Le Loup ◽  
Michel Benne ◽  
...  
Keyword(s):  
Power Systems ◽  
Rural Areas ◽  
Energy System ◽  
Design Stage ◽  
Multi Objective Optimization ◽  
Renewable Energy Resources ◽  
Nsga Ii ◽  
Renewable Integration ◽  
Multi Objective ◽  
Trade Offs

Microgrids operating on renewable energy resources have potential for powering rural areas located far from existing grid infrastructures. These small power systems typically host a hybrid energy system of diverse architecture and size. An effective integration of renewable energies resources requires careful design. Sizing methodologies often lack the consideration for reliability and this aspect is limited to power adequacy. There exists an inherent trade-off between renewable integration, cost, and reliability. To bridge this gap, a sizing methodology has been developed to perform multi-objective optimization, considering the three design objectives mentioned above. This method is based on the non-dominated sorting genetic algorithm (NSGA-II) that returns the set of optimal solutions under all objectives. This method aims to identify the trade-offs between renewable integration, reliability, and cost allowing to choose the adequate architecture and sizing accordingly. As a case study, we consider an autonomous microgrid, currently being installed in a rural area in Mali. The results show that increasing system reliability can be done at the least cost if carried out in the initial design stage.

A Spectral Optimization Algorithm for Multi-Objective Prototype Selection

1995 ◽  
Author(s):  
Andy Dong ◽  
Alice M. Agogino
Keyword(s):  
Optimization Algorithm ◽  
Parametric Design ◽  
Selection Process ◽  
Objective Evaluation ◽  
Design Synthesis ◽  
Multi Objective ◽  
Trade Offs ◽  
Spectral Optimization ◽  
The Right ◽  
Selection Of

Abstract In design synthesis, engineering prototypes make an ideal representation medium for preliminary designs. Unlike parametric design wherein a pre-specified design is parametrically varied, design synthesis demands artistic creativity and engineering experience to transform the previously known components, relationships and designs into a new form. The process compels the designer to ascertain which prototypes will, in some sense, best satisfy the design task. The challenge in this assignment lies in selecting the “right” design prototype. This selection process typically entails an objective evaluation of different designs that perform the same functions or have similar intended behavior and comparing trade-offs between alternate designs. This paper introduces a multi-objective spectral optimization algorithm for the selection of design prototypes based upon their functional representations. The optimization algorithm returns an index of rank, scoring the functional similarity of the proposed design to the goal design. Two illustrative examples apply the algorithm to the selection of a heat fin and beam.

Multi-objective optimisation of product quality in the manufacture of Ti-6Al-4V prostheses

2010 ◽  
Vol 5 (3) ◽  
pp. 353
Author(s):  
Jose Vicente Abellan Nebot ◽  
Hector R. Siller Carrillo ◽  
Carlos Vila Pastor ◽  
Ciro A. Rodriguez Gonzalez
Keyword(s):  
Product Quality ◽  
Multi Objective

Multi-objective optimization for safety and reliability trade-off: Optimization and results processing

2018 ◽  
Vol 232 (6) ◽  
pp. 661-676
Author(s):  
Cristina Johansson ◽  
Johan Ölvander ◽  
Micael Derelöv
Keyword(s):  
Decision Making ◽  
Solid Base ◽  
Multi Objective Optimization ◽  
Specific System ◽  
Multi Objective ◽  
Trade Offs ◽  
Design Alternatives ◽  
Safety And Reliability ◽  
Potential Issue ◽  
Selection Of

In early design phases, it is vital to be able to screen the design space for a set of promising design alternatives for further study. This article presents a method able to balance several objectives of different mathematical natures, with high impact on the design choices. The method (MOSART) handles multi-objective optimization for safety and reliability trade-offs. The article focuses on optimization problem approach and processing of results as a base for decision-making. The output of the optimization step is the selection of specific system elements obtaining the best balance between the targets. However, what is a good base for decision can easily transform into too much information and overloading of the decision-maker. To solve this potential issue, from a set of Pareto optimal solutions, a smaller sub-set of selected solutions are visualized and filtered out using preference levels of the objectives, yielding a solid base for decision-making and valuable information on potential solutions. Trends were observed regarding each system element and discussed while processing the results of the analysis, supporting the decision of one final best solution.

scholarly journals ANALISIS KEUNTUNGAN DAN TITIK IMPAS TERNAK AYAM KAMPUNG SUPER DAN AYAM BROILER DI DESA BANGUN HARJO BUAY MADANG TIMUR OKU TIMUR

2017 ◽  
Vol 2 (03) ◽  
pp. 23-31
Author(s):  
Imam Sulaiman
Keyword(s):  
Production Process ◽  
Production Cost ◽  
Production Volume ◽  
Total Production ◽  
Majority Population ◽  
Research Plan ◽  
Average Revenue ◽  
Break Even Point ◽  
The Cost ◽  
The Village

The objectives of this research are to: (1) To analyze the cost, income and income of chicken and chicken cattle in Bangu Harjo Village, Buay Madang Timur District, OKU Timur Regency, (2) To analyze whether broiler and joper cattle cultivated in Bangun Harjo Village, Buay Madang Timur Sub-district, OKU Timur Regency is beneficial, (3) To analyze break even point of broiler and joper livestock business in Bangun Harjo Village, Buay Madang Timur District, OKU Timur Regency. This research has been conducted in Bangun Harjo Village, Buay Madang Timur District, East OKU Regency. Site selection is done purposively with the consideration that in the village is able to represent from the existing population and have the criteria of research plan. Bangun Harjo village is a village whose majority population live as farmers and there are some farmers who seek the cultivation of super chicken (joper) and broiler (broiler). The study was conducted in June 2015. The study found that the total production cost incurred in the poultry livestock business in Bangun Harjo Village in one production process amounted to Rp 13,963,744, the average revenue was Rp 22,920,000 so that income Received amounted to Rp 8,956,256. The value of R / C ratio is 1.64 indicating that the chicken livestock business is profitable. The total production cost incurred in the broiler business in Bangun Harjo Village in one production process is Rp 30,609,006, the average revenue is Rp 54,676,250, so the income received is Rp 24,067,224. The value of R / C ratio is 1.79 indicates that the business of broiler livestock is profitable and BEP value of livestock production volume of chicken joper is 349 head, while the value of BEP price is Rp 24.569 / Tail and BEP value of broiler chicken production volume is equal to 2.017 Kg, while the BEP value of the price is Rp 8,496 / Kg which shows that the business of chicken and broiler cattle in Bangun Harjo Village is feasible financially.

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