A cost-effective optimization approach for improving the fatigue strength of diamond-burnished steel components

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
J. T. Maximov ◽  
G. V. Duncheva ◽  
A. P. Anchev ◽  
V. P. Dunchev ◽  
J. Capek
Keyword(s):  
Fatigue Strength ◽  
Cost Effective ◽  
Optimization Approach

scholarly journals Toward Decentralised Sanitary Sewage Collection Systems: A Multiobjective Approach for Cost-Effective and Resilient Designs

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1886
Author(s):  
Arezoo Zahediasl ◽  
Amin E. Bakhshipour ◽  
Ulrich Dittmer ◽  
Ali Haghighi
Keyword(s):  
Treatment Plant ◽  
Drainage System ◽  
Cost Effective ◽  
Optimization Approach ◽  
Hydraulic Design ◽  
Multiobjective Approach ◽  
Layout Generation ◽  
Plant Allocation ◽  
Problem Solving Process

In recent years, the concept of a centralized drainage system that connect an entire city to one single treatment plant is increasingly being questioned in terms of the costs, reliability, and environmental impacts. This study introduces an optimization approach based on decentralization in order to develop a cost-effective and sustainable sewage collection system. For this purpose, a new algorithm based on the growing spanning tree algorithm is developed for decentralized layout generation and treatment plant allocation. The trade-off between construction and operation costs, resilience, and the degree of centralization is a multiobjective problem that consists of two subproblems: the layout of the networks and the hydraulic design. The innovative characteristics of the proposed framework are that layout and hydraulic designs are solved simultaneously, three objectives are optimized together, and the entire problem solving process is self-adaptive. The model is then applied to a real case study. The results show that finding an optimum degree of centralization could reduce not only the network’s costs by 17.3%, but could also increase its structural resilience significantly compared to fully centralized networks.

scholarly journals A delayed differentiation multiproduct model with the outsourcing of common parts, overtime strategy for end products, and quality reassurance

2021 ◽  
pp. 143-158 ◽  
Author(s):  
Singa Wang Chiu ◽  
Victoria Chiu ◽  
Ming-Hon Hwang ◽  
Yuan-Shyi Peter Chiu
Keyword(s):  
Cost Effective ◽  
Sensitivity Analyses ◽  
Optimization Approach ◽  
Limited Capacity ◽  
Numerical Illustration ◽  
Delayed Differentiation ◽  
Modeling Analysis ◽  
End Products ◽  
Effective Decision ◽  
Effective Decision Making

Production planners today must simultaneously face with the time and quality demands of various goods externally and meet limited capacity internally. This study presents a two-stage delayed- differentiation multiproduct model that considers the outsourcing options for common parts, overtime strategy for end products, and quality reassurance to assist in making fabrication runtime decisions that are cost-effective. Stage one produces all necessary common intermediate components for end products. To reduce stage one’s utilization/uptime, this study adopts a partial outsourcing option. Stage two uses an overtime strategy to fabricate end products that further shorten the uptime. The production processes in both phases are assumed to be imperfect. This study employs the reworking/scrapping of random faulty items to reassure product quality. The researchers build a model to depict the proposed problem’s characteristics and used the mathematical modeling, analysis, and optimization approach to determine the best rotation cycle length that minimizes the system’s expenses. Further, in this study, the researchers provide sensitivity analyses and a numerical illustration, which validate the result’s applicability and exhibit its capability. This result contributes to practical multiproduct-fabrication by (1) deriving the optimal manufacturing policy for a delayed-differentiation multiproduct system with dual uptime reduction policies and quality reassurance; and (2) offering a decisional model that allows production planners to explore the collective/separate effect of a quality-ensured and dual uptime reduction strategy on a problem’s operating policy and crucial system performance indicators, which assists in cost-effective decision-making.

Design and Analysis of Automotive Bumper Covers in Transient Loading Conditions

2016 ◽  
Vol 715 ◽  
pp. 174-179 ◽  
Author(s):  
Chih Hsing Liu ◽  
Ying Chia Huang ◽  
Chen Hua Chiu ◽  
Yu Cheng Lai ◽  
Tzu Yang Pai
Keyword(s):  
Optimal Design ◽  
Numerical Model ◽  
Design Method ◽  
Experimental Tests ◽  
Cost Effective ◽  
Limited Range ◽  
Optimization Approach ◽  
Loading Conditions ◽  
Element Analysis ◽  
Design Guideline

This paper presents the analysis methods for design of automotive bumper covers. The bumper covers are plastic structures attached to the front and rear ends of an automobile and are expected to absorb energy in a minor collision. One requirement in design of the bumper covers is to minimize the bumper deflection within a limited range under specific loadings at specific locations based on the design guideline. To investigate the stiffness performance under various loading conditions, a numerical model based on the explicit dynamic finite element analysis (FEA) using the commercial FEA solver, LS-DYNA, is developed to analyze the design. The experimental tests are also carried out to verify the numerical model. The thickness of the bumper cover is a design variable which usually varies from 3 to 4 mm depending on locations. To improve the stiffness of the bumper, an optimal design for the bumper under a pre-defined loading condition is identified by using the topology optimization approach, which is an optimal design method to obtain the optimal layout of an initial design domain under specific boundary conditions. The outcome of this study provides an efficient and cost-effective method to predict and improve the design of automotive bumper covers.

scholarly journals Unsupervised Parameterization for Optimal Segmentation of Agricultural Parcels from Satellite Images in Different Agricultural Landscapes

2020 ◽  
Vol 12 (18) ◽  
pp. 3096
Author(s):  
Gideon Okpoti Tetteh ◽  
Alexander Gocht ◽  
Marcel Schwieder ◽  
Stefan Erasmi ◽  
Christopher Conrad
Keyword(s):  
Evaluation System ◽  
Reference Data ◽  
Cost Effective ◽  
Agricultural Landscapes ◽  
Bayesian Optimization ◽  
Absolute Difference ◽  
Optimization Approach ◽  
Lower Saxony ◽  
Optimal Segmentation ◽  
Unsupervised Methods

Image segmentation is a cost-effective way to obtain information about the sizes and structural composition of agricultural parcels in an area. To accurately obtain such information, the parameters of the segmentation algorithm ought to be optimized using supervised or unsupervised methods. The difficulty in obtaining reference data makes unsupervised methods indispensable. In this study, we evaluated an existing unsupervised evaluation metric that minimizes a global score (GS), which is computed by summing up the intra-segment uniformity and inter-segment dissimilarity within a segmentation output. We modified this metric and proposed a new metric that uses absolute difference to compute the GS. We compared this proposed metric with the existing metric in two optimization approaches based on the Multiresolution Segmentation (MRS) algorithm to optimally delineate agricultural parcels from Sentinel-2 images in Lower Saxony, Germany. The first approach searches for optimal scale while keeping shape and compactness constant, while the second approach uses Bayesian optimization to optimize the three main parameters of the MRS algorithm. Based on a reference data of agricultural parcels, the optimal segmentation result of each optimization approach was evaluated by calculating the quality rate, over-segmentation, and under-segmentation. For both approaches, our proposed metric outperformed the existing metric in different agricultural landscapes. The proposed metric identified optimal segmentations that were less under-segmented compared to the existing metric. A comparison of the optimal segmentation results obtained in this study to existing benchmark results generated via supervised optimization showed that the unsupervised Bayesian optimization approach based on our proposed metric can potentially be used as an alternative to supervised optimization, particularly in geographic regions where reference data is unavailable or an automated evaluation system is sought.

Simultaneous Determination of Disassembly Sequence and Disassembly-to-Order Decisions Using Simulation Optimization

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Mehmet Ali Ilgin ◽  
Gökçeçiçek Tuna Taşoğlu
Keyword(s):  
Simultaneous Determination ◽  
Simulation Optimization ◽  
Public Awareness ◽  
Cost Effective ◽  
Product Recovery ◽  
Optimization Approach ◽  
Order Problem ◽  
Disassembly Sequence ◽  
Disassembly Sequencing

Strict environmental regulations and increasing public awareness toward environmental issues force many companies to establish dedicated facilities for product recovery. All product recovery options require some level of disassembly. That is why, the cost-effective management of product recovery operations highly depends on the effective planning of disassembly operations. There are two crucial issues common to most disassembly systems. The first issue is disassembly sequencing which involves the determination of an optimal or near optimal disassembly sequence. The second issue is disassembly-to-order (DTO) problem which involves the determination of the number of end of life (EOL) products to process to fulfill the demand for specified numbers of components and materials. Although disassembly sequencing decisions directly affects the various costs associated with a disassembly-to-order problem, these two issues are treated separately in the literature. In this study, a genetic algorithm (GA) based simulation optimization approach was proposed for the simultaneous determination of disassembly sequence and disassembly-to-order decisions. The applicability of the proposed approach was illustrated by providing a numerical example and the best values of GA parameters were identified by carrying out a Taguchi experimental design.

Determination of Horizontal In-Situ Stress Profiles and Rock Deformation Moduli in Karamay Basin Using a Multiobjective Optimization Technique

SPE Journal ◽  
2021 ◽  
pp. 1-18
Author(s):  
Hongxue Han ◽  
Maurice B. Dusseault ◽  
Shunde Yin ◽  
Guowei Xia ◽  
Mingchao Peng
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Technique ◽  
Cost Effective ◽  
In Situ Stress ◽  
Rock Deformation ◽  
Optimization Approach ◽  
Stress Profiles ◽  
Optimum Solution ◽  
In Situ Stress Measurements

Summary We introduce a quick and cost-effective method of estimating horizontal in-situ stress profiles and rock elastic moduli vs. depth from geophysical logs taken in vertical well sections. A multiobjective optimization approach finds the optimum solution for the inversion of in-situ stresses and the rock mechanical parameters from elastic borehole deformations measured by the commonly available four-arm caliper tools. The four-arm caliper log responses also permit quality control (QC) of input and identification and classification of borehole sections that display breakouts and sloughing. The method is applied in the estimation of horizontal in-situ stress profiles and rock deformation moduli vs. depth in Karamay Basin, Northwestern China. The results have demonstrated good agreement with available field in-situ stress measurements, indicating promising broader applications of the method.

scholarly journals Thickness control in a new flexible hybrid incremental sheet forming process

2017 ◽  
Vol 231 (5) ◽  
pp. 779-791 ◽  
Author(s):  
Huan Zhang ◽  
Bin Lu ◽  
Jun Chen ◽  
Sule Feng ◽  
Zongquan Li ◽  
...  
Keyword(s):  
Production Efficiency ◽  
Thickness Distribution ◽  
Sheet Thickness ◽  
Cost Effective ◽  
Sheet Forming ◽  
Incremental Sheet Forming ◽  
Optimization Approach ◽  
Forming Process ◽  
Thickness Prediction ◽  
Flexible Forming Process

Incremental sheet forming is a cost-effective process for rapid manufacturing of sheet metal products. However, incremental sheet forming also has some limitations such as severe sheet thinning and long processing time. These limitations hamper the forming part quality and production efficiency, thus restricting the incremental sheet forming application in industrial practice. To overcome the problem of sheet thinning, a variety of processes, such as multi-step incremental sheet forming, have been proposed to improve the material flow and thickness distribution. In this work, a new process has been developed by introducing multi-point forming as preforming step before conducting incremental sheet forming processing. Employing an established hybrid sheet forming system and the corresponding thickness prediction model, the preform shape can be optimized by employing a two-step optimization approach to improve the sheet thickness distribution. In total, two case study examples, including a hemisphere part and an aerospace cowling part, are fabricated using the developed hybrid flexible process in this study. The experimental results show that the hybrid flexible forming process with the optimal preform design could achieve sheet parts with more uniform thickness distribution and reduced forming time.

scholarly journals A Global Dynamic Harmony Search for Optimization of a Hybrid Photovoltaic–Battery Scheme: Impact of Type of Solar Panels

2021 ◽  
Vol 14 (1) ◽  
pp. 109
Author(s):  
Jingchao Liu ◽  
Lixue Mei ◽  
Akbar Maleki ◽  
Roghayeh Ghasempour ◽  
Fathollah Pourfayaz
Keyword(s):  
Harmony Search ◽  
Cost Effective ◽  
Optimization Method ◽  
Optimization Approach ◽  
Solar Panels ◽  
Hybrid Scheme ◽  
Total Cost ◽  
Optimal Sizing ◽  
Global Dynamic ◽  
Performance Optimizations

The type of solar panels has a great impact on the optimal sizing of a hybrid photovoltaic–battery scheme. The optimization of these schemes based on a powerful optimization approach results in more cost-effective schemes. In this paper, a new global dynamic harmony search method, as an optimization method, is presented for the optimal sizing of a hybrid photovoltaic–battery scheme. The new optimization method is aimed at minimizing the total cost and loss of load supply probability of the scheme at the same time. In this regard, the effect of the type of solar panels on the optimal sizing of the hybrid scheme is investigated. Furthermore, performance optimizations are performed with an original global dynamic harmony search, an original harmony search, and simulated annealing to determine the effectiveness of the suggested optimization method. The effects of the initial costs and efficiency of monocrystalline and polycrystalline solar panels on the optimization of hybrid systems are analyzed. The superiority of the suggested method in terms of time and cost indicators of the hybrid scheme is presented comparing the other algorithm.

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