Parametric optimization of parameters affecting dimension precision of FDM printed part using hybrid Taguchi-MARCOS-nature inspired heuristic optimization technique

Mohanty, Abhishek; Nag, Keshab Singh; Bagal, Dilip Kumar; Barua, Abhishek; Jeet, Siddharth; Mahapatra, Siba Sankar; Cherkia, Hemanta

doi:10.1016/j.matpr.2021.06.216

Cited by 36 publications

(14 citation statements)

References 29 publications

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“…This Sun flower equivalent photo flow system was thought to enable the expansion of the Wolff rearrangement under solar light. 33–36 In order to pursue the same initially, a tilted solar panel with an angular position to take maximum light intensity, was established. It was observed that the solar panel with a 50-degree angular position had optimal light irradiation on the plate at CSIR-IICT, Hyderabad.…”

Section: Resultsmentioning

confidence: 99%

A solar tracker integrated microreactor for real-time sunlight induced ketene formation and API synthesis

et al. 2022

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Section: Resultsmentioning

confidence: 99%

A solar tracker integrated microreactor for real-time sunlight induced ketene formation and API synthesis

et al. 2022

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“…The meta-heuristic, also developed at GEMEC, has been successful in identifying cracks (Pereira et al [2020]) and delaminations (Pereira et al [2021]), isogrid tube optimization (Francisco et al [2020]; Pereira et al [2022a]), hydrogen production optimization (Souza et al [2022]), wind forecast optimization (Tian & Wang [2022]), parameter optimization in manufacturing processes (Challan et al [2022]; Mohanty et al [2022]), and multi-objective optimization (Pereira et al [2022]), among other applications. The LA algorithm in the mono-objective version has already been well explained in previous chapters.…”

Section: Lichtenberg and Multi-objective Lichtenberg Algorithmsmentioning

confidence: 99%

Sensor Placement Optimization of a Helicopter Main Rotor Blade

Pereira¹,

Francisco²,

Jorge³

et al. 2022

Uncertainty Modeling: Fundamental Concepts and Models

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This chapter describes the importance of one of the major areas within Structural HealthMonitoring and Health and Usage Monitoring Systems: Sensor Placement Optimization (SPO). In this sense, the most important SPO metrics are presented and discussed with the reader. The methodological procedure of the optimization problem statement is also considered and discussed. he significance of rotary-wing aircraft, damages that can occur in the blade, works related to damage identification, modern methods and algorithms that have been used in this context, and a comprehensive SPO study for a helicopter main rotor blade will be presented. Finally, a new technique that considers the number of sensors as an objective associated with some of the main metrics used in SPO. The technique uses the Multiobjective Lichtenberg Algorithm and Feature Selection, an important area used in Data Mining.

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“…Existing nature-inspired algorithms research primarily addresses the following areas of research: optimization [1, 2, 60, 61] using metaheuristics [62] or heuristics [63] approaches; greening processes, for example greening the supply chain [64], smart energy management [65], data center energy efficiency [66]; energy efficiency [67] and energy optimization [68] in wireless sensor network clustering. Our critical literature review has shown that to date, there is no research on energy efficient natureinspired algorithms and thus, our research aims to address this identified gap.…”

Section: Nature-inspired Algorithms and Energy Efficiencymentioning

confidence: 99%

Analyzing energy consumption of nature-inspired optimization algorithms

Jamil

Kor

2022

GRN TECH RES SUSTAIN

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Nature-Inspired Optimization (NIO) algorithms have become prevalent to address a variety of optimization problems in real-world applications because of their simplicity, flexibility, and effectiveness. Some application areas of NIO algorithms are telecommunications, image processing, engineering design, vehicle routing, etc. This study presents a critical analysis of energy consumption and their corresponding carbon footprint for four popular NIO algorithms. Microsoft Joulemeter is employed for measuring the energy consumption during the runtime of each algorithm, while the corresponding carbon footprint of each algorithm is calculated based on the UK DEFRA guide. The results of this study evidence that each algorithm demonstrates different energy consumption behaviors to achieve the same goal. In addition, a one-way Analysis of Variance (ANOVA) test is conducted, which shows that the average energy consumption of each algorithm is significantly different from each other. This study will help guide software engineers and practitioners in their selection of an energy-efficient NIO algorithm. As for future work, more NIO algorithms and their variants can be considered for energy consumption analysis to identify the greenest NIO algorithms amongst them all. In addition, future work can also be considered to ascertain possible relationships between NIO algorithms and the energy usage of hardware resources of different CPU architectures.

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Parametric optimization of parameters affecting dimension precision of FDM printed part using hybrid Taguchi-MARCOS-nature inspired heuristic optimization technique

Cited by 36 publications

References 29 publications

A solar tracker integrated microreactor for real-time sunlight induced ketene formation and API synthesis

A solar tracker integrated microreactor for real-time sunlight induced ketene formation and API synthesis

Sensor Placement Optimization of a Helicopter Main Rotor Blade

Analyzing energy consumption of nature-inspired optimization algorithms

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