Gearbox design for uncertain load requirements using active robust optimization

Avigad, Gideon; Purshouse, Robin C.; Fleming, Peter J.

doi:10.1080/0305215x.2015.1031659

Cited by 15 publications

(6 citation statements)

References 32 publications

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“…On the other hand, Ognjanovic & Milutinovic (2013) adopt a reliability-based methodology to design an automotive gearbox to operate under varying and random operation conditions. Salomon et al (2016) extend the gearbox design optimisation to consider uncertainties in load demand. The authors utilise active robust (AR) optimisation to optimise the number of transmissions and their gearing ratios for an uncertain load demand.…”

Section: /31mentioning

confidence: 99%

A method for robust design in a coupled decision environment

2021

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The design of a connected engineered system requires numerous design decisions that influence one another. In a connected system that comprises numerous interacting decisions involving concurrency and hierarchy, accounting for interactions while also managing uncertainties, it is imperative to make robust decisions. In this article, we present a method for robust design using coupled decisions to identify design decisions that are relatively insensitive to uncertainties. To account for the influence among decisions, design decisions are modelled as coupled decisions. They are defined using three criteria: the types of decisions, the strength of interactions and the decision levels. In order to make robust decisions, robust design methods are classified based on sources of uncertainty, namely, Type I (noise factors), Type II (design variables) and Type III (function relationship between design variables and responses). The design of a one-stage reduction gearbox is used as a demonstration example. To illustrate the proposed method for robust design using coupled decisions, we present the simultaneous selection of gear material and gearbox geometry in a coupled decision environment while managing the uncertainties involved in designing gearboxes.

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Section: /31mentioning

confidence: 99%

A method for robust design in a coupled decision environment

2021

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“…The methodology was first introduced in Salomon et al (2014), and part of the analysis provided in this thesis was published in Salomon et al (2016a). The methodology is described, demonstrated and analysed in Chapter 3.…”

Section: Contributionsmentioning

confidence: 99%

Active Robust Optimization: Optimizing for Robustness of Changeable Products

Salomon

2019

Springer Theses

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To succeed in a demanding and competitive market, great attention needs to be given to the process of product design. Incorporating optimization into the process enables the designer to find high-quality products according to their simulated performance. However, the actual performance may differ from the simulation results due to a variety of uncertainty factors. Robust optimization is commonly used to search for products that are less affected by the anticipated uncertainties. Changeability can improve the robustness of a product, as it allows the product to be adapted to a new configuration whenever the uncertain conditions change. This ability provides the changeable product with an active form of robustness.Several methodologies exist for engineering design of changeable products, none of which includes optimization. This study presents the Active Robust Optimization (ARO) framework that offers the missing tools for optimizing changeable products. A new optimization problem is formulated, named Active Robust Optimization Problem (AROP). The benefit in designing solutions by solving an AROP lies in the realistic manner adaptation is considered when assessing the solutions' performance.The novel methodology can be applied to optimize any product that can be classified as a changeable product, i.e., it can be adjusted by its user during normal operation. This definition applies to a huge variety of applications, ranging from simple products such as fans and heaters, to complex systems such as production halls and transportation systems. The ARO framework is described in this dissertation and its unique features are studied. Its ability to find robust changeable solutions is examined for different sources of uncertainty, robustness criteria and sampling conditions. Additionally, a framework for Active Robust Multi-objective Optimization is developed. This generalisation of ARO itself presents many challenges, not encountered in previous studies. Novel approaches for evaluating and comparing changeable designs comprising multiple objectives are proposed along with algorithms for solving multi-objective AROPs.The framework and associated methodologies are demonstrated on two applications from different fields in engineering design. The first is an adjustable optical table, and the second is the selection of gears in a gearbox.iii Statement of OriginalityUnless otherwise stated in the text, the work described in this thesis was carried out solely by the candidate. None of this work has already been

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“…Another opportunity, arising from the use of variable speed operation of the prime movers and lack of requirement for the synchronization of the generators, is the consideration of high speed ICEs and gas turbines as the principle prime movers for high speed generators. This presents the possibility to remove step up/reduction gearboxes, interfacing the prime movers and the generators, considering that their efficiency is around 70% and their size is considerable at high power levels [21]. A summary of the available prime mover technologies is provided in TABLE I.…”

Section: A Prime Moversmentioning

confidence: 99%