Survey on the use of computational optimisation in UK engineering companies

Tiwari, Ashutosh; Hoyos, Paula Noriega; Hutabarat, Windo; Turner, Christopher; Ince, Nadir; Gan, Xiao-Peng; Prajapat, Neha

doi:10.1016/j.cirpj.2015.01.003

Cited by 11 publications

(8 citation statements)

References 4 publications

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“…A multidisciplinary design optimization (MDO) platform, modeFRONTIER® was used for optimisation (https://www. esteco.com/modefrontier) which facilitates the process of integration of various design tables/tools and exchanging in-formation among them [57] and it is one of the widely used for computational optimisation in UK engineering industries [58]. Basically, the response surface model-based optimisation is built in three stages: firstly, to develop effective meta-models/ surrogate models based on the experimental/simulation trial results [59,60]; secondly, to validate the meta-models using one or more algorithms to estimate the accuracy of each of the Fig.…”

Section: Weld Quality-based Strength Optimizationmentioning

confidence: 99%

“…Basically, the response surface model-based optimisation is built in three stages: firstly, to develop effective meta-models/ surrogate models based on the experimental/simulation trial results [59,60]; secondly, to validate the meta-models using one or more algorithms to estimate the accuracy of each of the Fig. 18 Multi-layered joint weld interfaces for T-peel strength evaluation models with insights feature [58]; and lastly, to use it to perform a virtual (RSM-based) optimisation [61,62]. The optimisation workflow linking the input process parameters to output variables through developed response surface models is shown in Fig.…”

Section: Weld Quality-based Strength Optimizationmentioning

confidence: 99%

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Process robustness and strength analysis of multi-layered dissimilar joints using ultrasonic metal welding

Das

Masters

Williams

2018

Int J Adv Manuf Technol

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This paper investigates the effects of process parameters on the joint strength and process robustness when multi-layered joints of dissimilar metals are produced by ultrasonic metal welding (UMW). Three layers of 0.3-mm aluminium sheet are welded with a single 1.0-mm copper sheet which is representative of electric vehicle battery interconnects. A process robustness study in which welding pressure, amplitude of vibration and welding time are varied to produce satisfactory welds is reported. The weld quality is evaluated by performing lap shear and T-peel tests where maximum loads are considered as the quality indicator. Response surfaces are developed to identify the relationship and sensitivity between the input process parameters and output quality indicators. A feasible weldability zone is defined for the first time by identifying the under-weld, good-weld and over-weld conditions based on load-displacement curves and corresponding failure modes. Relying on the weldability zone and response surfaces, multi-objective optimisation is performed to obtain maximum lap shear and T-peel strength which resulted in Pareto frontier or trade-off curve between both objectives. An optimal joint is selected from the Pareto front which is verified and validated by performing confirmation experiments, and further, used for T-peel strength analysis of different interfaces of the multi-layered joint. To conclude, this paper determines both the optimal weld parameters and the robust operating range.

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Section: Weld Quality-based Strength Optimizationmentioning

confidence: 99%

Section: Weld Quality-based Strength Optimizationmentioning

confidence: 99%

Process robustness and strength analysis of multi-layered dissimilar joints using ultrasonic metal welding

Das

Masters

Williams

2018

Int J Adv Manuf Technol

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“…Computational optimisation process is widely used for finding the optimum solution to such problems [1]. For a problem with a single objective function, it is normally expected that the optimisation process, with a set of identified input data, will provide a maximum (or minimum) value for the objective function.…”

Section: Introductionmentioning

confidence: 99%

“…In such a process, the optimum solution can be defined as the best solution for the objectives chosen whilst satisfying any imposing constraints. Computational optimisation utilises computational power to perform the optimisation and is currently used in many different fields, particularly within engineering [1]. Within the design industry, computational optimisation can be used to find the optimum design for the required function, size, weight or cost, to name a few objectives.…”

Section: Introductionmentioning

confidence: 99%

Structural analysis and topology optimisation of an aftercooler cover for weight reduction in off-highway engine application

Murton

Rahmani

Crew

2018

IJPT

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It is endeavoured to gain design direction by use of computational topology optimisation methods on off-highway engines to improve fuel economy and costs to the service provider via weight reductions. Most published studies are focused on key functional components of an on-highway vehicle that are required for the engine or vehicle to function. However, this study aims to use topology optimisation methods on the off-highway Cummins Inc. QSK78 aftercooler cover to achieve an improved design that at least maintains the current product performance, while the weight of the component is reduced. Such analysis has not hitherto reported in the context of offhighway vehicles. The method involves using topology optimisation techniques based on the given objectives relating to strain energy and natural frequencies. The topology optimisation results are used to provide an informed direction for the design of an optimised 3D CAD model. FEA is used to investigate the structural response of both the baseline and optimised covers. The final optimised design shows an improvement even at worst case of generated stress results while a weight reduction of 6.5% is achieved. It was concluded that further improvements could be made in the optimised design considering limitations due to customer constraints.

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“…Select the optimisation algorithm: This step includes choosing the optimisation algorithm and setting the appropriate algorithm parameters. The sub-process for selecting the optimisation algorithm is adapted from the work of Tiwari et al [30]. The user is guided through a series of sequential steps to reveal the nature of the optimisation problem at hand.…”

Section: Define Constraintsmentioning

confidence: 99%

A Novel Framework for Simulation-based Optimisation of Maintenance Systems

Alrabghi¹,

Tiwari²

2016

Int. j. simul. model.

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The maintenance function in manufacturing has been gaining growing interest and significance. Simulation based optimisation has a high potential in supporting maintenance managers to make the right decisions in complex maintenance systems. Surveys in maintenance optimisation have repeatedly reported the need of a framework that provides adequate level of details to guide both academics and practitioners in optimising maintenance systems. The purpose of the current study is to address this gap by developing a novel framework that supports decision making for maintenance in manufacturing systems. The framework is developed by synthesising research attempts to optimise maintenance by simulation, examining existing maintenance optimisation frameworks and capturing framework requirements from review papers in the area as well as publications on future maintenance applications. As a result, the framework addresses current issues in maintenance such as complexity, multi-objective optimisation and uncertainty. The framework is represented by a standard flowchart to facilitate its use.

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Survey on the use of computational optimisation in UK engineering companies

Cited by 11 publications

References 4 publications

Process robustness and strength analysis of multi-layered dissimilar joints using ultrasonic metal welding

Process robustness and strength analysis of multi-layered dissimilar joints using ultrasonic metal welding

Structural analysis and topology optimisation of an aftercooler cover for weight reduction in off-highway engine application

A Novel Framework for Simulation-based Optimisation of Maintenance Systems

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