Visual Analytics for Evaluation of Value Impact in Engineering Design

Kipouros, Timoleon; Isaksson, Ola

doi:10.7712/100016.2269.9111

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…It is possible, on one end, to quantify all aspects of value in monetary terms, so that they can be more easily traded-off with more traditional requirements. Monetary units are convenient, practical, and universally understood metrics for value, and are beneficial in the design process to stress the potential success of investments [59]. This quantification process in the arena is driven by the implementation of Net Present Value (NPV) and Surplus Value (SV) from the Value Driven Design (VDD) literature [60].…”

Section: Value Analysismentioning

confidence: 99%

The Model-Driven Decision Arena: Augmented Decision-Making for Product-Service Systems Design

Wall

Bertoni

Larsson

2020

Systems

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The shift towards Product-Service Systems (PSS) stresses the need to embed new and unique capabilities in Decision Support Systems, with the aim of helping the engineering team in handling the pool of information and knowledge available during decision events. Emerging from a multiple case study in the Swedish manufacturing industry, this paper describes the development of the Model-Driven Decision Arena (MDDA), an environment for collaborative decision-making that focuses on the early design phases of PSS. Based on the findings from multiple case studies, this paper illustrates the main goals of the MDDA, detailing its main functions, its physical environment, and its software architecture and models. This paper demonstrates the use of the MDDA in a case study related to the development of an asphalt compactor, presenting and discussing the results of verification activities conducted with industrial practitioners on the current MDDA prototype.

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Section: Value Analysismentioning

confidence: 99%

The Model-Driven Decision Arena: Augmented Decision-Making for Product-Service Systems Design

Wall

Bertoni

Larsson

2020

Systems

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“…The ability to successfully trade off between diverse objectives -emphasising downstream lifecycle properties -is of major importance for industry today. This ability is generally linked to the systematic use of modelling and simulation techniques (e.g., Hazelrigg, 1998;Kokkolaras et al, 2004;Kipouros & Isaksson, 2016) organised within decision support systems (Sacks et al, 2010;White et al, 2015). There is currently a growing interest in how to configure these environments for the early design phases (Chandrasegaran et al, 2013;Schleich et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Using models as boundary objects in early design negotiations: analysis and implications for decision support systems

Panarotto

Bertoni

Johansson

2019

JDR

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Enhanced Interactive Parallel Coordinates using Machine Learning and Uncertainty Propagation for Engineering Design

Piotrowski

Kipouros

Clarkson

2019

2019 15th International Conference on eScience (eScience)

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The design process of an engineering system requires thorough consideration of varied specifications, each with potentially large number of dimensions. The sheer volume of data, as well as its complexity, can overwhelm the designer and obscure vital information. Visualisation of big data can mitigate the issue of information overload but static display can suffer from overplotting. To tackle the issue of overplotting and cluttered data, we present an interactive and touch-screen capable visualisation toolkit that combines Parallel Coordinates and Scatter Plot approaches for managing multidimensional engineering design data. As engineering projects require a multitude of varied software to handle the various aspects of the design process, the combined datasets often do not have an underlying mathematical model. We address this issue by enhancing our visualisation software with Machine Learning methods which also facilitate further insights into the data. Furthermore, various software within the engineering design cycle produce information of different level of fidelity (accuracy and trustworthiness), as well as with different speed. The induced uncertainty is also considered and modelled in the synthetic dataset and is also presented in an interactive way. This paper describes a new visualisation software package and demonstrates its functionality on a complex aircraft systems design dataset.

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Visual Analytics for Evaluation of Value Impact in Engineering Design

Abstract: Abstract. Many traditional engineering design processes in industry have

Cited by 3 publications

References 12 publications

The Model-Driven Decision Arena: Augmented Decision-Making for Product-Service Systems Design

The Model-Driven Decision Arena: Augmented Decision-Making for Product-Service Systems Design

Using models as boundary objects in early design negotiations: analysis and implications for decision support systems

Enhanced Interactive Parallel Coordinates using Machine Learning and Uncertainty Propagation for Engineering Design

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