A Bayesian Network Based Adaptability Design of Product Structures for Function Evolution

Li, Shaobo; Wu, Yongming; Xu, Yan; Hu, Jie; Hu, Jianjun

doi:10.3390/app8040493

Cited by 14 publications

(10 citation statements)

References 31 publications

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“…In the initial stage, product development must simply meet the market demands. Over time, however, some external factors force enterprises to develop their products to meet new consumer demands [18]. In this process, a product family tree is gradually formed.…”

Section: Product Serialization and Spider-web Structurementioning

confidence: 99%

“…Wang applied the genetic algorithm (GA) and a back propagation (BP) neural network to establish a nonlinear mapping relationship between product form and images and ultimately realized the multiobjective optimization design of product form [17]. Based on Bayesian networks, Li proposed a dynamic analysis model of product design evolution to study the dynamic relationship between consumer demand and product design [18]. Feng parameterized the shape of motorcycle seat, evaluated it with the method of Kansei Engineering, established the equation of Kansei regression analysis, and finally forecasted the shape of motorcycle with grey model [19].…”

mentioning

confidence: 99%

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Applications Virtually Augmenting Real Experiences for Behavioral Change

Carulli¹,

Bordegoni²,

Spadoni³

2021

CADandA

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Product serialization design is an effective method for product family development. To explore the development law of product serialization, the kansei image change law within the series, and the interaction mechanisms of kansei image and form between the series, this paper proposes an evolutionary design method of product form inspired by Spider-webs. Inspired by the special structure and mechanical properties of Spider-webs in nature, at the macro level, we use the structure of the Spider-webs to describe the relationship between products in the product family. At the micro level, based on the mechanical properties of spiderwebs, we analyzed the development law of the product form within and between the series in the product family and then proposed a calculation method for the crossover coefficient and variation coefficient (in the genetic algorithm) for product form evolution. This method provides a scientific basis for determining the crossover coefficient and the variation coefficient from a new perspective. The case study results show that this model can effectively simulate the changing laws of design cognition and the evolution laws of product form, thereby providing a theoretical basis for the intelligent design of product form in a product family.

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Section: Product Serialization and Spider-web Structurementioning

confidence: 99%

mentioning

confidence: 99%

Applications Virtually Augmenting Real Experiences for Behavioral Change

Carulli¹,

Bordegoni²,

Spadoni³

2021

CADandA

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“…The possibility of semantic linkage and the possibility of generating knowledge out of the represented data are particularly noteworthy. BN is also increasingly used in product development [30] and in the design of sustainable product lines under consideration of the multi-life cycle [31].…”

Section: Knowledge Representation Using Dynamic Bayesian Networkmentioning

confidence: 99%

A Knowledge-Based Digital Lifecycle-Oriented Asset Optimisation

Passath

Huber

Biedermann

et al. 2021

Teh. glas. (Online)

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The digitalisation of the value chain promotes sophisticated virtual product models known as digital twins (DT) in all asset-life-cycle (ALC) phases. These models. however, fail on representing the entire phases of asset-life-cycle (ALC), and do not allow continuous life-cycle-costing (LCC). Hence, energy efficiency and resource optimisation across the entire circular value chain is neglected. This paper demonstrates how ALC optimisation can be achieved by incorporating all product life-cycle phases through the use of a RAMS²-toolbox and the generation of a knowledge-based DT. The benefits of the developed model are demonstrated in a simulation, considering RAMS2 (Reliability, Availability, Maintainability, Safety and Sustainability) and the linking of heterogeneous data, with the help of a dynamic Bayesian network (DBN).

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“…Dou, Zhang, and Nan (2017) developed a dynamic model based on the Hegselmann-Krause model for analysing the changing trends of group opinions and the evolution regularity. Li et al (2018) proposed a quantitative product evolution design model that is based on Bayesian networks to model the dynamic relationship between customer needs and product structure design. Because product changes have often triggered a change or a series of changes in its manufacturing system, a biological analogy is utilised to establish a co-evolution model.…”

Section: Pfe Modelling and Mappingmentioning

confidence: 99%

Progressive modelling of feature-centred product family development

Zhang

Qin

et al. 2019

International Journal of Production Research

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Modelling a product family is critical for understanding the evolution of key design and manufacturing features associated with products in the product through-life development. This research aims to establish a model for the holistic description of the evolution process of a product family to support rapid development of new products with hybrid innovations. In this study, a new broader definition of the product family is proposed for products on cross-platforms but in the same class or category, called feature-centred product family. A progressive modelling of feature-centred product family is developed for progressively addressing the evolution of products and achieving the dynamic expression of a product family. A prototype system has been developed and tested with an industrial case study, which indicates that the proposed new feature-centred product family concept and progressive modelling method are not only supportive to realise the common and adaptive analysis of key design features but also helpful to improve the design and production efficiency of innovative products with knowledge and feature reuse.

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A Bayesian Network Based Adaptability Design of Product Structures for Function Evolution

Abstract: The designers and managers for product development in a production enterprise (e.g., the production of electric toothbrush) can obtain an optimal solution for structure dynamic design through the evolution design model based on Bayesian network proposed in this paper.

Cited by 14 publications

References 31 publications

Applications Virtually Augmenting Real Experiences for Behavioral Change

Applications Virtually Augmenting Real Experiences for Behavioral Change

A Knowledge-Based Digital Lifecycle-Oriented Asset Optimisation

Progressive modelling of feature-centred product family development

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