Virtual genes of manufacturing products and their reforms for product innovative design

Chen, KZ; Feng, XA

doi:10.1243/095440604323052337

Cited by 19 publications

(9 citation statements)

References 8 publications

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“…At present, methods for obtaining product genes mainly include reverse engineering-based (Feng et al ., 2002; Chen and Feng, 2004; Chen et al ., 2005 a , 2005 b ; Ai and Wang, 2012; Ai et al ., 2013; Zhu et al ., 2013; Waris et al ., 2016) and case-based (Tai et al ., 2007; Ai et al ., 2013) product-gene acquisition techniques. Most of these methods have only provided a structured model of the top-level acquisition process.…”

Section: Intelligent Acquisition Methods For Product Genesmentioning

confidence: 99%

Intelligent product-gene acquisition method based on K-means clustering and mutual information-based feature selection algorithm

Wang

Ren

Yan

et al. 2019

AIEDAM

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Conceptual design is a key stage of product design and has received increasing attention in recent years. However, this stage is characterized by limited information, large uncertainty, and multidisciplinary aspects. Thus, increased workload and time cost are associated with conceptual design information acquisition; sometimes, it is difficult to develop novel solutions and the feasibility of the solutions obtained according to these limited and uncertain information is difficult to guarantee. Genetics-based design (GBD) is an effective approach to develop novel solutions and improve the reuse of knowledge, which is consistent with the goal of the conceptual design process. Product-gene acquisition is the premise and basis of GBD. At present, there are few reported studies in this area; most of the existing works are constrained by the structural aspects of the acquisition process, and there are limited studies on specific implementation techniques. To explore the specific implementation technologies of product-gene acquisition, an intelligent acquisition method based on K-means clustering and mutual information-based feature selection algorithm is proposed in this paper. The product genes defined in this paper are key product information that determines the nature of the product and influences the conceptual design process. Thus, solutions obtained according to them are more feasible than that based on limited and uncertain information. An illustrative example is presented. The results show that the proposed method can achieve intelligent acquisition of product genes to a certain extent. Further, the proposed method will allow designers to quickly search for the corresponding product genes when performing similar functional design tasks.

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Section: Intelligent Acquisition Methods For Product Genesmentioning

confidence: 99%

Intelligent product-gene acquisition method based on K-means clustering and mutual information-based feature selection algorithm

Wang

Ren

Yan

et al. 2019

AIEDAM

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show abstract

“…In industrial product design, GA is often used in product gene research. Based on the overall form of the product, the shape is divided into several small feature units until it cannot be divided [27]. At present, related research studies of product gene mostly adopt genetic operations such as crossover and mutation to gradually cultivate a mature scheme after many iterations.…”

Section: Application Of Ga In Industrial Design and Ergonomicsmentioning

confidence: 99%

Dimensional Evolution of Intelligent Cars Human-Machine Interface considering Take-Over Performance and Drivers’ Perception on Urban Roads

2020

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The study analyzed the drivers’ take-over behaviors in intelligent cars when driving on urban roads and tried to find reasonable dimensions of the human-machine interface. Firstly, the main driving assistance functions in the process of take-over were analyzed based on the entropy theory, and the weight values of each function for the consumer’s purchase intention were calculated. Secondly, we explored the perceived comfortable dimensions of the interactive components under typical interaction modes. By means of experiments using a within-subjects design, the initial population of the evolutionary computation was obtained. The evolutionary mechanism of dimensions driven by users’ perception was constructed with a genetic algorithm. After debugging the parameters of the model, we verified the rationality of the model and evolved appropriate dimensions. Finally, the validity of the evolved dimensions was proved by a controlled experiment and paired-sample t-test. The results indicated that the completion time of most take-over tasks under the HMI with the evolved dimensions was significantly shorter, which ensured the HMI could be more conducive to the take-over quality and traffic efficiency.

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“…Genetic engineering comes from the field of biology. It is introduced into the manufacturing field for its similarity with products which have been studied in the literature [26][27][28]. To increase the efficiency and quality of designing, Shang et al [29] introduced the concept of the functional surface as the information carrier to link product function and structure together.…”

Section: Related Workmentioning

confidence: 99%

A Novel Quality Defects Diagnosis Method for the Manufacturing Process of Large Equipment Based on Product Gene Theory

Chen

Guo

et al. 2019

Symmetry

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Focusing on the problems of quality information management and quality defects diagnosis in the manufacturing process of large equipment, a novel quality defects diagnosis method based on product gene theory and knowledge base was developed. First, a product gene model and a sectional encoding method for the quality control of the manufacturing process of large equipment were proposed. In that model, the processing surface was the minimum information granularity to meet the production characteristics of large equipment and to improve the flexibility of the product gene model. Then, a similarity evaluation rule and an optimization method of the weights of elements based on particle swarm optimization (PSO) were addressed to filter the available knowledge of product gene from the product gene knowledge base. Aiming at the characteristic of many-to-many between quality defects and quality influence factors in some cases, a fuzzy comprehensive evaluation (FCE) method was developed for the further localization of diagnosis knowledge. Finally, an experiment of bearing spacer was applied to illustrate the proposed quality diagnosis approach. In the experiment, the data from the target gene and knowledge genes were described reasonably. On this basis, available knowledge genes could be accurately filtered with the proposed similarity rule and the method of filtration, where the PSO was proved to be effective. The diagnosis results of the experiment show that multiple factors lead to the defects that were verified. Therefore, the proposed quality defects diagnosis method is an effective way for quality control.

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Virtual genes of manufacturing products and their reforms for product innovative design

Cited by 19 publications

References 8 publications

Intelligent product-gene acquisition method based on K-means clustering and mutual information-based feature selection algorithm

Intelligent product-gene acquisition method based on K-means clustering and mutual information-based feature selection algorithm

Dimensional Evolution of Intelligent Cars Human-Machine Interface considering Take-Over Performance and Drivers’ Perception on Urban Roads

A Novel Quality Defects Diagnosis Method for the Manufacturing Process of Large Equipment Based on Product Gene Theory

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