A knowledge-based system for numerical design of experiments processes in mechanical engineering

Blondet, Gaëtan; Duigou, Julien Le; Boudaoud, Nassim

doi:10.1016/j.eswa.2019.01.013

Cited by 26 publications

(9 citation statements)

References 22 publications

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“…In recent years, the research focus of the field is gradually shifting to how to acquire and analyze dynamic requirements and technical knowledge to update the configuration model information. For instance, research topics include integrating expert knowledge and discovering new knowledge in configuration 34 or exploring how to improve the efficiency of design module capture and representation for product family reuse. 35…”

Section: Discussionmentioning

confidence: 99%

Customization design method for complex product systems based on a meta-model

Zhang

Qin

et al. 2019

Advances in Mechanical Engineering

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In order to effectively reuse the design knowledge of product family life cycle development and support holistic and rapid individual product design, this article presents a new meta-model-based systemic customization design method for complex product systems within a product-pedigree. The proposed method aims to synthetically analyze the common and adaptive customer demands and product features of a product-pedigree of complex product systems and to quickly respond to the changing demands based on knowledge accumulation in the field of customization design. The key to implement such a method is (1) to construct a product-pedigree-oriented product meta-model with a four-layered architecture where it is possible to achieve a high degree of abstraction of product and (2) to develop a special technique for configuring the meta-model of the complex product systems. We have tested the proposed method with the rapid design of product-pedigree of a high-speed train’s bogies as an illustrative example. In this work, a rapid customization design prototype system has been developed and applied to the design of a high-speed train’s bogie to illustrate how to construct a product meta-model and how to conduct configuration design on different layers and variant design for generating new products.

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Section: Discussionmentioning

confidence: 99%

Customization design method for complex product systems based on a meta-model

Zhang

Qin

et al. 2019

Advances in Mechanical Engineering

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“…As presented in Figure 1, the KBS prototype serves as a bridge for knowledge to pass from expert to user in an indirect path. Tacit knowledge should be explicitly represented to construct the computational system (Blondet et al, 2019). To fulfil its goal, the KBS should ensure not only the integration of experts' knowledge but also clearly present its decision process to help users make well-informed decisions (Blondet et al, 2019).…”

Section: Knowledge-based System Developmentmentioning

confidence: 99%

An artificial intelligence approach to support knowledge management on the selection of creativity and innovation techniques

Botega

Silva

2020

JKM

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Purpose Creativity is an important skill for design teams to reach new and useful solutions. Designers often use one or more of creativity and innovation techniques (CITs) to achieve the desired creative potential during new product development (NPD). The selection of adequate CITs requires considerable expertise, given the multiple application contexts and the extensive number of techniques available. The purpose of this study is to present a creativity support system able to manage this amount of information and provide valuable knowledge to improve NPD. Design/methodology/approach This study presents a knowledge-based system prototype using artificial intelligence (AI) to support knowledge management on the selection of CITs for design. CITs assertion is modelled through a double inference process using five categories, correlating over 500 different entry scenarios to 24 implemented CITs. The techniques are classified according to: design stage, innovation focus, team relationship, execution method and difficult of use. Prototype outputs explanations on the inference process and chosen techniques information. Findings To demonstrate the system scope, two opposite design cases are presented. The system was validated by experts in knowledge management and mechanical engineering design. The validation process demonstrates relevance of the approach and improvement directions for future developments. Originality/value Though literature contains toolkits and taxonomy for CITs, no work applies AI to identify design scenarios, select best CITs and instruct about their use. Validators reported to know less than half of the available techniques, showing a clear knowledge gap among design experts.

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“…Most of them can only realize the query function of knowledge. Essentially, they are only an information publishing system, and the intelligent range and decision-making ability of experts are difficult to surpass [66]. Traditional expert systems for crop diseases and pests have weak decision-making and reasoning abilities.…”

Section: A Expert Systemmentioning

confidence: 99%

“…The search engine framework based on knowledge map is shown in Figure 11. Blondet et al [66] proposed an advanced search engine based on knowledge mapping technology to search and list different types of biomedical entities, including genes, diseases, drugs, targets, and transcription factors associated with user queries with fast response.…”

Section: B Intelligent Semantic Searchmentioning

confidence: 99%

Review and Trend Analysis of Knowledge Graphs for Crop Pest and Diseases

et al. 2019

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Current techniques of knowledge management have some common defects in efficiency, scalability, and applicability. Knowledge graph provides a new way for knowledge management and is a more flexible knowledge management method. Considering the specific features of crop diseases and pest data, this paper analyzed and classified the key techniques and methods of knowledge graph technology in the field of crop diseases and pest in recent years. We introduced the definition and connotation of the crop diseases and pest knowledge, and the current construction method of it was analyzed in detail from four aspects: knowledge representation, extraction, fusion, and reasoning. Furthermore, the application of crop diseases and pest knowledge graph was introduced in detail in the expert system, search engine, and knowledge question-answering system. At last, this paper summarized the challenges and important problems of diseases and pest knowledge graph and forecasted the prospect of knowledge graph according to the key points and difficulties of current knowledge graph research.INDEX TERMS Knowledge graph, crop disease and pest, knowledge extraction, knowledge fusion, knowledge reasoning.

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A knowledge-based system for numerical design of experiments processes in mechanical engineering

Cited by 26 publications

References 22 publications

Customization design method for complex product systems based on a meta-model

Customization design method for complex product systems based on a meta-model

An artificial intelligence approach to support knowledge management on the selection of creativity and innovation techniques

Review and Trend Analysis of Knowledge Graphs for Crop Pest and Diseases

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