Machine learning and CBR integrated mechanical product design approach

Huo, Yunliang; Liu, Junbo; Xiong, Ji; Xiao, Wenjun; Zhao, Jianfeng

doi:10.1016/j.aei.2022.101611

Cited by 16 publications

(9 citation statements)

References 34 publications

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“…The model learns the latent structure of the domain from the case base to generate a new object that deliberately flouts that structure and then reintegrates the new object with known cases through adaptation to generate novel and valuable recipes. Huo et al (2022) proposed a mechanical product design method integrating ML and CBR to achieve the intelligent design of the whole process of mechanical product development. The method decomposes a design task into multiple small-scale subproblems based on the design knowledge criterion, and the design parameters are managed in groups to reduce the data dimension of the whole task.…”

Section: Design and Planningmentioning

confidence: 99%

A review of the development and future challenges of case-based reasoning

Yan

Cheng

2023

Preprint

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Case-based reasoning (CBR), which is based on the cognitive assumption that similar problems have similar solutions, is an important problem-solving and learning method in the field of artificial intelligence. In this article, the development of CBR is mainly reviewed, and the major challenges of CBR are summarized. The paper is organized into four parts. First, the basic framework and concepts of CBR are introduced. Then, the developed technology and innovative work that were formed in solving problems by CBR are summarized. Moreover, the application fields of CBR are sorted. Finally, according to the idea of deep learning and interpretable artificial intelligence, the main challenges for the future development of CBR are proposed.

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Section: Design and Planningmentioning

confidence: 99%

A review of the development and future challenges of case-based reasoning

Yan

Cheng

2023

Preprint

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“…It can store all the available problems or cases and classify them to the new clusters based on their similarity measure. The outputs are the top k cases with the highest similarity by calculating the similarity between the target case and the source case [42]. The calculation of the single attribute similarity Sim(s,t) between the target case and the source case is based on the following Equations,…”

Section: Plos Onementioning

confidence: 99%

Knowledge graph and CBR-based approach for automated analysis of bridge operational accidents: Case representation and retrieval

Xu,

Wei,

Cai

et al. 2023

PLoS ONE

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Bridge operational accident analysis is a critical process in bridge operational risk management. It provides valuable knowledge support for responding to newly occurring accidents. However, there are three issues: (1) research specifically focused on the past bridge operational accidents is relatively scarce; (2) there is a lack of mature research findings regarding the bridge operational accidents knowledge representation; and (3) in similar case retrieval, while case-based reasoning (CBR) is a valuable approach, there are still some challenges and limitations associated with its usage. To tackle these problems, this research proposed an automated analysis approach for bridge operational accidents based on a knowledge graph and CBR. The approach includes case representation and case retrieval, leveraging advancements in computer science and artificial intelligence. In the proposed approach, the case representation involves the adoption of a knowledge graph to construct multi-dimensional networks. The knowledge graph captures the relationships between various factors and entities, allowing for a comprehensive representation of accidents domain knowledge. In the case retrieval, a multi-circle layer retrieval strategy was innovatively proposed to enhance retrieval efficiency. Three target cases were randomly selected to verify the validity of the proposed methodology. The combination of a knowledge graph and CBR can indeed provide useful tools for the automated analysis of bridge operational accidents. Additionally, the proposed methodology can serve as a reference for intelligent risk management in other types of infrastructures.

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“…29 It makes the design process time-consuming and ineffective. Artificial intelligence technology provides convenience for designers to quickly explore solutions, 30,31 but human factors may still affect the outcome evaluation. 21 Other studies pay more attention to the detailed scheme design and evaluation of new product schemes, 24,25 but the functional requirements of product are mainly planned based on the designers’ knowledge.…”

Section: Introductionmentioning

confidence: 99%

An innovative design of mega shaft boring machine (SBM) cutterhead based on TRIZ and AD theory

Xiao

Liu

Mei

et al. 2023

Advances in Mechanical Engineering

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Cutterhead is the key component of the mega shaft boring machine (SBM), whose complex structure and huge size lead to high manufacturing difficulty and cost, and its reliability is difficult to guarantee under huge loads. It is difficult to design the cutterhead only referring to the existing small horizontal tunnel boring machine cutterhead. In order to brainstorm innovative ideas, the paper incorporates the TRIZ into AD to address the following issues. Firstly, engineering conflicts in designing process are eliminated by TRIZ tools to generating innovative ideas. Then, the decomposition of functional requirements and design parameters are employed based on independence axiom of AD, transferring the abstract ideas into concrete design solutions. Moreover, fuzzy comprehensive evaluation is adopted to choose a better design scheme from alternatives of critical component. Finally, the feasibility and practicality of the proposed approach has been demonstrated through case study of designing a novel mega SBM cutterhead. The cutterhead structure is significantly improved with embedded movable cutter boxes, which can excavate step by step to reduce the driving torque, and the manufacturing and transportation cost has been greatly reduced. The method can help designer to innovative design the key components of large-scale underground tunneling equipment.

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Machine learning and CBR integrated mechanical product design approach

Cited by 16 publications

References 34 publications

A review of the development and future challenges of case-based reasoning

A review of the development and future challenges of case-based reasoning

Knowledge graph and CBR-based approach for automated analysis of bridge operational accidents: Case representation and retrieval

An innovative design of mega shaft boring machine (SBM) cutterhead based on TRIZ and AD theory

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