Assembly process case matching based on a multilevel assembly ontology method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hanqing Gong ◽  
Lingling Shi ◽  
Xiang Zhai ◽  
Yimin Du ◽  
Zhijing Zhang
Keyword(s):  
Individual Case ◽  
Case Based Reasoning ◽  
Assembly Process ◽  
Matching Method ◽  
Process Knowledge ◽  
Content Type ◽  
Distance Model ◽  
Case Structure ◽  
Structure Assembly ◽  
Accurate Matching

Purpose The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience. Design/methodology/approach By integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed. Findings By fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components. Originality/value The process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.

A Computer Disassembly Method Based on Ontology-Case-Based Reasoning

2012 ◽  
Vol 452-453 ◽  
pp. 1398-1402 ◽  
Author(s):  
Ying Cheng ◽  
Jian Jun Yi ◽  
Hui Jiang ◽  
Yu Lin ◽  
Shao Li Chen
Keyword(s):  
Individual Case ◽  
New Method ◽  
Case Based Reasoning ◽  
The Individual ◽  
Case Structure ◽  
Case Based ◽  
The Way

The traditional computer disassembly method can only be used to deal with some simply disassembly. Meanwhile the process of disassembly solution is mainly done by manual with the help of specialists and computers. To solve these problems, a new computer disassembly method, ontology-case-based reasoning (OCBR) is presented in this paper. In this method, the traditional disassembly method CBR is improved. The ontology, which is employed to build the case structure and to describe the individual case, is applied to the modified CBR. Due to the properties of ontology, the new method performs quite in theory and it paves the way of computer disassembly research in future.

An agent-based supplier selection framework

2015 ◽  
Vol 8 (2/3) ◽  
pp. 180-205 ◽  
Author(s):  
Alireza Jahani ◽  
Masrah Azrifah Azmi Murad ◽  
Md. Nasir bin Sulaiman ◽  
Mohd. Hasan Selamat
Keyword(s):  
Supply Chain ◽  
Supplier Selection ◽  
Information Overload ◽  
Case Based Reasoning ◽  
Multi Agent Systems ◽  
Content Type ◽  
Agent Based ◽  
Common Framework ◽  
Multi Agent ◽  
Case Based

Purpose – The purpose of this paper is to propose an approach that integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning. Unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today’s supply chains. In addition, a few existing agent-based approaches are tied to real-world supply chain functions like supplier selection. These approaches are static and do not adequately take the qualitative and quantitative factors into consideration. Therefore, an agent-based framework is needed to address these issues. Design/methodology/approach – The proposed approach integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning, as a common framework. These perspectives were rarely used together as a common framework in previous studies. Furthermore, an exploratory case study in an office furniture company is undertaken to illustrate the value of the framework. Findings – The proposed agent-based framework evaluates supply offers based on customers’ preferences, recommends alternative products in the case of stock-out and provides a collaborative environment among agents who represent different supply chain entities. The proposed fuzzy case-based reasoning (F-CBR) approach reduces the information overload by organizing them into the relevant cases that causes less overall search between cases. In addition, its fuzzy aspect addresses the high uncertainty of supply chains, especially when there are different customers’ orders with different preferences. Research limitations/implications – The present study does not include the functions of inventory management and negotiation between agents. Furthermore, only the case description and case retrieval phases of the case-based reasoning approach are investigated, and the remaining phases like case retaining, case reusing and case revising are not included in the scope of this paper. Originality/value – This framework balances the interests of different supply chain structural elements where each of them is represented by a specific agent for better collaboration, decision-making and problem-solving in a multi-agent environment. In addition, the supplier selection and order gathering mechanisms are developed based on customers’ orders.

Contextual case-based reasoning applied to a mobile device

2017 ◽  
Vol 13 (3) ◽  
pp. 282-299 ◽  
Author(s):  
Djamel Guessoum ◽  
Moeiz Miraoui ◽  
Chakib Tadj
Keyword(s):  
Mobile Device ◽  
Inertial Sensors ◽  
Contextual Information ◽  
Similarity Measures ◽  
Case Based Reasoning ◽  
Two Stage ◽  
Minimal Processing ◽  
Current Case ◽  
Content Type ◽  
Case Based

Purpose This paper aims to apply a contextual case-based reasoning (CBR) to a mobile device. The CBR method was chosen because it does not require training, demands minimal processing resources and easily integrates with the dynamic and uncertain nature of pervasive computing. Based on a mobile user’s location and activity, which can be determined through the device’s inertial sensors and GPS capabilities, it is possible to select and offer appropriate services to this user. Design/methodology/approach The proposed approach comprises two stages. The first stage uses simple semantic similarity measures to retrieve the case from the case base that best matches the current case. In the second stage, the obtained selection of services is then filtered based on current contextual information. Findings This two-stage method adds a higher level of relevance to the services proposed to the user; yet, it is easy to implement on a mobile device. Originality/value A two-stage CBR using light processing methods and generating context aware services is discussed. Ontological location modeling adds reasoning flexibility and knowledge sharing capabilities.

Comprehensive identification of aircraft coordination feature based on complete importance modeling and its engineering application

2018 ◽  
Vol 38 (4) ◽  
pp. 398-411 ◽  
Author(s):  
Feiyan Guo ◽  
Fang Zou ◽  
Jian Hua Liu ◽  
Bo Zhao ◽  
Zhongqi Wang
Keyword(s):  
Engineering Application ◽  
Laboratory Method ◽  
Correction Coefficient ◽  
Assembly Process ◽  
Quality Loss ◽  
Content Type ◽  
Aircraft Manufacturing ◽  
Close Relationship ◽  
Geometric Size ◽  
Assembly Precision

Purpose Coordination feature (CF) is the information carrier in dimension and shape transfer process in aircraft manufacturing. The change of its geometric size, shape, position or other attributes would affect the consistency of accumulated errors between two or more assemblies. To identify these “key characteristics” that have a close relationship with the assembly precision, a comprehensive method was developed under digital manufacturing environment, which was based on importance calculation. The multi-hierarchy and multi-station assembly process of aircraft products were also taken into consideration. Design/methodology/approach First, the interaction and evaluation relationship between components at different manufacturing stages was decomposed with a hierarchical net. Second, to meet coordination accuracy requirements, with the integrated application of Taguchi quality loss function, accuracy principal and error correction coefficient H, the quality loss between target features and candidate features at adjacent assembly hierarchies were calculated, which was based on their precision variation. Third, the influence degree and affected degree of the features were calculated with DEMATEL (decision-making trial and evaluation laboratory) method, and the concepts of centrality degree index and cause degree index were proposed for calculating the complete importance degree to eventually identify the CFs. Findings Based on the proposed methodology, CFs, affecting the skin profile and the flush coordination accuracy, were successfully identified at different assembly hierarchies to a certain type of wing flap component. Originality/value Benefit results for the engineering application showed that the deviation of skin profile was more accurate than before, and the tolerance was also closer to the centerline of required assembly precision range. Moreover, the stability in the assembly process was increased by 26.9 per cent, which could bring a higher assembly quality and an enhancement on aircraft’s flight performance.

scholarly journals Process Knowledge Graph Modeling Techniques and Application Methods for Ship Heterogeneous Models

2021 ◽  
Author(s):  
Jinfeng Liu ◽  
Jianwei Dong ◽  
Xuwen Jing ◽  
Xuwu Cao ◽  
Chenxiao Du ◽  
...  
Keyword(s):  
Process Design ◽  
Welding Process ◽  
Mapping Method ◽  
Knowledge Graph ◽  
Case Based Reasoning ◽  
Test Model ◽  
Process Knowledge ◽  
Heterogeneous Model ◽  
Heterogeneous Models ◽  
Component Assembly

Abstract In the process design and reuse of marine component products, there are a lot of heterogeneous models, causing the problem that the process knowledge and process design experience contained in them are difficult to express and reuse. Therefore, a process knowledge representation model for ship heterogeneous model is proposed in this paper. Firstly, the multi-element process knowledge graph is constructed, and the heterogeneous ship model is described in a unified way. Then, the multi-strategy ontology mapping method is applied, and the semantic expression between the process knowledge graph and the entity model is realized. Finally, by obtaining implicit semantics based on case-based reasoning and checking the similarity of the matching results, the case knowledge reuse is achieved, to achieve rapid design of the process. This method provides reliable technical support for the design of ship component assembly and welding process, greatly shortens the design cycle, and improves the working efficiency. In addition, a case study of the test model is carried out to verify the feasibility and efficiency of the proposed method.

Integrating fuzzy case-based reasoning, parametric and feature-based cost estimation methods for machining process

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fentahun Moges Kasie ◽  
Glen Bright
Keyword(s):  
Cost Estimation ◽  
Intelligent System ◽  
Machining Process ◽  
Estimation Methods ◽  
Case Based Reasoning ◽  
Cost Estimates ◽  
Content Type ◽  
Estimation Techniques ◽  
Feature Based ◽  
Case Based

Purpose This paper aims to propose an intelligent system that serves as a cost estimator when new part orders are received from customers. Design/methodology/approach The methodologies applied in this study were case-based reasoning (CBR), analytic hierarchy process, rule-based reasoning and fuzzy set theory for case retrieval. The retrieved cases were revised using parametric and feature-based cost estimation techniques. Cases were represented using an object-oriented (OO) approach to characterize them in n-dimensional Euclidean vector space. Findings The proposed cost estimator retrieves historical cases that have the most similar cost estimates to the current new orders. Further, it revises the retrieved cost estimates based on attribute differences between new and retrieved cases using parametric and feature-based cost estimation techniques. Research limitations/implications The proposed system was illustrated using a numerical example by considering different lathe machine operations in a computer-based laboratory environment; however, its applicability was not validated in industrial situations. Originality/value Different intelligent methods were proposed in the past; however, the combination of fuzzy CBR, parametric and feature-oriented methods was not addressed in product cost estimation problems.

Variation analysis driven by small-sample data for compliant aero-structure assembly

2019 ◽  
Vol 39 (1) ◽  
pp. 101-112 ◽  
Author(s):  
Biao Mei ◽  
Weidong Zhu ◽  
Yinglin Ke ◽  
Pengyu Zheng
Keyword(s):  
Probability Distributions ◽  
Small Sample ◽  
Accurate Estimation ◽  
Production Volume ◽  
Analysis Method ◽  
Variation Analysis ◽  
Content Type ◽  
Aircraft Manufacturing ◽  
Sample Data ◽  
Structure Assembly

Purpose Assembly variation analysis generally demands probability distributions of variation sources. However, due to small production volume in aircraft manufacturing, especially prototype manufacturing, the probability distributions are hard to obtain, and only the small-sample data of variation sources can be consulted. Thus, this paper aims to propose a variation analysis method driven by small-sample data for compliant aero-structure assembly. Design/methodology/approach First, a hybrid assembly variation model, integrating rigid effects with flexibility, is constructed based on the homogeneous transformation and elasticity mechanics. Then, the bootstrap approach is introduced to estimate a variation source based on small-sample data. The influences of bootstrap parameters on the estimation accuracy are analyzed to select suitable parameters for acceptable estimation performance. Finally, the process of assembly variation analysis driven by small-sample data is demonstrated. Findings A variation analysis method driven by small-sample data, considering both rigid effects and flexibility, is proposed for aero-structure assembly. The method provides a good complement to traditional variation analysis methods based on probability distributions of variation sources. Practical implications With the proposed method, even if probability distribution information of variation sources cannot be obtained, accurate estimation of the assembly variation could be achieved. The method is well suited for aircraft assembly, especially in the stage of prototype manufacturing. Originality/value A variation analysis method driven by small-sample data is proposed for aero-structure assembly, which can be extended to deal with other similar applications.

A case-based reasoning system for fault detection and isolation: a case study on complex gearboxes

2019 ◽  
Vol 25 (2) ◽  
pp. 213-235 ◽  
Author(s):  
Soumava Boral ◽  
Sanjay Kumar Chaturvedi ◽  
V.N.A. Naikan
Keyword(s):  
Decision Making ◽  
Fault Detection ◽  
Large Scale ◽  
Fault Detection And Isolation ◽  
Decision Making Process ◽  
Case Based Reasoning ◽  
Content Type ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Case Based

Purpose Usually, the machinery in process plants is exposed to harsh and uncontrolled environmental conditions. Even after taking different types of preventive measures to detect and isolate the faults at the earliest possible opportunity becomes a complex decision-making process that often requires experts’ opinions and judicious decisions. The purpose of this paper is to propose a framework to detect, isolate and to suggest appropriate maintenance tasks for large-scale complex machinery (i.e. gearboxes of steel processing plant) in a simplified and structured manner by utilizing the prior fault histories available with the organization in conjunction with case-based reasoning (CBR) approach. It is also demonstrated that the proposed framework can easily be implemented by using today’s graphical user interface enabled tools such as Microsoft Visual Basic and similar. Design/methodology/approach CBR, an amalgamated domain of artificial intelligence and human cognitive process, has been applied to carry out the task of fault detection and isolation (FDI). Findings The equipment failure history and actions taken along with the pertinent health indicators are sufficient to detect and isolate the existing fault(s) and to suggest proper maintenance actions to minimize associated losses. The complex decision-making process of maintaining such equipment can exploit the principle of CBR and overcome the limitations of the techniques such as artificial neural networks and expert systems. The proposed CBR-based framework is able to provide inference with minimum or even with some missing information to take appropriate actions. This proposed framework would alleviate from the frequent requirement of expert’s interventions and in-depth knowledge of various analysis techniques expected to be known to process engineers. Originality/value The CBR approach has demonstrated its usefulness in many areas of practical applications. The authors perceive its application potentiality to FDI with suggested maintenance actions to alleviate an end-user from the frequent requirement of an expert for diagnosis or inference. The proposed framework can serve as a useful tool/aid to the process engineers to detect and isolate the fault of large-scale complex machinery with suggested actions in a simplified way.

Optimizing assembly sequence planning using precedence graph-based assembly subsets prediction method

2019 ◽  
Vol 40 (2) ◽  
pp. 361-375 ◽  
Author(s):  
Nan Zhang ◽  
Zhenyu Liu ◽  
Chan Qiu ◽  
Weifei Hu ◽  
Jianrong Tan
Keyword(s):  
High Efficiency ◽  
Prediction Method ◽  
Solution Space ◽  
Assembly Sequence Planning ◽  
Selection Strategy ◽  
Assembly Process ◽  
Assembly Sequence ◽  
Content Type ◽  
Sequence Planning ◽  
Precedence Graph

Purpose Assembly sequence planning (ASP) plays a vital role in assembly process because it directly influences the feasibility, cost and time of the assembly process. The purpose of this study is to solve ASP problem more efficiently than current algorithms. Design/methodology/approach A novel assembly subsets prediction method based on precedence graph is proposed to solve the ASP problem. The proposed method adopts the idea of local to whole and integrates a simplified firework algorithm. First, assembly subsets are generated as initial fireworks. Then, each firework explodes to several sparks with higher-level assembly subsets and new fireworks are selected for next generation according to selection strategy. Finally, iterating the algorithm until complete and feasible solutions are generated. Findings The proposed method performs better in comparison with state-of-the-art algorithms because of the balance of exploration (fireworks) and exploitation (sparks). The size of initial fireworks population determines the diversity of the solution, so assembly subsets prediction method based on precedence graph (ASPM-PG) can explore the solution space. The size of sparks controls the exploitation ability of ASPM-PG; with more sparks, the direction of a specific firework can be adequately exploited. Practical implications The proposed method is with simple structure and high efficiency. It is anticipated that using the proposed method can effectively improve the efficiency of ASP and reduce computing cost for industrial applications. Originality/value The proposed method finds the optimal sequence in the construction process of assembly sequence rather than adjusting order of a complete assembly sequence in traditional methods. Moreover, a simplified firework algorithm with new operators is introduced. Two basic size parameters are also analyzed to explain the proposed method.

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