Automatically generating assembly sequences with an ontology-based approach

Zhong, Yanru; Jiang, Chaohao; Qin, Yuchu; Yang, Gangyi; Huang, Meifa; Luo, Xiangfeng

doi:10.1108/aa-12-2018-0271

Cited by 15 publications

(4 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Taking information from the publications of Qian et al, [12] and Zhong et al [32], it can be concluded that mathematical models and algorithms linked to optimization processes ignore or omit the experience and knowledge of those involved who plan assembly sequences. Furthermore, Li and Hou [11] and Shyamsundar and Gadh [15] indicate that existing ASP approaches focus on precedence relationships and do not consider the utilization of available resources, and the lack of an integrated tool for the collaborative design of assemblies makes them disorganized and inefficient.…”

Section: Collaborative Planning Methodology Proposalmentioning

confidence: 99%

Collaborative Assembly Sequence Planning (CASP) based on data analysis for On-site Installation Products

Vélez,

Uribe,

Aristizabal

et al. 2023

Preprint

View full text Add to dashboard Cite

For the manufacture of significantly repetitive products that require assembly, different strategies have been proposed to improve times, the use of resources, and the reduction of associated costs. For this purpose, there are many documented methodologies that point to method and time studies, reduction of the number of components or the complexity of the assembly as the \acrfull{DFA}, sequence analysis with \acrfull{ASP}, Bourjault, and/or graphs, among others.In the case of products that require to be assembled at the site where they will operate, manufacturing in a fixed position, and of which several assemblies will be performed in different places, the execution of these has been done, almost always, in an intuitive way, that is, solving on the fly, starting from common sense and accumulating parts. The existing literature has limited information on the methods developed for assembly with these characteristics.This study presents a new methodology of sequence generation called \acrfull{CASP} for the on-site installation of a product in which, the criteria and knowledge of a group of engineers are considered, helping to identify the assembly operations, the sequences, the arrangement and allocation of resources and tasks for the development of the assembly.Additionally, this methodology is verified in a case study applied to a photovoltaic charging station, for which a feasible, effective, detailed, and structured assembly sequence was collaboratively generated for the assembly of such a product. The results show the applicability of the \Gls{CASP} methodology and suggest that it could be applied in other complex product assembly contexts requiring on-site assembly.

show abstract

Section: Collaborative Planning Methodology Proposalmentioning

confidence: 99%

Collaborative Assembly Sequence Planning (CASP) based on data analysis for On-site Installation Products

Vélez,

Uribe,

Aristizabal

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…(Zhou et al 2019) reviewed the existing main disassembly based sequence planning methods in terms of disassembly methods, disassembly modeling and planning methods. (Zhong et al 2018) abstracted the knowledge and empirical semantics required for assembly sequence planning into an ontology model. The ontology reasoning is implemented to judge the rationality of assembly sequences.…”

Section: Planning and Evaluation Methods Of Assembly Processmentioning

confidence: 99%

KGAssembly: Knowledge graph-driven assembly process generation and evaluation for complex components

Zhou

Bao

Chen

et al. 2021

International Journal of Computer Integrated Manufacturing

View full text Add to dashboard Cite

The semantic information of process documents for the assembly of complex components plays an important role in the guidance of assembly operations and the feasibility evaluation of process plans. There are many types of semantic elements contained in assembly process documents. The semantic relationship between assembly elements is complex. Additionally, there is a lack of effective modeling method to deal with the implicit associative semantic knowledge that exists among existing assembly process cases. In this case, it is a great challenge to use the professional knowledge in assembly process documents to guide the intelligent decision-making of assembly process planning and the intelligent analysis of assembly process enforceability evaluation. In this paper, a knowledge graph-driven assembly process generation and evaluation method for complex components is proposed. An APKG (assembly process knowledge graph) model is built. A distributed graph embedding-based model SKGCN (sequence knowledge graph convolutional network) is designed to generate assembly process planning. Furthermore, model and knowledge dual-driven evaluation method for assembly sequences is presented. It provides assembly expert knowledge support for the evaluation method of interference detection of assembly sequence based on point cloud assembly feature recognition. Finally, the approach is evaluated by assembling an aeroengine compressor rotor.

show abstract

“…Discovering and obtaining valuable process knowledge from existing process data, obtaining typical process routes [92] Design process ontology knowledge database: Wu et al [65] devised an ontological database for assembly process knowledge, enabling both standardization and systematization. Zhong et al [66] offered an ontologically based assembly sequence algorithm with integrated inference rules to streamline knowledge application. Šormaz et al [67] introduced the semantic integrated manufacturing planning model (SIMPM) ontology to articulate manufacturing constraints, utilizing axioms for problem-solving in process design.…”

Section: Build Different Granularity Informationmentioning

confidence: 99%

A Review and Prospects of Manufacturing Process Knowledge Acquisition, Representation, and Application

Wu,

Liang

2024

Machines

View full text Add to dashboard Cite

The evolution of knowledge acquisition and representation in manufacturing technologies is vital for translating complex manufacturing data into actionable insights and advancing a comprehensive knowledge framework. This framework is pivotal in driving innovation and efficiency in intelligent manufacturing. This review aggregates recent research on knowledge acquisition and representation within the manufacturing process, addressing existing challenges and mapping potential future developments. It includes an analysis of 123 papers that focus on harnessing advanced intelligent analytics to extract operationally relevant knowledge from the extensive datasets typical in manufacturing environments. The narrative then examines the methodologies for constructing models of knowledge in manufacturing processes and explores their applications in manufacturing principles, design, management, and decision-making. This paper highlights the limitations of current technologies and projects emerging research avenues in the acquisition and representation of process knowledge within intelligent manufacturing systems, with the objective of informing future technological breakthroughs.

show abstract

Automatically generating assembly sequences with an ontology-based approach

Cited by 15 publications

References 33 publications

Collaborative Assembly Sequence Planning (CASP) based on data analysis for On-site Installation Products

Collaborative Assembly Sequence Planning (CASP) based on data analysis for On-site Installation Products

KGAssembly: Knowledge graph-driven assembly process generation and evaluation for complex components

A Review and Prospects of Manufacturing Process Knowledge Acquisition, Representation, and Application

Contact Info

Product

Resources

About