Technical paper
A system for distributed sharing and reuse of design and manufacturing knowledge in the PFMEA domain using a description logics-based ontology

https://doi.org/10.1016/j.jmsy.2011.06.001Get rights and content

Abstract

Potential Failure Modes and Effects Analysis in Manufacturing and Assembly Processes (PFMEA) is an important preventive method for quality assurance, and through it the decisions based on the severity levels and probabilities of occurrences and detection of the failure modes can be planned and prioritized, seeking to improve the quality of the manufactured products. This activity generates a valuable source of knowledge about the manufacturing processes in the company. However, the sharing and reuse of this knowledge is a challenge, because usually the knowledge is not semantically organized, and therefore its meaning depends on the understanding of the specialists involved. Also, there is a high fragmentation and distribution of knowledge along the production chain. Considering this scenario, this paper presents the development of a system for distributed knowledge sharing and reuse in the PFMEA domain using an ontology based on description logics, which intends to allow knowledge inference and retrieval in manufacturing environments with distributed resources. The results show that the proposed approach is adequate to support knowledge sharing and reuse, allowing: (a) knowledge representation and organization; (b) distributed knowledge inference and retrieval; (c) management of organizational knowledge on manufacturing environments with distributed resources.

Highlights

► Process knowledge is fragmented along the production chain. ► We developed a prototype system for distributed sharing and reuse of this knowledge. ► We used PFMEA knowledge about a component that sustains the rollers in bearings. ► We applied ontology for knowledge representation, inference and retrieval. ► System performs detailed knowledge retrieval for establishing adequate actions.

Introduction

Nowadays, the social and economical environment is characterized by the appearance of new forms of industrial organizations, caused by complex factors such as market globalization, product life cycle reduction, high demand variability, need of high flexibility and responsiveness, and fast development of the technologies of information and communication [1]. In this perspective, new forms of organizational structures have been recognized by the scientific community and other professionals of this area, which include: extended enterprise, virtual enterprise, virtual organization, supply chain management and enterprise clusters [1], [2].

The key problem in these environments consists of integrating the distributed resources that contribute to production, since these new organizational structures are geographically distributed, composed by different commercial partners, each of them with its own specialization and resources directed to specific functions in the product life cycle [2], [3].

In this context, new challenges are also imposed on traditional models of management and quality improvement, which should be able to encompass not only internal processes of a single company [4], but also extend to cases involving external interconnected companies [3], [5], [6]. In these new environments, in particular, the solution of nonconformance problems is characterized by knowledge intensive activities heavily based on experience, which in complex cases can go beyond the knowledge and experience of members of a single company. Given this scenario, this paper proposes an architecture in which agents are used to share and retrieve knowledge resulting from the solution of previous nonconformance problems, together with the Potential Failure Mode and Effects Analysis in Manufacturing and Assembly Processes (PFMEA) method. PFMEA is a quality engineering method that is thoroughly used in improvement processes, which contributes to gathering information on manufacturing. Thus, PFMEA could be used to provide valuable knowledge that could be shared among the different links that compose the manufacturing chain.

The developed distributed system uses an ontology based on description logics (DL) for the knowledge representation in the PFMEA domain. This system seeks to provide means to share and reuse current knowledge in PFMEA tables in support to the management of the organizational knowledge regarding processes in manufacturing environments with distributed resources.

Section snippets

Some related work on knowledge representation and the PFMEA method

Potential Failure Mode and Effects Analysis in Manufacturing and Assembly Processes (PFMEA) is an important analytical method of quality engineering, whose purpose is, still in the initial design phases, to analyze all of the potential failure modes of a system, product or process, the potential cause of the failure associated with each one of those failure modes, as well as their effects. Consequently, with the results of this systematic analysis, the designers can review their designs in

Development of the PFMEA-DL ontology

Corcho et al. [20] present an extensive review on the main methodologies found in the literature about the construction of ontologies. In this work, the so-called methontology methodology proposed by López et al. [29] was adopted. In this methodology, the conceptualization activity organizes and converts a vision noticed informally from a domain in a semi-formal specification through a set of representations based on graphic or tabular notations that can be understood by the domain specialists.

Distributed approach and system organization

The proposed architecture, shown in Fig. 7, uses agents to perform distributed sharing and reuse of knowledge. It seeks to be compatible with the FIPA—Foundation for Intelligent Physical Agents specifications [36], which is currently responsible for disseminating the agent technology and the interoperability of its standards with other technologies. It comprises the following agent classes and their respective roles:

  • (1)

    Failure Mode Analysis Finder Agent (or Analysis Requester Agent): it is the

Conclusion

This paper described the development of a system for distributed knowledge sharing and reuse in the PFMEA domain using ontology-based knowledge retrieval approach. A prototype was implemented based on the Java Agent DEvelopment Framework (JADE). In the proposed architecture, the different knowledge bases can be distributed over the Intranet/Internet.

The proposed retrieval strategy allows the construction of a complex search pattern, enabling the combination of many concepts and roles of the

Acknowledgements

The second author would like to thank the National Council for Scientific and Technological Development (CNPq) of Brazil for the financial support to this project.

References (39)

  • O. Corcho et al.

    Methodologies, tools and languages for building ontologies

    Data and Knowledge Engineering

    (2003)
  • J. Cecil et al.

    A distributed internet-based framework for manufacturing planning

    International Journal Advanced Manufacturing Technology

    (2006)
  • K.-S. Chin et al.

    A computer-integrated framework for quality chain management

    International Journal of Advanced Manufacturing Technology

    (2006)
  • D.H. Stamatis

    Failure mode and effect analysis: FMEA from theory to execution

    (2003)
  • L. Dittmann et al.

    Performing FMEA using ontologies

  • K.-H. Chang et al.

    A risk assessment methodology using intuitionistic fuzzy set in FMEA

    International Journal of Systems Science

    (2010)
  • R.K. Sharma et al.

    System failure behavior and maintenance decision making using RCA, FMEA and FM

    Journal of Quality in Maintenance Engineering

    (2010)
  • S. Rebello et al.

    Software system reliability and safety assessment: an extended FMEA approach

    International Journal of Reliability and Safety

    (2010)
  • K. Case et al.

    A diagnostic service tool using FMEA

    International Journal of Computer Integrated Manufacturing

    (2010)
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