An ontology for maintenance activities and its application to data quality

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Semantic Web Pub Date : 2023-05-29 DOI:10.3233/sw-233299
Caitlin Woods, Matt Selway, Tyler Bikaun, Markus Stumptner, Melinda Hodkiewicz
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引用次数: 0

Abstract

Maintenance of assets is a multi-million dollar cost each year for asset intensive organisations in the defence, manufacturing, resource and infrastructure sectors. These costs are tracked though maintenance work order (MWO) records. MWO records contain structured data for dates, costs, and asset identification and unstructured text describing the work required, for example ‘replace leaking pump’. Our focus in this paper is on data quality for maintenance activity terms in MWO records (e.g. replace, repair, adjust and inspect). We present two contributions in this paper. First, we propose a reference ontology for maintenance activity terms. We use natural language processing to identify seven core maintenance activity terms and their synonyms from 800,000 MWOs. We provide elucidations for these seven terms. Second, we demonstrate use of the reference ontology in an application-level ontology using an industrial use case. The end-to-end NLP-ontology pipeline identifies data quality issues with 55% of the MWO records for a centrifugal pump over 8 years. For the 33% of records where a verb was not provided in the unstructured text, the ontology can infer a relevant activity class. The selection of the maintenance activity terms is informed by the ISO 14224 and ISO 15926-4 standards and conforms to ISO/IEC 21838-2 Basic Formal Ontology (BFO). The reference and application ontologies presented here provide an example for how industrial organisations can augment their maintenance work management processes with ontological workflows to improve data quality.
维护活动本体及其在数据质量中的应用
对于国防、制造业、资源和基础设施领域的资产密集型企业来说,每年的资产维护成本高达数百万美元。这些费用通过维护工作订单(MWO)记录进行跟踪。MWO记录包含日期、成本和资产标识的结构化数据,以及描述所需工作的非结构化文本,例如“更换泄漏泵”。本文的重点是MWO记录中维护活动术语(如更换、修理、调整和检查)的数据质量。我们在这篇论文中提出了两个贡献。首先,我们提出了维护活动术语的参考本体。我们使用自然语言处理从80万个mwo中识别出7个核心维护活动术语及其同义词。我们对这七个术语作了说明。其次,我们通过一个工业用例演示了在应用级本体中引用本体的使用。端到端nlp本体管道识别了离心泵8年来55%的MWO记录的数据质量问题。对于在非结构化文本中没有提供动词的33%的记录,本体可以推断出相关的活动类。维护活动术语的选择依据ISO 14224和ISO 15926-4标准,并符合ISO/IEC 21838-2基本形式本体(BFO)。本文介绍的参考本体论和应用程序本体论为工业组织如何使用本体论工作流增强其维护工作管理流程以提高数据质量提供了一个示例。
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来源期刊
Semantic Web
Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
8.30
自引率
6.70%
发文量
68
期刊介绍: The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.
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