结构化过程挖掘在维护性能分析中的应用:以海上油气行业为例

J. Ge, Kristoffer Wernblad Sigsgaard, N. Mortensen, K. B. Hansen, J. K. Agergaard
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引用次数: 0

摘要

维护在与生产相关的行业中起着重要的作用。随着在过程级别更好地理解维护性能的需求不断增长,过程挖掘技术在维护性能度量中的应用正在出现。提出了一种结构化过程挖掘方法来分析维护过程的性能。这种方法通过使用上下文信息增强维护事件日志,从而能够识别潜在的根本原因。为了方便过程挖掘的范围,引入了多级过滤规则。利用海上油气行业的经验数据进行了案例研究。结果表明,可以通过比较基准流程与典型流程偏差(跳过、自循环和回循环)来识别维护流程瓶颈和一致性问题。过程偏差影响和因果关系的量化可以帮助维护经理发现性能问题的潜在根本原因,并采取措施进行持续改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structured Process Mining in Maintenance Performance Analysis: A Case Study in the Offshore Oil and Gas Industry
Maintenance plays an important role in production-related industries. As the need to better understand maintenance performance at the process level continues to grow, the application of process mining techniques to maintenance performance measurement is emerging. This paper presents a structured process mining approach for analyzing maintenance process performance. This approach enables the identification of potential root causes by enhancing maintenance event logs with contextual information. Multi-level filtering rules are introduced to facilitate the scoping of process mining. A case study was conducted using empirical data from the offshore oil and gas industry. The results show that maintenance process bottlenecks and conformance issues can be identified by comparing the benchmark process to typical process deviations (skipping, self-loop, and back loop). The quantification of process deviation impacts and cause–effect correlation can support maintenance managers in discovering potential root causes of performance issues and taking action for continuous improvement.
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