Melinda Hodkiewicz and Mark Tien-Wei Ho
The purpose of this paper is to identify quality issues with using historical work order (WO) data from computerised maintenance management systems for reliability analysis; and…
Abstract
Purpose
The purpose of this paper is to identify quality issues with using historical work order (WO) data from computerised maintenance management systems for reliability analysis; and develop an efficient and transparent process to correct these data quality issues to ensure data is fit for purpose in a timely manner.
Design/methodology/approach
This paper develops a rule-based approach to data cleansing and demonstrates the process on data for heavy mobile equipment from a number of organisations.
Findings
Although historical WO records frequently contain missing or incorrect functional location, failure mode, maintenance action and WO status fields the authors demonstrate it is possible to make these records fit for purpose by using data in the freeform text fields; an understanding of the maintenance tactics and practices at the operation; and knowledge of where the asset is in its life cycle. The authors demonstrate that it is possible to have a repeatable and transparent process to deal with the data cleaning activities.
Originality/value
How engineers deal with raw maintenance data and the decisions they make in order to produce a data set for reliability analysis is seldom discussed in detail. Assumptions and actions are often left undocumented. This paper describes typical data cleaning decisions we all have to make as a routine part of the analysis and presents a process to support the data cleaning decisions in a repeatable and transparent fashion.