Goal hierarchy: Improving asset data quality by improving motivation

Unsworth, Kerrie; Adriasola, Elisa; Johnston-Billings, Amber; Dmitrieva, Alina; Hodkiewicz, Melinda

doi:10.1016/j.ress.2011.06.003

Cited by 35 publications

(36 citation statements)

References 32 publications

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“…One of the challenges with data quality is the number of different groups involved such as data collectors, those responsible for design and storage and data users. All groups involved in the data process need to play a part to ensure data's fitness for purpose (Murphy, 2009;Unsworth et al, 2011;Molina et al, 2013).…”

Section: Literature Reviewmentioning

confidence: 99%

Cleaning historical maintenance work order data for reliability analysis

Hodkiewicz

Ho²

2016

Journal of Quality in Maintenance Engineering

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -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.

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Section: Literature Reviewmentioning

confidence: 99%

Cleaning historical maintenance work order data for reliability analysis

Hodkiewicz

Ho²

2016

Journal of Quality in Maintenance Engineering

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“…Also the justification of budget plans as related to infrastructure conditions has been a recurring example in the sample. Articles, which cite from the Water and Utility Infrastructure Path, emphasise that agencies have an urgent need to justify higher budgets (Wood & Lence, 2006) given the poor water infrastructure conditions and potential severe effect on the community (Ana & Bauwens, 2010) in a period of shrinking public finances and incompetence to collect data for proper justification (Molina, Unsworth, Hodkiewicz, & Adriasola, 2013;Unsworth, Adriasola, Johnston-Billings, Dmitrieva, & Hodkiewicz,, 2011). Similarly, articles which cite the Life Cycle Decision Making and Organization Path propose to justify budgets when dealing with investment needs with an accounting system (Kobayashi, Ejiri, & Do, 2008), a model to estimate the intervention threshold for a given budget and plan (Khurshid, Irfan, & Labi, 2010;Younis & Knight, 2010) or the identification of immediate risks (Salman & Salem, 2012).…”

Section: Research Orientations Among Retrieved Articlesmentioning

confidence: 99%

Research orientations towards the ‘management’ of infrastructure assets: an intellectual structure approach

Schraven

Hartmann

Dewulf

2013

Structure and Infrastructure Engineering

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In recent decades, research on the management of infrastructure assets has increased steadily. However, there are concerns raised about the contribution of studies to a coherent body of knowledge. There is a call for a more structured understanding of the knowledge that is emerging around the management of infrastructure assets. This paper attempts to answer this call through an empirical study based on the reference lists of over 8200 articles that present their study relevant to the management of infrastructure assets. In so doing, we apply recognised techniques from bibliometric and social network analyses to visualise and identify major and minor topics, where researchers have oriented and contributed. We find that managing infrastructure assets traditionally was object-oriented, such as pavements, bridges, water and utility networks, and that attention is only now emerging on the life-cycle decision-making and organisational aspects, although the latter remains weakly linked with technical aspects. We conclude with shared research orientations in 'managing' infrastructure assets.

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“…The challenge of dealing with data from different sites is compounded by the generally poor quality of reporting on failures generally found in computerised maintenance management systems and the considerable time required to clean the data [14,15]. While it remains a possibility that the large original equipment manufacturers, especially those engaged in maintenance and repair contracts, have the data to perform this analysis, any work that has been done is not in the public domain.…”

Section: Introductionmentioning

confidence: 99%

Factors That Influence Failure Behaviour and Remaining Useful Life of Mining Equipment Components

Hodkiewicz

2013

Advances in Mechanical Engineering

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Mobile mining equipment often operates in harsh environments characterised by remote locations and highly variable rock and operating conditions. This research explores the hypothesis that the failure behaviour of mining equipment is influenced by the physical properties of the ore and waste. We describe a method of examining this relationship via data mining on maintenance records and apply it to the hydraulic cylinders of two classes of earthmoving mobile equipment. Failure data for the analysis are drawn from maintenance work orders from 14 sites mining for haematite iron, nickel sulphide, and coking and thermal coal. The results show that the distributions of the estimated life parameters for hydraulic cylinders on earthmoving equipment are distinctly different for haematite iron, coal, and nickel sulphide sites. Analysis of the relationship between selected physical properties identified the influence of rock impact hardness number, abrasion index, and absolute hardness of the ore as significant factors for these hydraulic cylinders. Their effects are significant when parameters are considered in combination, for example, rock impact hardness number and abrasion index, and vary according to the cylinder type and asset class. The engineering implications of these results are considered with respect to known failure modes of the cylinders.

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Goal hierarchy: Improving asset data quality by improving motivation

Cited by 35 publications

References 32 publications

Cleaning historical maintenance work order data for reliability analysis

Cleaning historical maintenance work order data for reliability analysis

Research orientations towards the ‘management’ of infrastructure assets: an intellectual structure approach

Factors That Influence Failure Behaviour and Remaining Useful Life of Mining Equipment Components

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