Search results

Maintenance is a compulsory cost in any asset's operation and requires sufficient budget to be supported. However, insufficient maintenance allocation would lead to maintenance prioritization being practiced as a solution to relief the maintenance demands. The purpose of this paper is to review and discuss the related literature on the factors considered and methods practiced in maintenance prioritization, especially in asset managements.

A thorough literature search related to factors and methods used in maintenance prioritization was conducted through several journal databases. The keywords maintenance priority, maintenance prioritization, priority management and maintenance planning were used. Publications related to maintenance priority from the period of 1990 to 2016 were reviewed and filtered out. Literature focusing on methods and factors related to maintenance prioritization were analyzed and discussed.

This study presented the trend and publications related to maintenance priority throughout 1990 to 2016. Publications related with methods and factors were analyzed. The most used priority-setting methods include analytical hierarchy process; priority criterion; priority matrix; and failure mode and effect analysis. Factors for maintenance priority were categorized into four categories which are technical, financial, social and political category. A discussion on the strategic direction of maintenance prioritization was conducted to highlight future research and possible improvements.

The paper contains a state of the art on publications and discussion related to the factors, methods and suggestions on the strategic aspect of maintenance prioritization. It offers insights and information on the current body of knowledge to academics, researchers, maintenance managers, practitioners and stakeholders concerned with asset management.

There is an increasing demand for research in maintenance prioritization methods, as budgets for maintenance of public buildings are unlikely to meet the maintenance needs. It is possible for government maintenance authorities to improve this situation by ensuring that the best solution is achieved in the maintenance programme through appropriate priority setting methods. A maintenance plan that is based on a rational assessment of priorities and up‐to‐date knowledge of the condition of the property stock will help to ensure the best use of available resources. Critically reviews various methods of maintenance priority setting for public buildings in the UK and Hong Kong. It also provides recommendations for maintenance managers in selecting and using the most appropriate method for their own organizations.

The purpose of this paper is to propose a maintenance programme for flat roofs in existing buildings, based on the inspection of 26 buildings in-service conditions, located in the Lisbon region, in Portugal. A proactive maintenance of flat roofs in existing buildings allows reducing their pathology, thus improving their performance and service life.

The maintenance plan was established based on the degradation state of the maintenance source elements (MSEs) analysed, the aggressiveness of the surrounding environment and the age of the roofs and maintenance actions carried out during the roofing systems’ life cycle.

The maintenance plan proposed in this study includes the prioritization of the interventions, the definition of the required maintenance operations and the definition of the frequency of the intervention, considering the service lives of the MSEs.

The study addresses only roofs located in the Lisbon area. Even though a relatively large sample of 26 roofs was used, the findings and conclusions can clearly be extrapolated for a much wider scope.

The maintenance plan proposed in this study considers a planning of proactive maintenance operations to continuously and effectively monitor all the relevant MSE.

This plan allows minimizing the incidence and spread of defects, thus enabling the optimization of resources, reducing the costs of the entire maintenance system and improving the quality of the built environment.

Knowing which services are essential to tenants gives the housing associations the background to set priorities in maintenance policy and purchasing. The purpose of this paper is to explore residents' perceived importance of various maintenance services.

The research question is explored through a large‐scale survey of more than 6,000 tenants of Dutch housing associations. Priorities were studied in three different ways: respondents were asked to provide direct importance ratings, importance weights were derived from regression analyses, and, an importance‐performance analysis (IPA) was performed.

The results with regard to the priorities differ somewhat according to which method is used. However, the methods agree in that maintenance of heating and water systems and maintenance of hinges and locks of windows and external doors should get priority. If the goal is to increase customer satisfaction, the maintenance of exterior paintwork and bathrooms should also get appropriate attention. According to the IPA, the maintenance of ventilation systems should be taken good care of.

One limitation of the study is that residents have provided their preferences in maintenance service delivery without noticing the costs that are included with the several options. Furthermore, the priorities between service aspects, i.e. the aspects that determine the service quality of the maintenance service delivery were not measured.

This paper provides insight into resident's priorities with regard to maintenance services. This can be of use for companies, such as housing associations. Furthermore, it contributes to scientific knowledge with regard to the impact of different measurement methods.

Different applied methods for measuring priorities lead to different results. Both practitioners and researchers should take this into account when measuring priorities. The goal of the research should determine the choice of which method to use.

This paper aims to develop predictive methods, based on recurrent neural networks, useful to support facility managers in building maintenance tasks, by collecting information coming from a computerized maintenance management system (CMMS).

This study applies data-driven and text-mining approaches to a CMMS data set comprising more than 14,500 end-users’ requests for corrective maintenance actions, collected over 14 months. Unidirectional long short-term memory (LSTM) and bidirectional LSTM (Bi-LSTM) recurrent neural networks are trained to predict the priority of each maintenance request and the related technical staff assignment. The data set is also used to depict an overview of corrective maintenance needs and related performances and to verify the most relevant elements in the building and how the current facility management (FM) relates to the requests.

The study shows that LSTM and Bi-LSTM recurrent neural networks can properly recognize the words contained in the requests, thus correctly and automatically assigning the priority and predicting the technical staff to assign for each end-user’s maintenance request. The obtained global accuracy is very high, reaching 93.3% for priority identification and 96.7% for technical staff assignment. Results also show the main critical building elements for maintenance requests and the related intervention timings.

This work shows that LSTM and Bi-LSTM recurrent neural networks can automate the assignment process of end-users’ maintenance requests if trained with historical CMMS data. Results are promising; however, the trained LSTM and Bi-LSTM RNN can be applied only to different hospitals adopting similar categorization.

The data-driven and text-mining approaches can be integrated into the CMMS to support corrective maintenance management by facilities management contractors, i.e. to properly and timely identify the actions to be carried out and the technical staff to assign.

The improvement of the maintenance of the health-care system is a key component of improving health service delivery. This work shows how to reduce health-care service interruptions due to maintenance needs through machine learning methods.

This study develops original methods and tools easily integrable into IT workflow systems (i.e. CMMS) in the FM field.

The purpose of this paper is to identify the productivity improvement potentials from maintenance planning practices in manufacturing companies. In particular, the paper aims at understanding the connection between machine criticality assessment and maintenance prioritization in industrial practice, as well as providing the improvement potentials.

An explanatory mixed method research design was used in this study. Data from literature analysis, a web-based questionnaire survey, and semi-structured interviews were gathered and triangulated. Additionally, simulation experimentation was used to evaluate the productivity potential.

The connection between machine criticality and maintenance prioritization is assessed in an industrial set-up. The empirical findings show that maintenance prioritization is not based on machine criticality, as criticality assessment is non-factual, static, and lacks system view. It is with respect to these finding that the ways to increase system productivity and future directions are charted.

In addition to the empirical results showing productivity improvement potentials, the paper emphasizes on the need for a systems view for solving maintenance problems, i.e. solving maintenance problems for the whole factory. This contribution is equally important for both industry and academics, as the maintenance organization needs to solve this problem with the help of the right decision support.

The purpose of this paper is to illustrate the maintenance prioritising for facilities services in high-rise residential buildings in Peninsular Malaysia. Maintenance prioritisation is becoming more prominent in the building maintenance industry due to budget constraints, poor maintenance management and to yield better maintenance performance.

Two main categories with eleven facilities services that require maintenance were identified through extensive literature review. A total of 321 returned questionnaires were analysed to distinguish the relationship between the maintenance priority and cost variance. Semi-structured interviews were then conducted to validate the findings.

The findings revealed that five essential facilities services were significantly correlated to cost variance and a regression model which examines the probability of over-budget was developed. Meanwhile, the interviews recognised that maintenance prioritisation has impact towards maintenance cost.

This research focusses on the maintenance priorities of facilities services and their effects to maintenance cost. However, it is undeniable that the maintenance cost can be affected by other factors, contributing to a lower percentage of the total variance in the regression model. Thus, it creates research opportunity to study the factors (i.e. manpower, materials, wear and tear, etc.) affecting the variance of maintenance cost.

This study is useful to property managers in efforts to enhance the cost performance via appropriate maintenance prioritisation. The essential facilities services should be highly prioritised compared to the value-added facilities services.

The paper signifies the importance of maintenance prioritisation. It serves as a guide to plan and execute maintenance planning in a more logical way within budget and time constraints.

This paper presents a comparative study of three well‐established building maintenance forecasting models in conjunction with a quantitative model which has been developed recently. After a brief introduction of each method, data collected from a large building survey were mapped into four distinctive methods and comparison was carried out in terms of priorities that these four methods adopt for future maintenance work. An analysis of responses to a questionnaire including 100 companies and individuals involved in maintenance and facilities management work (including quantity surveyors’ organisations) revealed that 100 percent of the public sector organisations use maintenance assessment methods for their prioritisation of maintenance management work. It also revealed that 92 percent of the private sector and 95 percent of all the organisations use condition based maintenance assessment methods for the prioritisation of maintenance operations. Results of this questionnaire have been used as introductory material to support the necessity for this piece of research.

The purpose of this paper is to deal with the performance modeling and assessment of maintenance priorities for steam generation unit of a sugar plant.

The unit comprises of four subsystems, i.e., Bagasse elevator, Bagasse carrier, boiler and feed pump. The Chapman–Kolmogorov equations are generated on the basis of transition diagram and further solved recursively to obtain the performance modeling with the help of normalizing condition using the Markov approach.

Decision matrices are formed with the help of different combinations of failure and repair rates of all subsystems. The performance of steam generation unit is evaluated in terms of availability levels depicted in decision matrices and plots of failure rates and repair rates of various subsystems. The maintenance priorities of various subsystems of steam generation unit are decided on the basis of effect of failure and repair rates of subsystems on the availability of steam generation unit. The key finding is that the boiler subsystem is the most critical subsystem and hence should be kept on top maintenance priority for performance enhancement of the steam generation unit.

The acceptance of both performance modeling and maintenance priorities decision by the management of sugar plant will result in the enhancement of unit availability and reduction of maintenance cost.

A large number of roads have been constructed in the rural areas of India to connect habitations with the nearest major roads. With time, the pavements of these roads have deteriorated and they need some kind of maintenance, although they all do not need maintenance at the same time, as they have all not deteriorated to the same level. Hence, they have to be prioritized for maintenance.

In order to present a scientific methodology for prioritizing pavement maintenance, the factors affecting prioritization and the relative importance of each were identified through an expert survey. Analytic Hierarchy Process (AHP) was used to scientifically establish weight (importance) of each factor based on its relative importance over other factors. The proposed methodology was validated through a case study of 203 low volume rural roads in the state of Himachal Pradesh in India. Ranking of these roads in order of their priority for maintenance was presented as the final result.

The results show that pavement distresses, traffic volume, type of connectivity and the socioeconomic facilities located along a road are the four major factors to be considered in determining the priority of a road for maintenance.

The methodology provides a comprehensive, scientific and socially responsible pavement maintenance prioritization method which will automatically select roads for maintenance without any bias.

Timely maintenance of roads will also save budgetary expenditure of restoration/reconstruction, leading to enhancement of road service life. The government will not only save money but also provide timely benefit to the needy population.

Road transportation is the primary mode of inland transportation in rural areas. Timely maintenance of the pavements will be of great help to the socioeconomic development of rural areas.

The proposed methodology lays special emphasis on rural roads which are small in length, but large in number. Instead of random, a scientific method for selection of roads for maintenance will be of great help to the public works department for better management of rural road network.