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A simulation modelling, using a simulation language SIMPLE++, was used to study the personnel capacity utilisation in a maintenance department. Input data included work orders with different throughput times, different personnel profile based on work order requirements, and different prioritisation rules. A decentralised maintenance department was assumed, whereby each department had its own maintenance unit. The effects of personnel organisational policies on the capacity utilisation of the personnel and on the throughput time of maintenance work orders were studied. The results of the simulation show that the best utilisation of the personnel and the best throughput time of maintenance work orders is obtained if the maintenance personnel are allowed to function across the borders of their department (here termed as exchangeability of personnel). Likewise, if there were universal maintenance personnel (i.e. who could take both electrical and mechanical work orders), then there would have been an optimum staffing of the maintenance department.

The aim of this paper was to study current practices in FM work order processing to support and improve decision-making. Processing and prioritizing work orders constitute a critical part of facilities and maintenance management practices given the large amount of work orders submitted daily. User-driven approaches (UDAs) are currently more prevalent for processing and prioritizing work orders but have challenges including inconsistency and subjectivity. Data-driven approaches can provide an advantage over user-driven ones in work-order processing; however, specific data requirements need to be identified to collect and process the functional data needed while achieving more consistent and accurate results.

This paper presents the findings of an online survey conducted with facility management (FM) experts who are directly or indirectly involved in processing work orders in building maintenance.

The findings reflect the current practices of 71 survey participants on data requirements, criteria selection, rankings, with current shortcomings and challenges in prioritizing work orders. In addition, differences between criteria and their ranking within participants’ experience, facility types and facility sizes are investigated. The findings of the study provide a snapshot of the current practices in FM work order processing, which aids in developing a comprehensive framework to support data-driven decision-making and address the challenges with UDAs.

Although previous studies have explored the use of selected criteria for processing and prioritizing work orders, this paper investigated a comprehensive list of criteria used by various facilities for processing work orders. Furthermore, previous studies are focused on the processing and prioritization stage, whereas this paper explored the data collected following the completion of the maintenance tasks and the benefits it can provide for processing future work orders. In addition, previous studies have focused on one specific stage of work order processing, whereas this paper investigated the common data between different stages of work order processing for enhanced FM.

Current industry practices illustrate there is no standard method to estimate the number of hours worked on maintenance activities; instead, industry experts use experience to guess maintenance work hours. There is also a gap in the research literature on maintenance work hour estimation. This paper investigates the use of machine-learning algorithms to predict maintenance work hours and proposes a method that utilizes historical preventive maintenance order data to predict maintenance work hours.

The paper uses the design research methodology utilizing a case study to validate the proposed method.

The case study analysis confirms that the proposed method is applicable and has the potential to significantly improve work hour prediction accuracy, especially for medium- and long-term work orders. Moreover, the study finds that this method is more accurate and more efficient than conducting estimations based on experience.

The study has major implications for industrial applications. Maintenance-intensive industries such as oil and gas and chemical industries spend a huge portion of their operational expenditures (OPEX) on maintenance. This research will enable them to accurately predict work hour requirements that will help them to avoid unwanted downtime and costs and improve production planning and scheduling.

The proposed method provides new insights into maintenance theory and possesses a huge potential to improve the current maintenance planning practices in the industry.

The purpose of this paper is to describe the most important areas of maintenance management system for heavy industries for helping maintenance mangers to focus on measuring the effectiveness of maintenance system. This work aimed at inferring relationships between maintenance management, maintenance practices and maintenance improvement.

In relation to maintenance management, as a case study approach, it can be applied to continuous improvement maintenance systems through 15 maintenance process areas.

The general picture evidences some criticalities, such as those areas which help in the success of maintenance management and areas which lead to the failure of maintenance management. It was found that by using the maintenance management system in the cement industry, it was possible to measure and improve about 15 percent maintenance performance which can be achieved by enhancing maintenance in the suggested areas.

Continuous maintenance improvement (CMI) is an ongoing effort to improve maintenance aimed at maintenance process simplification and reduction or elimination of maintenance process waste. To support CMI, maintenance engineers continually examine maintenance processes to discover and eliminate problems.

Other researchers have reported on the maintenance management system, but most of them have focussed on limited areas. The lack of useful and practical research has been determined. It seems that the scientific knowledge of maintenance management still needs more effort. This study is one of the first in-depth studies into actual condition-based maintenance practice to test 15 maintenance process areas.

The police service in England and Wales is increasingly focusing upon crime detection with the result that the patrol function, including the vital aspect of order maintenance, is being neglected. This article explores the role of police community safety officers (PCSOs) and argues that it is necessary to equip them with sufficient legal powers to perform this task.

The purpose of this paper is to present the use of activity-based costing (ABC) approach as an alternative option to the traditional cost accounting system. The contribution of this study is to demonstrate, through a simple example, the application of that costing system in a service (maintenance) industry, i.e. the paper intended to develop a procedure for a cost model that help in calculating any maintenance job cost, to a reasonable degree of accuracy, based on the actual activities performed.

This research uses a simple example whereby hypothetical activities and cost data of maintaining an injector and a pump, of an internal combustion engine, are used, presented and analyzed based on the use of the developed procedure.

ABC system provides more accurate cost estimates rather than the traditional “order costing” methods that uses unit-level costs which are variable in relation to change in service volume. Traditional cost methods distort the costs by applying overhead uniformly over different jobs of varied complexities and activities scope. On the other hand, ABC is a useful means to distribute the overhead costs in proportion (fairly) to the actual activities performed in a specific job and, hence, enhance the rationality of decision making, i.e. will not distort the accounting information used for cost reduction, pricing, and evaluation matters. The results obtained from the analysis showed that allocating costs to the maintained injector decreased from $83.55 to $71.95 and, finally, to $67.57 when using the workshop-wide, two-stage and ABC overhead allocation methods, respectively; while that of the pump increased from $298.90 to $340.34 and, finally, to $359.48 when using the same three methods, in the same order, respectively. The result is quite fair when considering the complexity of the fuel pump, in terms of design and maintenance, when compared with the injector. Notice that using volume to allocate overhead costs results in over costing high-volume products, e.g. injectors (simple in terms of design and operation) and under costing low-volume products, e.g. pumps (more complex in terms of design and operation). The paper recommends to use ABC as a more accurate and fair method when charging maintenance job orders based on the analysis of costing two maintained items in the same premise while consuming different overhead resources.

This study attempts to analyze different methods to calculate a specific corrective maintenance job order. It strives to remedy the drawbacks of the traditional overhead costing of a job order when using principles related to the size of service, such as the direct labor cost/hours, as an allocation base. Consequently, the study proposed a new costing method, i.e. application of ABC. The traditional costing approach is considered by many firms as the best costing method. Nevertheless, it allocates overhead cost over job performed uniformly (equally) not differentiating between the complexity of the job and variety of the activities performed, e.g. using the same allocation base for “oil change” and “fuel pump adjustment” activities. So, ABC prevents cost distortions (unfairness) that could not be prevented by traditional cost accounting system. The author believes that the method presented in this paper will provide a useful management tool for costing maintenance jobs based on the appropriate selected activity drivers in maintenance workshops. The method could be applied for costing maintenance activities in maintenance of all industrial sectors.

The use of traditional costing method has proven to be distorted by applying overhead uniformly over different jobs of varied complexities and activities scope. In this paper the authors strive to present an effective costing alternative that outperforms the traditional ones with regard to overhead allocation. The paper aims to find reliable and fair maintenance costing method, i.e. to find out the relationships between maintenance activities and cost drivers. Although, ABC is widely used in manufacturing industry, no application or current research has presented an applicable thorough worked-out example, with the exception, to the author’s knowledge, of one in the aeronautical industry, to implement ABC method in maintenance industry. The importance of using this method comes from the fact that it provides, relatively, accurate and fair maintenance bills that provide customer satisfaction and firm good image. Hence, the paper is relevant in this respect and intended to contribute to the practice of maintenance management.

Maintenance management consists of an aggregate effort to perform maintenance by effectively utilizing manpower and material through the application of standard procedures. It is a complex and multifaceted task. An ever‐growing number of computerized maintenance management information systems are available on the market to facilitate this task. In order to install a computerized maintenance management system, a company has two options: either to buy or to develop such a system. Briefly describes the major functions of maintenance management and suggests an instrument to evaluate comparatively the available computerized maintenance management systems.

The purpose of this paper is to explore the value of K-12 indirect facility maintenance and operation expense spending in Arizona and how the prioritization of work enables academic performance.

Data were collected from more than 200 academic districts over a five-year period to measure the correlation between plant maintenance and operations and academic outcomes. A qualitative analysis provided an in-depth understanding of how routine work is prioritized.

Results of the correlative model indicate that no positive relationship exists between academic performance and facility expense spending within the sample population. The lack of a positive correlation may be a result, in whole or in part, of many variables. The qualitative analysis, however, provided a more in-depth understanding of how academic districts manage educational facilities and how the prioritization of work may factor into a correlation.

This paper addresses the link between academic performance, expressed in terms of a return-on-assets, and facility management. The contribution of this paper is the documentation of facility maintenance and operations organizational structures to include the method of prioritizing routine work and the process of indirect expense spending in support of K-12 public education in the state of Arizona.

Literature shows that the economics of early failures in maintenance and electric utilities have not been deeply analyzed. This study aims to focus on quantifying the economic impact that early failures in current transformers have on total maintenance costs. The empirical study is conducted in a regional transmission division of an electric utility located in Mexico.

The utility's database was accessed to collect 219 maintenance records. Clustering techniques were used to identify early failures from a bimodal distribution of failures. Confirmatory goodness-of-fit procedures followed the analysis, and finally, direct and opportunity costs were estimated by adapting the cost-of-quality (PAF) Model.

Around 11% of all maintenance activities are triggered by early failures, and they account for up to US$2.2m during the eight-year period under study, which represents 16% of total maintenance costs. Additionally, opportunity costs represent close to two-thirds of the total costs due to early failures. This was obtained after finding and validating a clear-cut border of 3.5 months between early failures and the rest.

Failures in energy grids and power transmission can have a large economic impact on the power industry and the society in general. Thus, the maintenance function in equipment such as current transformers is a crucial entry of the budget of any electric utility. This study is one of the very few that highlights the magnitude and importance of direct and opportunity costs derived from early failures.

Productivity, based on estimated and actual hours, of most maintenance workers is only 30 to 50 per cent. Given the significance of maintenance to manufacturing competitiveness, it is surprising how little research is being carried out. Scheduling is a crucial component of maintenance management and is a focus of research. Identifies the areas of concern in maintenance scheduling and surveys representative work from the academic and practitioner literature. Specific points of practice and theory which need further investigation are pinpointed.