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The purpose of this paper is to provide an overview of research and development in the measurement of maintenance performance. It considers the problems of various measuring parameters and comments on the lack of structure in and references for the measurement of maintenance performance. The main focus is to determine how value can be created for organizations by measuring maintenance performance, examining such maintenance strategies as condition‐based maintenance, reliability‐centred maintenance, e‐maintenance, etc. In other words, the objectives are to find frameworks or models that can be used to evaluate different maintenance strategies and determine the value of these frameworks for an organization.

A state‐of‐the‐art literature review has been carried out to answer the following two research questions. First, what approaches and techniques are used for maintenance performance measurement (MPM) and which MPM techniques are optimal for evaluating maintenance strategies? Second, in general, how can MPM create value for organizations and, more specifically, which system of measurement is best for which maintenance strategy?

The body of knowledge on maintenance performance is both quantitatively and qualitatively based. Quantitative approaches include economic and technical ratios, value‐based and balanced scorecards, system audits, composite formulations, and statistical and partial maintenance productivity indices. Qualitative approaches include human factors, amongst other aspects. Qualitatively based approaches are adopted because of the inherent limitations of effectively measuring a complex function such as maintenance through quantitative models. Maintenance decision makers often come to the best conclusion using heuristics, backed up by qualitative assessment, supported by quantitative measures. Both maintenance performance perspectives are included in this overview.

A comprehensive review of maintenance performance metrics is offered, aiming to give, in a condensed form, an extensive introduction to MPM and a presentation of the state of the art in this field.

The purpose of this paper is to develop a model that can measure the equipment maintenance performance of the energy company K-company.

The case study method was adopted for the investigation of maintenance performance indicators (MPIs). The development of a model for measuring maintenance performance suggested new ways to apply the methodologies of existing papers to evaluate the level of maintenance.

Maintenance indicators, which are managed differently for each plant, were assessed for their performance relevance, applicability and data reliability and then standardized into five key MPIs. The MPI model, which enables comprehensive and quantitative measurement of maintenance performance using the five selected MPIs, was presented, and the criteria for assessing the maintenance level were presented in five stages.

The authors selected MPIs that match the characteristics of the company and proposed a model that can comprehensively and quantitatively evaluate maintenance performance. The model also standardizes maintenance indicators that are individually managed and provides a basis for comparing and indexing the level of maintenance indicators at each plant.

The criterion for selecting the key MPIs considering the characteristics of the company and a model that can comprehensively and quantitatively evaluate maintenance performance were presented. In addition, a standard for evaluating the level of maintenance at the global level of maintenance management was suggested.

Multidisciplinary business process management (BPM) research can reap significant impact. We can particularly benefit from incorporating accounting concepts to address some of the key BPM challenges, such as value-creation and return on investment of BPM activities. However, research which addresses a relationship between BPM and accounting is scarce. The purpose of this paper is to provide a detailed synthesis of the current literature that has integrated accounting aspects with BPM. The authors profile and thematically describe existing research, and derive evidence-based directions to guide future research.

A multi-staged structured literature review approach to search for the two broad themes, accounting and BPM, supported by NVivo (to manage the papers and the coding and analysis processes) was designed and followed.

The paper confirms the dearth of work that ties the two disciplines, despite the synergetic multidisciplinary results that can be attained. Available literature is mostly from the management accounting perspective and relates to describing how performance management, in particular performance measurement, can be applicable to process improvement initiatives together with tools such as activity-based costing and the balanced scorecard. There is a lack of research that examines BPM in relation to any financial accounting perspectives (such as external reporting). Future research directions are proposed together with implications for practitioners with the findings of this structured literature review.

The paper provides a detailed synthesis of the existing literature on the nexus between accounting and BPM. It summarizes the implications for practitioners and provides directions for future research by identifying key gaps and opportunities with a sound contextual basis for extension and new work.

Effective literature reviews create strong foundations for future research and accumulate the otherwise scattered knowledge into a single place. This is the first structured literature review that provides a detailed synthesis of the research that ties together the accounting and BPM disciplines, providing a basis for future research directions together with implications for practitioners.

The purpose of this paper is to examine the application of C-shaped QFD 3D Matrix in comparing process characteristics (PC), performance aspects (PA) and customer requirements, simultaneously and to prioritize the first two sets, respectively.

A three dimensional matrix has been developed with three sets of PC, PA and customers’ requirements and C-shaped matrix has been applied for simultaneous comparison of the dimensions and prioritization of the subsets of PC and PA. The proposed approach has been examined in a post bank.

Findings confirm the possibility of simultaneous comparison and prioritization of the three sets of dimensions of this study in post bank services. In addition, “growth and learning” and “bilateral relationship with suppliers” had the first priorities among PA and PC, respectively.

While the proposed approach has many advantages, filling the matrixes is time-consuming. Since illustrating the 3D matrix was not possible, the matrix was separated into five two-dimensional matrixes.

Compared to the studied literature, the proposed approach is practically new in the post bank services.

This paper demonstrates a multi-criteria analytic hierarchy process (AHP) framework for evaluating and benchmarking maintenance performance in the select agro-based industry.

Initially, 20 maintenance practices (criteria) have been identified after a detailed literature review and discussion with the agro-based industry (sugar, textile and dairy industry) executives. These are then grouped into six maintenance management areas referred to as group criteria. The multi-criteria methodology consists of three steps: criteria identification, hierarchical modeling and data collection and maintenance performance evaluation, and benchmarking. The multi-criteria methodology proposed in this work facilitates two ways of carrying out benchmarking: (1) within the agro-based industry and (2) between the agro-based industry. The methodology has been explained by taking a case example of 45 agro-based industries (18 dairy, 13 sugar and 14 textile) from the western region of India. The sensitivity analysis of the model has been performed to ascertain the robustness of the results.

There is a difference in the maintenance performance across the agro-based industries due to different maintenance practices perceived differently.

The outcome of the model is mainly given by the judgments of the agro-based industry executives. It is also sensitive to any change in the relative importance to the evaluation criteria or the perception about the maintenance performance.

The study contributes in identifying the weakness, if any, by comparing the agro-based industry under investigation with the benchmark factory at three levels, namely, overall performance (factory level), group criteria (maintenance management area level) and criteria (maintenance practice level) allowing further improvement.

The methodology assists in better decision-making and in improving maintenance performance.

The purpose of this paper is to identify key variables that affect the quantifiable key performance indicators (KPIs) and to derive equations to measure these indicators. Qualitative KPIs are also discussed in terms of the aspects that need to be covered while carrying out qualitative performance assessment.

A combination of literature and an industry opinion-based qualitative approach is applied to develop equations to calculate the quantifiable KPIs. A facility asset management consulting firm is included in the process of deriving the equations. Key aspects of a facility's qualitative performance assessment are categorized and discussed by performing a literature review.

Mathematical expressions for core performance indicators are presented and discussed along with key variables. In addition, the information needed to quantify these core indicators is also discussed.

This paper represents the second step towards establishment of a relevant list of quantifiable and measurable core KPIs, which were identified and categorized in Part I of this paper. In Part II, the authors derive equations to quantify the core KPIs. Future research is needed to use relevant information from industry for validating these equations.

A need for a concise and relevant list of KPIs was identified in Part I of this paper. Part II provides an approach to quantify the core KPIs based on information that is available in the industry. This research will help facility management professionals in not only selecting the indicators of choice, but also quantifying them based on available information yielding enhanced facility management decisions with measurable facility performance outcomes.

This paper provides equations and variables to measure a facility's physical, functional and financial performance using both quantitative and qualitative performance assessments.

The aim of this research study is to develop a risk-based framework that can quantify maintainability to forecast future maintainability of a building at early stages as a decision tool to minimize increase of maintenance cost.

A survey-based approach was used to explore the risk factors in the domain of maintainability risks under tropical environmental conditions. The research derived ten risk factors based on 58 identified causes related to maintainability issues as common to high-rise buildings in tropical conditions. Impact of these risk factors was evaluated using an indicator referred to as the “maintenance score (MS)” which was derived from the “whole-life maintenance cost” involved in maintaining the expected “performance” level of the building. Further, an ensemble neural network (ENN) model was developed to model the MS for evaluating maintainability risks in high-rise buildings.

Results showed that predictions from the model were highly compatible and in the same order when compared with calculations based on actual past data. It further showed that, maintainability of buildings could be improved if the building was designed, constructed and managed properly by controlling their maintainability risks.

The ENN model was used to analyze maintainability of a high-rise building. Thus, it provides a useful tool for designers, clients, facilities managers/maintenance managers and users to analyze maintainability risks of buildings at early stages.

In the present time, there are large databases with parameters related to the maintenance of different equipment and installations. Given that manual analysis of sensors connected to machines is practically impossible, maintenance decisions from these databases can be difficult if the information automatically updated from these sensors is huge. Those great amounts of information are essentially useless if the knowledge contained inside cannot be extracted. Rough set theory facilitates this work by detecting those parameters that are truly significant for establishing the decision rules of the maintenance. In order to show the power of rough sets this paper contains a real case of a plastic injection installation for the analysis. Practical implications. An effective use of resource allocation in manufacturing processes could be achieved by using certain decision rules to indicate where and when maintenance decisions and tasks should be undertaken. This paper illustrates how the powerful theory of rough sets handles these issues. Therefore, the use of this technique is highly recommended for those industrial processes with a great amount of data and time (or in general, any resource) limitations.

The purpose of this paper is to review the literature on Total Productive Maintenance (TPM) and to present an overview of TPM implementation practices adopted by the manufacturing organizations. It also seeks to highlight appropriate enablers and success factors for eliminating barriers in successful TPM implementation.

The paper systematically categorizes the published literature and then analyzes and reviews it methodically.

The paper reveals the important issues in Total Productive Maintenance ranging from maintenance techniques, framework of TPM, overall equipment effectiveness (OEE), TPM implementation practices, barriers and success factors in TPM implementation, etc. The contributions of strategic TPM programmes towards improving manufacturing competencies of the organizations have also been highlighted here.

The literature on classification of Total Productive Maintenance has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of various TPM implementation practices demonstrated by manufacturing organizations globally. It also highlights the approaches suggested by various researchers and practitioners and critically evaluates the reasons behind failure of TPM programmes in the organizations. Further, the enablers and success factors for TPM implementation have also been highlighted for ensuring smooth and effective TPM implementation in the organizations.

The paper contains a comprehensive listing of publications on the field in question and their classification according to various attributes. It will be useful to researchers, maintenance professionals and others concerned with maintenance to understand the significance of TPM.