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The present study empirically compares maintenance practices under asset performance management (APM), employed by firms in developed and developing countries (Belgium and Kenya, respectively).

Empirical observations and theoretical interpretations on maintenance practices under APM are delineated. A comparative cross-sectional survey study is conducted through an online questionnaire with 151 respondents (101 Kenya, 50 Belgium). Descriptive statistics and inferential statistics like independent t-test and phi coefficient were used for analyzing the data.

In both countries, reduction of maintenance and operational budget, return on assets, asset ageing and compliance aspects were established as critical factors influencing the implementation of asset maintenance and performance management (AMPM). A significant difference in staff competence in managing vibration, ultrasound and others like predictive algorithms was found to exist between the firms of the two countries. The majority of firms across the divide utilize manual and computer-based tools to integrate and analyse various maintenance data sets, while standardization and maintenance knowledge loss were found to adversely affect maintenance data management.

The study findings are based on the limited number of returned responses of the survey questionnaire and focused on only two countries representing developed and developing economies. This study not only provides practitioners with the practical guidelines for benchmarking, but also induces the need to improve the asset maintenance strategies and data application practices for asset performance management.

The paper provides insights to researchers and practitioners in the articulation of imperative effective maintenance strategies, benchmarking and challenges in their implementation, considering the different operational context.

The paper contributes to theory and practice within the field of AMPM where no empirical research comparing developed and developing countries exist.

The purpose of this paper is to develop a maintenance decision support system (DSS) framework using in-service lubricant data for fault diagnosis. The DSS reveals embedded patterns in the data (knowledge discovery) and automatically quantifies the influence of lubricant parameters on the unhealthy state of the machine using alternative classifiers. The classifiers are compared for robustness from which decision-makers select an appropriate classifier given a specific lubricant data set.

The DSS embeds a framework integrating cluster and principal component analysis, for feature extraction, and eight classifiers among them extreme gradient boosting (XGB), random forest (RF), decision trees (DT) and logistic regression (LR). A qualitative and quantitative criterion is developed in conjunction with practitioners for comparing the classifier models.

The results show the importance of embedded knowledge, explored via a knowledge discovery approach. Moreover, the efficacy of the embedded knowledge on maintenance DSS is emphasized. Importantly, the proposed framework is demonstrated as plausible for decision support due to its high accuracy and consideration of practitioners needs.

The proposed framework will potentially assist maintenance managers in accurately exploiting lubricant data for maintenance DSS, while offering insights with reduced time and errors.

Advances in lubricant-based intelligent approach for fault diagnosis is seldom utilized in practice, however, may be incorporated in the information management systems offering high predictive accuracy. The classification models' comparison approach, will inevitably assist the industry in selecting amongst divergent models' for DSS.

To provide a framework that can identify and evaluate the effectiveness of a given maintenance strategy in a company. This can help in the strategic management of maintenance.

The framework is developed using Hayes and Wheelwright's four‐stage framework on manufacturing strategy as a guideline. To gain a clearer understanding of the framework and its usefulness the subject topic is elaborated in two phases: definition of maintenance strategy, framework description and operationalization using case examples. The scope of the paper is limited to performance measurement of maintenance strategies.

It is found that the framework is applicable and useful for the strategic management of the maintenance function. The case example depicting the fourth stage shows that maintenance can also contribute to enhancing the competitive advantage of a company.

Given the current position of maintenance, the framework used in this paper also suggests the strategic direction to progress for long‐term effectiveness. It helps in stimulating practising managers to manage maintenance with a strategic thinking and mindset. It also helps them to visualize the capabilities of maintenance in enhancing the competitive advantage of a company.

Unlike other functions like manufacturing and business, the strategic literature on maintenance is meagre. Many tools and techniques have been developed and applied in other fields. However, the applicability of those tools to maintenance function has never been tried. In that respect this topic is new. It helps in managing maintenance more effectively, given its growing technical and technological complexity.

Maintenance management is a business function of which the considerable operational and tactical importance is still growing. As problems and opportunities are needed to be anticipated in time in order to make the necessary adjustments, sound performance reporting is indispensable. Presents a short overview of commonly used maintenance performance measurement systems based on literature study and industrial practice. Discusses experiences with the implementation of an in‐house developed performance measurement tool in Belgian industry. Presents recommendations concerning the introduction of a maintenance performance reporting system.

Approaches maintenance management in a systematic way so as to achieve its business objectives. From a managerial point of view, this so‐called object/objective‐oriented maintenance management (OOMM) is an integral process of asset (equipment) management with behavior‐based maintenance (BBM) as a major element. Within the OOMM concept, the objective‐approach focuses on the managing of the maintenance processes so as to achieve the business objectives, and the object‐approach emphasizes the object (asset or equipment) and the behavioral failures. Furthermore, combined together, the two approaches reflect the basic characteristics of the maintenance process. Also, both sides affect and influence each other, and are inseparable within OOMM. BBM addresses the monitoring and controlling of the technical and economic behavior of a piece of equipment in two ways.

This paper aims to substantiate the need for additional research into a more holistic and multidisciplinary approach to managing the supporting supply chains that may also capture contextual information, also pointing out emerging avenues for further scholarly contributions.

The supply chain is viewed from a spare part consumer as well as from a supplier perspective. Key to the discussion is an accurate description of the maintenance demand pattern (MDP) known at the consumer's side as a valuable information source for the entire supply chain.

Solving the spare parts supply chain puzzle exceeds the realms of a single scientific discipline and involves hard and soft sciences. Besides, extending on the quantitative modelling aspects of MDPs, soft modelling and analysis is needed to define cooperative settings in which the supply chain parties can operate effectively.

In this paper, the authors argue for the sharing of the appropriately balanced combination of quantitative and qualitative information that is currently hidden, or exists in isolation, within supply chains. Debatably, such information sharing may potentially generate substantial benefits for all “players” within a given supply chain.

This contribution is unique in the sense that it provides a most accurate characterization of MDPs based on the proven maintenance concept design theory. In addition, the supply chain problem is analysed in a realistic context, with an open and broad mindset rather than approaching this issue from a single hard science perspective.

The information revolution and its impact on businesses, academic life and everyday life is still receiving much attention at conferences, in business publications and academic journals. This paper addresses some important opportunities created by the information technology (r)evolution for maintenance management. It also indicates how IT is already actively used in a number of normal working situations and points to possible new uses.

A literature review, confirmed by in‐depth interviews in industry, indicated a high level of reluctance to implement horizontal collaboration in business. One of the main reasons is the lack of a strategic decision support framework for the implementation of horizontal collaboration. An appropriate feasibility or fitness test could be helpful here. Two companies strategically ready to work together should first test whether any insurmountable practices (e.g. difference in culture) inhibit the collaboration. If such practices are present, the collaborative initiative will probably be a waste of time and effort. This paper therefore aims to present a method to check the strategic fit.

By means of a general literature study, 300 performance indicators were collected. In a next step, they were reduced to 58 key elements by means of a focused literature study on partnerships and eight in‐depth case studies in Belgian industry. Metrics have been assigned to each of these elements using the Supply Chain Operation Reference Model (SCOR). The elements are then combined into sub‐criteria and criteria. Furthermore, the elements (both qualitative and quantitative) have been integrated through a multi‐criteria decision‐making method, namely analytic hierarchy process (AHP). Three different alternatives are considered: no‐collaboration, informal collaboration, or partnership. By means of pairwise comparison of all criteria, sub‐criteria and elements, an indication of the preferred form of collaboration is obtained and an improvement analysis per element can be performed.

The paper suggests and tests a method for evaluating the strategic fit, incorporating key performance indicators.

The research assumes integrity of all partners.

This paper presents a straightforward tool that demonstrates how to measure the strategic fit of inventory pooling in a horizontal collaboration between different organizations.

The paper provides valuable information on measuring the strategic fit in horizontal collaboration initiatives.

States that companies are moving more and more towards becoming learning organizations. It is expected that in the future the ability to learn will be a core competence and an essential competitive element of successful companies. Today, more and more techniques are used to enable companies to learn, e.g. performance benchmarking, the facts and figures culture of TQM, etc. As a consequence registration tools are an essential step in the process of learning. Describes the authors’ experience with the development of models to register all kind of disturbances in production systems.

The purpose of this paper is to review current literature analyzing human factors in maintenance, and areas in need of further research are suggested.

The review applies a novel framework for systematically categorizing human factors in maintenance into three major categories: human error/reliability calculation, workplace design/macro-ergonomics and human resource management. The framework further incorporates two well-known human factor frameworks, i.e., the Swiss Cheese model and the ergonomic domains framework.

Human factors in maintenance is a pressing problem. The framework yields important insights regarding the influence of human factors in maintenance decision making. By incorporating various approaches, a robust framework for analyzing human factors in maintenance is derived.

The framework assists decision makers and maintenance practitioners to evaluate the influence of human factors from different perspectives, e.g. human error, macro-ergonomics, work planning and human performance. Moreover, the review addresses an important subject in maintenance decision making more so in view of few human error reviews in maintenance literature.