PurposeIn the present context of globalization, maintenance of production systems is very important. A lot of organizations are facing many problems in maintenance management. Therefore, the purpose of this paper is to identify the main problems in maintenance operations and compare these problems with those in manufacturing operations as found in the literature for effective maintenance.Design/methodology/approachTo identify the main problems in maintenance operations and to compare them with those in manufacturing operations, a large amount of published literature was studied. The paper systematically categorizes the published literature and then analyzes and reviews it theoretically.FindingsLack of top management support, lack of measurement of overall equipment effectiveness (OEE), lack of strategic planning and implementation and many more problems are biggest problems in the maintenance operations as well as manufacturing operations. These have emerged as top problems in the implementation of effective maintenance strategies in industries.Research limitations/implicationsFrom the findings, the authors can conclude that for good maintenance, top management is supposed to be supportive in taking different initiatives. Industrial organizations should focus on improving overall performance of machines identified as OEE rather than only productivity of machines. This paper will be extremely useful for the researchers, maintenance professionals and others concerned with maintenance to understand the significance of maintenance problems in industries.Originality/valueThese findings will be highly useful for professionals from the manufacturing sector in implementing effective maintenance strategy in the maintenance management system.

PurposeFrom on-board automotive diagnostics to real-time aircraft state of health, the implementation of health monitoring and management systems are an increasing trend. Further, reductions in operating budgets are forcing many companies and militaries to consider new operating and support environments. Combined with longer service lives for aircraft and other systems, maintenance and operations processes must be reconsidered. The majority of research efforts focus on health monitoring techniques and technologies, leaving others to determine the maintenance and logistics impact on the systems. The paper aims to discuss these issues.Design/methodology/approachThis research analyzes the impact of a health monitoring system on a squadron of aircraft. Flight, maintenance and logistics operations are stochastically modeled to determine the impact of program decisions on supply metrics. An arena discrete event simulation is utilized to conduct this research on 20 components on each of the 12 aircraft modeled. Costs and availability are recorded for comparison across three sparing scenarios to include economic order quantity (EOQ) for baseline and health monitoring cases and a just-in-time (JIT) health monitoring set of simulations.FindingsData are presented for EOQ and JIT supply methods. A comparison of health monitoring enabled supply to current methods shows cost savings and availability gains. The different methodologies are compared and discussed as a trade-space for programmatic decisions.Originality/valueThis work demonstrates the ability of health monitoring systems and condition based maintenance to affect supply ordering decisions. The development of trade-spaces within operating environments is demonstrated along with the ability to conduct cost benefit analyses.

PurposeThe purpose of this paper is to exemplify and discuss the context aspect for predictive analytics where in parallel condition monitoring (CM) measurements data and information related to the context are gathered and analysed.Design/methodology/approachThis paper is based on an industrial case study, conducted in a manufacturing company. The linear axis of a machine tool has been selected as an object of interest. Available data from different sources have been gathered and a new CM function has been implemented. Details about performed steps of data acquisition and selection are provided. Among the obtained data, health indicators and context-related information have been identified.FindingsMultiple sources of relevant contextual information have been identified. Performed analysis discovered the deviations in operational conditions when the same machining operation is repeatedly performed.Originality/valueThis paper shows the outcomes from a case study in real word industrial setup. A new visualisation method of gathered data is proposed to support decision-making process.

Purpose – The purpose of this paper is to introduce an algorithm based only on local extreme analysis of a time sequence to further the detection and diagnosis of inter-turn short circuits and unbalanced voltage supply using vibration signals. Design/methodology/approach – The upper and lower extreme envelopes from a modulated and oscillatory time sequence present a particular characteristic being of, theoretically, symmetrical versions with regard to amplitude reflection around the time axis. Thus, one may say that they carry the same characteristics in terms of waveforms and, consequently, frequency content. These envelopes can easily be built by an interpolation process of the local extremes, maximums and minimums, from the original time sequence. Similar to modulator signals, they contain more detailed and useful information about the required electrical fault frequencies. Findings – Results show the efficiency of the proposed algorithm and its relevance to detecting and diagnosing faults in induction motors with the advantage of being a technique that is easy to implement in any computational code. Practical implications – A laboratory investigation carried out through an experimental setup for the study of faults, mainly related to the stator winding inter-turn short circuit and voltage phase unbalance, is presented. Originality/value – The main contribution of the work is the presentation of an alternative tool to demodulate signals which may be used in real applications like the detection of faults in three-phase induction machines.

Purpose– The purpose of this paper is to show that maintenance performance is potentially better predictable from recording routines.Design/methodology/approach– An attempt is made to observe an effect of a policy. Maintenance cases seem exceptional because of the efficiently obtainable evidence about policy violations which potentially provides access to the counterfactual reality to be avoided by the decision maker. The approach followed in this work is to use maintenance policy compliance to observe the effect of a maintenance policy.Findings– Conventional maintenance scorecards are not geared to accommodate maintenance performance predictions. The proposed alternative representation of maintenance performance indicators much better accommodates maintenance performance predictions.Research limitations/implications– This work focuses on the operationalisation and the sampling procedure of maintenance performance indicators; the selection of a predictive model is not considered.Practical implications– This work demonstrates that maintenance decision makers have the possibility to observe the effects of their policy, which potentially enables them to better control their objectives. This work provides guidelines to construct performance indicators that much better accommodate maintenance performance predictions than conventional maintenance performance indicators.Originality/value– The approach to make the effects of maintenance policy compliance observable is an original contribution to normative decision theory. To construct a maintenance scorecard that accommodates maintenance performance predictions is an original contribution to the field of maintenance performance measurement.

Purpose – The purpose of this paper is to review current literature analyzing human factors in maintenance, and areas in need of further research are suggested. Design/methodology/approach – 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. Findings – 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. Originality/value – 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.

Purpose – Overall equipment effectiveness (OEE) provides a quantitative metric based on the elements availability, performance and quality for measuring the performance effectiveness of individual equipment or entire processes. Although these elements are important, other performance factors such as the efficient use of raw materials and the production environment (e.g. production system, logistics, labour, etc.) in which the equipment or process operates may also have a significant contribution to process performance. The purpose of this paper is to present an alternative measure derived from OEE, overall resource effectiveness (ORE), which considers these factors. Design/methodology/approach – The paper reviews the OEE’s background and explores its limitations. Then, it shows the conceptual and mathematical development of the ORE measure and the formulas used for its calculation. Empirical and simulation-based investigations and applications of ORE are carried out through two cases study for its validation. Findings – The results derived from both the empirical and simulation-based investigations demonstrate that OEE may not be an appropriate measure for some specific processes and that ORE may offer a more complete perspective on and information of key performance indicators. Practical implications – ORE can provide production managers with more complete information concerning the performance of their processes. This will allow them to take better decisions regarding the management and actions needed to improve their processes. Originality/value – This paper presents a novel and alterative approach to measure the performance of manufacturing equipment and processes.

Purpose – The purpose of this paper is to describe the development of a balanced scorecard (BSC) for flight line maintenance (MX) activities in the US Air Force. Design/methodology/approach – The BSC development process consists of three stages: groundwork, design beginning with structuring of organizational strategic elements through performance measure identification and construction of the BSC framework, and finalization for continuous improvement. Findings – Based on logistics expert responses the authors validated a case BSC for flight line MX activities within an aircraft maintenance unit. Validation was done with respect to perspective measures including mission, influencing factors, management, and information enhancement. Originality/value – BSC development through identification of mission critical performance measures should improve performance of aircraft scheduling and achievement of mission objectives. Guidelines were used to develop a case validated by Air Force logistics personnel.

Purpose – This paper deals with the identification and diagnosis of operational variability in chemical processes, which is a common problem in mills but little explored in literature. The Cross-Industry Standard Process for Data Mining (CRISP-DM) is a widely used approach in problem solving. The purpose of this paper is to: first, contribute to the body of knowledge on applying CRISP-DM in a pulp mill production process and the special issues that need to be considered in this context. Exact amounts of a cost increase due to variation in pulp production have not been reported previously. Second, to quantify the cost of variation. Design/methodology/approach – In the case studied, the variation in a pulp mill batch cooking process had increased. In order to identify the causes of variation, CRISP-DM was applied. Findings – The cycle of variation was identified and found to be related to the batch cooking process cycle time. By using information from this analysis it was possible to detect otherwise unobserved defective steam nozzles. The defective equipment was repaired and improved. Further improvement was achieved when the fouling of a heat exchanger was found by analysis to be the root cause of long-term variability parameters. By applying CRISP-DM, equipment defects and fouling were identified as the root causes of the higher manufacturing costs due to increased variation were detected and estimated. The Taguchi loss function is a possible tool for estimating the cost of variation in pulp manufacturing. Originality/value – This paper provides new knowledge in the context of implementing CRISP-DM and the Taguchi loss function in the pulp and paper manufacturing process.