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The purpose of this paper is to provide a brief overview of condition based maintenance (CBM) with definitions of various terms, overview of some history, recent developments, applications, and research challenges in the CBM domain.

The article presents the insight into various maintenance strategies and provides their respective merits and demerits in various aspects. It then provides the detailed discussion of CBM that includes applications of various methodologies and technologies that are being implemented in the field. Finally, it ends with open challenges in implementing condition based maintenance systems.

This paper surveys research articles and describes how CBM can be used to optimize maintenance strategies and increase the feasibility and practicality of a CBM system.

CBM systems are completely practical to implement and applicable to various domains including automotive, manufacturing, aviation, medical, etc. This paper presents a brief overview of literature on CBM and an insight into CBM as a maintenance strategy. CBM has wide applications in automotive, aviation, manufacturing, defense, and other industries. It involves various disciplines like data mining, artificial intelligence, and statistics to enable the systems to be maintenance intelligent. These disciplines help in predicting the future consequences based on the past and current system conditions. Based on the authors’ studies, implementation of such a system is easy and cost effective because it uses existing subsystems to collect statistical data. On top of that it requires building a software layer to process the data and to implement the prognosis techniques in the form of algorithms.

The design of CBM systems highly impact the society in terms of maintenance cost (i.e. reduces the maintenance cost of automobiles, safety by providing real time reporting of the fault using prognosis).

To the best of the authors’ knowledge, this paper is first of its kind in the literature which presents several maintenance strategies and provides a number of possible research directions listed in open research challenges.

This paper seeks to study maintenance policies on a plant‐wide level. It focuses on the effectiveness of condition‐based maintenance (CBM). It highlights the role of the production context and the importance of using appropriate metrics to assess CBM.

A simulation model was developed to explore the effects of production context using traditional performance indicators (costs and availability of each piece of equipment) and a more comprehensive metric (line efficiency).

The results showed that CBM has the best performance among other PM policies in loosely coupled processes. By contrast, in tightly coupled processes, CBM has a negative effect on the production line efficiency because it increases equipments' blockage and starvation states.

The simulation model was developed to reflect the reality. Nevertheless, some assumptions have been used to develop the conceptual and computerized model, which can be explored further in future research.

The idea of this paper originates from empirical findings of fellow researchers. The findings in this paper provide a better understanding of how CBM affects key performance indicators in different production contexts and therefore help managers to appropriately execute CBM programmes.

This study focuses on CBM from a new angle. The majority of the literatures on condition‐based maintenance either discusses pure technical issues, or focusses on single equipment only. In this research, the effectiveness of CBM for two processes is studied and CBM is compared with block and age‐based replacement policies using a comprehensive performance indicator.

The purpose of this paper is to demonstrate how Internet of Things (IoT) technology can enable highly distributed elevator equipment servicing by using remote-monitoring technology to facilitate a shift from traditional corrective maintenance (CM) and time-based maintenance (TBM) to more predictive, condition-based maintenance (CBM) in order to achieve various benefits.

Literature review indicates that CBM has advantages over conventional CM and TBM from a theoretical perspective, but it depends on continuous monitoring enhancement via advanced IoT technology. An in-depth case study was carried out to provide practical evidence that IoT enables elevator firms to achieve CBM.

From a theoretical perspective, the CBM of elevators makes business sense. The challenges lie in data collection, data analysis and decision making in real-world business contexts. The main findings of this study suggest that CBM can be commercialized via IoT in the case of elevators and would improve the safety and reliability of equipment. It would, thus, make sense from technological, process and economic perspectives.

Our longitudinal real-world case study demonstrates a practical way of making the CBM of elevators widespread. Integrating IoT and other advanced technology would improve the safety and reliability of elevator equipment, prolong its useful life, minimize inconvenience and business interruptions due to equipment downtime and reduce or eliminate major repairs, thus greatly reducing maintenance costs.

The main contribution of this paper lies in the empirical demonstration of the benefits and challenges of CBM via IoT relative to conventional CM and TBM in the case of elevators. The authors believe that this study is timely and will be valuable to firms working on similar research or commercialization strategies.

The introduction of ever more complicated machinery and associated operating procedures is placing an increasing strain on the maintenance function. The options available to a company engaged in the manufacture of a range of sheet metal products, for which a flexible manufacturing facility has been installed, are examined. The introduction of this system has caused the company to examine its maintenance procedures, which are based on a traditional breakdown and repair approach, and has prompted an investigation into the possibility of implementing a condition based approach to maintenance. This investigation is presented here, together with a review of currently available options, and an outline of the planned move towards condition based maintenance.

The purpose of this paper is to perform an extensive literature review in the area of decision making for condition-based maintenance (CBM) and identify possibilities for proactive online recommendations by considering real-time sensor data. Based on these, the paper aims at proposing a framework for proactive decision making in the context of CBM.

Starting with the manufacturing challenges and the main principles of maintenance, the paper reviews the main frameworks and concepts regarding CBM that have been proposed in the literature. Moreover, the terms of e-maintenance, proactivity and decision making are analysed and their potential relevance to CBM is identified. Then, an extensive literature review of methods and techniques for the various steps of CBM is provided, especially for prognosis and decision support. Based on these, limitations and gaps are identified and a framework for proactive decision making in the context of CBM is proposed.

In the proposed framework for proactive decision making, the CBM concept is enriched in the sense that it is structured into two components: the information space and the decision space. Moreover, it is extended in a way that decision space is further analyzed according to the types of recommendations that can be provided. Moreover, possible inputs and outputs of each step are identified.

The paper provides a framework for CBM representing the steps that need to be followed for proactive recommendations as well as the types of recommendations that can be given. The framework can be used by maintenance management of a company in order to conduct CBM by utilizing real-time sensor data depending on the type of decision required.

The results of the work presented in this paper form the basis for the development and implementation of proactive Decision Support System (DSS) in the context of maintenance.

This paper aims to propose a methodology to assist manufacturing companies in the implementation of condition-based maintenance (CBM) to their equipment. The developed methodology intends to consider the use of sensors already installed on the equipment and, when required, to support the selection of sensors available on the market. Since CBM using sensors is not always feasible, the information gathered for the feasibility study of CBM implementation is also used to assign other maintenance strategies.

Based on the literature review, requirements and specifications were established for endowing the methodology with relevant and distinctive characteristics. The structure of the methodology and the associated steps were defined based on this information. Then, the methodology was validated and refined using a case study.

In the case study company, following the methodology and the respective steps, appropriate maintenance strategies were assigned to a selected manufacturing machine, considering information related to the failure modes with the most significant impact, and CBM was applied to a selected component for which the benefit outweighs the costs involved, using data acquired by sensors subsequently installed on the analyzed machine.

Due to its comprehensiveness, this methodology can contribute to make CBM implementation accessible to a high number of companies and encourage the application of a wide variety of monitoring techniques.

This new methodology can be easily integrated into a computerized maintenance management system and has the advantage of facilitating the collection, organization and standardization of technical knowledge required to support CBM implementation and define the most appropriate maintenance strategy systematically and automatically. It guides the prioritization of equipment and failure modes, and the decision-making regarding the selection of sensors and the allocation of maintenance strategies with the aim of reducing costs.

The purpose of this paper is to develop the steps required for establishing and running cost‐effective condition‐based maintenance (CBM) exemplified for vibration‐based maintenance (VBM) and compared with real implementations in case companies.

The study is based on published knowledge and experience within condition monitoring (CM) and CBM, and three case studies.

The study has shown that all three case companies are in a big need for systematic procedures for doing right things right, in the right time cost‐effectively (establishing and running a cost‐effective CBM).

The paper focuses on development of cost‐effective CBM exemplified for VBM. Also, the case companies belong to three branches: paper and pulp mills, energy producer and engineering manufacturing. The case companies have different levels in applying CBM/VBM, experience and knowledge in CM and CBM.

Systematic procedures for establishing CBM/VBM policy are developed, motivated and discussed in a way which enables the user to establish and run CBM/VBM policy cost‐effectively.

The steps of establishment of CBM/VBM provide a unique model for companies to establish and run cost‐effective maintenance its originality.

The purpose of this paper is to describe a flexible architecture concept to provide a ubiquitous computing framework where condition‐based maintenance (CBM) data and information can be easily accessed, and maintenance decisions may be performed wherever required.

The architecture is based on a platform of intelligent web services, and logically structured decision layers based on the open systems architecture for CBM definition, from condition monitoring to decision support, and provides automated extraction of results. The application of web services is demonstrated, first related with an original vision on the adoption of mobile devices for dynamic maintenance management solutions, and then with a more conventional web‐based predictive maintenance management system.

Scenarios for the upgrade of existing preventive maintenance practices towards condition‐based strategies are sufficiently different to require customised solutions. A web‐based platform can work with such differences in a cost‐effective way.

Further research can expand the actual platform by embedding new complementary web services.

Condition‐based strategies can provide clear savings in many maintenance activities. The platform described will provide the necessary flexibility to industrial users to manage the volume of data and information needed in CBM.

The platform is flexible enough to provide intelligent processing “on‐demand” and ubiquitously, with a three‐level configuration of web services, agents and interfaces that facilitates interoperability with existing legacy systems. Finally, the platform can grow according to the needs of the user (e.g. new information, increased knowledge on the process, new measurements, etc.).

The purpose of this paper is the development of an empirically based typology of condition based maintenance (CBM) approaches, including the relevant characteristics and requirements.

An exploratory case study was conducted in a major gas production facility. The CBM typology that resulted from this case study was subsequently tested against a large set of CBM literature.

In the literature, CBM is usually presented as a single theory or practice. The paper finds that CBM in fact includes several different approaches and that each of the approaches is only suitable in situations where the specific characteristics of the approach match the situational characteristics. Aided by these findings, a new typology for CBM was developed. The typology is based on the method for obtaining the expected value, or trend (through statistical vs analytical modeling) and the type of data used (process vs failure data). A subsequent literature survey reveals that the proposed typology is applicable for the categorization of a large number of CBM cases found in the literature.

One of the most important requirements in selecting and using a CBM approach is the availability and integration of various types of knowledge, in particular process engineering and maintenance engineering knowledge. Practitioners can use these insights to assess current CBM cases, and identify the key characteristics of current and future use of various CBM types.

This paper presents a novel and empirically based framework for the classification of the different CBM types. Such frameworks were lacking in the current literature. The paper adds to maintenance engineering literature by identifying the key dimensions of the various types along with their key requirements.

When induction motors are considered, there is no specific cost model for net savings per year due to condition-based maintenance (CBM) covering various parameters such as downtime, energy, quality, etc. The purpose of this paper is to develop a cost model for the financial viability of the implementation of CBM for induction motors.

A literature review has been carried out to identify the existing failure modes of motor, available condition monitoring techniques, the usefulness of CBM and different maintenance models available. Then, a cost model considering all parameters has been proposed.

A cost model has been proposed for the maintenance of induction motors. Method for the economic evaluation of the model has also been suggested in the paper. The application of the model has been illustrated through a case study of a steel plant, which suggests that investment in the condition monitoring of induction motors increases the net profit of the organization.

The proposed model is specifically designed for induction motors. All the motors under consideration are assumed to be of the same specifications, and fault in any motor is supposed to have the same effect on quality, cost, criticality, etc., of the operation and end product.

This paper will help the maintenance manager in decision making when maintenance action has to be carried out for a given motor under CBM for the better utilization of the equipment and resources. This paper also shows how to compute ROI on CBM investment.

The paper provides a cost model for the economic evaluation of implementing CBM for induction motors which will be useful to researchers and maintenance managers in effective decision making and maintenance planning. The methodology and the cost models are the original contribution of the authors.