Concept Of E-maintenance Research Articles

Rationalization of the operation process of intrusion and hold-up alarm systems

Intrusion and hold-up alarm systems (I&HAS) are part of electronic security systems. They are now installed in many facilities, including those classified as critical infrastructure. The variety of available alarm control panels and their configurations means that I&HAS are installed with the use of alarm control panels with various functional and diagnostic capabilities. In the process of operation of intrusion and hold-up alarm systems, maintenance actions are most often used when no damage has occurred. This is referred to as preventive maintenance. These activities are aimed at carrying out preventive maintenance that will reduce the likelihood of damage or deterioration of the system. An extension and also an evolution of preventive maintenance activities is the development of the eMaintenance concept. By implementing modern solutions in diagnosing intrusion and hold-up alarm systems and using advanced IT applications, it is possible to monitor them and manage the operational process in real-time with the possibility of observing the degradation of the I&HAS. This makes it possible to take action to prevent the transition to a state of partial fitness or unfitness. As a result of the analysis of the operation process of the intrusion and hold-up alarm systems, taking into account diagnostic information, a graph of relations occurring in the system was developed. Then, dependencies were determined to calculate the probabilities of the I&HAS being in a state of full ability, states of periodic service, states of partial ability, and a state of unfitness. The issues of modelling the operation process of intrusion and hold-up alarm systems presented by the authors make it possible to rationalize the intensity of periodic inspections. The result is an increase in the value of the readiness index of I&HAS, which is particularly important in the case of securing critical infrastructure facilities.

Effective vibration-based condition monitoring (eVCM) of rotating machines

PurposeThe purpose of this paper is mainly to highlight how a simplified and streamlined approach to the condition monitoring (CM) of industrial rotating machines through the application of frequency domain data combination can effectively enhance the eMaintenance framework.Design/methodology/approachThe paper commences by providing an overview to the relevance of maintenance excellence within manufacturing industries, with particular emphasis on the roles that rotating machines CM of rotating machines plays. It then proceeds to provide details of the eMaintenance as well as its possible alignment with the introduced concept of effective vibration-based condition monitoring (eVCM) of rotating machines. The subsequent sections of the paper respectively deal with explanations of data combination approaches, experimental setups used to generate vibration data and the theory of eVCM.FindingsThis paper investigates how a simplified vibration-based rotating machinery faults classification method based on frequency domain data combination can increase the feasibility and practicality of eMaintenance.Research limitations/implicationsThe eVCM approach is based on classifying data acquired under several experimentally simulated conditions on two different machines using combined higher order signal processing parameters so as to reduce CM data requirements. Although the current study was solely based on the application of vibration data acquired from rotating machines, the knowledge exchange platform that currently dominates present day scientific research makes it very likely that the lessons learned from the development of eVCM concept can be easily transferred to other scientific domains that involve continuous CM such as medicine.Practical implicationsThe concept of eMaintenance as a cost-effective and smart means of increasing the autonomy of maintenance activities within industries is rapidly growing in maintenance-related literatures. As viable as the concept appears, the achievement of its optimum objectives and full deployment to the industry is still subjective due to the complexity and data intensiveness of conventional CM practices. In this paper, an eVCM approach is proposed so that rotating machine faults can be effectively detected and classified without the need for repetitive analysis of measured data.Social implicationsThe main strength of eVCM lies in the fact that it permits the sharing of historical vibration data between identical rotating machines irrespective of their foundation structures and speed differences. Since eMaintenance is concerned with driving maintenance excellence, eVCM can potentially contribute towards its optimisation as it cost-effectively streamlines faults diagnosis. This therefore implies that the simplification of vibration-based CM of rotating machines positively impacts the society with regard to the possibility of reducing how much time is actually spent on the accurate detection and classification of faults.Originality/valueAlthough the currently existing body of literature already contains studies that have attempted to show how the combination of measured vibration data from several industrial machines can be used to establish a universal vibration-based faults diagnosis benchmark for incorporation into eMaintenance framework, these studies are limited in the scope of faults, severity and rotational speeds considered. In the current study, the concept of multi-faults, multi-sensor, multi-speed and multi-rotating machine data combination approach using frequency domain data fusion and principal components analysis is presented so that faults diagnosis features for identical rotating machines with different foundations can be shared between industrial plants. Hence, the value of the current study particularly lies in the fact that it significantly highlights a new dimension through which the practical implementation and operation of eMaintenance can be realized using big data management and data combination approaches.

A Proactive Event-driven Decision Model for Joint Equipment Predictive Maintenance and Spare Parts Inventory Optimization

Manufacturing operations can take substantial advantage of the proactivity concept by utilising event-driven information systems, able to process the sensor data and to provide proactive recommendations. Despite the recent advances in technology and information systems and the variety of methods for prognosis, decision models for joint maintenance and inventory optimization on the basis of real-time prognostic information have not been explored. We propose a proactive event-driven decision model for joint predictive maintenance and spare parts inventory optimization which addresses the Decide phase of the “Detect- Predict- Decide- Act” model and can be embedded to an Event Driven Architecture (EDA) for real-time processing in the frame of e-maintenance concept. The proposed approach was tested in a real manufacturing scenario in automotive lighting equipment industry and proved that maintenance and inventory costs can be significantly reduced by transforming the company's maintenance strategy from time-based to Condition Based Maintenance (CBM).

Implementation of a condition monitoring system on an electric arc furnace through a risk-based methodology

This article presents the deployment of a condition monitoring system on an electric arc furnace in a steel-making company, ranging from the development of the system until its implementation and the results achieved by its use in the plant. A step-wise risk-based methodology is introduced and it is adopted to deploy the condition monitoring system. The electric arc furnace is a relevant asset for safety issues; due to the characteristics of the furnace – running continuously at high temperatures and in harsh environmental conditions – many components cannot be visually inspected; thus, a maintenance system, with real-time monitoring capabilities, represents a proper solution to keep under control the asset health state. Besides the monitoring activity, appropriate risk information must also be shown to maintenance personnel to effectively improve maintenance activity. In this concern, the condition monitoring system, herein presented, can be considered an E-maintenance tool, integrated within an existing information and communication technology infrastructure, and representing one practical application of E-maintenance concept within industry.

Comprehensive Analysis for Air Supply Fan Faults Based on HVAC Mathematical Model

Due to the growing demand on high efficient heat ventilation and air conditioning (HVAC) systems, how to improve the efficiency of HVAC system regarding reduces energy consumption of system has become one of the critical issues. Reports indicate that efficiency and availability are heavily dependent upon high reliability and maintainability. Recently, the concept of e-maintenance has been introduced to reduce the cost of maintenance. In e-maintenance systems, the fault detection and isolation (FDI) system plays a crucial role for identifying failures. Finding healthy HVAC source as the reference for health monitoring is the main aim in this area. To dispel this concern a comprehensive transient model of heat ventilation and air conditioning (HVAC) systems is developed in this study. The transient model equations can be solved efficiently using MATLAB coding and simulation technique. Our proposed model is validated against real HVAC system regarding different parts of HVAC. The developed model in this study can be used for a pre tuning of control system and put to good use for fault detection and isolation in order to accomplish high-quality health monitoring and result in energy saving. Fan supply consider as faulty device of HVAC system with six fault type. A sensitivity analysis based on evaluated model shows us three features are sensitive to all faults type and three auxiliary features are sensitive to some faults. The magnitude and trait of features are a good potential for automatic fault tolerant system based on machine learning systems

Comprehensive Analysis for Air Supply Fan Faults Based on HVAC Mathematical Model

Due to the growing demand on high efficient heat ventilation and air conditioning (HVAC) systems, how to improve the efficiency of HVAC system regarding reduces energy consumption of system has become one of the critical issues. Reports indicate that efficiency and availability are heavily dependent upon high reliability and maintainability. Recently, the concept of e-maintenance has been introduced to reduce the cost of maintenance. In e-maintenance systems, the fault detection and isolation (FDI) system plays a crucial role for identifying failures. Finding healthy HVAC source as the reference for health monitoring is the main aim in this area. To dispel this concern a comprehensive transient model of heat ventilation and air conditioning (HVAC) systems is developed in this study. The transient model equations can be solved efficiently using MATLAB coding and simulation technique. Our proposed model is validated against real HVAC system regarding different parts of HVAC. The developed model in this study can be used for a pre tuning of control system and put to good use for fault detection and isolation in order to accomplish high-quality health monitoring and result in energy saving. Fan supply consider as faulty device of HVAC system with six fault type. A sensitivity analysis based on evaluated model shows us three features are sensitive to all faults type and three auxiliary features are sensitive to some faults. The magnitude and trait of features are a good potential for automatic fault tolerant system based on machine learning systems

Special issue on eMaintenance solutions and technologies

The term eMaintenance was coined in the early 2000s and has gained its popularity as a component of the eManufacturing and eBusiness concepts, which exploit and gain strength from the emerging information and communication technologies. eMaintenance is a new concept and can be defined as a technique for maintenance support, which includes the resources, services and management necessary to enable and implement a proactive decision making process. This support includes not only eTechnologies, but also eMaintenance activities such as eMonitoring, eDiagnosis, and ePrognosis. This special issue reflects the challenges and future trends discussed during the First International Congress on eMaintenance Technologies and Solutions ‘‘eMaintenance 2010’’, held in Lulea, June 22–24, 2010. The Congress was initiated and organized by the Division of Operation and Maintenance Engineering of Lulea University of Technology, Lulea, Sweden. The main theme of the congress was ‘‘Trends in Technologies and Methodologies, Challenges, Possibilities and Applications of eMaintenance’’. While most of the articles have been taken from the proceedings of eMaintenance 2010, a few invited articles are also included in this special issue. In total, nine papers have been selected for this issue after peer reviewing of the manuscript. The first paper, ‘‘Maintenance optimization models and criteria’’, outlines the reasons for the emergence of the eMaintenance concept and reviews the literature on maintenance optimization models, with a specific focus on the optimization criteria and objectives used. To overcome the flaws in the present optimization models, a generic classification framework of maintenance optimization models is presented. The framework is a starting point for the development of business-specific optimization models and enables decision making in eMaintenance. The authors of the second paper, ‘‘Economical and technological prospects for eMaintenance’’, have elaborated the benefits of eMaintenance and its influence in the life cycle cost of an asset, providing a critical assessment of the current status. The article seeks to assess how eMaintenance end users can benefit from eMaintenance and deals with the financial implications related to its adoption. The main explanation of the benefits is that they result from the new capabilities provided by eMaintenance. If the eTechnologies provide some of these capabilities, maximizing the eMaintenance benefits for the overall maintenance efficiency is possible. However, there are some business and human-related issues that need to be resolved before the actual application of remote maintenance. The paper, ‘‘Organizational dimension of eMaintenance: a contextual perspective’’, introduces and discusses a contextual perspective for better understanding of the opportunities and challenges associated with organizational learning and innovation in eMaintenance deployment. To achieve success, eMaintenance needs to be aligned with the overall organizational objectives. Risk management in eMaintenance activities involves a trade-off between protection, on the one hand, and functionality, performance and ease-of-use, on the other. This aspect is considered in the article ‘‘An enterprise risk management framework for evaluation of eMaintenance’’, where a risk management framework for the evaluation of eMaintenance solutions is proposed. Further, U. Kumar (&) A. Parida R. Karim Division of Operation and Maintenance Engineering, Lulea University of Technology, Lulea, Sweden e-mail: Uday.Kumar@ltu.se

Using SVM based method for equipment fault detection in a thermal power plant

Due to the growing demand on electricity, how to improve the efficiency of equipment in a thermal power plant has become one of the critical issues. Reports indicate that efficiency and availability are heavily dependant upon high reliability and maintainability. Recently, the concept of e-maintenance has been introduced to reduce the cost of maintenance. In e-maintenance systems, the intelligent fault detection system plays a crucial role for identifying failures. Data mining techniques are at the core of such intelligent systems and can greatly influence their performance. Applying these techniques to fault detection makes it possible to shorten shutdown maintenance and thus increase the capacity utilization rates of equipment. Therefore, this work proposes a support vector machines (SVM) based model which integrates a dimension reduction scheme to analyze the failures of turbines in thermal power facilities. Finally, a real case from a thermal power plant is provided to evaluate the effectiveness of the proposed SVM based model. Experimental results show that SVM outperforms linear discriminant analysis (LDA) and back-propagation neural networks (BPN) in classification performance.

Economic value of technologies in an e-Maintenance platform

In the past years, scientific papers appeared about the opportunities offered by new technologies in e-Maintenance context. Indeed, a great number of contributions can be found in literature analyzing and proposing different prospects to improve maintenance processes by leveraging on the e-Maintenance concept and its applications using a myriad of e-technologies. On the other hand, little attention has been paid on the selection and configuration of these technologies based on their economic value for the user. This has rarely been discussed and the present paper wants to provide an initial step to fulfil this gap. The results of the analysis, carried out in companies located in Italy and Finland, are reported in order to compare different situations where an evaluation of the economic value was studied. The examples were selected to be representative and to help opening the discussion on the economic feasibility and business perceptions of this kind of applications.

Conceptual framework for e-Maintenance: Illustration by e-Maintenance technologies and platforms

At present we can find different complementary definitions of the term e-Maintenance. These definitions apply to maintenance several principles and concepts such as collaboration, pro-activity, knowledge, intelligence, web services or the Internet. A clear consensus is not yet reached, even when some contributions try to propose unique repositories to ensure consistency. Consequently the aim of this paper is: (a) to discuss, briefly, on the concept of e-Maintenance and on a first conceptual e-Maintenance framework based on 5 abstraction levels in order; (b) to detail the last level named “infrastructure” for illustrating e-Maintenance technologies and platforms. This level allows to put in evidence new technologies supporting e-Maintenance services and to describe e-Maintenance architecture resulting from the technology's integration. The main illustration is done with a TELeMAintenance platform (TELMA).

E-maintenance: review and conceptual framework

E-maintenance is an emerging concept generally defined as ‘a maintenance management concept whereby assets are monitored and managed over the Internet’. Nevertheless a lot of complementary definitions exist in which are introduced the principles of collaboration, knowledge, intelligence, etc. There is no consensus and the number of references and work is huge1 without a unique repository to ensure consistency. Consequently the aim of this research and review note is to define more precisely the emerging concept of e-maintenance and then to propose and discuss a conceptual e-maintenance framework based on a Zachman framework. Such a framework can facilitate a widespread understanding of e-maintenance and provide useful guidance for supporting e-maintenance deployment through services, processes, organisation and infrastructure. It should serve as a reference for an inventory on all the work related to this topic.

On the concept of e-maintenance: Review and current research

The importance of the maintenance 1 1 The maintenance terminology used in this paper is extracted from the European standard EN 13306:2001 de/fr/en European Standard on Maintenance Terminology. function has increased because of its role in keeping and improving system availability and safety, as well as product quality. To support this role, the development of the communication and information technologies has allowed the emergence of the concept of e-maintenance. Within the era of e-manufacturing and e-business, e-maintenance provides the opportunity for a new maintenance generation. As we will discuss later in this paper, e-maintenance integrates existing telemaintenance principles, with Web services and modern e-collaboration principles. Collaboration allows to share and exchange not only information but also knowledge and (e)-intelligence. By means of a collaborative environment, pertinent knowledge and intelligence become available and usable at the right place and time, in order to facilitate reaching the best maintenance decisions. This paper outlines the basic ideas within the e-maintenance concept and then provides an overview 2 2 Last year, within a current research project called “Modelling policies for the improvement of production systems dependability” (Project number DPI 2004-01843) and sponsored by the Spanish government, we have launched a call for paper on e-maintenance to better understand the nature and the impact of the e-maintenance phenomenon. The results were presented in different conferences and some of them are published within a special issue on e-maintenance for Computers in Industry, Guest Editors B. Iung and A. Crespo Marquez [1]. of the current research and challenges in this emerging field. An underlying objective is to identify the industrial/academic actors involved in the technological, organizational or management issues related to the development of e-maintenance. Today, this heterogeneous community has to be federated in order to bring up e-maintenance as a new scientific discipline.

E-MAINTENANCE: PRINCIPLES, REVIEW AND CONCEPTUAL FRAMEWORK

AbstractE-maintenance is an emerging concept generally defined as “a maintenance management concept whereby assets are monitored and managed over the Internet”. Nevertheless a lot of complementary definitions exists in which are introduced the principles of collaboration, knowledge, intelligence … A consensus is not approved and the number of references and work is huge without a unique repository to ensure consistency. Consequently the aim of this research and review note is to define more precisely the emerging concept of e-maintenance and then to propose and discuss a conceptual e-maintenance framework based on Zachman framework. Such a framework can facilitate a widespread understanding of e-maintenance and provide useful guidance for supporting e-maintenance deployment through services, processes, organisation and infrastructure. Because of this, it can be used to classify recent e-maintenance contributions.

From Remote Maintenance to Co-Operative Expertise-Based E-Maintenance

Over the last several years, we have witnessed a change in many areas of the economy from the seller market to the buyer market. In the context of the Extended Enterprise, the main consequence has been the need to reconsider the traditional relationship between the customer and the supplier in order to ensure the quality of service delivered, at minimum cost, by the product over its life cycle. The challenges faced by such an Enterprise are thus as well of an industrial as organisational and human nature, so that the Enterprise be able to adapt to changes in business environment and to develop innovative customer-supplier relationships. New communication and co-operation methods are needed to support these relationships. The combination of modern information processing and telecommunication tools, commonly referred to as Tele-service, offers the technical support required to access remote information. Indeed, it is easier to transfer information and knowledge to different actors than to move an actor to the site. However, even if this technical support is necessary for information communication, it is insufficient to develop a co-operation-based working situation that involves many customers and suppliers. That means an evolution from Tele-service to e-work and e-Maintenance in particular. Consequently, this paper underlines the issues, solutions and challenges related to the development and implementation of the e-Maintenance concept for our IMS-TEMIIS industrial platform.