Predictive maintenance, its implementation and latest trends

Selcuk, Sule

doi:10.1177/0954405415601640

Cited by 262 publications

(127 citation statements)

References 53 publications

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“…[24] provides examples of various methods for the monitoring of OGC processes alongside the rationale for using CBM technology. In [25][26][27], various aspects of the application of CBM technology are analyzed.…”

Section: Environmental Monitoring and Safe Operatiomentioning

confidence: 99%

Analysis and New Approaches to the Solution of Problems of Operation of Oil and Gas Complex as Cyber-Physical System

Fətəliyev¹,

Mehdiyev²

2018

IJITCS

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The application of modern information technologies in the oil and gas sector is constantly developing, which facilitates the acceleration of exploration and detection of oil, the increase in oil production and reduction in risks relates to health, human safety, and the environment. The Internet of things in the oil and gas sector, like in all sectors of industry, has great prospects from an economic point of view. The article is devoted to the study of the current state and avenues of solving key problems of effective and reliable functioning of the oil and gas industry as a cyber-physical system using the Internet of things in the Azerbaijani oil company SOCAR. The main technological processes and existing opportunities for the application of information technologies in the oil and gas complex are analyzed. New approaches are proposed to solve the problems in the oil and gas complex as cyber-physical system based on the smart sensors, the Internet of things, wireless networks and cloud technologies. The implementation of the proposed model is aimed at increasing the effectiveness, resource storage, exploration reliability and durability of the oil and gas complex.

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Section: Environmental Monitoring and Safe Operatiomentioning

confidence: 99%

Analysis and New Approaches to the Solution of Problems of Operation of Oil and Gas Complex as Cyber-Physical System

Fətəliyev¹,

Mehdiyev²

2018

IJITCS

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“…Recent advances in information, communication, and computer technologies, as Internet of Things and RFID (radio-frequency identifications), support prognostic and health management philosophy and make predictive maintenance applications more efficient, applicable, affordable, and consequently more common and available for different industrial domains [20].…”

Section: Energy Efficiency Measures Identification and Optimizationmentioning

confidence: 99%

“…Predictive maintenance techniques are closely associated with sensor technologies, but a comprehensive approach, integrating sensing with subsequent maintenance activities, is needed to increase their efficiency. Recent advances in information, communication, and computer technologies, as Internet of Things and RFID (radio-frequency identifications), support prognostic and health management philosophy and make predictive maintenance applications more efficient, applicable, affordable, and consequently more common and available for different industrial domains [20].…”

Section: Bitumen Processing Case Studymentioning

confidence: 99%

Using Field Data for Energy Efficiency Based on Maintenance and Operational Optimisation. A Step towards PHM in Process Plants

2018

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Energy saving is an important issue for any industrial sector; in particular, for the process industry, it can help to minimize both energy costs and environmental impact. Maintenance optimization and operational procedures can offer margins to increase energy efficiency in process plants, even if they are seldom explicitly taken into account in the predictive models guiding the energy saving policies. To ensure that the plant achieves the desired performance, maintenance operations and maintenance results should be monitored, and the connection between the inputs and the outcomes of the maintenance process, in terms of total contribution to manufacturing performance, should be explicit. In this study, a model for the energy efficiency analysis was developed, based on cost and benefits balance. It is aimed at supporting the decision making in terms of technical and operational solutions for energy efficiency, through the optimization of maintenance interventions and operational procedures. A case study is here described: the effects on energy efficiency of technical and operational optimization measures for bituminous materials production process equipment. The idea of the Conservation Supply Curve (CSC) was used to capture both the cost effectiveness of the measures and the energy efficiency effectiveness. The optimization was thus based on the energy consumption data registered on-site: data collection and modelling of the relevant data were used as a base to implement a prognostic and health management (PHM) policy in the company. Based on the results from the analysis, efficiency measures for the industrial case study were proposed, also in relation to maintenance optimization and operating procedures. In the end, the impacts of the implementation of energy saving measures on the performance of the system, in terms of technical and economic feasibility, were demonstrated. The results showed that maintenance optimization could help in reaching an energy costs recovery equal to the 10% of the total costs for an electric motor system.

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“…A predictive maintenance apparatus monitors an electrical machine continuously to prevent a breakdown in the insulation system [1][2][3][4]. Electrical, mechanical and thermal stress sources systematically contribute to deteriorate motors.…”

Section: Introductionmentioning

confidence: 99%

Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus

et al. 2020

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The online monitoring of a high voltage apparatus is a crucial aspect for a predictive maintenance program. Partial discharges (PDs) phenomena affect the insulation system of an electrical machine and—in the long term—can lead to a breakdown, with a consequent, significant economic loss; wind turbines provide an excellent example. Embedded solutions are therefore required to monitor the insulation status. The paper presents an online system that adopts unsupervised methodologies for assessing the condition of the monitored machine in real time. The monitoring process does not rely on any prior knowledge about the apparatus; nonetheless, the method can identify the relevant drifts in the machine status. In addition, the system is specifically designed to run on low-cost embedded devices.

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Predictive maintenance, its implementation and latest trends

Cited by 262 publications

References 53 publications

Analysis and New Approaches to the Solution of Problems of Operation of Oil and Gas Complex as Cyber-Physical System

Analysis and New Approaches to the Solution of Problems of Operation of Oil and Gas Complex as Cyber-Physical System

Using Field Data for Energy Efficiency Based on Maintenance and Operational Optimisation. A Step towards PHM in Process Plants

Unsupervised Monitoring System for Predictive Maintenance of High Voltage Apparatus

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