Condition-Based Monitoring and Maintenance: State of the Art Review

Manufacturing firms face great pressure to reduce downtime as well as maintenance costs. Condition-based maintenance (CBM) can be used to effectively manage operations and maintenance by monitoring detailed machine health information. CBM policies and the development of the mathematical models have been growing recently. This paper provides a review of the theoretical and practical development in the field of condition-based maintenance and its current advancements. Standard CBM platform could make it effective and efficient in implementation and performance improvement.

Digital Twin-Driven Condition-Based Maintenance

The world is witnessing an all-level digitalization that guides the industry and business to a restructuration in order to adapt to the new requirements of the surrounding environment. That change also concerns the labour of the technical professionals and their formation. As a consequence of this deep consciousness-raising, this chapter will investigate and develop simulation models based on the current digitalization. The aim of this chapter is the exposition of a real case development of “digital twin” models framed as part of the condition-based maintenance paradigm to improve real-time assets operation and maintenance. This model contributes by providing real-time results that could turn into a basis for the industrial management decisions and place them in the Industry 4.0 paradigm environment.

Virtual Reality Training Application for the Condition-Based Maintenance of Induction Motors

The incorporation of new technologies as training methods, such as virtual reality (VR), facilitates instruction when compared to traditional approaches, which have shown strong limitations in their ability to engage young students who have grown up in the smartphone culture of continuous entertainment. Moreover, not all educational centers or organizations are able to incorporate specialized labs or equipment for training and instruction. Using VR applications, it is possible to reproduce training programs with a high rate of similarity to real programs, filling the gap in traditional training. In addition, it reduces unnecessary investment and prevents economic losses, avoiding unnecessary damage to laboratory equipment. The contribution of this work focuses on the development of a VR-based teaching and training application for the condition-based maintenance of induction motors. The novelty of this research relies mainly on the use of natural interactions with the VR environment and the design’s optimization of the VR application in terms of the proposed teaching topics. The application is comprised of two training modules. The first module is focused on the main components of induction motors, the assembly of workbenches and familiarization with induction motor components. The second module employs motor current signature analysis (MCSA) to detect induction motor failures, such as broken rotor bars, misalignments, unbalances, and gradual wear on gear case teeth. Finally, the usability of this VR tool has been validated with both graduate and undergraduate students, assuring the suitability of this tool for: (1) learning basic knowledge and (2) training in practical skills related to the condition-based maintenance of induction motors.

Manufacturing, Control, and Automation

This chapter identifies the common needs for process controls and automation that include methodologies to enable in-situ-level process controls, optimization at the plant or industry level, open-architecture software tools, adaptive control systems, methods and diagnostic tools for condition-based maintenance of process equipment in a manufacturing industry.

Development of a Novel Methodology for Remaining Useful Life Prediction of Industrial Slurry Pumps in the Absence of Run to Failure Data

Smart remaining useful life (RUL) prognosis methods for condition-based maintenance (CBM) of engineering equipment are getting high popularity nowadays. Current RUL prediction models in the literature are developed with an ideal database, i.e., a combination of a huge “run to failure” and “run to prior failure” data. However, in real-world, run to failure data for rotary machines is difficult to exist since periodic maintenance is continuously practiced to the running machines in industry, to save any production downtime. In such a situation, the maintenance staff only have run to prior failure data of an in operation machine for implementing CBM. In this study, a unique strategy for the RUL prediction of two identical and in-process slurry pumps, having only real-time run to prior failure data, is proposed. The obtained vibration signals from slurry pumps were utilized for generating degradation trends while a hybrid nonlinear autoregressive (NAR)-LSTM-BiLSTM model was developed for RUL prediction. The core of the developed strategy was the usage of the NAR prediction results as the “path to be followed” for the designed LSTM-BiLSTM model. The proposed methodology was also applied on publically available NASA’s C-MAPSS dataset for validating its applicability, and in return, satisfactory results were achieved.

Pact All Electric - One Step Closer to Autonomy

E&P companies are increasingly challenged with cost-effective development or upgrade of remote fields, ensuring crew safety and regulatory requirements for reducing environmental impact. Remote operations and unmanned platforms have significantly lower CO2 emissions and lowerCAPEX and OPEX in areas of sparse infrastructure. Complete electrification of safety critical control systems is key to maintain safe production while digitization, automation and condition based maintenance reduce required on-site personnel. An all-electric wellhead- and production tree valve actuator for handling emergency situations has been developed under a Joint Industry Project by Equinor, Baker Hughes and TECHNI. PACT utilize a completely new, patent pending failsafe mechanism that is inherently safe without requirement for redundancy. PACT contains an embedded controller and sensors with extremely low power consumption rendering it well suited for solar/alternate power sources. A new super-capacitor is under development in partnership with the University of Southeast Norway, that in combination with the fastest failsafe mechanism ever ensure safety in all modes of operation, even with all lines down or consumed by flames. Electric actuators offer significant CAPEX savings over hydraulic actuators by eliminating costly hydraulic control systems and hydraulic lines as well as saving space and weight. Overall system cost is significantly lower than hydraulic systems (Equinor estimates at around USD 2million per well for an unmanned platform) while also reducing emissions and environmental impact. Globally, there are approximately 7000 offshore platforms of which 1600 are unmanned (200 in the Middle East). The existing population of unmanned platforms is undergoing continual upgrades and there are significant cost savings by using the PACT as a drop-in replacement for existing hydraulic systems, while enabling fully digitized, remote control and autonomous operations. Low power consumption, weight and a small footprint renders it equally suited for land wells, including retrofit upgrades without reinforcing infrastructure. PACT is designed to be an integral part of automated and remote-control systems and the modular technology is also being adopted for subsea trees, as well as other mission critical pressure control applications. Given the significant benefits in simplifying operations and reducing cost while improving HSSE, leading E&P companies including Equinor, Total, Aker BP and others have chosen electric operations as future technology platform for both topside and subsea operations. Embedded force-, pressure-, temperature- and vibration sensors enable data-driven, fact- and condition based maintenance. Aggregating real-time and historical data, component- and system models ensures fully remote/autonomous operation with a digital twin. The novel failsafe-mechanism fronts the most reliable action of all times while the patent pending solution ensures closing times down to 1 second. In 2020 the consortium was awarded USD 950 000 in government support funding and in May 2021 PACT won OTC Spotlight on New Technology award. The paper aims to show how the technology works and underline why it will take a place in the future of well control and production.