Development of a Methodology for Condition-Based Maintenance in a Large-Scale Application Field

Cocconcelli, Marco; Capelli, Luca; Molano, Jacopo Cavalaglio Camargo; Borghi, Davide

doi:10.3390/machines6020017

Cited by 17 publications

(9 citation statements)

References 66 publications

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Section: Overview and Review Of Rcm Related Workmentioning

confidence: 99%

“…The condition-monitoring system (CMS) is an integral component of RCM to increase productivity and reliability of machines as shown in Figure 6 below (Item 3). The conditions leading to failure mode must have been or be investigated using sensors like accelerometers, encoders, current/torque sensors, and pressure sensors as well as temperature sensors [23]. RCM should be a continuous process that requires sustaining because it is known that any system's best maintenance can only sustain a system to its inherent reliability and availability level within the operating context [22].…”

Section: Maintenance Policiesmentioning

confidence: 99%

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A Reliability-Centered Maintenance Study for an Individual Section-Forming Machine

et al. 2018

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This study investigated the breakdown trend in an automated production with an aim to recommend the application of reliability-centered maintenance (RCM) for improved productivity via a new preventive maintenance (PM) program. An individual section-forming machine (ISM)—a glass blowing machine for making glass bottles—was used as the case study for an automated production system. The machine parts and the working mechanisms were analysed with a special focus on methods of processes and procedures. This will enable the ISM maintenance department to run more effectively and achieve its essential goal of ensuring effective machine operation and reduction in machine downtime. In this work, information is provided on the steps and procedures to identify critical components of the ISM using failure modes and effect analysis (FMEA) as a tool to come up with an optimal and efficient maintenance program using the reliability data of the equipment’s functional components. A relationship between the failure rate of the machine components and the maintenance costs was established such that using the recommended PM program demonstrates evidence of an improvement in the machine’s availability, safety, and cost-effectiveness and will result in an increase in the company’s profit margin.

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Section: Overview and Review Of Rcm Related Workmentioning

confidence: 99%

Section: Maintenance Policiesmentioning

confidence: 99%

A Reliability-Centered Maintenance Study for an Individual Section-Forming Machine

et al. 2018

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“…In this way the high number of rolling bearings reduces the Mean Time Before Failure (MTBF) of the whole machine, but at the same time, thanks to the independent control and the independent monitoring of each cart, it is possible to implement condition monitoring strategies for each cart. At the present time the condition-based maintenance of this complex system is widely applicable thanks to the development of smart factories and industries 4.0 [4]. Several condition monitoring methods can evaluate the state of bearings and predict the future conditions of the system [5,6].…”

Section: Introductionmentioning

confidence: 99%

A bearing fault model for Independent Cart Conveyor System and its validation

et al. 2020

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Independent Cart Conveyor System is one of the most promising technology in automation industries. It combines the benefits of servo motors with the advantages of linear motors. It consists of a close path made up of modular linear motors having a curved or a straight shape that control a fleet of carts independently. Each cart is placed along the motors and it is connected, through rolling bearings, to a rail set on the motors themselves. The bearings are subject to wear and the condition monitoring of these elements is challenging for the non-stationary working conditions of variable load and variable speed profiles. This paper provides a bearing fault vibration model that takes into account the mechanical design of the cart, its motion profile, the shape of the conveyor path, the load variation and the type of fault on the rolling bearing.

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“…The issue of the condition monitoring of bearings for fault detection and diagnostics purposes results of great industrial interest and has been successfully dealt for decades with different methods based on the analysis of the vibration signals [1][2][3][4][5][6][7][8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Condition Monitoring Techniques of Ball Bearings in Non-stationary Conditions

Strozzi

Rubini

Cocconcelli

2019

Lecture Notes in Mechanical Engineering

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Frequently, the Industry suggests non-trivial problems and new fields of research for the Academy. This is the case of the ball bearing diagnostics in direct-drive motors. Direct-drive motors are brushless motors fully controlled by the drive system. Thanks to an encoder or a resolver mounted on the shaft, they can perform complex motion profiles, such as polynomials or splines, including reverse rotation of the shaft. The main advantage of directdrive motors is the removal of cams or gearboxes afterwards motor with a consequent strong reduction of economic and maintaining costs. Indeed, their main drawback is the difficulty to make diagnostics on the bearings. Regarding bearing diagnostics, most of the techniques present in literature are based on the search of fault-characteristic frequencies in the vibration spectrum of the motor. These fault frequencies are linearly dependent on the rotational frequency of the shaft if it is supposed constant. However, in direct-drive motors the rotational speed changes continuously and consequently the fault frequencies are meaningless. The paper reports a brief overview of some techniques for the condition monitoring of ball bearings in non-stationary conditions used by the Authors in the case of a packaging machine working under variable speed. The techniques adopted include an improved version of the computed order tracking, the crosscorrelation function and three supervised learning approaches: artificial neural networks, artificial immune systems and support vector machines.

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Development of a Methodology for Condition-Based Maintenance in a Large-Scale Application Field

Cited by 17 publications

References 66 publications

A Reliability-Centered Maintenance Study for an Individual Section-Forming Machine

A Reliability-Centered Maintenance Study for an Individual Section-Forming Machine

A bearing fault model for Independent Cart Conveyor System and its validation

Condition Monitoring Techniques of Ball Bearings in Non-stationary Conditions

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