Sequential imperfect preventive maintenance models with two categories of failure modes

2001 ◽  
Vol 48 (2) ◽  
pp. 172-183 ◽  
Author(s):  
Daming Lin ◽  
Ming J. Zuo ◽  
Richard C. M. Yam
Keyword(s):  
Preventive Maintenance ◽  
Failure Modes

Preventive Maintenance for Roller and Journal Bearings of Induction Motor Based on the Diagnostic Signature Analysis

1986 ◽  
Vol 108 (1) ◽  
pp. 26-31 ◽  
Author(s):  
T. Koizumi ◽  
M. Kiso ◽  
R. Taniguchi
Keyword(s):  
Preventive Maintenance ◽  
Diagnostic Procedure ◽  
Failure Modes ◽  
Induction Motors ◽  
Early Stage ◽  
Diagnostic System ◽  
Journal Bearings ◽  
Diagnostic Signature ◽  
Almost All ◽  
Practical Field

This paper is concerned with the preventive maintenance of roller and journal bearings installed in induction motors. Almost all kinds of failure modes happening on both roller and journal bearings have been reproduced and classified using time and frequency domain data analysis. Diagnostic procedure also has been derived using these analyzed results and statistical method. Finally, an actual diagnostic system for the early stage detection of defected roller bearings has been developed for practical field use.

Effective Maintenance PM Task Selection Requirements

2003 ◽  
Author(s):  
J. K. August ◽  
Krishna Vasudevan ◽  
W. H. Magninie
Keyword(s):  
Relational Database ◽  
Preventive Maintenance ◽  
Failure Modes ◽  
Selection Process ◽  
Cost Effective ◽  
Risk Tolerance ◽  
Diagnostic Methods ◽  
Work Practices ◽  
Task Selection ◽  
Maintenance Program

Developing an effective scheduled maintenance program requires a profound awareness of risk tolerance, dominant failure modes, failure symptoms, diagnostic methods, and work practices. Effective PM task selection is hard work. Identifying applicable and effective tasks quickly and consistently for critical equipment is the first step towards reliable, cost-effective operations. Automating the PM task selection process by using relational database software removes developmental ambiguity, which speeds up analysis, but poses practical problems. Preventive maintenance (PM) work order development can be standardized and automated to achieve this objective.

scholarly journals Reliability-Based Preventive Maintenance Strategy of Truck Unloading Systems

2020 ◽  
Vol 10 (19) ◽  
pp. 6957
Author(s):  
Awsan Mohammed ◽  
Ahmed Ghaithan ◽  
Mashel Al-Saleh ◽  
Khalaf Al-Ofi
Keyword(s):  
System Reliability ◽  
Preventive Maintenance ◽  
Failure Modes ◽  
Reliability Function ◽  
Petroleum Products ◽  
Maintenance Strategy ◽  
Mean Time Between Failures ◽  
Time Period ◽  
Critical Components ◽  
One Year

The unloading of petroleum products is a complex and potentially dangerous operation since the unloading system contains complex interdependency components. Any failures in one of its components lead to a cut in the petroleum supply chain. Therefore, it is important to assess and evaluate the reliability of the unloading system in order to improve its availability. In this context, this paper presents the operation philosophy of the truck unloading system, failure modes of the components within the system, and a bottom-up approach to analyze the reliability of the system. In addition, it provides reliability data, such as failure rates, and mean time between failures of the system components. Furthermore, the reliability of the whole system was calculated and is presented for different time periods. The critical components, which are major contributors towards the system reliability, were identified. To enhance the system reliability, a reliability-based preventive maintenance strategy for the critical components was implemented. In addition, the preventive maintenance scheduling was identified based on the reliability plots of the unloading system. The best schedule for preventive maintenance of the system was determined based on the reliability function to be every 45 days for maintaining the system reliability above 0.9. Findings reveal that the reliability of the unloading system was significantly improved. For instance, the system reliability at one year improved by 80%, and this ratio increased dramatically as the time period increased.

Risk-Informed Preventive Maintenance Optimization

2004 ◽  
Author(s):  
James K. Liming ◽  
James E. Salter
Keyword(s):  
Asset Management ◽  
Preventive Maintenance ◽  
Human Error ◽  
Failure Modes ◽  
Cost Benefit ◽  
Nuclear Safety ◽  
Target System ◽  
Maintenance Optimization ◽  
Pressurized Water Reactor ◽  
Pressurized Water

Past and ongoing electric generating station owner investments in plant information technology (such as database query applications and other client workstation tools) have made it possible for plant staffs to utilize information contained in the work management systems to quickly link equipment failure modes to related preventative maintenance (PM) activities. A typical pressurized water reactor feedwater (FW) system is applied as the “target system” for examples in this paper. This typical FW system is comprised of approximately 3,800 “tag” or “part number” items which in turn represent about 16,300 failure modes. Effective risk-informed asset management (RIAM) of FW preventive maintenance (PM) activities requires these failure modes to be modeled in a plant availability model. In this paper we present development of a process for supporting PM optimization, applying cost-benefit-risk analysis and RIAM tools and techniques. In this preventive maintenance optimization (PMO) process, PM activities are evaluated for their projected impacts on plant profitability and nuclear safety. PM activities (PMs) are “optimized” for desirable impact to help ensure electric utilities maintain or improve upon high levels of nuclear safety and profitability. In this PMO application the level of detail of the target system(s) is enhanced to support plant decision-making at the component failure mode and human error mode level of indenture. Results of case studies in FW system PMO using typical plant data are presented.

First Cost-Savings Step: Critical Equipment Selection

2006 ◽  
Author(s):  
J. K. August ◽  
Ed Dundon ◽  
Krishna Vasudevan ◽  
Wayne H. Magninie
Keyword(s):  
Preventive Maintenance ◽  
Failure Modes ◽  
Cost Savings ◽  
Maintenance Management ◽  
Equipment Selection ◽  
Multiple Systems ◽  
Functional Failure ◽  
Computerized Maintenance Management System ◽  
Complex Equipment ◽  
Selection For

The typical plant Computerized Maintenance Management System (CMMS) holds several thousand components tags, although nuclear units may exceed 100,000. “Critical equipment” simplifies equipment selection for PM assessment and prioritizes corrective maintenance. However, critical equipment holds subtle meaning. Complex equipment, multiple failure modes, and multiple systems functional failure effects, can diminish critical equipment value. Applied to failure-preventing tasks, critical terminology should support performance-based preventive maintenance plans. Identifying critical equipment is only the start.

Criticality-based reliability-centered maintenance for healthcare

2019 ◽  
Vol 26 (2) ◽  
pp. 311-334
Author(s):  
Abdulrahim Shamayleh ◽  
Mahmoud Awad ◽  
Aidah Omar Abdulla
Keyword(s):  
United Arab Emirates ◽  
Preventive Maintenance ◽  
Medical Equipment ◽  
Current Practice ◽  
Failure Modes ◽  
Healthcare Management ◽  
Failure Rates ◽  
Opportunity Identification ◽  
Content Type ◽  
Reliability Centered Maintenance

Purpose Medical technologies and assets are one of the main drivers of increasing healthcare cost. The rising number and complexity of medical equipment have forced hospitals to set up and regulate medical equipment management programs to ensure critical devices are safe and reliable. The purpose of this paper is to gain insights into maintenance management-related activities for medical equipment. The paper proposes applying a tailored reliability-centered maintenance (RCM) approach for maintenance activities selection for medical equipment. Such approach will support assets management teams in enhancing operation, decrease risk and cost, and ultimately improve health of patients served by these equipment. Design/methodology/approach The traditional RCM approach will be used with a focus on criticality reduction. By criticality, the authors refer to the severity of failures and occurrence. The proposed method relies on the use of reliability growth analysis for opportunity identification followed by a thorough failure mode and effect analysis to investigate major failure modes and propose ways to reduce criticality. The effectiveness of the proposed method will be demonstrated using a case of one of the leading obstetric and gynecological hospitals in United Arab Emirates and in the Gulf Cooperation Council region. Findings The case examines the relationship between the current practice of planned preventive maintenance and the failure rates of the equipment during its life span. Although a rigorous preventive maintenance program is implemented in the hospital under study, some critical equipment show an increasing failure rates. The analysis highlights the inability of traditional time-driven preventive maintenance alone in preventing failures. Thus, a systematic RCM approach focused on criticality is more beneficial and more time and cost effective than traditional time-driven preventive maintenance practices. Practical implications The study highlights the need for utilizing RCM approach with criticality as the most important prioritization criterion in healthcare. A proper RCM implementation will decrease criticality and minimize the risk of failure, accidents and possible loss of life. In addition to that, it will increase the availability of equipment, and reduce cost and time. Originality/value This paper proposes a maintenance methodology that can help healthcare management to improve availability and decrease the risk of critical medical equipment failures. Current practices in healthcare facilities have difficulty identifying the optimal maintenance strategy. Literature focused on medical maintenance approach selection is rather limited, and this paper will help in this discussion. In addition to that, the Association for the Advancement of Medical Instrumentation supports the initiative of adopting RCM on a large scale in healthcare. Therefore, this paper address the gap in the literature for medical equipment maintenance and the work is in line with the recommendation of leading healthcare association. The paper also presents statistical review of the total number of received maintenance work orders during one full year in the hospital under study. The analysis supports the need for more research to examine current practice and propose more effective maintenance approaches.

scholarly journals Penentuan Interval Waktu Preventive Maintenance Pada Nail Making Machine Dengan Menggunakan Metode Reliability Centered Maintenance (RCM) II

2019 ◽  
Vol 2 (2) ◽  
pp. 49
Author(s):  
Muhammad Arizki Zainul Ramadhan ◽  
Tedjo Sukmono
Keyword(s):  
Preventive Maintenance ◽  
Failure Modes ◽  
Engine Performance ◽  
High Technology ◽  
Time Interval ◽  
Machine Maintenance ◽  
Reliability Centered Maintenance ◽  
The Hours ◽  
Motor Component ◽  
Maintenance Activities

With the increasing needs of productivity and the use of high technology in the form of machines and production facilities, the need for maintenance functions is growing. At PT. Surabaya Wire that produces nails and wires of problems that arise especially related to damage to nail making machine, it causes the hours to stop (downtime) and delay in the production process so that the engine performance becomes less effective. The purpose of the research is to determine the time interval schedule of care and know the action or maintenance activities to be done. To solve the problem in this research using Reliability Centered Maintenance (RCM) II method with Failure Modes and Effect Analyze (FMEA) calculation. RCM II defined a process used to determine what should be done for machine maintenance, whereas for FMEA it is defined as a method to identify the highest failure form on any machine malfunction. From the calculation result using FMEA and RCM II, we got treatment interval result on side shaft component (metal handlebar) with maintenance interval for 63 hours, for crank shaft component (metal road) with maintenance interval for 81 hours, and for Electric motor component with maintenance interval for 374 hours.

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