Reliability Centered Maintenance Program Research Articles

Evaluating the Effectiveness of Reliability-Centered Maintenance Programs in Food and Beverage Manufacturing Facilities; A Review.

While reliability-centered maintenance (RCM) boasts widespread success across industries, its efficacy within the complex environment of food and beverage manufacturing remains unclear. This study addresses this gap by analyzing the implementation and outcomes of an RCM program at a representative facility. Leveraging quantitative data, the research demonstrates the program’s transformative impact, including significant reductions in downtime, improved asset reliability, and substantial cost savings. Beyond these metrics, the study delves into the practical challenges encountered during RCM adoption and offers actionable solutions for potential implementers. This research extends beyond its case study, aiming to serve as a catalyst for broader industry adoption. By highlighting the tangible benefits and practical considerations of RCM in a food and beverage context, the study empowers manufacturers to unlock its potential, paving the way for enhanced food safety, optimized production flows, and a more resilient and competitive sector.

Automatic identification of maintenance significant items in reliability centered maintenance analysis by using functional modeling and reasoning

Complex industrial systems adopt reliability centered maintenance (RCM) for maintenance optimization to improve safety and reduce maintenance cost. Preserving function is the core maintenance principle, yet the function concept has not been systematically studied in the context of RCM. This article presents a framework of model-based RCM analysis, which is driven by functional modeling and reasoning. The study focuses on identifying the so-called maintenance significant items through assessment of failure consequences. Multilevel flow modeling (MFM) is proved competitive to identify sufficient system functions that expect maintenance to preserve. It is also able to define failure modes and represent their interactions with system functions, which are essential to RCM. A failure analysis tool for RCM is developed by taking advantage of the causal reasoning capability of MFM, which can be used to automatically analyze consequences of all failures predefined for a target system and generate equipment classifications useful to maintenance optimization. The study provides the possibility of RCM automation, which has been highly demanded by various complex industries. Moreover, as a fundamental functional knowledge framework, MFM can easily accommodate changes in design and operation, which affords the opportunity of implementing a living RCM program.

A budget allocation and programming-based RCM approach to improve the reliability of power distribution networks

Reliability-centered maintenance (RCM) has recently emerged as a powerful tool to reasonably cut the operation and maintenance cost of power destruction systems, whilst meeting both power quality and reliability requirements. This study introduces a new RMC approach that allocates maintenance budgets based on component criticality and importance. A new diagnostic importance factor, implemented based on the criticality and importance of each component, is introduced as a new index for prioritizing components for maintenance activities and budget allocation. The process of budget allocation is carried out without using any optimization method and just by multiplying the maintenance budget by this newly designed factor. A multi-attribute decision-making technique (MAXIMAX) is considered to find the appropriate weighting coefficient of failure causes to reduce the effect of human dependency in the modeling failure rate of each component. Based on the priority and amount of budget allocated, a reliability-centered maintenance program for the sample distribution system is designed and implemented. The proposed RMC framework was implemented to a part of a distribution network in Iran to highlight its effectiveness and practicality. The obtained results showed an improvement in reliability indexes, which in turn confirms that prioritizing component criticality in budget allocation and maintenance programming enables reaching the reliability goals. Improvement in reliability indexes leads to maintenance cost reduction in future time intervals and efficient management of limited resources. A further comparison analysis with other approaches have shown that the proposed framework outperforms these methods in terms of speed, accuracy and budget allocation.

IMPROVE THE OPERATING PERFORMANCE OF SEA WATER SYSTEM IN MED/TCD UNIT IN EGYPT USINGSIX SIGMA METHOD

The purpose of this paper is to establish a maintenance program for the sea water System as a critical part from Desalination Unit type (MED/TCD), to satisfy all requirements needed as the main supplier for most of the systems in the desalination unit, improve the performance of desalination unit, and increase the life time of its components. The methodology/approach – by applying the scientific method (four step method) plus the PDCA cycle, it means we apply the Six Sigma philosophy. To improve the performance of the multi effects Desalination unit and increase the operational lifetime, we will work on one of the critical system in the MED/TCD unit (Sea Water System SWS) establishing maintenance program using the Six Sigma philosophy, define, measure, analyze, improve, and control (DMAIC) method for problem-solving methodology in MED/TCD Unit, to increase the Reliability and Availability of the MED/TCD Unit and increase the unit lifetime. Keywords: Six Sigma, Multi Effect Desalination, Sea Water System, Reliability Centered Maintenance, Plan-Do-Check-Act Cycle, Reliability, Availability. Abbreviations:- SWS Sea Water System. PDCA plan – Do – Check – Act Cycle. MED Multi Effect Desalination. MED/TCD Multi Effect Desalination/ Thermo-compression Desalination. DMAIC Define – Measure – Analysis – Improve – Control Cycle. RCM Reliability Centered Maintenance. PMP Preventive Maintenance Program. IMS Integrated Management System. DPMO Defects Per Million Opportunity. DOE Design Of Experiment . DFSS Design For Six Sigma. PHE Plate Heat Exchanger. SIPOC Supplier, Inputs, Process, Outputs, and Customers . CTQ Critical To Quality. ANOVA Analysis Of Varience. DPU Defects Per Unit. RCMP Reliability Centered Maintenance Program.

Reliability and Cost Model of P.M. in A Component of an Electrical Distribution System Considering Ageing Mechanism

Application of Reliability Centered Maintenance (RCM) in a system results in a decrease in component failure rates and as such improvement in the system reliability. One of the major subjects of the RCM is focused on the Online and Offline Preventive Maintenance (OPM and FPM which together will be denoted by OFPM) of the components which repairing the component needs or doesn’t need to stop the mission carrying out by it. The RCM is classified as a preventive maintenance policy and has significant contribution in practical applications. However, little research has been devoted to modeling the online and offline Preventive Maintenance. This research assumes that the component failure rate will be improved if the OFPM is performed for a long period of time as a part of an RCM program. Application of an OFPM program could cause the component set at least to “as bad as old state but cannot reach the “as good as new” state. The emphasis of this research is to model the OFPM for critical components or any equipment with critical failure in a system. The proposed model is based on the concept of PM and improvement factor of reliability in a system with critical components which their failure could cause a failure in the system (first-order cut- sets). DOI: http://dx.doi.org/10.11591/ijece.v4i2.5514

Advanced progressive real coded genetic algorithm for nuclear system availability optimization through preventive maintenance scheduling

One of the main goals of reliability-centered maintenance programs is to find optimal maintenance strategies. Availability of emergency systems through preventive maintenance scheduling has an important role in Probabilistic Safety Analysis (PSA). Preventive maintenances can be replaced with reloading time maintenance and reduce unavailability of the system, especially in the last days of reload cycle. Of course, the emergency core cooling systems connect to circuit in accidents and control the intensity of the unavailability. For reducing unavailability of standby emergency systems, preventive maintenance scheduling method is offered. In this paper, an Advanced Progressive Real Coded Genetic Algorithm (APRCGA) is applied to optimize the availability of standby systems with preventive maintenance scheduling. Using APRCGA in nuclear maintenance systems and considering appropriate objective functions, the most suitable conditions are obtained. The preventive maintenance scheduling keeps unavailability of systems within safe and reliable conditions. In order to demonstrate the effectiveness of the proposed method, it is applied for two nuclear power plant emergency systems. First, for the nuclear emergency core cooling system of a two-loop pressurized water reactor, most available maintenance scheduling is presented. In the second case, for a four-loop pressurized water reactor, the maintenance scheduling for emergency core cooling system is proposed. The results are compared with those obtained by some standard maintenance policies, and previously published papers.

Coast Guard Reliability‐Centered Maintenance

AbstractSince 2001, the Coast Guard's surface fleet has had a condition‐based maintenance (CBM) policy. The reliability‐centered maintenance (RCM) process is used to implement the policy by identifying minimum system maintenance requirements. The Coast Guard's RCM program provides the standards and capabilities needed to develop preventive maintenance systems that satisfy operational requirements. RCM requirements are based on the industry standard SAE JA‐1011, which provides evaluation criteria for RCM processes. Department of Defense (DoD) data‐deliverable specifications, training programs, continuous improvement functions, information system requirements, and condition assessment programs complete the Coast Guard's RCM program. This paper discusses the genesis of the Coast Guard surface fleet's RCM program, how it is managed, and the benefits that it provides.