Introduction

Framework for predictive maintenance and reliability-centered maintenance (RCM)– both are used to enhance asset performance and processes in industrial industries.

These strategies are highly successful in terms of lengthening equipment lifespans, improving dependability, and maximizing savings. Though both concepts entail pre-scheduling work orders based on consumption, time, or performance factors, they are not synonymous. For example, predictive maintenance (PdM) is a maintenance strategy that involves asset performance monitoring to track the performance and condition of equipment during regular operation, aiming to decrease the chance of failures. In contrast, RCM is a maintenance plan that integrates several forms of maintenance to maximize efficiency.

Both have the same overarching goal: to maximize asset dependability and longevity by instituting a maintenance system of planned labor. Except for jobs designated for run-to-failure maintenance, both typically plan and schedule maintenance work in advance. Maintenance chores are then executed according to a specified schedule, which may be triggered by time, consumption, or performance. This article will look through the differences and learn more about these techniques.

What is RCM?

RCM is a method that guarantees maintenance chores are completed in an efficient, cost-effective, dependable, and safe way. Maintenance tasks might be preventative, predictive, or entail nondestructive examinations to detect and monitor defects. RCM is one component of a comprehensive asset integrity management program from cradle to grave. Similarly, a successful RCM program will record the complete process for every asset in the facility throughout the system, equipment, or component life-cycle. RCM aims to guarantee that maintenance and inspection duties are focussed on enhancing equipment dependability and safety.

RCM’s core sense is best understood by examining its root words:

  • Reliability is the capacity to operate well continually.
  • Maintenance is the process of ensuring that assets continue to work as intended.

In essence, Reliability-Centered Maintenance (RCM) provides a pathway for analyzing and acting on the core causes of equipment failures—inefficiencies in technology, culture, design, and maintenance strategy—in pursuit of affordable asset reliability.

Naturally, downtime is unavoidable when working with complicated gear. On the other hand, top-tier firms implement RCM processes to avoid unexpected breakdowns that need lengthy maintenance, costly outsourcing, and lost production time.

What is predictive Maintenance?

Predictive maintenance, also known as condition-based maintenance, includes monitoring performance and equipment conditions during ordinary operations to lessen the likelihood of a breakdown. Manufacturers first used predictive maintenance in the 1990s. The primary purpose of predictive maintenance is to forecast equipment breakdowns based on specific metrics and circumstances. When an analysis is foreseen, manufacturers take the necessary precautions to prevent it through corrective or regular maintenance.

Predictive maintenance anticipates issues using historical and real-time data from many sections of your business. Predictive maintenance considers three significant aspects of your organization:

  • Monitoring of asset condition and performance in real-time
  • Data analysis on job orders
  • Inventory usage benchmarking

What are the steps to implement RCM?

The following questions should be asked before beginning the RCM analysis:

  • What is the piece of equipment’s usual operating and performance standards?
  • How does the piece of equipment fail to satisfy these requirements?
  • What are the reasons?
  • What are the practical implications?
  • How may these failures be avoided?
  • What steps may be made to compensate for the lack of a proactive solution?

Following the investigation of these problems, the deployment of a reliability-centered maintenance method consists of seven significant steps:

  • System selection and data collecting
  • The limits of the system are defined.
  • System description, functional scheme
  • Functional failures and system functions are defined.
  • Analysis of Failure Modes and Effects
  • Making a reasonable decision tree to prioritize the function’s demands based on failure modes (see below)
  • Preventive maintenance job selection that is relevant, applicable, and effective.

What are the steps to implement Predictive maintenance?

Creating a predictive maintenance program typically consists of the following steps:

First, management and information technology teams identify vital and valuable assets. They document their optimal performance, including the range of intended values for certain characteristics, such as the location of wind turbine blades under specific weather situations. This data offers baseline measurements for an asset’s planned operation.

Second, each asset’s information is entered into a CMMS database. Historical asset maintenance records, insights from maintenance and operational workers, and manufacturer equipment information give useful insights into probable failure mechanisms.

Third, system analysts employ failure mode and effects analysis (FMEA) to determine the potential causes of system component failure, the likelihood of failure (from highly probable to unlikely), and the possible repercussions (from risk to life to slight equipment damage). These rankings are used to prioritize work orders.

Fourth, technicians set up condition-monitoring devices such as sensors and PLCs.

Fifth, data scientists develop prediction algorithms to compare an asset’s real-time behavior and status to its baseline functioning. Collecting sensor data, preprocessing it into a format from which useful condition indicators for a specific support can be extracted, injecting condition indicators into an ML model, and finally deploying the algorithm, initially to pilot investments to test the algorithm, is the workflow involved in creating a predictive algorithm.

Sixth, automated remedial activities and technician instructions are developed in response to notifications concerning potential component failures.

What are the benefits of RCM?

  1. To address the primary causes of equipment failure, reliability-centered maintenance may be utilized to develop a more cost-effective maintenance approach.
  2. It is a more creative way to develop a routine maintenance schedule comprised of more cost-effective chores designed to protect critical operations.
  3. It focuses on better using scarce economic resources on objects that would cause the most disruption if they failed while also improving asset performance and lowering asset downtime.
  4. It reduces the amount of maintenance necessary. This reduces the amount of money the asset owner must pay a maintenance provider and increases asset production.

What are the benefits of Predictive maintenance?

  1. The benefits of predictive maintenance are enormous in terms of cost savings and include avoiding planned downtime.
  2. It aids in enhancing equipment longevity, as well as improving staff productivity and income.
  3. Another benefit of predictive maintenance is its capacity to alter both a maintenance team and an organization since deploying PdM enables asset managers to enhance outcomes, identify impending failure, and better balance priorities like profitability and dependability.

Final Words

Because the final result of a well-executed RCM analysis is selecting an appropriate maintenance strategy for each piece of equipment, the impact is an overall increase in dependability. By using RCM procedures, you may avoid the one-size-fits-all mentality that can waste critical time and money. Again, predictive maintenance (PdM) is a sort of condition-based maintenance that uses sensor devices to monitor the status of assets. You now have a thorough understanding of the maintenance strategies. Contact us to improve plant operations.

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Blog: Condition-Based Maintenance vs Predictive Maintenance