When working for Petrobras at PRSI (Pasadena Refining System Inc.) I had this opportunity to share my experience as a Maintenance Manager in Brazil with PRSI operators and maintenance crew.
Introduction to Reliability Centered MaintenanceDibyendu De
Introduces Reliability Centered Maintenance, strategies employed, formulation of effective maintenance plan, reduction of consequences of failures and failure rate.
Reliability Centered Maintenance Implementation and Case StudyWaseem Akram
This is the presentation based on final year project which deals with the implementation of "Reliability Centered Maintenance and Contribution of Quality Management System". A case study analysis has also been attached in this presentation.
Introduction to Reliability Centered MaintenanceDibyendu De
Introduces Reliability Centered Maintenance, strategies employed, formulation of effective maintenance plan, reduction of consequences of failures and failure rate.
Reliability Centered Maintenance Implementation and Case StudyWaseem Akram
This is the presentation based on final year project which deals with the implementation of "Reliability Centered Maintenance and Contribution of Quality Management System". A case study analysis has also been attached in this presentation.
Maintenance Planning and Scheduling are key elements that influence the true success of any organization. Many times we have a planner or planner/scheduler, but do not know how to use him or her effectively or efficiently.
This presentation outlines the processes and benefits of applying enhanced maintenance planning techniques such as Reliability Centred Maintenance at your place of work. Please go to www.simenergy.co.uk for more information.
Reliability Centered Maintenance (RCM) and Total Productive Maintenance (TPM)...Flevy.com Best Practices
More Information:
https://flevy.com/browse/business-document/reliability-centered-maintenance-rcm-and-total-productive-maintenance-tpm--2-day-presentation-1081
BENEFITS OF DOCUMENT
Improve reliability of plant & equipment
Measure the machine performance losses and understand better
Introduce autonomous maintenance
DOCUMENT DESCRIPTION
Reliability Centered Maintenance and Total Productive Maintenance presentation is intended to help as a 2-day workshop material for Operations and Maintenance personnel.
This presentation consists of over 200 slides and comprises of the following:
Group Activity - Define Maintenance Excellence
Maintenance Excellence - Activity
What is RCM?
Objective & goal of RCM
Techniques employed by RCM
Primary RCM Principles
Types of Maintenance Tasks
RCM Considerations, Applicability + Benefits
Steps in RCM Implementation
TPM vision, definition, origins, principles
8 Pillars of TPM
TPM Self-Assessment
Autonomous maintenance
Equipment & Process Improvement
Equipment Losses, Manpower & Material Losses
OEE - what it is & Calculations
Activity OEE Calculation
Other pillars of TPM
TPM Implementation - 12 steps
Benefits & OEE Tracker
Proactive Maintenance Analysis
Liaison with Ops, Communicating OEE,
Group Activity - OEE Communication/Importance
Ops. Skills, Cleanliness,
Monitoring - Gauges, Lubrication, Contamination, Vibration, One point Lesson
Activity - Maintenance / Operations
Analysis of Maintenance History, MTBF and its calculation
Activity - MTBF Calculation
Improving Equipment performance
FMEA, Types, Calculating RPN
Maintenance Planning and Scheduling are key elements that influence the true success of any organization. Many times we have a planner or planner/scheduler, but do not know how to use him or her effectively or efficiently.
This presentation outlines the processes and benefits of applying enhanced maintenance planning techniques such as Reliability Centred Maintenance at your place of work. Please go to www.simenergy.co.uk for more information.
Reliability Centered Maintenance (RCM) and Total Productive Maintenance (TPM)...Flevy.com Best Practices
More Information:
https://flevy.com/browse/business-document/reliability-centered-maintenance-rcm-and-total-productive-maintenance-tpm--2-day-presentation-1081
BENEFITS OF DOCUMENT
Improve reliability of plant & equipment
Measure the machine performance losses and understand better
Introduce autonomous maintenance
DOCUMENT DESCRIPTION
Reliability Centered Maintenance and Total Productive Maintenance presentation is intended to help as a 2-day workshop material for Operations and Maintenance personnel.
This presentation consists of over 200 slides and comprises of the following:
Group Activity - Define Maintenance Excellence
Maintenance Excellence - Activity
What is RCM?
Objective & goal of RCM
Techniques employed by RCM
Primary RCM Principles
Types of Maintenance Tasks
RCM Considerations, Applicability + Benefits
Steps in RCM Implementation
TPM vision, definition, origins, principles
8 Pillars of TPM
TPM Self-Assessment
Autonomous maintenance
Equipment & Process Improvement
Equipment Losses, Manpower & Material Losses
OEE - what it is & Calculations
Activity OEE Calculation
Other pillars of TPM
TPM Implementation - 12 steps
Benefits & OEE Tracker
Proactive Maintenance Analysis
Liaison with Ops, Communicating OEE,
Group Activity - OEE Communication/Importance
Ops. Skills, Cleanliness,
Monitoring - Gauges, Lubrication, Contamination, Vibration, One point Lesson
Activity - Maintenance / Operations
Analysis of Maintenance History, MTBF and its calculation
Activity - MTBF Calculation
Improving Equipment performance
FMEA, Types, Calculating RPN
Failure mode and effects analysis (FMEA)—also "failure modes", plural, in many publications—was one of the first highly structured, systematic techniques for failure analysis. It was developed by reliability engineers in the late 1950s to study problems that might arise from malfunctions of military systems. An FMEA is often the first step of a system reliability study. It involves reviewing as many components, assemblies, and subsystems as possible to identify failure modes, and their causes and effects. For each component, the failure modes and their resulting effects on the rest of the system are recorded in a specific FMEA worksheet. There are numerous variations of such worksheets. An FMEA can be a qualitative analysis.
The ultimate guide on constructing a FMEA process for Manufacturing, Maintenance, Services and Design.
The presentation include step by step on how to determine the failure modes, failure effects, assign severity, assign occurrence, assign detection, calculate risk priority numbers and prioritize the RPNs for action. With some examples and illustrations.
Presentation contents:
1. Determing failure modes, effects and causes.
2. FMEA team & team leader.
3. Brainstorming.
4. The basic steps of FMEA.
5. Examples.
Total Quality Managment - TPM - final year B.E.cs - Presented by DR. K. BARANIDHARAN, SAIRAM INSTITUTE OF MANAGMENT STUDIES (sims) SRI SAI RAM INSTITUTE OF TECHNILIGY (sit) CHENNAI
This presentation provides a nice introduction to Failure Mode, Effects and Criticality Analysis (FMECA). Includes history and background, definitions, timelines for implementing and describes the FMEA methodology.
TPM is for improving productivity by making processes more reliable and less wasteful. To achieve this objective, preventive and predictive maintenance is adopted. The objective of TPM is to maintain the plant or equipment in good condition.
Advanced Maintenance Strategy Workshop by TetrahedronSagar Sangam Sahu
Developing a World-Class Maintenance Practice is one step towards Business Excellence. Advanced Maintenance Strategy can help you to maintain core disciplines, drive improvement, identify best practices, and develop a maintenance organization, effective failure management and program development.
TPM Total Productive Maintenance Workshop for Quarry Plant (1) 09Oct16Timothy Wooi
This course will guide you through to assess the activities of Autonomous Maintenance (AM) on your current Equipment and to plan the execution of your Maintenance Activities using a Visual Schedule. TPM defines your Maintenance schedule and Goals. TPM helps you plan and develop the optimal program for your facility, resulting in increased efficiencies and cost savings.
Day1
Introduction to TPM
Types of Maintenance
Overall Equipment Efficiency ( OEE )
The Pillars of TPM (Part 1)
The 6 Major Equipment waste
Day2
Steps in Introduction of TPM
The 5’S Step towards TPM
Conditions Required for TPM
TPM Strategy
TPM Tools
Set-back of TPM Implementation
Course Evaluation, Recap and Closing
Availability performance testing with Application Insights.John Pourdanis
Availability-Performance testing to any website all over the world.
Learn how to set up web tests to different regions all over the world using Application Insights. Discover how to set alerts if a website becomes unavailable or responds slowly.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
2. Evolution of Maintenance
At the very beginning, Maintenance was an appendix
to Operations / Production:
It existed only to fix failures, when they happened.
These were the days of absolute
Corrective Maintenance
3. Evolution of Maintenance
As times went by, it was detected that many failures
have an almost regular pattern, failing after an
average period. Therefore, one could choose regular
intervals to fix the equipment BEFORE the failure:
Preventive Maintenance
Also know as Time Based Maintenance.
4. Evolution of Maintenance
However, very often these failures happen in irregular
periods. To avoid an unwanted failure, the periods of
Preventive Maintenance are shortened. If equipment
conditions were known, the maintenance could be later.
Technology development enabled to identify failure
symptoms:
Predictive Maintenance
Also know as Condition Based Maintenance.
5. Evolution of Maintenance
Many pieces of equipment have sporadic activity (alarms,
stand-by equipments, etc.). However, we must be sure that
they are ready to run. These are "hidden faults“. Detect and
prevent hidden failure is called:
Detective Maintenance
6. Evolution of Maintenance
The different failure modes mean that there’s not
one only approach, about Corrective, Preventive or
Predictive Maintenance Programs.
The correct balance will give in return better
equipment reliability, thus the name:
Reliability Centered Maintenance
Take it easy,
Remember, my grandma, not
kid, Prevention always!
is better than
Cure....
7. Reliability Centered Maintenance (RCM)
John Moubray 1949-2004
After graduating as a mechanical engineer in 1971, John Moubray worked
for two years as a maintenance planner in a packaging plant and for one
year as a commercial field engineer for a major oil company.
In 1974, he joined a large multi-disciplinary management consulting
company. He worked for this company for twelve years, specializing in the
development and implementation of manual and computerized
maintenance management systems for a wide variety of clients in the
mining, manufacturing and electric utility sectors.
He began working on RCM in 1981, and since 1986 was
full time dedicated to RCM, founding Aladon LCC, which
he led until his premature death in 2004.
John Moubray is today considered a synonym of RCM.
8. Reliability Centered Maintenance (RCM)
Its origins
What about a failure rate of 0.00006/event?
Quite good, no?
This was the average failure rate in commercial flights
takeoffs, in the 50’s. Two thirds of them caused by
equipment failures.
Today, this would mean 2 accidents per day, with
planes with more than 100 passengers!!!
That’s why Reliability Centered Maintenance has begun
in the Aeronautical Engineering. Pretty soon, Nuclear
activities, Military, Oil & Gas industries also began to
use RCM concepts and implement them in their
facilities.
9. Reliability Centered Maintenance (RCM)
Reliability and Availability
Reliability
Reliability is a broad term that focuses on the ability of a product
to perform its intended function. Mathematically speaking,
reliability can be defined as the probability that an item will
continue to perform its intended function without failure for a
specified period of time under stated conditions.
Reliability is a performance expectation.
It’s usually defined at design.
Availability
Depends upon Operation uptime and Operating cycle.
Availability is a performance result.
Equipment history will tell us the availability.
Bibliography: Kardec, Alan y Nascif, Julio - Manutenção- Função Estratégica, Editora Qualitymark
10. Reliability Centered Maintenance (RCM)
Reliability and Availability
MTBF = Mean Time Between Failures
MTTR = Mean Time To Repair
A first definition:
MTBF
Availability =
MTBF + MTTR
Bibliography: Kardec, Alan y Nascif, Julio - Manutenção- Função Estratégica, Editora Qualitymark
11. Reliability Centered Maintenance (RCM)
Availability definitions
MTBF = Mean Time Between Failures
MTTR = Mean Time To Repair
MTBM = Mean Time Between Maintenance actions
M = Maintenance Mean Downtime (including preventive
and planned corrective downtime)
Inherent Availability: consider only corrective downtime
Achieved Availability: consider corrective and preventive
maintenance
Operational Availability: ratio of the system uptime and total
time
MTBF
Inherent Availability =
MTBF + MTTR
MTBM
Achieved Availability =
MTBM + M
Uptime
Operational Availability =
Operation Cycle
12. Reliability Centered Maintenance (RCM)
Reliability and Availability
250 days 360 days 200 days 120 days = 947 days
Downtime 9d 6 2
MTBF = (250 + 360 + 200 + 120) / 4 = 232.5 days
MTTR = (9 + 6 + 2) / 3 = 5.67 days
Availability = 232.5 / (232.5 + 5.67) = 97.62 %
180 days 400 days 120 days 233 days = 947 days
Downtime 7 4 3
MTBF = (180 + 400 + 120 + 233) / 4 = 233.25 days
MTTR = (7 + 4 + 3) / 3 = 4.67 days
Availability = 233.25 / (233.25 + 4.67) = 98.04 %
13. Reliability Centered Maintenance (RCM)
Reliability and Availability
Achieved Availability↑ = MTBM↑/ (MTBM+M↓)
To improve Availability:
Improve MTBM:
•Reduce Preventive Programs to a minimum, or, have Preventive intervals as well
defined as possible.
•Using Predictive techniques whenever possible
•Implementing Maintenance Engineering (RCM, TPM...)
Minimize M:
•Implementing Maintenance Engineering (Planning, Logistics...)
•Improving personnel technical skills (training)
•Developing Integrated Planning (Mntce+Ops+HSE+Inspection+...)
Bibliography: Kardec, Alan y Nascif, Julio - Manutenção- Função Estratégica, Editora Qualitymark
14. Reliability Centered Maintenance (RCM)
Improving Productivity
Productivity Improvement Factors:
Detailed work planning
Delivering equipments to Maintenance as clean as possible
Check-list at the end of Maintenance activities
Complete and comprehensive Equipment data available
Supplies available on job site
Skilled personnel
Bibliography: Kardec, Alan y Nascif, Julio - Manutenção- Função Estratégica, Editora Qualitymark
16. Reliability Centered Maintenance (RCM)
Translating percents to daily routine...
Availability % Downtime per year Downtime per month* Downtime per week
90% 36.5 days 72 hours 16.8 hours
95% 18.25 days 36 hours 8.4 hours
98% 7.30 days 14.4 hours 3.36 hours
99% 3.65 days 7.20 hours 1.68 hours
99.5% 1.83 days 3.60 hours 50.4 min
99.8% 17.52 hours 86.23 min 20.16 min
99.9% ("three nines") 8.76 hours 43.2 min 10.1 min
99.95% 4.38 hours 21.56 min 5.04 min
99.99% ("four nines") 52.6 min 4.32 min 1.01 min
99.999% ("five nines") 5.26 min 25.9 s 6.05 s
99.9999% ("six nines") 31.5 s 2.59 s 0.605 s
17. Reliability Centered Maintenance (RCM)
Maintenance Programs costs
Maintenance Program Cost US$/HP/year
Corrective (unplanned) 17 to 18
Preventive 11 to 13
Predictive / Planned Corrective 7 to 9
NMW Chicago
19. Reliability Centered Maintenance (RCM)
Definitions
Failure rate (λ)
Failure rate (λ) is defined as the reciprocal of MTBF:
1
λ (t ) =
MTBF
Reliability: R(t)
Let P(t) be the probability of failure between 0 and t; reliability is defined as:
R(t) = 1 – P(t)
Bibliography: Lafraia, João Ricardo - Manual de Confiabilidade, Mantenabilidade e Disponibilidade, Editora Qualitymark
20. Reliability Centered Maintenance (RCM)
Some math...
Considering rate failure (λ) constant, it is proven (check at www.weibull.com),
that R(t), meaning the probability of having operated until instant t, is given by:
− λt
R (t ) = e
This reinforces the idea that Reliability is function of time, it isn’t a definite
number. So, it’s incorrect to affirm: “This equipment has a 0.97 reliability
factor...”. We should rather say: “This equipment has 97% reliability for
running, let’s say, 240 days...”
21. Reliability Centered Maintenance (RCM)
Tricks and tips...
Historically, an equipment has 4 failures per year. Which is the
reliability of this equipment for a 100 days run?
λ =4/365 λ =0.011/day R(100) = e-0.011x100 = e-1.1 = 0.333 = 33.3%
The probability of having no failure until 100 days is 33.3%
Some upgrades have been made, so failure rate now is 2 per year
(meaning that MTBF has doubled). Which is the reliability for a 100
days run?
λ =2/365 λ =0.0055/day R(100) = e-0.0055x100 = e-0.55 = 0.577 = 57.7%
The probability of having no failure until 100 days is 57.7%.
As seen, doubling MTBF doesn’t double reliability.
22. Reliability Centered Maintenance (RCM)
Trick and tips...
Historically, an equipment has a MTBF = 200 days. To improve
10% its reliability to operate on a 100 days run, which percent
should MTBF be improved?
λ =1/200 λ =0.005/day R(100) =e-0.005x100 = e-0.5 = 0.607 = 60.7%
To improve this reliability in 10%, new reliability should be:
R’(100) = 1.1 x 0.607 = 0.668 = e-λ’x100
Ln 0.668 = -λ’ x 100 -0.403 = -λ’ x 100 λ’= 0.00403
1/MTBF’ = 0.0043 MTBF’ = 232 days
232/200 = 1.16 MTBF should improve 16%
23. Reliability Centered Maintenance (RCM)
Trick and tips...
As per the manufacturer, an equipment has a 90%
reliability to run over one year. If you want to have a 95%
confidence that it will not fail, how long should it take
until the equipment undergo a Preventive maintenance or
some predictive technique?
0.9 = e-λx365 ln 0.9 = -λ x 365 -0.1054 = -λ x 365
λ = 2.89 x 10-4/day
0.95 = e-λt ln 0.95 = -λt -0.0513 = - 2.89 x 10-4 x t
t = 177.5 days
For practical purposes, this equipment could be in a
semester preventive / predictive program.
25. Reliability Centered Maintenance (RCM)
System in series
1 2 3
Let P1=5%, P2=10% and P3=20% be the failure probability of each component of
this system, in a certain period. Which is the reliability of this system, in series?
This system will run, provided that ALL its components run. So, their reliabilities
are multiplied.
R1 = 1 – P1 = 1 – 0.05 = 0.95
R2 = 1 – P2 = 1 – 0.10 = 0.90
R3 = 1 – P3 = 1 – 0.20 = 0.80
R = R1 x R2 x R3 = 0.95 x 0.90 x 0.80 = 0.6840 = 68.4%
System failure probability 31.6%
System failure probability is bigger than each individual component. System
reliability is less than each component.
Bibliography: Lafraia, João Ricardo - Manual de Confiabilidade, Mantenabilidade e Disponibilidade, Editora Qualitymark
26. Reliability Centered Maintenance (RCM)
System in parallel
1
2
3
Let P1=5%, P2=10% and P3=20% be the failure probability of each component of this
system, in parallel, in a given period. Which is the reliability of the system, in parallel?
This system will run until ALL components fail. In this case, the failure probabilities
are multiplied.
P = P1 x P2 x P3 = 0.05 x 0.10 x 0.20 = 0.0010
R = 1 – P = 0.999 = 99.9%
System failure probability 0.1%
System failure probability is less than each component. System reliability is bigger
than each component.
Bibliography: Lafraia, João Ricardo - Manual de Confiabilidade, Mantenabilidade e Disponibilidade, Editora Qualitymark
27. Reliability Centered Maintenance (RCM)
Mixed systems
1 2 3
4 5
If P1=10%, P2=5%, P3=15%, P4=2% and P5=20%, which is the system reliability?
123 R1= 1 – 0.10 = 0.90
R2= 1 – 0.05 = 0.95 R123 = 0.9 x 0.95 x 0.85 = 0.7268 P 123= 0.2733
45
R3= 1 - 0.15 = 0.85
R4= 1 – 0.02 = 0.98 R45 = 0.98 x 0.80 = 0.7840 P45= 0.2160
R5= 1 – 0.20 = 0.80
P123= 0.2733 Psystem = 0.2733 x 0.2160 = 0.0590
System
P45= 0.2160 Rsystem = 1 – 0.0590 = 0.941 = 94.1%
28. Reliability Centered Maintenance (RCM)
Redundancy
A The pumps A, B y C are feed pumps of a plant. To
operate in full condition, it’s necessary that at least
B two of these three pumps are running. Failure
probability of each one is 10%. Which is the
reliability to run this plant at full production?
C
Failure probability is P= 0.1 (10%), and reliability is R=1-0.1= 0.9 (90%)
Three pumps in parallel, so:
(R + P)3 = R3 + 3R2P + 3RP2 + P3= 0.93 + 3x0.92x0.1 + 3x0.9x0.12 + 0.13
(R + P)3 = 0.729 + 0.243 + 0.027 + 0.001
Three running: 0.729
Two running and one off: 0.243 Reliability = 0.972 = 97.2 %
One running and two off: 0.027
None running: 0.001 No full production = 0.028 = 2.8 %
29. Reliability Centered Maintenance (RCM)
Redundancy
A The pumps A, B y C are feed pumps of a plant.
Pump A flow rate is 2,000 gpm, pump B flow rate is
B 1,800 gpm and pump C flow rate is 1,700 gpm. To
operate, the plant need at least a feed rate of 3,600
gpm. Reliabilities are: RA=0.95, RB=0.90 and
C RC=0.85. Which is the plant reliability?
As the plant needs at least 3,600 gpm, to supply this, there will be these cases:
A∩B∩C 0.95 x 0.90 x 0.85 = 0.72675
A ∩ B ∩ notC 0.95 x 0.90 x (1 – 0.85) = 0.12825
A ∩ notB ∩ C 0.95 x (1 – 0.90) x 0.85 = 0.08075
Plant reliability = 0.93575 93.6%
32. Reliability Centered Maintenance (RCM)
System and Component Redundancy
A B A B
A’ B’ A’ B’
Component Redundancy System Redundancy
Which of these systems would have a better overall reliability
(let’s assume all components have the same reliability R)?
AA’ and BB’ subsystems’ reliability: AB and A’B’ subsystems’ reliability:
1 - (1-R)2 =1 – 1 + 2R – R2 = 2R – R2 R2
System reliability: System reliability:
R component redundancy = (2R-R2)2 R system redundancy = 1 – (1-R2)2
R system redundancy = 1 – 1 + 2R2-R4
R system redundancy = 2R2 - R4
R comp red - R syst red = (2R-R2)2 - (2R2 - R4) = 4R2 – 4R3 + R4 - 2R2 + R4
R comp red - R syst red = 2R4 – 4R3 + 2R2 = 2R2(R2 – 2R + 1) = 2R2(R-1)2≥ 0
R comp red ≥ R syst red
33. Reliability Centered Maintenance (RCM)
Active and Passive Redundancy
A
B
Active Redundancy: Passive Redundancy:
Both equipment are One equipment is
operating at the same operating, and the other
time, sharing the load. one is at stand-by,
If one fails, the other starting operating after
one will carry the load the failure of the first
alone. one, pending upon a
switch system.
34. Reliability Centered Maintenance (RCM)
Getting closer to real world...
In systems with active redundancy all redundant components are in
operation and are sharing the load with the main component. Upon
failure of one component, the surviving components carry the load,
and as a result, the failure rate of the surviving components may be
increased.
The reliability of an active, shared load, parallel system can be
calculated as follows:
where: λ1 is the failure rate for each unit when both are working and
λ2 is the failure rate of the surviving unit when the other one has
failed.
If 2λ1 = λ2, then:
35. Reliability Centered Maintenance (RCM)
Getting closer to real world...
In a system with active redundancy, reliability of each of the two components for
100 days is R=0.96, when sharing the load. If one compontents fails, the
surviving one will have a 50% increase in its failure rate. Which is it the system
reliability for 100 days?
R(100) = 0.96 = e-λx100 ln 0.96 = -100λ λ1 = 0.00041
λ2 = 1.5 x λ1 = 0.000615
2 × 0.00041
R (100) = e − 2×0.00041x100 +
× e (
− 0.000615 100
×
− e −2×0.00041×100 )
2 × 0.00041 − 0.000615
( )
R (100) = e −0.082 + 4 × e −0.0615 − e −0.082
R (100) = 0.9213 + 4 × (0.9404 − 0.9213)
R (100) = 0.9977
If there were no increase in failure rate, system reliability would be 0.9984. Look
like nothing, but this means a 30.5% decrease in system MTBF!!!
36. Reliability Centered Maintenance (RCM)
Getting closer to real world...
The redundant or back-up components in passive or standby systems start
operating only when one or more fail. The back-up components remain dormant
until needed.
For two identical components (primary and back-up) the formula is:
R(t) = e-λt (1+λt), considering a perfect switch
If the reliability of the switch is less than one, the reliability of the system is
affected by the switching mechanism and is reduced accordingly:
R(t) = e-λt (1+Rswλt), Rsw switch reliability
The reliability of a standby system consisting of one primary component with
constant failure rate λ1 and a backup component with constant failure rate λ2 is
given by:
37. Reliability Centered Maintenance (RCM)
Getting closer to real world...
Two feed pumps in a nuclear power plant are connected in a
stand-by mode. One is active and one is on standby. The
power plant will have to shut down if both feed pumps fail. If
the time between failures of each pump has an exponential
distribution with MTBF = 28,000 hours, and the failure rate of
the switching mechanism λsw is 10-6 what is the probability that
the power plant will not have to shut down due to a pump
failure in 10,000 hours?
R(t) = e-λt (1+Rswλt)
R(t) = e-λt (1+Rswλt),
10−6 ×104 10−2
Switch reliability: Rsw = e =e = e −0.01 = 0.9900
λ = 1/MTBF
−1 ×10000 1
R (10000) = e 28000
× (1 + 0.9900 × ×10000)
28000
R (10000) = e −0.3571 × (1 + 0.3536)
R (10000) = 0.6997 ×1.3536
R (10000) = 0.9471
38. Reliability Centered Maintenance (RCM)
Bathtub Curve
Early Life (Burn-in, infant mortality)
• large number of new component failures which decreases with time
Useful Life
• small number of apparently random failures during working life
(λ constant)
Wear-out
• increasing number of failures with time as components wear out
39. Reliability Centered Maintenance (RCM)
Bathtub Curve
Early Life:
• sub-standard materials
• often caused by poor / variable manufacturing and poor
quality control
• prevented by effective quality control, burn-in, and run-in, de-
bugging techniques
• weak components eventually replaced by good ones
• probabilistic treatment less important
Useful Life:
• random or chance failures
• may be caused by unpredictable sudden stress
accumulations outside and inside of the components beyond
the design strength
• over sufficiently long periods frequency of occurrence (λ) is
approximately constant
• failure rate used extensively in Safety & Reliability analyses
Wear-out period:
• symptom of component ageing
• prediction is important for replacement and maintenance
policy
40. Reliability Centered Maintenance (RCM)
Different bathtub curves
These statistics are from
aeronautical industry. In a
process plant, like a
refinery, do you think the
percent of each one
would be about the
same?
41. Reliability Centered Maintenance (RCM)
Different bathtub curves
Which of these curves
would be applicable to:
A pump?
An electronic instrument?
A tire?
42. Reliability Centered Maintenance (RCM)
Failure modes
Common sense tells that the best way to optimize the availability of plants is to
implement some Preventive maintenance.
Preventive maintenance means fixing or replacing some pieces of equipments and/or
components in fixed intervals. Useful lifespan of equipments may be calculated with
Failure Statistical Analysis, enabling Maintenance Department to implement Preventive
Programs.
This is true for some simple pieces of equipment and components, which may have a
prevailing failure mode. Many components in contact with process fluids have a regular
lifespan, as well as cyclic equipment, due to fatigue and corrosion.
But, for many pieces of equipment there’s no connection between reliability and time.
Furthermore, as seen in Reliability curves, defining the optimum interval for Preventive
maintenance may be a hard task. Besides, fixing or even replacing the equipment may
bring you back to Infant Mortality period...
43. Reliability Centered Maintenance (RCM)
Preventive maintenance may cause failures earlier....
Failures are likely to happen…
Here begins wear-out period.
Let’s define Preventive
maintenance here…
λ
Time
The failure likelihood is earlier!!!!
44. Reliability Centered Maintenance (RCM)
Turnarounds
Turnarounds are often seen by Operations as an unique opportunity to have all
problems solved, all equipment fixed…
Meanwhile, for Maintenance, a Turnaround is a huge event, time & resources & costs
consuming, in which ONLY should be done whatever CANNOT be done on the run,
during normal operation.
Frequently, Maintenance is asked to perform General Maintenance in ALL rotating
equipment of a Unit, during its Turnaround. Matter of fact, if these equipment have
spares, this General Maintenance should be done out of the TAR.
Why do Operations want everything to be done during the TAR?
1) Because Ops don’t have enough confidence that it will be done during routine
maintenance.
2) Because they don’t feel comfortable running with an equipment momentarily without
spare… the same way when we have a flat tire, we just drive with the spare tire
enough to hit the tire repair shop…
45. Reliability Centered Maintenance (RCM)
Turnarounds
1) Ops don’t have enough confidence that it will be done during routine maintenance.
To improve TAR results, reversing the vicious cycle below, Maintenance
management has to improve Routine Maintenance!
To much to
be done Not in excess
during TAR equipments to
be done
during TAR
TAR won’t be
Many able to TAR will carry Good routine
equipments perform all out all services maintenance
left to TAR that has to be needed
done
Many
equipments Unit running
left to well
Routine
Maintenance
46. Reliability Centered Maintenance (RCM)
Turnarounds
2) Because they don’t feel comfortable running with an equipment momentarily without
spare… the same way when we have a flat tire, we just drive with the spare tire
enough to hit the tire repair shop…
Consider these two pumps in a Passive Redundancy
(one will be as stand-by). Assume that during the first
100 h after a General Maintenance such a pump will
have a 70% reliability, and after this, for an one year
period, it would run with 97% reliability (which are
reasonable assumptions!!!).
If General Maintenance is performed in a Preventive or Predictive Program, during
normal operations, during repair time the unit will be running pending upon a unique
pump, with a 97% reliability.
If during TAR both pumps will be under General Maintenance, during the first 100
hours the system reliability (considering a perfect switch) would be 94.5% (using the
R(t) = e-λt(1+λt) formula) . So, the unit would run for a period of time with two
available pumps, but with an overall reliability below if it would be running with only
one pump!
47. Reliability Centered Maintenance (RCM)
RCM Implementation Flowchart
Will the failure affect No
directly Health, Safety or
Environment?
Will the Failure affect
Yes adversely the Mission, Vision No
and Core Values of the
Company?
Yes Will the failure cause
Yes
major economic losses?
(harm to systems and / or
Is there some Cost- machines)?
No
effective Monitoring
Technology available? No
Yes
Are there regular failure
Deploy Monitoring No
patterns (time
techniques
intervals)?
Yes
Predictive Maintenance Preventive Re-design the system, Run-to-fail?
Maintenance accept failure risk, or
install redundancy
48. Reliability Centered Maintenance (RCM)
Another RCM Implementation Flowchart
If this thing breaks will it If this thing breaks will it If this thing breaks will it No
Yes No
be noticed? hurt someone or the slow or stop production?
environment?
No Yes
Yes
Can preventing it break Can preventing it break Is it cheaper to prevent it Is it cheaper to prevent
reduce the likelihood of reduce the reduce the breaking than the loss of it breaking than to fix it?
multiple failures? risk to the environment production?
and safety?
Yes No Yes No Yes No Yes No
Prevent it Check to see Prevent it Re-design it Prevent it Let it break Prevent it Let it break
breaking if it is broken breaking breaking breaking