This is a presentation to the top management as to why reliability is important and what is the difference between a maintenance engineer and a reliability engineer.
This is a three parts lecture series. The parts will cover the basics and fundamentals of reliability engineering. Part 1 begins with introduction of reliability definition and other reliability characteristics and measurements. It will be followed by reliability calculation, estimation of failure rates and understanding of the implications of failure rates on system maintenance and replacements in Part 2. Then Part 3 will cover the most important and practical failure time distributions and how to obtain the parameters of the distributions and interpretations of these parameters. Hands-on computations of the failure rates and the estimation of the failure time distribution parameters will be conducted using standard Microsoft Excel.
Part 1. Reliability Definitions
1.Reliability---Time dependent characteristic
2.Failure rate
3.Mean Time to Failure
4.Availability
5.Mean residual life
This seminar session provides an overview of major aspects of reliability engineering, including general introduction of reliability engineering (definition of reliability, function of reliability engineering, a brief history of reliability, etc.), reliability basics (metrics used in reliability, commonly-used probability distributions in reliability, bathtub curve, reliability demonstration test planning, confidence intervals, Bayesian statistics application in reliability, strength-stress interference theory, etc.), accelerated life testing (ALT) (types of ALT, Arrhenius model, inverse power law model, Eyring model, temperature-humidity model, etc.), reliability growth (reliability-based growth models, MTBF-based growth model, etc.), systems reliability & availability (reliability block diagram, non-repairable or repairable systems, reliability modeling of series systems, parallel systems, standby systems, and complex systems, load sharing reliability, reliability allocation, system availability, Monte Carlo simulation, etc.), and degradation-based reliability (introduction of degradation-based reliability, difference between traditional reliability and degradation-based reliability, etc.).
Authors: (i) Prashanth Lakshmi Narasimhan,
(ii) Mukesh Ravichandran
Industry: Automobile -Auto Ancillary Equipment ( Turbocharger)
This was presented after the completion of our 2 months internship at Turbo Energy Limited during our 3rd Year Summer holidays (2013)
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.
This is a three parts lecture series. The parts will cover the basics and fundamentals of reliability engineering. Part 1 begins with introduction of reliability definition and other reliability characteristics and measurements. It will be followed by reliability calculation, estimation of failure rates and understanding of the implications of failure rates on system maintenance and replacements in Part 2. Then Part 3 will cover the most important and practical failure time distributions and how to obtain the parameters of the distributions and interpretations of these parameters. Hands-on computations of the failure rates and the estimation of the failure time distribution parameters will be conducted using standard Microsoft Excel.
Part 1. Reliability Definitions
1.Reliability---Time dependent characteristic
2.Failure rate
3.Mean Time to Failure
4.Availability
5.Mean residual life
This seminar session provides an overview of major aspects of reliability engineering, including general introduction of reliability engineering (definition of reliability, function of reliability engineering, a brief history of reliability, etc.), reliability basics (metrics used in reliability, commonly-used probability distributions in reliability, bathtub curve, reliability demonstration test planning, confidence intervals, Bayesian statistics application in reliability, strength-stress interference theory, etc.), accelerated life testing (ALT) (types of ALT, Arrhenius model, inverse power law model, Eyring model, temperature-humidity model, etc.), reliability growth (reliability-based growth models, MTBF-based growth model, etc.), systems reliability & availability (reliability block diagram, non-repairable or repairable systems, reliability modeling of series systems, parallel systems, standby systems, and complex systems, load sharing reliability, reliability allocation, system availability, Monte Carlo simulation, etc.), and degradation-based reliability (introduction of degradation-based reliability, difference between traditional reliability and degradation-based reliability, etc.).
Authors: (i) Prashanth Lakshmi Narasimhan,
(ii) Mukesh Ravichandran
Industry: Automobile -Auto Ancillary Equipment ( Turbocharger)
This was presented after the completion of our 2 months internship at Turbo Energy Limited during our 3rd Year Summer holidays (2013)
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.
Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition. Poor reliability can doom a product and jeopardize the reputation of a brand or company. Inadequate reliability also presents financial risks from warranty, product recalls, and potential litigation. When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met. This 4-Hour course provides an overview of quantitative methods for predicting product reliability from data gathered from physical testing or from field data
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.
This is a three parts lecture series. The parts will cover the basics and fundamentals of reliability engineering. Part 1 begins with introduction of reliability definition and other reliability characteristics and measurements. It will be followed by reliability calculation, estimation of failure rates and understanding of the implications of failure rates on system maintenance and replacements in Part 2. Then Part 3 will cover the most important and practical failure time distributions and how to obtain the parameters of the distributions and interpretations of these parameters. Hands-on computations of the failure rates and the estimation of the failure time distribution parameters will be conducted using standard Microsoft Excel.
Part 3. Failure Time Distributions
1.Constant failure rate distributions
2.Increasing failure rate distributions
3.Decreasing failure rate distributions
4.Weibull Analysis – Why use Weibull?
Is Reliability Centered Maintenance (RCM) right for you?Nancy Regan
This presentation outlines the goals of a Reliability Centered Maintenance (RCM) analysis. It debunks the top misconceptions about RCM. And it poses and answers the top four questions about RCM most people don’t know to ask.
Definition of RCM, principles and goals of RCM; Four major components of RCM: reactive maintenance, preventive maintenance, predictive testing and inspection and proactive maintenance; RCM strategies.
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
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.
Mechanical Reliability Prediction: A Different ApproachHCL Technologies
This paper critically analyses the current industry practices for making reliability prediction prevalent among the aircraft manufacturers and further explores the more accurate and cost effective methods for predicting the failure rate of a component or subsystem during the early design phase of the product development cycle namely NSWC method , PoF approach and SSI theory. It elucidates the effectiveness of these alternative approaches with the help of a case study on Hydraulic Accumulator (HYDAC).
Achieving high product reliability has become increasingly vital for manufacturers in order to meet customer expectations amid the threat of strong global competition. Poor reliability can doom a product and jeopardize the reputation of a brand or company. Inadequate reliability also presents financial risks from warranty, product recalls, and potential litigation. When developing new products, it is imperative that manufacturers develop reliability specifications and utilize methods to predict and verify that those reliability specifications will be met. This 4-Hour course provides an overview of quantitative methods for predicting product reliability from data gathered from physical testing or from field data
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.
This is a three parts lecture series. The parts will cover the basics and fundamentals of reliability engineering. Part 1 begins with introduction of reliability definition and other reliability characteristics and measurements. It will be followed by reliability calculation, estimation of failure rates and understanding of the implications of failure rates on system maintenance and replacements in Part 2. Then Part 3 will cover the most important and practical failure time distributions and how to obtain the parameters of the distributions and interpretations of these parameters. Hands-on computations of the failure rates and the estimation of the failure time distribution parameters will be conducted using standard Microsoft Excel.
Part 3. Failure Time Distributions
1.Constant failure rate distributions
2.Increasing failure rate distributions
3.Decreasing failure rate distributions
4.Weibull Analysis – Why use Weibull?
Is Reliability Centered Maintenance (RCM) right for you?Nancy Regan
This presentation outlines the goals of a Reliability Centered Maintenance (RCM) analysis. It debunks the top misconceptions about RCM. And it poses and answers the top four questions about RCM most people don’t know to ask.
Definition of RCM, principles and goals of RCM; Four major components of RCM: reactive maintenance, preventive maintenance, predictive testing and inspection and proactive maintenance; RCM strategies.
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
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.
Mechanical Reliability Prediction: A Different ApproachHCL Technologies
This paper critically analyses the current industry practices for making reliability prediction prevalent among the aircraft manufacturers and further explores the more accurate and cost effective methods for predicting the failure rate of a component or subsystem during the early design phase of the product development cycle namely NSWC method , PoF approach and SSI theory. It elucidates the effectiveness of these alternative approaches with the help of a case study on Hydraulic Accumulator (HYDAC).
Reliability and Maintenance Conference - 7-9 April 2014, Al Khobar, Kingdom o...Ricky Smith CMRP, CMRT
Despite the best efforts and precautions, equipment
failures do occur hampering the equipment performance
and adversly impacting the profitibility of the business.
Rotating Equipment Reliability and Maintenance
Conference aims to create a learning platform for all the
maintenance and reliability professionals to share the
best maintenance practices and discuss the strategies to
improve reliability.
This three day conference will cover all aspects of
reliability and maintenance including reliability centered
maintenance, availability, machinery failures, risk
assessment, spare parts optimization, techniques to
facilitate equipment maintenance, root cause analysis,
condition monitoring, maintenance planning and
scheduling.
Reliability Maintenance Engineering Day 2 session 3 Measuring Maintainability
Three day live course focused on reliability engineering for maintenance programs. Introductory material and discussion ranging from basic tools and techniques for data analysis to considerations when building or improving a program.
Hannover Messe 2017 is going to be a watershed for the Digital Technologies taking over the Manufacturing world like a storm. The presentation gives a detailed look into what the worlds largest exhibition is going to give a feel of.
Guidelines to Understanding to estimate MTBFijsrd.com
To quantifying a reparable system or reliability we can use MTBF. It has been used for various decisions. MTBF is determining the reliability. For developing the MTBF model we can use Poisson distribution, Weibull model and Bayesian are the most popular approach. In this paper we are talking about complexities and misconceptions of MTBF and clarify in sequence what are the items and concerns that need to be consider in estimating MTBF.
Application of Lifetime Models in Maintenance (Case Study: Thermal Electricit...iosrjce
IOSR Journal of Mathematics(IOSR-JM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
CS672 – System Engineering and Analysis Discussion 6 - 1192018.docxmydrynan
CS672 – System Engineering and Analysis
Discussion 6 - 11/9/2018
Samson Kamal Victor
Chapter 12, Question 1:
Reliability:
Reliability is an ability of software to run with minimum number of failure rate in the given period of time. The software failure may be some errors, uncertainty, and misinterpretation of initial system requirement. Software faults are the design faults of the system (Jiantao, 1999)
Characteristics:
· Design faults cause
· Errors may occur without warnings
· Restart in certain time period will reduce the failure
· Reliability of prediction is depend on the human design
· Software interfaces are not visual or physical it is only conceptual
· Software reliability is not operational time dependence but depend on number of successful operations
· Based on the number of failure rate to predict the future system
· Proper well designed framework can lead more reliable software
Chapter 12, Question 2:
System design:
The reliability in system design is very important to predict of failure, quantitative and qualitative reliability requirement of mean time between failure (MTBF) and meantime between maintenance (MTBM)
The reliability need to be checked in each stage of the lifecycle. In the conceptual design stage, preliminary design, detail design and development, production, operation and support. Complete weaved in development cycle
To extend the reliability in the system design then in the conceptual design stage must be done in detailed with the reliability requirements. If the reliability is analyzed properly then it would product may work for extend period of life time. The reliability analyses, evaluation prediction and the formal design review and approval
Chapter 12, Question 3:
Quantitative measure of reliability:
Understanding the nature of system thoroughly and the product metric help to measure the quantitative measure of software reliability. The size of the product can be measured using the line of code (LOC), also using the source line of code (SLOC) and thousand source line of code (KSLOC) with no comments, allows to understand the functionality and complexity of the code, the flow chart diagram will show simplified representation of code, testing of the code functionality and estimate the fault will make the product more reliable (Jiantao, 1999)
The quantitative measure of personal reliability can be measured based on the three factors over time (test-retest reliability) the intelligence of the personal in consistent across time. Internal consistency is represents the self esteem or good qualities of the personal and interact reliability of social skills and how they interaction with others (ReliabilityMeasurement, 2015)
The hardware system is physical device like sensor, controllers and actuators. The hardware reliability is required of time related model to check the physical device fail over time to avoid the physical faults
The quantitative measure of data reliability supported by the positivis.
The FMEA embodies a process that is intended to identify equipment failure modes, their causes, and finally the effects that might result should these failure modes occur during product operation.
1BetaC 2021 by Dr. Paul Battaglia as prepared at Florida TeTatianaMajor22
1
BetaC 2021 by Dr. Paul Battaglia as prepared at Florida Tech
MGT5061-FA21
Systems & Log Support Mgt
note15-W05
Chapter 2 RMA (aka RAM)
We are
here
Introduction to the Course
Ch 1 - Introduction to logistics
Ch 2 - Reliability, Maintainability, and Availability Measures
Ch 3 - Measures of Logistics and System Support
Ch 4 -The Systems Engineering Process
Ch 5 - Logistics and Supportability Analysis
Ch 6- Logistics in System Design and Development
Ch 7 - Logistics in the Production/Construction Phase
Ch 8- Logistics in the System Utilization, Sustaining Support,
and Retirement Phases
Ch 9- Logistics Management
2
We originally skipped chapter 2 (reliability, maintainability,
and availability measures).
We jumped from chapter 1 (introduction) to chapter 3
(measures of logistics and system support).
Chapter 3 is a more general case of systemic metrics.
On the other hand, Chapter 2 on reliability, maintainability,
and availability is pretty specific.
It seemed to me that Chapters 2 and 3 were in reverse sequence
in the subject matter as addressed by Blanchard.
At any rate, here we are in chapter 2.
3
On page iv look at how chapter 2 is developed.
** We know there is an introduction
2.1 Then Reliability measures & factors
2.2 Maintainability measures and factors
2.3 Availability (measures) and factors
That is RMA.
-=-=
Often referred to in a slightly different sequence, yes?
RAM.
4
On page 73, in section 2.4 look at the summary.
** Back on page 11 in figure 1.4 we saw that there are a wide
variety of logistics and system support activities for both
** forward; and
** reverse flows.
** How well the system successfully accomplishes these activities
is due, in large part, to how the system is designed.
*** BUT do note that design is not the entire story.
There are other factors!
5
One big considerations is the behavior of employees/people in
general.
An example?
GTYA!
We can make an electrical connector so that it only fits one
way.
Thereby helping to ensure that the circuit is “always”
connected properly and will work.
But inevitably [some] people will try to force the connector in
an improper orientation.
** It is very hard to make a system or product that is
entirely
employee proof (or aka GI proof).
-=-=
Glad that you asked.
** Availability is a function of reliability and maintainability
and “other” considerations
A = f (R,M,O)
Now we see why the chapter is titled reliability,
maintainability, and then availability. It aligns better with the
equation.
In this view, the term RAM basically has the sequence
not-quite-correct.
** Also we should to look at a “systems approach”. Consider
other factors such as
** software
** people
** facilities
** data
** etc (all the factors mentioned in the work so far)
6
** Chapter 2 focuses on terms and metrics for reliability ...
Measurement and Evaluation of Reliability, Availability and Maintainability o...IOSR Journals
The growing complexity of equipments and systems often lead to failures and as a consequence the
aspects of reliability, maintainability and availability have come into forefront. The failure of machineries and
equipments causes disruption in production resulting from a loss of availability of the system and also increases
the cost of maintenance. The present study deals with the determination of reliability and availability aspects of
one of the significant constituent in a Railway Diesel Locomotive Engine. In order to assess the availability
performance of these components, a broad set of studies has been carried out to gather accurate information at
the level of detail considered suitable to meet the availability analysis target. The Reliability analysis is
performed using the Weibull Distribution and the various data plots as well as failure rate information help in
achieving results that may be utilized in the near future by the Railway Locomotive Engines for reducing the
unexpected breakdowns and will enhance the reliability and availability of the Engine. In this work, ABC
analysis has been used for the maintenance of spare parts inventory. Here, Power pack assemblies, Engine
System are used to focus on the reliability, maintainability and availability aspects
The Quality “Logs”-Jam: Why Alerting for Cybersecurity is Awash with False Po...Mark Underwood
What happens when the (Observe) Plan-Do-Check-Adjust cycle is undermined by lapses in data integrity? Observations are questioned. Plans may be ill-conceived. Actions may be undertaken that undermine rather than enhance. “Checks” can fail. Adjustments may be guesswork. In cybersecurity, the results of poor data integrity can be expensive outages, ransom requests, breaches, fines -- even bankruptcy (think Cambridge Analytica). But data integrity issues take many forms, ranging from benign to malicious. The full range of these issues is surveyed from a cybersecurity perspective, where logs and alerts are critical for defenders -- as well as quality engineers . Techniques borrowed from model-based systems engineering and ontology AI to are identified that can mitigate these deleterious effects on PDCA.
Paper on the issues with mtbf published in the Spring 2011 issue of the RMSP Journal.
MTBF is widely used to describe the reliability of a component or system. It is also often misunderstood and used incorrectly. In some sense, the very name “mean time between failures” contributes to the misunderstanding. The objective of this paper is to explore the nature of the MTBF misunderstandings and the impact on decision-making and program costs.
Mean-Time-Between-Failure (MTBF) as defined by MIL-STD-721C Definition of Terms for Reliability and Maintainability, 12 June 1981, is
A basic measure of reliability for repairable items: The mean number of life units during which all parts of the item perform within their specified limits, during a particular measurement interval under stated conditions.
The related measure, Mean-Time-To-Failure (MTTF) is define as
A basic measure of reliability for non-repairable items: The total number of life units of an item divided by the total number of failures within that population, during a particular measurement interval under stated conditions.
Industry 4.0 is changing the Landscape of how we live in this world. And Education is undergoing a Paradigm change to keep up with the changing times. What should India do to change its education system is explained through examples.
An unfinished guide to Industry 4.0 in Industries. This can be used by anyone to teach Industry 4.0 anywhere. You can add material to it. And I will also build up the presentation with some more details. This can also be used in conjunction with other presentations like "How did Industry 4.0 Begin". Overall a comprehensive guide.
Going beyond Industry 4.0, Smart cities and Smart Factory, Japan takes it to the next level of a super smart society by 2030. Encompassing all the above and making it clear and easily implementable. It is a step forward which needs to be understood by many.
Four years back, during my interactions with certain big groups, I had offered to set up the Hub and spoke model for pilot projects in Industry 4.0. I thought a few of them will accept and become the hubs for smart manufacturing in India. Support was readily available from external trade development councils. Then came "demonetization" and "GST" and all these big groups disappeared. Then I approached some of the SME groups and textile associations. But as was expected after a 6 hour presentation, they maintained silence. I was expected to bring in money from these external councils. Investment was a big factor. I was not even paid for these "free" presentations.
Cut to a few days back, after 4 years of silence, I was approached by some of the above whether we can have the Hub and Spoke model projects of Industry 4.0 in India. I offered them end to end solutions. And listed out the cost factor. To my surprise, with so much research material available on Industry 4.0 projects, why are we hesitant to spend money for something good baffles me. For eg. in today's age if I want to buy a mobile, will I buy a Smartphone or an old relic. Even the poor desire a smartphone. Then why as a factory owner, we shy away from investing in Industry 4.0 technologies.
Then what is the way forward is the question oft asked. So I gave them another "free" presentation. Hope they buy the smartphone at least now.
In 2017, the World Economic Forum recognized the potential of advanced manufacturing technologies. In 2018, from among more than 1,000 examined production facilities, 16
companies were recognized as Fourth Industrial Revolution leaders in advanced manufacturing for demonstrating step-change results, both operational and financial, across individual sites. They had succeeded in scaling beyond the pilot phase and their sites were designated advanced manufacturing “Lighthouses”. In 2019, 28 additional facilities were identified and added to the network, which now provides an opportunity for cross-company learning and collaboration, and for setting new benchmarks for the global manufacturing community.
Lighthouses have succeeded by innovating new operating systems, including in how they manage and optimize business and processes, transforming the way people work and use technology. These new operating systems can become the blueprint for modernizing the entire company operating system; therefore, how they prepare for scaling up and engaging the workforce matters.
How the Digital Transformation is going to change the world of Work 4.0 with respect to the Introduction of Industry 4.0 technology. Will Jobs reduce or we will have more jobs with higher pay. An interesting analysis.
Education4.0 - How Industry 4.0 is going to change the Education SystemWg Cdr Jayesh C S PAI
Education 4.0 is Empowering education to produce innovation. Students will work in peer-to-peer networks or organizations which are open and structurally liquid. They will be hired (and laid off) on demand or work as free agents. They will have to compete for employment on a global market. New skills and competencies will become more important such as non linear thinking, social and intercultural skills, self-management and self-competence. Universities would have to re-calibrate their strategies across all the levers for Edn to remain relevant in the age of Industry 4.0.
To those who want to know how Industry 4.0 began and why it began, an easy presentation highlighting all relevant points. There is a fundamental curiosity as to how it all started and where is it headed towards. And whether it will be useful. To those who are still waiting to accept the change, look at what happened to Nokia when the iPhone started. It is better to start implementing the small changes soon.
Drop by drop the ocean builds up. Similarly, small innovations build up to count in implementing Industrie 4.0 across the world.Presently there are more examples in German Factories but the other countries are fast catching up. All these small examples give a remarkable picture of how the world is changing. And also gives us a direction to how we should change our skill sets to meet the ever growing Knowledge Economy. For students, you get an idea where research work is headed. The examples of Applications of Industrie 4.0 will give an idea of how small drops of technology changes is building into an ocean of Innovative ideas across the Industrial Spectrum.
To beat the Industry 4.0 movement in Germany the South Koreans under the Creative Economy Engine Project started the MII 3.0. The basic motto is to develop the Industries especially the SME sector to Industry 4.0 standards but also include emphasis on areas where Korea is very strong such as automotive industries and Ship building Industries.
The revolution in Supply Chain Management is through Digital Technology revolution in Industry 4.0. it brings in Transparency and accountability into the system bringing waste down to minimal. Procurement 4.0, Transportation 4.0, Supply 4.0 or Logistics 4.0, Whatever we may call it is going to change the face of the Industry. Data Analytics is going to make every ones life easy.
India is on the cusp of a manufacturing revolution towards Industry 4.0 provided the Government and the Industry get together its acts. A number of policies require to be formulated and implemented especially in the SME sector. Not just announced and left for no one to understand and implement.
Technology that is going to create a revolution in every Industry including Health care. What is it, what are the tools and what is the outcome?
NASA started the research on Twins due to space travel and the need to have real time feedback of components. Now it is extending to even Health care to having a Human twin.
The path to realization of Industry 4.0 involves a clear understanding of the ways in which the physical can inform the digital, and vice versa.
INDUSTRIE 4.0 connects embedded system production technologies and smart production processes to pave the way to a new technological age which will radically transform industry and production value chains and business models.
Hannover 2016 is going to start in a few days and the integrated Industry is one of the main key topics. An attempt to analyse the key points in Integrated Industry has been made. All points related to the topic are explained briefly.
The Industrie 4.0 has 9 pillars of Technological transformation that one needs to know and understand first before they start implementing it in their company. From Big Data & Analytics to Autonomous Robots to Augmented reality, the whole world is changing.
From Why a Smart City to What in a Smart city and "How" in a Smart City. The importance of being connected in a growing Urbanisation world is crucial now. Sustainability is a crucial issue in an Urban city.
Where is Europe with respect to Industry 4.0 and what should European Countries have to do to reach the level of Industry 4.0 competence achieved by Germany. Will Europe loose out to China / India as a manufacturing superpower or will Europe with this effort in the SMEs bring a revolution in the digital age.
China trying to be a world manufacturing Superpower by 2025 with clear laid down policies. It has been recognised that Manufacturing sector is what would take China to even more greater heights.
Taiwan has recently introduced a Policy for improving the economy and the Manufacturing Sector to gear upto Industry 4.0. Smart Automation in Service, Agriculture and Manufacturing.
5. DEMING Quotes "There is no substitute for knowledge." "The most important things cannot be measured." "The most important things are unknown or unknowable.“ "Experience by itself teaches nothing.“ "I think that people here expect miracles. American management thinks that they can just copy from Japan—but they don't know what to copy!"
6. Defect Rate Analysis GOAL: GET AN OVERVIEW ABOUT THE AMOUNT AND STATE OF THE REPORTED DEFECTS. TO OBTAIN AN OVERVIEW OF THE PATTERN OF DEFECTS ARISING IN IT WITH A VIEW TO HIGHLIGHT POSSIBLE TROUBLE PRONE AGGREGATES FOR THE FUTURE AND SUGGEST REMEDIES FOR IMPROVEMENT.
7. DATA COLLECTION 1. DR/PWR DATA (RECEIVED FROM UNITS) - WING - AIRCRAFT SQUADRON - AIRCRAFT No. - DR/PWR No. & DATE - DIR/PWIR No. & DATE - NOMENCLATURE OF COMPONENT - PART NUMBER - SYSTEM - TRADE - TBO - LIFE COMPLETED SINCE LAST OVERHAUL - LIFE COMPLETED SINCE NEW - REPORTED DEFECT - DI AGENCY 2. DIR / PW IR DATA (Received from DI agency) - CONFIRMATION AND FINDINGS - RECOMMENDATIONS
8. PIE – CHART TRADE - AIRFRAME DEFECT DATA – AIRFRAME SYSTEMS OTHERS, (18) 10% AIR CONDITIONING SYSTEM (28) 15% TAKE OFF/LANDING SYSTEM (13) 7% FUEL SYSTEM (31) 17% PNEUMATIC SYSTEM (35) 19% HYDRAULIC SYSTEM (58) 32%
9. Recent NASA Accidents Genesis vehicle slammed into Utah desert, probably because Lockheed engineers installed four small switches backward Climate orbiter crashed into Mars because Lockheed used English measurement while NASA used metric Mars polar vehicle crashed when descent rockets shut off prematurely Television infrared observation satellite (TIROS) fell off its transport stand because an adapter plate was not properly secured
16. Process Control Chart Upper control limit Process average Lower control limit 10 9 1 2 3 4 5 6 7 8 Sample number
17. Cause-and-Effect Diagram Machines Measurement Human Faulty testing equipment Out of adjustment Poor supervision Tooling problems Incorrect specifications Lack of concentration Old / worn Improper methods Inadequate training Quality Problem Inaccurate temperature control Defective from vendor Poor process design Ineffective quality management Not to specifications Dust and Dirt Deficiencies in product design Material- handling problems Process Environment Materials
18. Engineers—wake up! Most engineers need to understand they are a dying breed if they plan to maintain equipment using only the seat of their pants, qualitative data, for making decisions. Engineers must fluently use reliability data so they can reduce costs and avoid failures by using data to make wise decision. Without the numbers, we engineers will soon be viewed as technical amateurs with declining pay scales and unemployment as the byproduct. Use the data in your maintenance systems to solve technical problems and make improvements!
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20. RELIABILITY vs MAINTENANCE ENGINEER The task of reliability engineers is to avoid failures which carry a requirement for solving problems with data. The task of maintenance engineers is to quickly restore equipment to operating conditions which requires understanding failure modes and the failure data. Both reliability engineers and maintenance engineers can use a common set of data for an excellent communication tool to solve the vitally few problems in the shortest interval of time using facts from the data to reduce costs.
21. Reliability Reliability Reliability is the ability of a system or component to perform its required functions under stated conditions for a specified period of time [IEEE 90]. In other words, it is the likelihood that the system or component will succeed within its identified mission time, with no failures. An aircraft mission is the perfect example to illustrate this concept. When an aircraft takes off for its mission, there is one goal in mind: complete the flight, as intended, safely (with no catastrophic failures).
22. Reliability Reliability data requires definition of a failure. Failures can be catastrophic failures or slow degradation—you decide by defining the failures. Units of measure for the data must be in units of the degradation— it can be hours, miles, cycles, and so forth—in short, whatever motivates the failure.
23. What is a Failure? Reliability is quantified as MTBF (Mean Time Between Failure) for repairable product and MTTF (Mean Time To Failure) for non-repairable product. MTBF is often quoted without providing a definition of failure. This practice is not only misleading but completely useless. MTBF impacts both reliability and availability.
24. What is a Failure? One could argue there are two basic definitions of a failure: 1) The termination of the ability of the product as a whole to perform its required function. 2) The termination of the ability of any individual component to perform its required function but not the termination of the ability of the product as a whole to perform.
25. Example If the inverter of a UPS fails and the UPS switches to static bypass, the failure does not prevent the UPS from performing its required function which is supplying power to the critical load. However, the inverter failure does prevent a component of the UPS from performing its required function of supplying conditioned power. According to definition 1, this is not a failure, but according to definition 2, it is a failure.
26. What is a Failure? In reality there are more then two definitions of failure, in fact they are infinite. Is customer misapplication considered a failure? Are shipping damages considered failures? Is the expected wear out of a consumable item such as a battery considered a failure if it failed prematurely? If an LED (Light Emitting Diode) on a computer were to fail is it considered a failure even though it hasn’t impacted the operation of the computer?
27. Definition of Failure Failure itself must also be thoroughly defined at system and module levels. It may be necessary to define more than one type of failure (for example, total system failure or degradation failure) or failures for different operating modes (for example, in flight or on ground) in order to describe all the requirements.
28. Definition of Failure MTBFs might then be ascribed to the different failure types. MTBFs and failure rates often require clarification as to the meaning of ‘failure’ and ‘time’. The latter may refer to operating time, revenue time, clock time, etc. Types of failure which do not count for the purpose of proving the reliability (for example, maintenance induced or environment outside limits) have also to be defined.
30. MAINTAINABILITY ESSENTIALLY, THE EASE AND SPEED WITH WHICH A FAILED EQUIPMENT CAN BE BROUGHT BACK INTO OPERATING CONDITIONS IS MAINTAINABILITY ALSO CALLED AS MEAN TIME TO REPAIR (MTTR) OF AN ITEM. 3/10/2010 CSDO 30
31. MTTR Mean Time to Repair (or Recover), is the expected time to recover a system from a failure. MTTR impacts Availability and not Reliability. The longer the MTTR, the worse off a system is. As the MTBF goes up, Availability goes up. As the MTTR goes up, Availability goes down.
32. MEAN TIME TO REPAIR DETECTION OF FAULT ALLOCATION OF MAINTENANCE TEAM DIAGNOSE FAULT OBTAIN SPARE PARTS (LOGISTIC DELAY) REPAIR TIME(MTTR-THIS IS THE MANUFACTURERS INFORMATION) TEST AND ACCEPT REPAIR CLOSING UP THE SYSTEM AND RETURNING TO NORMAL OPERATION. SKILL OF THE MAINTENANCE ENGINEERS AND THE MAINTENANCE STAFF AVAILABLE AT THE BASES 3/10/2010 CSDO 32
33. MEAN TIME TO REPAIR If a Mean Time To Repair (MTTR) or Down Time (MDT) is specified, then the meaning of repair time must be defined in detail. Mean time to repair is often used when it is mean down time which is intended.
34. MTBF Mean Time Between Failure, is a basic measure of a system’s reliability. It is typically represented in units of hours. The higher the MTBF number is, the higher the reliability of the product. MTBF: Misquoted and Misunderstood
35. MTBF A common misconception about MTBF is that it is equivalent to the expected number of operating hours before a system fails, or the “service life”. It is not uncommon, however, to see an MTBF number on the order of 1 million hours, and it would be unrealistic to think the system could actually operate continuously for over 100 years without a failure.
36. MTBF There are 500,000 humans aged 25-year-old in the sample population. Over the course of a year, data is collected on failures (deaths) for this population. The operational life of the population is 500,000 x 1 year = 500,000 people years. Throughout the year, 625 people failed (died). The failure rate is 625 failures / 500,000 people years = 0.125% / year. The MTBF is the inverse of failure rate or 1 / 0.00125 = 800 years. So, even though 25-year-old humans have high MTBF values, their life expectancy (service life) is much shorter and does not correlate.
37. It’s all about Assumptions! So, what is the MTBF of 25-year-old humans, 80 or 800? It’s both! But, how can the same population end up with two such drastically different MTBF values? If the MTBF of 80 years more accurately reflects the life of the product (humans in this case), is this the better method?
38. MTBF The biggest limitation is time. In order to do this, the entire sample population would have to fail, and for many products this is on the order of 10-15 years. In addition, even if it were sensible to wait this duration before calculating the MTBF, problems would be encountered in tracking products. For example, how would a manufacturer know if the products were still in service if they were taken out of service and never reported? Who would want the MTBF value of a product that has been superceded by several generations of technology updates?
39. Availability Availability, on the other hand, is the degree to which a system or component is operational and accessible when required for use [IEEE 90]. Availability is often looked at because, when a failure does occur, the critical variable now becomes how quickly the system can be recovered.
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41. For Equation 1 and Equation 2 above to be valid, a basic assumption must be made when analyzing the MTBF of a system.
42. Unlike mechanical systems, most electronic systems don’t have moving parts.
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44. METHODS OF PREDICTING AND ESTIMATING MTBF Reliability Prediction Methods :- MIL-HDBK 217, Telcordia, HRD5 RBD (Reliability Block Diagram) Markov Model FMEA / FMECA Fault Tree Highly Accelerated Life Testing (HALT)
45. METHODS OF PREDICTING AND ESTIMATING MTBF Reliability Estimation Methods :- Similar Item Prediction Method Field Data Measurement Method The FIDES Prediction Model (FIDES Guide 2004 Issue, A Reliability Methodology for Electronic Systems) was designed by the FIDES Group, a consortium of European companies from the aeronautics and defense fields, to apply to all domains using electronics, including the military, commercial industry, and telecommunications.
49. Failure Reporting Analysis and Corrective Action System (FRACAS) An effective FRACAS process provides for gathering and tracking failure data in a central database so that this data can be analyzed to determine underlying causes. Yet, in many organisations, the individuals participating in the process are distributed across multiple groups or locations, and are recording information in different sources or databases. As a result, the ability to quickly isolate failure trends is compromised. FRACAS Standard helps organisations to overcome this fragmented approach to reliability. 3/10/2010 CSDO 47
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51. ASL Average Service Life = Sum of the hours logged after last overhaul of the components received as Cat D / DI during the period ____________________________________________ Total No of Components received as Cat D / DI during the period (The number of Engines / Rotables withdrawn for FOD / Bird Hit / Defect Not Confirmed are excluded)
52. DEMING Quotes "There is no substitute for knowledge." "The most important things cannot be measured." "The most important things are unknown or unknowable.“ "Experience by itself teaches nothing.“ "I think that people here expect miracles. American management thinks that they can just copy from Japan—but they don't know what to copy!"