Continuous improvement in predictive maintenance

Slides:



Advertisements
Similar presentations
Slide 1 The basic problem Working Age t PDF f(t) Failures do not happen at fixed times. They occur randomly based on a distribution. Probabilty Density.
Advertisements

Continuous Improvement in CBM
The Normal Distribution
Sampling Distributions (§ )
Descriptive statistics Experiment  Data  Sample Statistics Experiment  Data  Sample Statistics Sample mean Sample mean Sample variance Sample variance.
Chapter 3 Hypothesis Testing. Curriculum Object Specified the problem based the form of hypothesis Student can arrange for hypothesis step Analyze a problem.
1 Confidence Intervals for Means. 2 When the sample size n< 30 case1-1. the underlying distribution is normal with known variance case1-2. the underlying.
QM-1/2011/Estimation Page 1 Quantitative Methods Estimation.
Section 9-4 Hypothesis Testing Means. This formula is used when the population standard deviation is known. Once you have the test statistic, the process.
Review – Using Standard Deviation Here are eight test scores from a previous Stats 201 class: 35, 59, 70, 73, 75, 81, 84, 86. The mean and standard deviation.
1 6. Reliability computations Objectives Learn how to compute reliability of a component given the probability distributions on the stress,S, and the strength,
Correlation and Prediction Error The amount of prediction error is associated with the strength of the correlation between X and Y.
CBM Optimization – Complex items An item is a group of components that is convenient to monitor and analyze together Equipment units, as defined in the.
Section 7-3 Estimating a Population Mean: σ Known.
1 EXAKT SKF Phase 1, Session 2 Principles. 2 The CBM Decision supported by EXAKT Given the condition today, the asset mgr. takes one of three decisions:
Mystery 1Mystery 2Mystery 3.
BASIC STATISTICAL CONCEPTS Statistical Moments & Probability Density Functions Ocean is not “stationary” “Stationary” - statistical properties remain constant.
Time Remaining 20:00.
网上报账系统包括以下业务: 日常报销 差旅费报销 借款业务 1. 填写报销内容 2. 选择支付方式 (或冲销借款) 3. 提交预约单 4. 打印预约单并同分类粘 贴好的发票一起送至财务 处 预约报销步骤: 网上报账系统 薪酬发放管理系统 财务查询系统 1.
Using uncertainty to test model complexity Barry Croke.
Slide (Ch.22) 1 Tian: Software Quality Engineering Software Quality Engineering: Testing, Quality Assurance, and Quantifiable Improvement Jeff Tian Chapter.
SUR-2250 Error Theory.
Psych 231: Research Methods in Psychology
ESTIMATION.
Chapter 4: The Normal Distribution
Math a Discrete Random Variables
STATISTICS POINT ESTIMATION
10.2 Regression If the value of the correlation coefficient is significant, the next step is to determine the equation of the regression line which is.
CHAPTER 2 Modeling Distributions of Data
CHAPTER 2 Modeling Distributions of Data
Psychology 202a Advanced Psychological Statistics
Surveys and Presenting Results
Introduction to Summary Statistics
(re. Zikmund, Chapter 14). (re. Zikmund, Chapter 14)
Hypothesis Testing: Hypotheses
عمل الطالبة : هايدى محمد عبد المنعم حسين
Introduction to Summary Statistics
ANATOMY OF A CONFIDENCE INTERVAL FOR m WHERE n 30
Coefficient of Determination and Standard Error of the Estimate.
Variance Variance: Standard deviation:
5.3 The Central Limit Theorem
Introduction to Summary Statistics
12/1/2018 Normal Distributions
Standard deviation and the normal curve
Correlation and Regression-III
Estimating the Value of a Parameter Using Confidence Intervals
LESSON 18: CONFIDENCE INTERVAL ESTIMATION
CHAPTER 2 Modeling Distributions of Data
Sampling Distributions
CHAPTER 2 Modeling Distributions of Data
THE NORMAL DISTRIBUTION AND THE 68–95–99.7% RULE
CHAPTER 2 Modeling Distributions of Data
Making Decisions about a Population Mean with Confidence
SUMMARISING NUMERICAL DATA
CHAPTER 2 Modeling Distributions of Data
CHAPTER 2 Modeling Distributions of Data
CHAPTER 2 Modeling Distributions of Data
Chapter Outline Inferences About the Difference Between Two Population Means: s 1 and s 2 Known.
Sampling Distributions (§ )
CHAPTER 2 Modeling Distributions of Data
Estimating Population Parameters Based on a Sample
Modes and Modal Classes
Describing Location in a Distribution
Sampling Distributions
CHAPTER 2 Modeling Distributions of Data
Section 9.2: Sample Proportions
Remaining 10.1 Objectives State in nontechnical language what is meant by a “level C confidence interval” Explain what it means by the “upper p critical.
ELEMENTARY STATISTICS, BLUMAN
CHAPTER 2 Modeling Distributions of Data
Presentation transcript:

Continuous improvement in predictive maintenance RULE = Remaining useful life estimate It is commonly called the "Remaining Useful Life Estimate" or by the acronmym "RULE". One performance measure of a predictive maintenance program is the spread of the distribution around the mean (i.e. around the RULE). This spread  is quantified by the standard deviation. Conditional MTBF Continuous improvement in the RULE occurs over time as more experience is gathered. Not only is the RULE adjusted, but the spread narrows. Is the well-known MTBF, except that it is measured from the current moment. That is, the moment when one needs to make an on-condition maintenance decision. And narrows further. Improving RULE The RULE improves Increasing confidence Confidence in prediction increases in a measurable way so that it may be reported as a CBM KPI. Conditional Density Function Continuous improvement in predictive maintenance t0 Working age Current time

Conditional Density in EXAKT