Description

Course title: Optimizing Equipment Maintenance and Replacement Decisions

 

The course answers the important questions in asset replacement strategy:

  • Should we keep running or should we replace the asset now?
  • What are the number of spare parts we should have?
  • What is the optimal time of replacement? Is it a software for that?
  • How to use the data to make condition based replacement?
  • How to find the optimal time when the operation cost is increasing?
  • How to optimize the emergency spare requirements?
  • How to determine optimum asset life?
  • How to decide whether to rebuild or replace your equipment to minimize the life cycle costs?
  • How to make alarm function to optimize condition based replacement?
  • How to make Data-driven Decision to optimize asset maintenance?

If you need answers for these questions, this course is for you.

 

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Course outlines:

  1. Physical Asset Management & Survival Analysis Concepts
  • From Maintenance Management to Physical Asset Management
  • Challenges of physical asset management
  • The maintenance types
  • Total Productive Maintenance
  • Reliability Centered Maintenance
  • Survival Life data Analysis
  • The 4 functions
  • Reliability distributions
  • Exponential distribution
  • Weibull distribution
  • Bath-Tub Curve
  • Failures patterns
  1. Exercise in Analyzing Component Failure Data Using the Weibull Distribution
  • Estimating the Weibull Parameters
  • Using Median Rank Tables
  • Using Many Software
  1. Dealing with Censored Data, the 3-Parameter Weibull, and Fitting Test
  • Censoring Data
  • Estimating the Location Parameter in the Weibull Distribution
  • Checking the Goodness-of-Fit of the Distribution
  1. Preventive Maintenance & Spare Parts Replacements
  • Deterministic and Stochastic Replacements
  • Optimal Replacement Times for Equipment Whose Operating Cost Increases with Use
  • Block Replacement Policies
  • Age-Based Replacement Policy
  • Component Replacement Procedures including Glasser’s Graph
  • Repairable systems replacement concept
  1. Case Studies in Component Preventive Replacement
  • Using graphical and software methods
  1. Spare parts provisioning
  • Fast moving spares
  • Emergency (insurance) spares
  • Case studies in spares provisioning
  1. Hands-On Use of PC Software for Preventive Replacement Strategies
  2. Asset Health Monitoring & Inspection
  • Inspection Intervals to Maximize Profit
  • Maximizing Equipment Availability
  • Optimizing CBM Decisions
  • The Proportional Hazards Model
  • Blending Hazard and Economics: Optimizing the CBM Decision
  • Optimization of Condition-Based Maintenance Procedures
  • Role of software for CBM optimization
  • Many Case studies
  1. Optimal Replacement Interval for Capital Equipment
  • Estimating the Interest Rate Appropriate for discounting
  • Present-Value Calculations
  • The effects of Inflation in the Analysis
  • Calculating the Equivalent Annual Cost (EAC)
  1. Economic Life of Capital Equipment
  • The “Classic” Economic Life Model
  • The Repair-vs-Replace Decision
  • Life-Cycle Costing LCC
  • Technological Improvement
  1. Use of PC Software for Capital Equipment Replacement Analysis
  2. Data- Driven Maintenance
  • Data Analysis and Knowledge Extraction in Maintenance
  • Decision making based on the machine learning, data mining Logical Analysis of Data.
  • Case Study shows the comparison between the traditional reliability analysis technique and decision making based on the machine learning, and data mining.

The instructor: DR. Yasser shaban

Course duration: 30 Hours – 10 Lectures