1400 Preston Rd #400
Plano, TX 75093
USA
Reliability Engineering Principles Training for Managers Course Description
Reliability Engineering Training for Managers, covers the basic principles, concepts, practical problem solving techniques, and a brief review of statistical calculations. Because this training is designed for non-engineers who often don’t have a strong background in math, the focus of training is mostly on principals of reliability engineering and problem solving practices and less on statistics and mathematical models. Reliability Engineering Principles (REP) Training hands-on training will assist you to enhance your business performance by cutting the costs associated with unreliability. REF training will teach you how to apply reliability tools to identify and resolve cost issues rather than functioning as technical miracles.
Learn About:
- Mean time frame between failures events
- TPM relationship with reliability principles
- Analyzing reliability data
- Weibull failure
- Monte Carlo simulations
- Pareto distributions
- Fault tree analysis
- Design review
- Load/strength interactions
- Sudden death and simultaneous testing
- Reliability growth models and displays
- Reliability strategies and standards
- Reliability audits
- Bathtub curves
- Effectiveness: availability, reliability, maintainability, and capability
- Weibull, normal, & log-normal probability plots
- Decision trees merging reliability and costs
- Critical items highly impacting safety/costs
- Failure rate
- Prediction
- Availability vs. Reliability
- MTTF, MTBF, and MTTR
- FMEA
- FMECA
- FTA
- RBD
- QFD
- Reliability testing strategies
- Accelerated testing
- Failure recording, analysis, and corrective action
- Contracting for reliability
- Management’s role in reliability improvements
TONEX REP Training Framework
- Long on concepts and problem solving techniques, short on math and statistics
- Fun, interactive, dynamic class
- Including labs, group activities, and hands-on workshop
Audience
Reliability Engineering Principles Training is a 3-day course designed for:
- Project managers
- Business owners
- Safety managers
- Quality managers
- Reliability managers
- Production/design managers
- Warranty analysts
- Problem-solving team personnel
- Asset reliability managers
- Capacity and predictive maintenance managers
Training Objectives
Upon the completion of Reliability Engineering Principles training for non-engineers, attendees are able to:
- Describe the bases, rationale, and concepts of reliability engineering
- Use the most relevant probability distribution to measure model times to failure
- Articulate the relationship between the time to failure distribution, the reliability function, and the hazard rate
- Estimate reliability values from test data and identify confidence limits on the results
- Use required tools to ensure a reliable product
- Explain the differences between assessing the reliability of a fixable and non-fixable systems
- Derive and sustain a strategic reliability engineering
- Derive control protocols to reduce risks and increase asset use
- Develop predictive strategies
- Construct an efficient predictive maintenance process
- Establish a root cause analysis procedure to reduce the wasted time, increase productivity, and a culture of continuous improvement
Course Outline
Overview of Reliability Engineering Principals
- What are the reliability engineering principals?
- Why reliability is important?
- Impact of reliability on the system
- Reliability dictionary
- Why would you want to enhance reliability?
- Reliability is art as well as science
- Predictive techniques
- Reliability improved system features
- Availability
- Maintenance management policies
Reliability Risk Assessments
- Engineering techniques
- Reliability hazard analysis
- Failure mode and effects analysis (FMEA)
- Fault tree analysis (FTA)
- Reliability Centered Maintenance (RCM)
- Load and material stress
- Fatigue and creep analysis
- Human error analysis
- Manufacturing defect analysis
- Reliability testing
Measuring Reliability
- Requirements
- The bathtub curve
- Life distributions
- Distribution functions
- Particular life distributions
- Modeling system reliability
- Series systems
- Active redundancy
- M-out-of-N redundancy
- Reliability prediction
Design for Reliability (DoE)
- Life cycle
- Reliability approaches
- Top-down methods
- Bottom-up methods
Reliability Engineering Actions
- Maintenance Prevention
- LCC Assessment
- Positive Maintenance
- Capital Equipment Replacement
- Cost/effective estimation
Working with Reliability Engineering Tools
- Attaining reliability associated data
- Reliability indices
- Decision trees
- Availability concepts, effectiveness equation and costs
- Probability plots
- Bathtub curves
- Pareto distributions and critical items lists
- Reliability block diagrams
- FMEA
- FMECA
- FTA
- Design reviews
- Vendor and parts control
- Thermal analysis (TA)
- Environmental stress screening (ESS)
- Crow/AMSAA reliability growth models
- Reliability strategies
- Benchmarking reliability
Essential Principles of Reliability Investigation
- Non-Probabilistic Reliability Methods
- Probabilistic Reliability Methods
- Historical Frequencies
- Manufacturers’ survivorship/mortality curves
- Expert Opinion Elicitation (EOE)
Warranty and Maintenance
- Product warranties review
- A review of maintenance
- Warranty and corrective maintenance
- Warranty and preventive maintenance
- Extended warranties and service contracts
- Stochastic point processes
- Perfect maintenance
- Minimal repair
- Imperfect or worse repaid
- Complex maintenance policy
- Reliability growth
Preventive Maintenance Models
- Block replacement models
- Age replacement models
- Ordering models
- Inspection models
Maintenance and Optimum Policy
- Replacement policies
- Preventive maintenance policies
- Inspection policies
Accelerated Life Testing
- Design of accelerated life testing plans
- Accelerated life testing models
- Extensions of the proportional hazards model
Human and Medical Device Reliability
- Human and medical device reliability terms and definitions
- Human stress—performance effectiveness, human error types, and causes of human error
- Human reliability analysis methods
- Human unreliability data sources
- Medical device reliability related facts and figures
- Medical device recalls and equipment classification
- Human error in medical devices
- Tools for medical device reliability assurance
- Data sources for performing medical device reliability
- Guidelines for reliability engineers with respect to medical devices
Probabilistic Risk Assessment
- Probabilistic risk assessment methodology
- Engineering risk vs environmental risk
- Risk measures and public impact
- Transition to risk-informed regulation
- Some successful probabilistic risk assessment applications
- Comments on uncertainty
- Deterministic, probabilistic, prescriptive, performance-based
Random-Request Availability
- System description and definition
- Mathematical expression for the random-request availability
- Numerical examples
- Simulation results
- Approximation
Failure Reporting and corrective action system (FRACAS)
- Definition of FRACAS
- Closed Loop Reporting System
- FRACAS Procedure
- Failure Identification
- FRACAS Process
- FRACAS Responsibilities
- Keys players
- How to prepare it
- Role of Engineering Managers and Program/ Project Managers
- Role of Reliability and Maintainability Engineers
- System Maintainers and Production/ QA Staff
- Integration & Test Engineering
Reliability Management
- Key aspects of reliability management
- Reliability plan elements
- Best practices