Living Reliability in Maintenance
IIR Qatar
Living Reliability in Maintenance
Course Goal
To deliver a comprehensive set of living reliability engineering procedures and to develop skill in their application.
To show how participants, equipped with these procedures and skills, can attain for their organizations an optimal balance of availability, high performance, and reliability, at an affordable life cycle cost, while adhering to all known safety and environmental regulations.
Course Participants
Reliability engineering and operations personnel involved in improving reliability, availability, safety, maintainability and profit performance in existing or proposed process systems and equipment. Participants should have foundation skills in statistical analysis and reliability techniques for equipment.
At the end of the course, the delegates will be able to:
1. Define, measure, and predict reliability
2. Undertake fundamental reliability analysis
3. Improve maintenance performance
4. Track maintenance performance
5. Enable RCM in the day-to-day maintenance context
6. Discover condition monitoring (CBM) variables that are significant failure risk factors
7. Calculate failure probability as a function of condition monitoring data
8. Predict remaining useful life (RUL) with confidence intervals from condition monitoring data
9. Optimize operation and maintenance by combining Monte Carlo simulation and condition based maintenance (CBM)
10. Populate the CMMS work order with the correct information for subsequent reliability analysis.
11. Predict life cycle costs in order to make buy/replace decisions and to determine which equipment or system will create the most value for the business.
12. Analyze system design to determine if projected capacity will meet capital requirement
Reliability Engineering Fundamentals
Information drives the maintenance process. Enterprises devote significant resources to their maintenance information systems. Yet, those systems rarely deliver needed optimal, unambiguous, and verifiable decision support. Reliability engineers are seldom able to analyze their equipment health monitoring and work order databases so as to improve their predictive performance. Benefits derived from a variety maintenance initiatives undertaken over the years are difficult or impossible to prove via current management systems. What element of control does the reliability engineer lack? Participants in this course will learn that the missing process is “living” RCM (LRCM). The topics in this module will introduce the basics upon which the reliability engineer will proceed, methodically and surely to remove all obstacles to the conversion of data to optimal and verifiable maintenance decision models. Topics in this section:
1. The Reliability Engineering Role
2. Knowledge management
3. Workflow oversight
4. Predictive model building, tracking, and continuous improvement
Living Reliability Centered Maintenance (RCM)
The principles of RCM are used to establish "good" maintenance tasks and their frequencies. In the event that no appropriate maintenance task can be found, RCM establishes the requirements, if any, for redesign. RCM identifies those failure modes whose occurrence should notbe prevented. In this section we provide an overview of RCM. Most importantly we identify the activities by which maintenance goals may be achieved through a naturally interactive application of the basics to achieve a process of continuous improvement. The topics to be covered are:
1. Failure Modes and Effects Analysis
1. Functions - Primary and Secondary
2. Functional Failures
3. Failure modes
4. Effects
2. Consequences
1. Hidden failures
2. Health, safety, and environmental consequences
3. RCM Decision Logic
3. Criticality analysis (FMECA)
4. Facilitation methods
5. Living RCM and Continuous Process Improvement
Reliability Statistics
Reliability Analysis (RA) discovers knowledge about failure behavior. Such knowledge reveals itself through samples of data points (called histories or life cycles) acquired at the granularity of the failure mode. Well tried conventional failure codes cannot provide the precision or consistency needed for RA. As a result, most maintenance departments encounter difficulty in converting large amounts of data into verifiable decisions. They rarely achieve a confirmable process of continuous improvement. It is to this gap that we address this module. This module will convey to participants the procedures of “living reliability” that link knowledge to the maintenance work order. Each significant work order will, as a result of that relationship, contribute a useable data point to the analysis of reliability. Why analyze reliability? Because it is the prerequisite to measurable, systematic improvement in maintenance performance. The topics to be covered:
1. The nature of data
2. The failure distribution (age-reliability relationship)
1. hazard, survival, cumulative distribution representations of the age-reliability relationship
2. Plotting the age-reliability relationship
3. Weibull analysis
1. Complex systems
4. Suspended data
5. Linear regression, standard Deviation, MTBF and MTTF
3. Preventive maintenance optimization
4. Reliability predictions
5. Weibayes
Condition Based Maintenance
Where “applicable” and “effective”, CBM is the preferredform of maintenance. By applicable we mean that each CBM program must be practical, realistic, and technically feasible. By effective we mean that CBM is worthwhile. That is it must result in increased reliability (availability, productivity, quality, safety, economy) without exceeding an environmental regulation. Maintenance organizations seek condition based maintenance solutions that are applicable and effective because such methods will usually be less costly, less intrusive, and more conservative than age or time based maintenance (TBM). Yet CBM has proven an elusive target. A systematic method for selecting condition indicators and their action triggering limits is not obvious from the data. This module will present participants with the methodology for identifying significant condition indicators, finding the precise relationship of those indicators to failure probability, and applying an optimized verifiable on- condition decision. Topics to be covered:
1. Extending the age-reliability relationship to multiple dimensions
2. Internal and external variables and their influence on failure probability
3. The conditional density function, remaining useful life estimation (RULE), and confidence intervals
4. The elusive P-F Interval and RCM II special cases.
5. Tracking CBM predictive capability
6. Tracking CBM effectiveness.
7. Implementing a living RCM workflow through leadership.
Life Cycle Cost Analysis
Maintenance expenditure often amounts to many times the initial cost of the asset. Although an asset may be constructed with a particular design life, in reality it often remains in service well beyond the design life. Such assets require a balanced view between maintenance strategies and renewal/rehabilitation. The reliability engineer must apply life cycle cost calculations to evaluate the appropriateness of a maintenance strategy and the optimal point for renewal. The process requires an assessment based on the expected performance of the asset including the consequences and probabilities of failures occurring, and the level of expenditure in maintenance to keep the asset functioning acceptably, and to avert disaster. The topics to be included:
1. LCC Philosophy and Benefits
2. Financial Statements
3. The Cost of Money
4. ROI & ROA
5. Life Cycle Cost Calculations, the equivalent annualized cost of options
Root Cause Analysis (RCA)
Often, particularly in complex systems there is no obvious link between observed undesirable conditions or events and a deep understand of their root causes. RCA is a class of techniques that guide us to one or more root causes and their solutions. A variety of techniques are used to encourage the trouble-shooter to avoid assumptions and logic traps, but instead to trace the chain of causality in direct increments from the effect through various layers to one or more root causes. The topics of this module are:
1. Examples of RCA techniques improving OEE
2. Logic Trees Discuss
3. Causal Factor Mapping
4. Pareto analysis to select chronic failures to address with RCA
5. Obtaining management support for RCA
Availability Simulation
Reliability engineers use Monte Carlo simulation methods to mathematically model a complex system and predict its availability, reliability, costs, spares, and resource consumption. Proper application of this tool requires an understanding of its principles. This module will explain step-by-step how to perform a Monte Carlo simulation. It will demonstrate the analysis techniques, what inputs are required, and how to use the information obtained from the analysis. The topics are:
1. Reliability Block Diagrams
2. Series and Parallel Systems
3. Management Considerations
4. System Complexity
5. Simulation Benefits
Human Reliability
In the universe of failures, failures caused by the human operating or maintaining equipment constitute a great percentage of the total failures, especially the ones with catastrophic consequences. Although human failure is said to be random it usually has specific (latent) causes associated with the organization’s policies and procedures. This module is directed to presenting the basics of designing effective maintenance procedures focused on reducing the failure frequency and time to repair, reducing infant mortality, eliminating reworks and improving the overall quality of the maintenance work performed. The topics of this module are:
1. Knowledge and skills (job descriptions, benchmarks, training, verification, and motivation)
2. Maintainability and operability (ergonomy, safety, accessibility, modularity, simplicity, standardization)
3. Maintenance process mapping (sequence, grouping, engineering, planning, scheduling, execution, verification)
4. Procedure based maintenance (effectiveness, objective setting, formulating, certifying)
Reliability Centered Design (RCD)
New projects confront an unprecedented range of safety, environmental, regulatory, technological, and business challenges. New technology, reliability improvement, the need to reduce operating expenditures calls for the application of the rigour of RCM to front end engineering and design. Topics are:
1. Purpose of RCD
2. Importance of RCD
3. RCD Process
4. RCD FMEA
5. Ramifications of RCD
Failure Reporting, Analysis and Corrective Action System (FRACAS)
A FRACAS closes the feedback loop from user to manufacturer in a purposeful coordination of information flow. The user captures predetermined data related to problems encountered with the machinery and related software. Design and manufacturing expertise are brought to bear on each issue in order apply a permanent resolution, called a corrective action, to the underlying cause. Topics are:
1. Policies and Procedures
2. Basic Elements
3. Failure Reporting
4. Roles and Responsibilities
5. Analysis Methods Database Elements