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Performing FMEA Using
Ontologies
The paper aims to introduce an approach that integrates a technique of
knowledge engineering (Ontologies) and a technique of quality engineering
(Failure Mode and Effects Analysis). An approach will be set up that shows
the potentials of combining IT-based systems of knowledge and quality
engineering. Particularly with regard to the quality engineering technique,
the paper aims to demonstrate the advantages of this approach. |
Expanded FMEA
(EFMEA)
The main FMEA objective is the identification of ways in which a product,
process or service fail to meet critical customer requirements, as well as
the ranking and prioritization of the relative risks associated with
specified failures. The effectiveness of prioritization can be significantly
improved by using a simple graphical tool, as described by the authors.
Evaluation of the adequacy of correction actions proposed to improve
product/process/service, and the prioritization of these actions, can be
supported by implementing the procedure proposed here, which is based on the
evaluation of correction action feasibility. The procedure supports
evaluation of both the feasibility of a corrective action implementation and
impact of the action taken on failure mode. |
Using FMEA for early
robustness analysis of Web-based systems
Time pressure and quality issues are two main challenges facing today’s web
development professionals. To achieve quick development of high quality
systems, a lot of methods and techniques have been proposed. A widely
recognized strategy in current practice is to emphasize early quality
assurance techniques, as the late detection of defects are well known to be
expensive and time-consuming. In this paper we take robustness as a
critically important quality attribute, and propose a general framework for
conducting early robustness analysis for web-based systems, based on
Jacobson’s analysis method and FMEA (failure mode and effect analysis). |
COST BASED FAILURE MODES
AND EFFECTS ANALYSIS (FMEA) FOR SYSTEMS OF ACCELERATOR MAGNETS
The proposed Next Linear Collider (NLC) has a proposed 85% overall
availability goal, the availability specifications for all its 7200 magnets
and their 6167 power supplies are 97.5% each. Thus all of the electromagnets
and their power supplies must be highly reliable or quickly repairable.
Improved reliability or repairability comes at a higher cost. We have
developed a set of analysis procedures for magnet designers to use as they
decide how much effort to exert, i.e. how much money to spend, to improve
the reliability of a particular style of magnet. We show these procedures
being applied to a standard SLAC electromagnet design in order to make it
reliable enough to meet the NLC availability specs. First, empirical data
from SLAC’s accelerator failure database plus design experience are used to
calculate MTBF for failure modes identified through a FMEA. Availability for
one particular magnet can be calculated. Next, labor and material costs to
repair magnet failures are used in a Monte Carlo simulation to calculate the
total cost of all failures over a 30-year lifetime. Opportunity costs are
included. Engineers choose from amongst various designs by comparing
lifecycle costs. |
Factors
Affecting Error and Event Probabilities
The model proposes three components that make human task performers
resilient to error: situational awareness, risk perception, and knowledge. |
FAILURE MODE
IDENTIFICATION THROUGH CLUSTERING ANALYSIS
Research has shown that nearly 80% of the costs and problems are created in
product development and that cost and quality are essentially designed into
products in the conceptual stage. Currently failure identification
procedures (such as FMEA, FMECA and FTA) and design of experiments are being
used for quality control and for the detection of potential failure modes
during the detail design stage or postproduct launch. Though all of these
methods have their own advantages, they do not give information as to what
are the predominant failures that a designer should focus on while designing
a product. This work uses a functional approach to identify failure modes,
which hypothesizes that similarities exist between different failure modes
based on the functionality of the product/component. In this paper, a
statistical clustering procedure is proposed to retrieve information on the
set of predominant failures that a function experiences. The various stages
of the methodology are illustrated using a hypothetical design example. |
Risk –Informed Regulation of
Marine Systems Using FMEA
The marine industry is recognizing the powerful techniques that can be used
to perform risk analysis of marine systems. One technique that has been
applied in both national and international marine regulations is Failure
Mode and Effects Analysis (FMEA). This risk analysis tool assumes a failure
mode occurs in a system/component through some failure mechanism; the effect
of this failure is then evaluated. A risk ranking can be developed in a more
detailed variant of FMEA called Failure Mode and Effects Criticality
Analysis (FMECA). |
Using a
Failure Modes, Effects and Diagnostic Analysis (FMEDA) to Measure Diagnostic
Coverage in Programmable Electronic Systems.
One of the key issues in the quantitative evaluation of programmable
electronic systems is the diagnostic capability of the equipment. This is
measured by a parameter called the Coverage Factor, C. This factor can vary
widely. The range of possible values is often the subject of great debate.
Within limits, the diagnostic coverage factor can be calculated by knowing
which component failure modes are detected by diagnostics. An extension of
the Failure Modes and Effects Analysis (FMEA) can be used to show this
information. This extension, called a Failure Modes, Effects and Diagnostic
Analysis can serve as a useful design verification tool as well as a means
to provide more precise input to reliability and safety modeling. |
Create a
Simple Framework To Validate FMEA Performance
Any Green or Black Belt should be able to use the information in this
article to explain to management why an FMEA validation process is a
valuable tool that will produce both quality improvement and real profit
enhancing results. |
Using Health Care Failure
Mode and Effect Analysis™: The VA National Center for Patient Safety’s
Prospective Risk Analysis System
The authors describe the prospective risk assessment method currently being
rolled out throughout the Veterans Affairs health care system. |
Idea Paper: A
Failure Analysis Matrix
The goal of this dissertation is the creation of a usable and useful model
for prioritizing solutions to potential failures in information systems.
Sincell et al. (1998) pointed out that many benefits of FMEA can be obtained
by alternative methods. Hindson, Cook, and Kochhar (1997) stated that many
benefits of FMEA can be obtained without formally using the tool. The
dissertation's new model will be called a failure analysis matrix (FAM). |
New Techniques for Failure
Analysis and Test Program Design
This paper discusses a currently proposed technique (sensitivity analysis)
for analog fault analysis and describes several new software techniques
already in use to perform analysis, diagnosis, and isolation of failures in
analog and mixed-signal circuits and systems. Unique methods and algorithms
for schematic entry, setting of failure characteristics, definition of test
strategies, recording of simulation-based measurements, reduction of
time-constrained simulation problems, creation of fault trees, and test
sequencing are all discussed. |
Prediction and Diagnosis of
Propagated Errors in Assembly Systems Using Virtual Factories
Large-scale automated assembly systems are widely used in automotive,
aerospace and consumer electronics industries to obtain high quality
products in less time. However, one disadvantage of these automated systems
is that they are composed of too many working parameters. Since it is not
possible to monitor all these parameters during the assembly process, an
undetected error may propagate and result in a more critical detected error.
In this paper, a unique way of detecting and diagnosing these types of
failures by using Virtual Factories is discussed. A Virtual Factory was
developed by building and linking several software modules to predict and
diagnose propagated errors. A multi-station assembly system was modeled and
a previously discussed ‘‘off-line prediction and recovery’’ method was
applied. The obtained results showed that this method is capable of
predicting propagated errors, which are too complex to solve for a human
expert. |
Combining Functional and Structural
Reasoning for Safety Analysis of Electrical Designs
Increasing complexity of design in automotive electrical systems has been
paralleled by increased demands for analysis of the safety and reliability
aspects of those designs. Such demands can place a great burden on the
engineers charged with carrying out the analysis. This paper describes how
the intended functions of a circuit design can be combined with a
qualitative model of the electrical circuit that fulfils the functions, and
used to analyse the safety of the design. FLAME, an automated failure mode
effects analysis system based on these techniques, is described in detail.
FLAME has been developed over several years, and is capable of composing an
FMEA report for many different electrical subsystems. The paper also
addresses the issue of how the use of functional and structural reasoning
can be extended to sneak circuit analysis and fault tree analysis. |
SCENARIO-BASED FMEA: A LIFE
CYCLE COST PERSPECTIVE
Failure Modes and Effects Analysis (FMEA) is a method to identify and
prioritize potential failures of a product or process. The traditional FMEA
uses three factors, Occurrence, Severity, and Detection, to determine the
Risk Priority Number (RPN). This paper addresses two major problems with the
conventional FMEA approach: 1) The Detection index does not accurately
measure contribution to risk, and 2) The RPN is an inconsistent
risk-prioritization technique. The authors recommend two deployment
strategies to address these shortcomings: 1) Organize the FMEA around
failure scenarios rather than failure modes, and 2) Evaluate risk using
probability and cost. The proposed approach uses consistent and meaningful
risk evaluation criteria to facilitate life cost-based decisions.
KEYWORDS: FMEA, FMECA, Risk Priority Number (RPN), reliability, risk
management |
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