Watch our New YouTube Videos Recorded at the Naval Post Graduate School in Monterey California about Prognostics and Health Management at:
and about Condition-Based Maintenance, Systems Engineering Methodolgy and the Systems Engineering Process at:
Prognostic technology is for preventing catastrophic failures rather than react to them after they occur. It includes using predictive algorithms that relate past behavior to future behavior with certainty.
Our algorithms illustrate the prognostic markers present in normal appearing diagnostic data from fully functional equipment or products for trained personnel to convert equipment or product performance data into a measurement of the remiaming usable life.
Measuring equipment or product usable life from common performance data replaces the product reliability paradigm that says that 100% reliability is unachievable. This reliability paradigm was created decades ago when probability reliability analysis engineering was adopted hoping to stop premature equipment failures.
Probabilistic reliability is the likelihood of success or failure, which is unrelated to real world usable life.
Prognostic technology was created by companies wanting to identify the products that were going to fail prematurely that often frustrated customers and reduced profits.
100% "measured" reliability means that equipment and products have had their reliability, physically measured invasively, using prognostic algorithms.
Prognostic algorithms illustrate the early signs of premature failure/aging also known in different industries by a variety of other lables such as accelerated aging, prognostic markers, prognostic identifiers, failure precursors, deterministic behavior, cannot duplicates (CND), no failure found (NFF), no failure identified (NFI) and retest-OK (RTOK).
We offer the only prognostic algorithms for equipment and products working in a full RF and/or electrical noise environment that corrupts the integrity of the product data used for completing a prognostic analysis to measure and confirm remaining usable life.
PREDICTIVE SERVICES HAS MULTI-INDUSTRY APPLICATIONS
Police - Predictive policing is used by cities with less police personnel than desired. Both Santa Cruz and Los Angeles California have adopted a vigorous predictive policing program with great success. Predictive policing is the future of police work but was not tried until the financial crisis forced cities to drastically reduce their police force. Itis based on the anlysis of past crimes, their location and time of day, officers are assigned locations with the highest likelihood of a crime occurring. Predictive policing entails becoming less reactive and more proactive. The predictive vision moves law enforcement from focusing on what has happened to focusing on what will happen and how to deploy resources in front of crime effectively, thereby changing outcomes.
Predictive Medicine - Predictive diagnostics using a prognostic analysis predicts when future disease will occur with certainty, so that health care professionals and the patient can be proactive in instituting lifestyle modifications and increased physician surveillance. Predictive medicine is intended not for those with disease but for individuals or those that have not yet acquired a disease. Its purpose is to determine whether a disease will occurand if if so chnages can be implemented to stop the disease from occurring. Predictive medicine is the next level of a proactive medical program, designed to stop disease and illness before they occur thus lowering the total medical cost of a nation by eliminating disease through predictive diagnostics techniques.
Semi-Conductor Industry - Product reliability is measured before shipping with a prognostic analysis or embedded algorithms so that the company will know with certainty that their products left the factory fully operational and will function normally for at least one year. Companies that are selling assemblies with several chips that are integrated into other equipment can stop returns, by ensuring that their products do not fail prematurely.
Telecommunications Industry - Companies that produce high-reliability (99.999% availability) public telephone switching network (PTSN) embedded computer servers use prognostic technology to identify the internal PTSN computer server equipment that will be failing in the near future for replacement. This allows the high companies such as Avaya, AT&T and Verizon to meet the stringent industry wide 99.999% availability requirement because equipment that is replaced before it fails is not considered a failure.
Aerospace & Space Industries: Companies are embedding data-driven and model-based prognostic algorithms in equipment so that products and equipment can self prognose their remaining usable life. This offers a new paradigm in maintenance we call condition-based maintenenace, decreasing life cycle cost while increasing reliability to near perfect.
Satellites and launch vehicles of all types still suffer from premature equipment failures getting to space and working in space. These often result in severe financial losses. Today's satellites and launch vehicle were not designed to use prognostic technology but our data-driven prognostic algorithms were developed specifically to search the space vehicle factory test data to identify the on-board equipment that will fail prematurely for replacement by conducting a prognostic analysis of the data. A prognostic analysis is a scientific analysis that illustrates the prognostic markers that indicate the unit will fail prematurely.
For satellites and spacecraft already in space, a prognostic analysis using equipment telemetry will identify the equipment that will be failing within one year of the analysis, stopping surprise equipment failures that often remove spacecraft from service allowing equipment failures to be managed to a positive conclusion.
For satellites that use "single string" equipment, a prognostic analysis completed while the equipment is still on the ground will identify the equipment that will fail prematurely after arriving on orbit for replacement, eliminating the risk for quicker, faster, better, cheaper missions.
Defense Industry: When soldiers and machines are ordered to start marching, the first actions include the shipping of a majority of their vehicles back to the base for repair. Defense industry can meet the 27 hour requirement for infant mortality failures.
Heavy Equipment Industry: In the large equipment industries , prognostic technology and embedded prognostic algorithms allows the identification of heavy equipment that will be failing in the near future so that it can be replaced at a convenient time. This minimizes equipment downtime that often result in huge financial losses associated with equipment that is unproductive.
Nuclear Power Industry: The equipment used to monitor critical processes in nuclear power plants rely on prognostic algorithms for preventing equipment failures that increase risk and uncertainty in the operations of nuclear power plants that are vital the the community.
Financial and Investment Industries: Prognostic algorithms now replace the stock trader on Wall Street to decide which investment is to be purchased and when it should be sold. Companies using these algorithms report that they are no longer susceptable to the financial losses experieneced using current diagnostic tools and probabalistic data.
The presence of a company or organization's logo on our web site is for an aesthetic reason only. Companies and organizations provide their logos into the public domain and we use them along with our public relations and marketing information to accent our technology potential applications. As long as companies and organizations actively provide their logos to the public domain will will make every effort to use them.
Our web site is for the dissemination of information related to our technology to industries. Our statements, claims and marketing information will be in the best perspective for our company and may not be consistent with the interpretation by all who read them. Failure Analysis is not responsible for visitors to our web sites individual interpretation of our claims, statements and marketing information. We make no attempt to coordinate our statements a=priori with the organizations mentioned in our information before we provide it here.
We welcome all contacts with industry regarding the use of their logos. For those that want to contact us regarding our information, please use the contact information provided on this web site. We will provide a quick and timely response. We hope that any organization wanting to contact Failure Analysis will determine first that their logos are not being made available in the public domain.
Copyright All Rights Reserved Failure Analysis, 2007