Anticipatory Failure Determination (AFD) is a method for analyzing, predicting and eliminating failures in systems, products, and processes.. It has the objective of identifying and mitigating failures. Rather than asking developers to look for a cause of a failure mode, it reverses the problem by asking developers to view the failure of interest as the intended consequence and try to devise ways to assure that the failure always happens reliably.

 

Anticipatory Failure Determination is an application of I-TRIZ specifically designed for:

 
  • Failure Analysis -- A systematic procedure for identifying the root causes of a failure or other undesired phenomenon in a system, and for making corrections in a timely manner.
  • Failure Prediction -- A systematic procedure for identifying beforehand, and then preventing, all dangerous or harmful events that might be associated with a system.

 

 

How is does AFD® differ from other failure analysis methods?

 

Systems in which failures have occurred -- or might occur -- are zones of "poor information." The reason? Little information is published about negative effects with unknown causes, or about the causes of dangerous or harmful failures. In fact, such information is often intentionally concealed. Without adequate information, it is very difficult to identify the root causes (existing or possible) of a failure. One must rely on guesswork -- as is the case with traditional failure methods. AFD overcomes this obstacle with a core 3-step model, providing unprecedented effectiveness:

 

 

 

STEP 1: INVERT THE PROBLEM

 

For Failure Analysis: Instead of asking "Why did the failure happen?" ask instead: "How can I make it happen?" For Failure Prediction: Instead of asking "What failures might happen?" ask instead: "How can I make all possible dangerous or harmful failures happen?" Now we can employ a wealth of available information based on what inventors have profited from since the dawn of mankind: how to make something happen. In other words, we have converted a failure problem into an inventive problem.

 

 is available:

 

  • Are the required substances and materials present?
  • Is the necessary energy available or producible?
  • Is there time in which the failure can "mechanize"?
  • Is the space available for the failure to take place?
  • . . . and more

 

THE RESULT: NO MORE GUESSING

 

 

 

 

AFD AND OTHER TECHNIQUES

 

The principle difference between AFD and conventional techniques, such as Failure Mode and Effects Analysis (FMEA) and Hazard and Operability Analysis (HAZOP), is the perspective from which potential failures are determined. With conventional techniques, the process of failure prediction proceeds linearly from an articulation of the system's function(s) to what may occur if there is a failure (absence) in delivering these functions. In other words, the analytical line of reasoning follows design intent. Given a potential failure, the effect of the failure, the probability that it will occur, and the ability to detect it are determined. Once these parameters are quantified (often very subjectively), a calculation of risk is made. If the risk is determined to be unacceptably high, changes in design or in detection capability can be suggested. 

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