Isak Bukhman and Stephen Brown
To identify the right problem and solve it quickly, or to invent at the highest level of creativity, engineers need to leverage scientific and technical knowledge, often beyond their immediate personal experience or field of expertise. Engineers must be able to find appropriate concepts from among thousands of scientific effects and from tens of millions of articles, patents, and other sources of information.
Although Altshuller identified this “informational fund” as an essential component of the TRIZ methodology, little could be done until the sources became digitized and readily accessible. Still, their promise remained unfulfilled due to ineffective retrieval technologies. Traditional keyword search methods return documents rather than concepts, and lack the precision needed to navigate right to the passage that addresses the engineer’s functional requirement.
Through new breakthroughs in computational linguistics, it is now possible to generate, from virtually any digitized information source, a Cause-Effect Experience Base of semantically extracted concepts that aggregates and generalizes patterns of effects, or failure signatures, and their causes. Over 15 million patents have already been analyzed. When integrated into a Root Cause or FMEA workflow, such an Experience Base enhances and accelerates problem understanding by acting as a virtual subject matter expert.
Using the improvement of artificial bone scaffolds as a case study, this presentation illustrates how such a Cause-Effect Experience Base can be easily generated and then tapped to leverage technical insights. Altshuller’s information fund is now a usable reality.