Stop learning to innovate through trial and error

Learn TRIZ, a methodology developed by Genrick Altshuller for solving problems more efficiently and intuitively.

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One of the oft encountered problems while applying TRIZ to real world problems is to identify from a large set of promising solution directions, the ones that are most promising, elegant or closest to ideality. This is especially true when the problem can be defined at multiple system levels, each level having multiple paths flowing towards the ideal final result. This paper describes such a situation encountered while analyzing a real world problem (rebar tying) with TRIZ. Steel reinforcement bars are tied together to form grids and reinforce concrete. Rebar tying machines have evolved over the years from pneumatic and mechanical systems to electro-mechanical systems with embedded electronics. TRIZ-based analysis and ideation resulted in a large number of interesting evolution paths for the rebar tying system. However, the question “Which paths would evolution favor” was difficult to answer. TRIZ does offer clues to pre-select the most promising paths in advance, but needs an integrated approach for the same. The paper describes such an integrated approach with the rebar tying case study as reference.




Karthikeyan Iyer (Karthik) is Co-crafter, Founder Director at Crafitti Consulting Private Limited, an innovation research and consulting think tank. In a  career spanning more than a decade, he has pioneered and facilitated the use of structured innovation frameworks like Lean and TRIZ in live business and technology contexts, working especially closely with inventors on patent strategy, analysis and design.
Several of his papers and articles on innovation and strategy have been published in leading online journals. His current areas of interest include innovation culture and chaos theory, open innovation, inventive principles and technology evolution trends. He blogs at http://kartzpot.blogspot.com.

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