The Theory of Inventive Problem Solving (TRIZ) has been widely employed in the fields of business and industry. The degree of difficulty in a problem usually depends on its description and degree of standardization. Using an appropriate description and maintaining standardization can minimize the scope of the problem and significantly increase the likelihood of resolving it successfully. Most problems can be resolved easily with innovative principles and standard resolutions. However, non-standard complex invention problems must be analyzed and resolved using the Algorithm for Inventive-Problem Solving (ARIZ), which contains numerous systematic tools of the TRIZ. This study applies the behavioral properties of a Petri net to the description of a problem to establish a problem model and perform scenario analysis. When describing the problem, the developer was provided with suitable directions of thinking or with wrong messages for reference. To create more specific effects on the varied problem models and scenario analyses of the TRIZ, this study combines the TRIZ with Petri nets and Markov chains to help new learners of TRIZ or professional researchers obtain appropriate resolutions rapidly.
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