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Purpose Creativity is an important skill for design teams to reach new and useful solutions. Designers often use one or more of creativity and innovation techniques (CITs) to achieve the desired creative potential during new product development (NPD). The selection of adequate CITs requires considerable expertise, given the multiple application contexts and the extensive number of techniques available. The purpose of this study is to present a creativity support system able to manage this amount of information and provide valuable knowledge to improve NPD. Design/methodology/approach This study presents a knowledge-based system prototype using artificial intelligence (AI) to support knowledge management on the selection of CITs for design. CITs assertion is modelled through a double inference process using five categories, correlating over 500 different entry scenarios to 24 implemented CITs. The techniques are classified according to: design stage, innovation focus, team relationship, execution method and difficult of use. Prototype outputs explanations on the inference process and chosen techniques information. Findings To demonstrate the system scope, two opposite design cases are presented. The system was validated by experts in knowledge management and mechanical engineering design. The validation process demonstrates relevance of the approach and improvement directions for future developments. Originality/value Though literature contains toolkits and taxonomy for CITs, no work applies AI to identify design scenarios, select best CITs and instruct about their use. Validators reported to know less than half of the available techniques, showing a clear knowledge gap among design experts.

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Organizações devem aprimorar sua habilidade criativa para melhor atender às necessidades dos usuários. Técnicas de criatividade auxiliam no processo de inovação e no desenvolvimento de ideias adequadas. Cada técnica possui situações de uso apropriadas e a seleção delas requer experiência do facilitador. Como um recurso raro, expertise humana pode ser representada utilizando Inteligência Artificial. O protótipo desenvolvido identifica o cenário de projeto através de perguntas e correlaciona técnicas de criatividade adequadas. A fim de obter de um software capaz de mitigar possíveis erros de uso, investigou-se aspectos de usabilidade através de questionários com estudantes e especialistas.