A Model Used for the Generation of Innovative Construction Alternatives

• Main Authors: Wu, Chih-Ming, 吳誌銘
• Other Authors: Yu, Wen-Der
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/96177933989877361221

博士 === 中華大學 === 科技管理博士學位學程 === 100 === Previous research on the innovation of construction technologies includes constructability analysis and process simulation. Such approaches were limited to existing processes or innovator’s experiences and knowledge, thus are essentially incremental. This research proposes a Model Used for the Generation of Innovative Construction Alternatives (MUGICA) for innovation of construction technologies, which contains two models: a Systematic Technology Innovation Process (STIP) and a Model for Automated Generation of Innovative Alternatives (MAGIA). The STIP model integrates roots cause analysis, function modeling, TRIZ, and computer aided innovation (CAI) to provide a systematic approach for effective construction innovation. The MAGIA model adopts previous technological information stored in the public patent databases as the design knowledge for building the function model of target technology; it is then translated into a genetic operation tree (GOT) for evolution with GA; finally, a computer prototype system was developed for the MUGICA. Four construction technologies are selected as case studies to demonstrate the feasibility and potential of the proposed method for automated innovation of construction technologies. Major results of the current research include: (1) a modeling language for representing construction technologies; (2) an appropriate objective function for guidance of technology innovation; and (3) proposes a model used for the generation of innovative construction alternatives. Future directions for research include: (1) a more suitable fitness function is needed to reflect the objectives set up by the user, e.g., the more sustainable or green solutions; (2) a more powerful computational algorithm is desired, e.g., an algorithm to tackle evolutions of inter-species of candidate innovative alternatives; (3) a more systematic approach for model realization to replace the current manual approach.