段定夫 / Mr. Andy Tuan



段定夫​ / Mr. Andy Tuan

President - Flagship International (Partner of IIA)

Consultant – SEMI Smart Manufacturing Committee


  • MBA – International Business Management

  • BS, Ch.E. – National Tsing Hua University


  • Linx Consulting USA

  • SEMI Taiwan

  • Air Products and Chemicals Inc. USA

  • Merck KGaA Germany

  • Fujitsu Ltd. Japan

  • Merck-Kanto Advanced Chemicals Taiwan



  • As “Big Data Analytics” evolution continuing and the wave of “Industry 4.0” hitting various industry segments, many enterprises have been too eager to jump on the bandwagon and rush to evaluate and deploy various new data analytics technologies without clearly thinking through what they really need and how they can prepare their organizations for implementing all the necessary changes in order to truly extract values of exponentially increasing data in their business operation. 

  • In semiconductor industry segment, fab operation environments are becoming increasingly complex, smarter enterprise-wide data-driven solutions are required in order to overcome various new challenges in both front end and backend fabs. The trend of a step-by-step evolution towards a “smart fab of the future” has taken place and is expected to continue to expand to the rest of the global semiconductor value chain in the upcoming years.

  • However each enterprise in semiconductor value chain has different requirements for data analytics because they are so different from vision, market position, business strategy, factory design, organizational structure, work process, to company culture…etc. One-size-fits-all approach won’t work. The suggested step one for semiconductor value chain players to move toward “smart manufacturing” is to think beyond tactical manufacturing objectives. First they need to define their enterprise level vision and targets (TO BE). And then assess their current baseline data analytics capabilities (AS IS) through a well designed and field-proven  management tool so that enterprises can Identify their gaps and decide priority on analytics strategies and action plans to improve from here (AS IS) to there (TO BE).

  • The goal is that the whole organization can be fully aligned on the strategic direction and each member knows exactly how to better learn and use data analytics to deliver better job performance and drive more insightful decisions to achieve overall business success of the enterprise. 

  • In this co-authored presentation, Analytics Maturity Assessment TM (AMA)  management tool developed by IIA and assisted by Flagship International including DELTA Model and 5 Stages of Analytics Maturity framework will be introduced. Also an semiconductor industry value chain wide implementation by a tailored Syndicated Research Collaboration through SEMI Taiwan Smart Manufacturing Committee will be proposed to the forum audience. 





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