PCBA demand forecasting using an evolving Takagi-Sugeno system

This paper investigates the use of using an evolving fuzzy system for printed circuit board (PCBA) demand forecasting. The algorithm is based on the evolving Takagi-Sugeno (eTS) fuzzy system, which has the ability to incorporate new patterns by changing its internal structure in an on-line fashion. We argue that these capabilities could aid in forecasting dynamic demand patterns such as those experienced in the electronic manufacturing (EMS) industry. An eTS fuzzy system is implemented in the R statistical programming language and is tested on both synthetic and real-world data. To our knowledge, this is one of the first applications of an evolving fuzzy system to forecast product demand. The results indicate that the evolving fuzzy system outperforms competing approaches for the application considered.