With the advancement of manufacturing technology, production systems have become increas- ingly complex. Digital twin has gained attention in these complex systems for enhancing pro- ductivity and optimizing operations. This paper proposes a method for developing a digital twin capable of predicting future abnormal situations in assembly production systems. Real-time syn- chronization between the actual manufacturing system and its digital twin enables the imple- mentation of a virtual factory. This virtual factory can accurately represent the real-time status of the target system using state calculation logic. Based on the real-time monitoring informa- tion provided by the virtual factory, it is possible to set the initial condition of simulation. When the digital twin predicts production issues, it provides the manufacturing operators with this pre- diction information. The operators then use this information to identify the cause and take pro- active actions. Finally, this paper presents a case study where the proposed digital twin development method has been applied to a domestic home appliances assembly line.
