In an automated industry PLC plays a central role to control the automation system. Therefore, fault free operation of PLC controlled automation system is essential in order to maximize a firm’s productivity. A prior test of control system is a practical way to check fault operations, but it is a time consuming job and can not check all possible fault operation. A formal verification of PLC program could be a best way to check all possible fault situation. Tracing the history of the study on formal verification, we found three problems, the first is that a formal representation of PLC control system is incomplete, the second is a state explosion problem and the third is that the verification result is difficult to use for the correction of control program. In this paper, we propose a transformation method to reproduce the control system correctly in formal model and efficient procedure to verify and correct the control program using verification result. To demonstrate the proposed method, we provided a suitable case study of an automation system.

In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.