In process plant operation, stability and instability are assessed using trend graphs that track the behavior of individual variables. While stabilizing individual variables is essential, the ultimate goal is to stabilize each unit, which ultimately contributes to the overall stability of the entire plant. Clustering analysis is also employed for analyzing the entire plant or specific units. Currently, qualitative evaluation dominates clustering analysis, with quantitative assessment being rare. This paper introduces the Process Operation Stability Indicator (POSI), a newly developed tool that leverages clustering analysis results to quantitatively evaluate process plant operation stability. We demonstrated the effectiveness of POSI in quantitatively assessing stability improvements through Advanced Process Control (APC).

In recent years, robots working in human living space with human-robot interactions are actively studied. To these robots, it is important to perform environmental cognition not only building environment map for autonomous motion of the robots but also estimating presences of human around the robots. In this study, by utilizing human state estimation function and SLAM based mapping technology, a concept and architecture of Human Motion Map by representing human behavior in the human living space as a hybrid map system are proposed. Beyond the conventional map which represents the existence of wall and objects, Human Motion Map represents not only the existence of humans in a particular location but also motion distributions. With recent improvements of the cloud computing technology, Human Motion Map can be accumulated as a kind of big data while measurements of robots are performed continuingly while it is moving around. In this paper, we propose a motion feature classification algorithm for clustering human motions geographically. Some experiment result of basic motion feature extraction, geographical clustering, and human motion behavior analyzing are provided for illustrating the validity of proposed algorithm.

A high-speed workstation network system which interconnects distributed workstations and servers through a 100 Mbps optical LAN employing the OSI protocol is developed. The network throughput is maximized by employing a newly developed intelligent high-speed network controller consisted of a 100 Mbps token-ring processor(TRP) and 32-bit MPU which executes all the 7-layered OSI protocol. The remote retrieval capability of database of the system is theoretically confirmed and is experimentally proved.>