Process Analytics

Process analytics is an analytic methodology that is used for understanding, managing, and improving the business processes by defining and explaining each factor and relationship between the factors. When analyzing the past data by the method, it can get some information that can know only from the field; the information cannot recognize from the related documents. According to analytics based on the field’s situations, it can solve the problems practically. Thus, the laboratory studies about 1. Process visualization, diversification of the analytic viewpoint, and methods of drawing processes using data, 2. Conformance analytics of the process model and method of processing the missing an anomaly data using the results, 3. Process optimization and simulation according to the drawn process and the analytic results. According to the topics, the lab discovers and deals with the processes, and researches the application plans used the drawing results.

Process visualization, diversification of the analytic viewpoint, and methods of drawing processes using data

Defining the events that exist in the process, deciding the fixed factors used for process analytics by standardizing the components of the meta data, and drawing the optimal fixed process
Methodology developments that analyze and draw the process model immediately when urgent changes occur in the field that the real process are run.
Studying the algorithm of analyzing and visualizing the process that helps understand the intuitive expression of the analytic results easily by the domain experts and that connect with the fields in real time.

Conformance analytics of the process model and method of processing the missing and anomaly data using the results

Development of an algorithm that gives stable comparison by simplifying the data based on the statistics with maintaining the equivalence of the methodologies of process conformance analytics used before.
Processing the missing and anomaly data according to the order and connection of the operating data by using process models.
Making a processing methodology that improve the accuracy of the processing the missing or anomaly data with process analytics, predictions, and log data generated results of the outdoor environment connected of field data.

Process optimization and simulation according to the drawn process and the analytic results

Flexible process operation support to decide the needs of new scheduling and schedule again by reflecting the log data in real time.
Assistant of drawing the optimal operating environment for optimization of process by development of a simulation tool that assume and apply the decision making list based on process mining.
Managing plans automatically and improving flexibility by development of scheduling methodology based on log data with artificial intelligence or reinforcement learning