Understanding the state transition of a process from the time series data obtained from the process is important from the viewpoint of both analyzing and controlling the process. In particular, it is important to clarify a turning point of the state transition, that is, the point of change in the process and to find the cause of the state transition by observing and analyzing the data from the process. This paper considers the method of detecting several change points in a process based on the likelihood theory and information criterion when a series of data from the process follows the Poisson process. Then, the method of finding any process state fluctuation and points of change is called “the process state track- ing method”. The validity and applicability of the process state tracking method introduced in this paper is confirmed through some numerical applications.

In Japan, manufacturers are required to dispose of their electronic products properly after use, which means in accordance with the Home Appliance Recycling Law. As a case study, a mathematical model for optimizing the operation plan of a factory that recycles used home appliances is constructed. The company makes a profit by selling the resources that are produced after dismantling the home appliances. However, the processing capacity is insufficient to dispose of the total amount of collected products, so the company has been outsourcing the storage of the excess beyond its warehouse capacity. As a method for improving this situation, this paper proposes an integer programming model that outputs an operation plan considering the entire disassembly process of the factory, and then shows the effectiveness of the model through numerical experiments and sensitivity analysis. The experimental results show that the proposed model can reduce the total cost, especially the contributions of transportation and inventory, without making major changes. The sensitivity analysis shows that, not only an appropriate increase in the number of employees, but also flexible personnel allocation leads to a decrease in the total cost.