Personalized Prediction of Optimal Replacement Point Using Data Assimilation  

Oleh:

Yokoyama, Masahiro ; Yamashita, Toshie ; Yamamoto, Watalu ; Suzuki, Kazuyuki

Jenis: Article from Proceeding
Dalam koleksi: Asian Network for Quality (ANQ) Congress 2011, Ho Chi Minh City, Vietnam, 27-30 September 2011, page 1-19.
Topik: Data assimilation; Particle filter; Reliability; Risk communication; Usage frequency
Fulltext: JP11_Yokoyama_Fullpaper.pdf (401.46KB)

Isi artikel

In recent years, from technological advances in ICT, it has been able to take advantage of real-time information regarding the operational conditions and functional performance of each individual customer. We have studied “data assimilation” of this kind of customer’s real-time information to offer the optimal replacement for the individual customer. When considering the use of a customer’s real-time information, at the first stage, monitoring the status at regular intervals is carried out. Then, when the time of replacement is approaching, updating the forecast by this kind of real-time information may be considered in order to improve the accuracy. In this paper, we propose a method updating the prediction by data assimilation which takes the customer's daily information of a consumable good when the time of its replacement is approaching. This method enables to provide an optimal replacement for individual customer, which captures real-time information on the changes in the usage of customers. In addition, in the proposed method, improving the prediction by updating the distribution of the usage frequency of customer, it can make a stable update of the forecast, and can thus prevent a premature replacement, and it is expected to reduce maintenance costs for manufacturers.

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