Graduate School of Systems and Information Engineering, University of Tsukuba, Tennoudai 1-1-1, Tsukuba, Ibaraki 305-8573, Japan
Copyright © 2009 Ushio Sumita and Jia-Ping Huang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The class of counting processes constitutes a significant part of applied probability. The classic counting processes include Poisson processes, nonhomogeneous
Poisson processes, and renewal processes. More sophisticated counting processes,
including Markov renewal processes, Markov modulated Poisson processes, age-dependent counting processes, and the like, have been developed for accommodating
a wider range of applications. These counting processes seem to be quite different
on the surface, forcing one to understand each of them separately. The purpose
of this paper is to develop a unified multivariate counting process, enabling one to
express all of the above examples using its components, and to introduce new counting processes. The dynamic behavior of the unified multivariate counting process is
analyzed, and its asymptotic behavior as is established. As an application,
a manufacturing system with certain maintenance policies is considered, where the
optimal maintenance policy for minimizing the total cost is obtained numerically.