# Bayesian Estimation for the Reuse of Mechanical Parts Using Part Agents

- 404 Downloads

## Abstract

To realize effective reuse of mechanical parts for the development of a sustainable society, it is essential to manage individual parts over their entire life cycle. Product users have difficulties carrying out appropriate maintenance on the multitude and variety of parts in their products. Addressing these considerations, we propose a scheme whereby a part manages itself and supports user maintenance activities. In previous work, we proposed and developed an application of Bayesian estimation to a part agent system that advises a user regarding the replacement of hard disk drives (HDDs). In this study, we create a Bayesian network on the deterioration of the HDD to find the probability of an unobservable event. We also discuss the application of this method to life cycle simulation performed by part agents.

## Keywords

Part agent Bayesian network Life cycle## Notes

### Acknowledgment

This work was supported by JSPS KAKENHI Grant Number 15 K05772.

## References

- 1.Ministry of the Environment. http://www.env.go.jp/recycle/circul/reuse/index.html. Accessed 10 June 2017.
- 2.Yokoki Y, Nanjyo K,Yamamori Y, Hiraoka H. User model in the life cycle simulation of mechanical parts, Eco design; 2015. p. 353–365.Google Scholar
- 3.Hiraoka H, Ueno K, Katou K, Ookawa H, Arita M, Nanjo K, Kawaharada H. Part agent advice for promoting reuse of the part based on life cycle information. In: 20th CIRP international conference on life cycle engineering; 2013. p. 335–340.CrossRefGoogle Scholar
- 4.Ueno T, Katou K, Ookawa H, Nanjyo K, Kawaharada H, Hiraoka H. Reuse support of mechanical parts by part agents using bayesian estimation. J JSPE. 2013;79(12):1258–64. (in Japanese).Google Scholar
- 5.Fukunaga Y, Yokoki Y, Hiraoka H. Bayesian network for the reuse of mechanical parts using part agents, JSPE Autumn Meeting. 2016;385–386. (in Japanese).Google Scholar
- 6.Nanjo K, Yamamori Y, Yokoki Y, Sakamoto Y, Hiraoka H. Maintenance decisions of part agent based on failure probability of a part using Bayesian estimation. In: The 22nd CIRP conference on Life Cycle Engineering, Sydney, Australia; 2015.Google Scholar
- 7.Nanjo K, Yamamori Y, Kawaharada H, Hiraoka H. Part agent that proposes replacement of a part considering its life cycle using a Bayesian network. In: 21st CIRP Conference on Life Cycle Engineering, Trondheim; 2014. p. 514–519.Google Scholar
- 8.Yokoki Y, Hiraoka H. Life cycle simulation of mechanical parts with part agents considering user behavior. In: The 24th CIRP conference on life cycle engineering, Kamakura, Japan; 2017.Google Scholar
- 9.Hiraoka H, Nagasawa A, Fukumashi Y, Fukunaga Y. Replacement of parts by part agents to promote reuse of mechanical parts. In: Ríos J, Bernard A, Bouras A, Foufou S, editors. Product lifecycle management and the industry of the future. Berlin: Springer; 2017. p. 394–403.CrossRefGoogle Scholar
- 10.Bayesian Network introduction. https://www.synergy-marketing.co.jp/blog/introduction-bayesian-network. Accessed 21 May 2017.