Manufacturing Management Approach with AI and Statistical Methods for Improvement of Printed Circuit Boards Manufacturing Quality
プリント配線板製造品質向上に向けたAIと統計学的手法を用いた製造管理アプローチ
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20266125
- Paper/Info type
- Proceedings (Autumn)
No.118-26
- Pages
- 1-6(Total 6 p)
- Date of publication
- Oct 2026
- Publisher
- JSAE
- Language
- Japanese
- Event
- 2026 JSAE Annual Congress (Autumn)
Detailed Information
| Author(J) | 1) 成田 隼翼, 2) 堀川 敦, 3) 上野 智之 |
|---|---|
| Author(E) | 1) Shunsuke Narita, 2) Tai Horikawa, 3) Tomoyuki Ueno |
| Affiliation(J) | 1) 日産自動車, 2) 日産自動車, 3) 日産自動車 |
| Affiliation(E) | 1) Nissan Motor, 2) Nissan Motor, 3) Nissan Motor |
| Abstract(J) | 自動車の電子化が進み，プリント配線板には更なる高度化が求められ，その実現には高い製造品質が望まれる．そこで，製造管理を閾値管理から分布管理に変更する事で，品質と効率を両立する手法を検討した．本研究ではAI，MLの高い演算能力を用いてベイズ推定を適用し，早期の推定分布作成と外れ値判定のプロセスを提案する． Translation |
| Abstract(E) | High manufacturing quality is necessary for the realization of further advancement of printed circuit boards by the advancement of electronics in automobiles. We investigated a method to reconcile quality and efficiency by shifting manufacturing management from threshold-based management to distribution-based management. In this research, we propose the process of early generation of estimated distribution and outlier detection through the application of Bayesian Estimation from AI and ML processing capabilities. |
