生產系統中利用製程不良率評估設備預防維護之研究

顧尚芳

doi:10.6840/cycu200300207

3.236.52.68，Hello！

Close
Search Quick Search Advanced Search Publication Search	Personal Service Member Login Searching History Use Bonus Card SYMSKAN
Browse Browse by University of Graduate Thesis Browse by Pinyin of Graduate Thesis Browse by Conference Proceedings Topic Browse by Conference Proceedings Publisher Browse by Pinyin of Conference Proceedings Browse by eBook Category Browse by eBook Topic Browse by eBook Publisher
Customer Services Authorize Airiti Recommend a Journal

Search Symbol (Half-width)	Description of Search Symbols
Space	"AND" indicates the intertwining of key terms used in a search
Double Quotation Marks ("") ( " " )	Double quotation marks indicate the beginning and end of a phrase, and the search will only include terms that appear in the same order of those within the quotations. Example: "image process" ： " image process "
?	Indicates a variable letter. Entering two ? will indicate two variable letters, and so on. Example: "Appl?", search results will yield apple, apply… e , appl y … ( (often used to English word searches) )
*	Indicates an unlimited number of variable letters to follow, from 1~n. Example: Enter "appl*", search results will yield apple, apples, apply, applied, application…(often used in English word searches) e , appl es , appl y , appl ied , appl ication … ( (often used to English word searches) )
AND、OR、NOT	Boolean logic combinations of key words is a skill used to expand or refine search parameters. (1) AND (1) AND: Refines search parameters (2) OR (2) OR: Expands search parameters (3) NOT: Excludes irrelevant parameters

DOI stands for Digital Object Identifier （ D igital O bject I dentifier ） ,
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.

Using DOI as a persistent link

To create a persistent link, add「http://dx.doi.org/」「 http://dx.doi.org/ 」 before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: http://dx.doi.org/ 10.5297/ser.1201.002 。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.

Cite a document with DOI

When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.

DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ）。

Data Source

College of Engineering > Graduate Institute of Industrial Engineering
Engineering > General Engineering

Bibliography Management Tool

Related Links

Report an Issue

Search for full text in Holdings

There is no full-text available at the moment. Airiti would like to request author's authorization. I would like to provide authorization.

生產系統中利用製程不良率評估設備預防維護之研究

A Study of Equipment Preventive Maintenance (EPM) with Applying Process Defective Rate for Production System

顧尚芳 , Masters　　Advisor：江瑞清　　

繁體中文 DOI： 10.6840/cycu200300207

預知性預防；可靠度；倒傳遞網路；預防維護；不良率； Defective Rate ； Back-Propagation Neural Network ； Prevention by Prediction ； Reliability ； Preventive Maintenance

Abstract │ Reference (49) │ Times Cited (9) │ Altmetrics

Abstract 〈TOP〉

Parallel Abstract 〈TOP〉

Abstract

The purpose of this research is about combining the concepts of reliability and cost-effect analysis to develop a preventive maintenance decision system based on manufacturing process defective rate for those industries with the feature of high maintenance cost for the equipments.   
Parameters mainly considered in this paper include: Mean Time Between Failure (MTBF), Production Lot (N), Preventive Maintenance Cost (PMC), Item Cost (IC) and Process Time per Unit (PT). We expect not only to build a preventive maintenance model by using these parameters but also to decide the upper limit of process defective rate (P). Once the process defective rate is beyond to this limit, an immediate equipment maintenance has to be carried out. During this study, we use eM-Plant to simulate the proposed model, and use back-propagation neural network to construct the decision system.
In this study, data collected from the simulation process are utilized to demonstrate the feasibility of this model. The unique feature of the preventive maintenance decision system is that it can be applied to practical manufacturing process, and use its capability of prevention by prediction to detect the time to maintain in advance.

Key Word：Preventive Maintenance , Reliability , Defective Rate , Back-Propagation Neural Network , Prevention by Prediction

Reference ( 49 ) 〈TOP〉

5. Charles, E. Ebeling, An Introduction To Reliability and Maintainability Engineering, McGraw-Hill, International Editions, 1997.
連結：
6. Charytoniuk, W. and M. S. Chen, “ Neural-network-based demand forecasting in aderegulated environment ”, IEEE Transactions on industry applications, Vol.36, No.3, pp.893-898, May/June 2000.
連結：
7. Dantas, A., K. Yamamoto, M. V. Lamar and Y. Yamashita, “ Neural network for travel demand forecasting using GIS and Remote Sensing ”, IEEE proceeding, pp.435-440, 2000.
連結：
9. Hornik, K., M. Stinchcombe and H White, “ Multilayer Feedforward Networks are Universal Approximators”, Neural Networks, Vol. 2, pp.359-366, 1989.
連結：
11. Johnson, Perry L., Kantner, Rob and Kikora, Marcia A., TQM Team-Building and Problem Solving, Southfield, MI: Perry Johnson, Inc., pp.1-1 ~ 10-15, 1990.
連結：

Times Cited (9) 〈TOP〉

Altmetrics

〈TOP〉

E-mail ：

When an article is available to download, a notice will be sent to your mailbox address.

E-mail ：