線上品質監控系統以塑膠射出成型機為例之分析

The Analysis for Statistical Process Control System of Plastic Injection Molding Machine

陳海清(Hai-Chin Chen)

國立虎尾科技大學/工程學院/機械與機電工程研究所/碩士(2007年)

摘要

在傳統管理模式下，生產線上之射出成型機台產能資訊需由人工監視、抄錄，並進行事後分析，當發生產能或品質異常時往往無法即時得知，只能於事後進行品質檢驗與相關異常補救措施，既無效率，也不容易真正抓到異常原因。生產線效率之提升需結合生管資訊與生產線上之射出機成型資訊。運用最新的射出成型遠端監控技術，除了可以線上即時監控射出成型品質與產能狀況外，並提供製造資訊與生產資訊之分析與記錄。
本文針對射出成型機發展之遠端監控系統，分析其線上品質監控系統的性能。藉由遠端線上品質監控系統之分析結果，即可求得改善產品品質與生產效率所需之機器參數，或者可以判讀設備故障情況。如此，設備商可即時掌握設備操作情形，在最省時、省人力與成本的狀況下，提供客戶最亟需的服務。經由實例分析的結果知此線上品質監控系統確實有效且可行。

並列摘要

Under traditional management, it needs person(s) to monitor, record, and analyze the production efficiency information. There's no immediate treatment when production or quality abnormality occurs, and problems can only be solved afterwards. Thus, it lacks of efficiency and hard to obtain accurate solutions at once. Production line efficiency can be improved by combining production management information and online mold injection information. Using the latest mold injection remote monitor/control technology, the users not only can monitor current production quality and productivity, but also can collect production data for analysis.
Based on the remote monitor/control system for mold injection manufacturer, the analysis for statistical process control of plastic injection molding machine is done by this paper. Via the analysis of statistical process control, the parameters to promote the quality of products and the efficiency of production can be acquired, and the equipment provider can judge the conditions of plastic injection molding machine. Thus, the equipment provider can provide the customer the best services with the smallest costs about the time, labors and money. From the practical experiments, they show that the statistical process control system is feasible.

參考文獻

[7] J.F. MacGregor and T. Kourti, “Statistical Process Control of Multivariate Processes,” Control Engineering Practice, Vol. 3, No. 3, pp. 403-414, 1995.

[8] P.A. Jokinen, “On the Usage of Spreadsheet Packages for Automating Statistical Process Control Tasks,” ISA Transactions, Vol. 34, pp. 29-37, 1995.

[9] N.D.C. Lewis, “Assessing the Evidence from the Use of SPC in Monitoring, Predicting & Improving Software Quality,” Computers & Industrial Engineering, Vol. 37, pp. 157-160, 1999.

[10] J.A. Westerhuis, S.P. Gurden and A.K. Smilde, “Generalized Contribution Plots in Multivariate Statistical Process Monitoring,” Chemometrics and Intelligent Laboratory Systems, Vol. 51, pp. 95-114, 2000.

[11] M.C. Song, Z. Liu, M.J. Wang, T.M. Yu and D.Y. Zhao, “Research on Effects of Injection Process Parameters on the Molding Process for Ultra-Thin Wall Plastic Parts,” Journal of Materials Processing Technology, Vol. 187-188, pp. 668-671, 2007.