Study and Integration of Automatic Manufacturing Planning and Optimized Manufacturing Scheduling for Plastic Injection Mold
| Autor: | Po-Jung Lai, 賴柏榕 |
|---|---|
| Jazyk: | zh-TW |
| Rok vydání: | 2014 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 102 Changing demand for plastic products and shortening the delivery time are the main challenge for the plastic injection mold industry. In order to improve the production lead time effectively and obtain mold manufacturing scheduling for the minimum makespan, this study used the secondary development in computer-aided design (CAD) environment to build applying the web-based injection mold manufacturing navigating system, and the system is divided into the manufacturing planning and the scheduling management modules. The manufacturing planning module is through automatic feature recognition and searches the corresponding manufacturing processes in the database applying the group technology for many mold project components. When the component process has electric discharge machining (EDM), the system will provide a knowledge navigating step to use the electrode design for users. In addition, the system provides the tool selection function by linking the process with the database to navigate the user facilitating the manufacturing numerical control (NC) program design for mold components, which realizes the integration of CAD/computer-aided process planning (CAPP)/computer-aided manufacturing (CAM). The scheduling management module obtains the scheduling information for all project components through the database and applies genetic algorithms and ant colony system to solve the problem of mold manufacturing scheduling. The optimized results are provided by the scheduling Gantt chart for users to read and make comparisons. The case proved that the computer-aided process planning can save up to 90% of lead time. The optimized scheduling results can save up to 48% of makespan. Using this system can avoid human errors, and reduce mold manufacturing time effectively, also help new staffs to learn quickly and speed up the production efficiency. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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