Fig。 2。 Example Component 1 (All dimensions are in mm, sheet material – Brass, sheet thickness – 1。0 mm)

The present investigation contributes towards automating the design process of progressive die using KBS approach。  The output of system modules includes the type and dimensions of major components of progressive die such as die block, die gages, stripper, stripper plate, punches, punch plate, back plate, die-set and fasteners。 The system is flexible enough  as  its knowledge base can be modified and updated depending upon the capabilities of a specific shop floor and advances in new technology。 The system has been tested for a wide variety of industrial sheet metal components。 Recommendations imparted by the system for selection of progressive die components were found to be reasonable and very similar to those actually used in sheet metal industries。 The data stored in output files generated by the system modules can be further utilized for automatic modeling of progressive die components and die assembly。 The system is a low cost alternative for die designers working in small and medium sized stamping industries。

[1] H。S。 Ismail, K。K。B。 Hon, K。 Huang, An intelligent object- oriented approach to the design and assembly of press tools, Annals of the CIRP, 44 (1995) 91-96。

[2] M。C。 Cakir, O。 Irfan, K。 Cavdar, An expert system approach for die and mold making operations, Robotics and Computer-Integrated Manufacturing, 21(2005) 175-183。

[3] S。 Kumar, R。 Singh, A low cost knowledge base system framework for progressive die design, Journal of Material Processing Technology, 153-154 (2004) 958-964。

[4] S。 Kumar, R。 Singh, An intelligent system for selection of die- set of press tool for metal stampings, Journal of Materials Processing Technology, 164-165 (2005) 1395-1401。

[5] M。 Tisza, Expert systems for metal forming, Journal of Materials Processing Technology, 53 (1995) 423-432。

[6] Vivek Goel, Jianhua Chen, Application of expert network for material selection in engineering design, Computers in Industry, 30 (1996) 87-101。

[7] J。Y。 Li, A。Y。C。 Nee, B。T。 Cheok, Integrated feature-based modelling and process planning of bending operations in progressive die design, International Journal of Advanced Manufacturing。 Technology,  20 (2002) 883-895。

[8] S。 Kumar, R。 Singh, Trends and developments in intelligent computer aided design of progressive dies, Journal of Advanced Materials Research, 6-8 (2005) 241-248。

[9] W。 Myers, Introduction to expert systems, Spring, 1986。 [10] M。 Detroit, Die design handbook, ASMTE, 1955。

[11] C。W。 Hinman, Press working of metals, McGraw Hill, 1950。 [12] D。F。 Ostergard, Advanced die making, McGraw Hill, 1967。 [13] A。 Singh, Working with AutoCAD 2000, TMH, New Delhi, 2002。 [14]  G。O。  Head,  AutoLISP  in  Plain  English,  Venlana    press,

North Carolina, 1987。

[15] S。 Kumar, R。 Singh, A knowledge-based system for  design of strip layout of metal stamping work on progressive die, Proceedings of the International Conference “Advances in Materials and Processing Technology” (AMPT-2006), Las Vegas, USA, 2006, AII 243 (CD-Rom)。

摘要

目的：本文描述了一种知识库系统（KBS），用于选择级进模具部件，用于自动化冲压工业中的级进模的设计。

设计/方法：基于人工智能（AI）和基于生产规则的KBS方法被用于构造所提出的系统。该系统已被构造成七个KBS模块。模块是用户交互式的，并设计为加载到AutoCAD的提示区域。

结果：系统模块的输出包括级进模部件的类型和适当的尺寸，模具规格（前隔垫和背盖），剥离器，冲头，冲孔板，背板，模具和紧固件。该系统已经被设计成使得其模块赋予的专家意见自动存储在不同的输出数据文件中。这些数据文件可以进一步用于自动建模的模具部件和模具组装。