Process planning is an effective way to integrate design and manufacturing. The use of computer techniques to automate the tasks of process planning has been the subject of extensive research for computer integrated manufacturing. This paper presents a survey of research in artificial neural network techniques for process planning. Neural network-based approaches can eliminate some drawbacks of the classic methods, and therefore have been prevalent in recent years. The four main issues related to the neural network-based techniques, namely the network architecture, input representation, the output format and the training method are discussed with the current applications. Finally, the research outcomes, limitations and future directions are outlined.
|Number of pages||6|
|Publication status||Published - 25 Jun 2001|
|Event||International Conference on Imaging Science, Systems, and Technology (CISST 2001) - Las Vegas, Nevada, USA United States|
Duration: 25 Jun 2001 → 28 Jun 2001
|Conference||International Conference on Imaging Science, Systems, and Technology (CISST 2001)|
|Country||USA United States|
|City||Las Vegas, Nevada|
|Period||25/06/01 → 28/06/01|
Ding, L., Yue, Y., & Ahmet, K. (2001). Artificial Neural Network Applications to Process Planning. 778-783. Paper presented at International Conference on Imaging Science, Systems, and Technology (CISST 2001), Las Vegas, Nevada, USA United States.