التفاصيل البيبلوغرافية
العنوان: |
A closed-loop control architecture for CAM accounting for shop floor uncertainties |
المؤلفون: |
Lee, Hyunsoo1, Sharda, Bikram2, Banerjee, Amarnath1 banerjee@tamu.edu |
المصدر: |
Journal of Manufacturing Systems. Oct2008, Vol. 27 Issue 4, p166-175. 10p. |
مصطلحات موضوعية: |
ELECTRONIC systems, ELECTRONICS, ELECTRONIC equipment, ANALOG electronic systems |
مستخلص: |
Abstract: The primary focus of this paper is to demonstrate an enhanced closed-loop computer-aided manufacturing (CAM) architecture using a Petri net based analysis mechanism, which incorporates shop floor uncertainties to generate process plans and alternative processing sequences under dynamic conditions such as machine failures. Modern CAM software provide efficient, error-free, and user-friendly interfaces to develop processing sequences for manufacturing tasks. However, their effective scope is still limited from the post-process planning stage to the pre-machining stage. These types of software fail to incorporate the variability encountered in an actual shop floor to develop effective process plans. This is caused due to CAM software’s limitations in input handling mechanisms, limited simulation functionality, and inability to handle complex process variability from the shop floor. In this paper, CAM functionality is augmented with Petri net models to capture alternative process plans and shop floor variability arising due to equipment failures, repairs, and setups. The output from the analysis of the Petri net model provides a better understanding of the process characteristics and provides information to the CAM system to adapt to shop floor variability. The resulting information from the Petri net model allows the CAM system to compare alternative process plans while taking shop floor information into account. This mechanism can result in better decisions, reduced processing times, and better overall resource utilization, and provide alternative process plans based on current resource information. [Copyright &y& Elsevier] |
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قاعدة البيانات: |
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