Modular hybrid timed Petri Nets are used to model and analyze behavior of random topology multi-operational production systems. Each such system is decomposed into 3 fundamental modules, followed by derivation of thei...
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Modular hybrid timed Petri Nets are used to model and analyze behavior of random topology multi-operational production systems. Each such system is decomposed into 3 fundamental modules, followed by derivation of their corresponding modular HPN models. The overall system model is obtained via synthesis of the individual modules, satisfying system constraints (routes, production rates, machine expected up- down- or idle- time and priorities). For any topology multi-operational production system, overall HTPN model nodes are calculated, followed by derivation of model invariants. Results show applicability of the proposed methodology and justify its modeling power and generality.
This paper deals with the subsystem of yield management for semiconductor manufacturing. One of the major causes of defects in semiconductor products is the adherence of particles on the wafer, and reduction of such p...
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This paper deals with the subsystem of yield management for semiconductor manufacturing. One of the major causes of defects in semiconductor products is the adherence of particles on the wafer, and reduction of such phenomena will be one of the most relevant policies to realize higher yield performance. Aiming to improve the yield of such products, this paper focuses on classifying the types of identification errors for each particle, and analyses the error characteristics of the current particle-monitoring/identification procedure through computer simulation. Further, a revised procedure is proposed to realize better identification performance.
An experimental system that can accurately align and place SMDs (surface mount devices) on a printed circuit board is described. Features of the system are fine positioning and endpoint sensing after an IBM 7576 robot...
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An experimental system that can accurately align and place SMDs (surface mount devices) on a printed circuit board is described. Features of the system are fine positioning and endpoint sensing after an IBM 7576 robot coarsely aligns the SMD to its target. Fine positioning is done using a customer-designed micropositioning device. The endpoint sensor is a single camera vision system that by image analysis determines the alignment error of the SMD to the board. System performance was evaluated by placing SMDs of 100 leads with 25 mil lead spacing on a board. The alignment error is less than 0.5 mil and 0.015 degrees , independent of feeder and board position error or robot repeatability. The average cycle time is less than 10 s.< >
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