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Simulating the Semiconductor Manufacturing Process through AutoSched Advanced Processing : An Exploratory Study to Enhance NXP’s ASAP Model Forecast Accuracy

Lambalgen, N.R. van (2024) Simulating the Semiconductor Manufacturing Process through AutoSched Advanced Processing : An Exploratory Study to Enhance NXP’s ASAP Model Forecast Accuracy.

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Abstract:This thesis explores modifications to improve the accuracy of NXP’s AutoSched Advanced Processing (ASAP) model, addressing challenges in enhancing operation efficiency at ICN8, NXP’s semiconductor plant. Analysis of ICN8 operations identified inefficiencies in operation rate as the largest source of loss, with tool availability rate as the third largest. These inefficiencies are areas where ASAP could provide improvement. As of 2023, NXP’s 72-hour ASAP model forecasts daily moves with an average deviation of 15.8% per cap group, limiting its effectiveness, especially in forecasting bottlenecks. A deviation of no more than 5% is needed to make the model reliable. To enhance forecasting accuracy, we incorporated tool process times and idle times into the ASAP model. Validation of these changes resulted in a 39.2% reduction in forecast deviation, lowering the average absolute deviation for the 35 largest cap groups from 19.1% to 11.7% in 2024. Although the 5% target was not reached, this improvement marks significant progress. Further refinements could achieve better accuracy, aiding NXP in decisions on operator staffing, tool maintenance, and reducing weekly maintenance time for the ASAP model itself, ultimately improving ICN8’s production efficiency.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:58 process technology
Programme:Industrial Engineering and Management MSc (60029)
Link to this item:https://purl.utwente.nl/essays/104647
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