TY - JOUR
T1 - Maintenance, shutdown and production scheduling in semiconductor robotic cells
AU - Tonke, Daniel
AU - Grunow, Martin
N1 - Publisher Copyright:
© 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2018/5/3
Y1 - 2018/5/3
N2 - Our approach is the first to study simultaneous scheduling of preventive maintenance, shutdowns and production for robotic cells in semiconductor manufacturing. It hereby exploits the frequent periods of overcapacity in semiconductor manufacturing to reduce wear and tear. In contrast to existing approaches, our scheduling approach is able to deal with different preventive-maintenance types. We borrow the Resource Task Network representation from the process-industry domain to represent our problem and facilitate its formulation as a mathematical model. In addition, we develop efficiency-improving constraints based on the characteristics of the preventive-maintenance activities. In numerical tests based on industry data, we show that the model generates high-quality schedules even without applying the inequalities, although the optimality gap is reduced only when including inequalities. We furthermore assess the trade-off between shutdowns and batch lead times. We compare our model’s schedule quality to (i) the simple industry practice of shutting down chambers permanently to reduce wear and tear and (ii) an approach that schedules maintenance and production sequentially. The numerical tests yield the following managerial insights. First, integrating maintenance and production scheduling has substantial advantages. Second, the practice of shutting equipment down permanently diminishes scheduling flexibility and solution quality. Third, shutdowns scheduling must also consider the impact on batch waiting times.
AB - Our approach is the first to study simultaneous scheduling of preventive maintenance, shutdowns and production for robotic cells in semiconductor manufacturing. It hereby exploits the frequent periods of overcapacity in semiconductor manufacturing to reduce wear and tear. In contrast to existing approaches, our scheduling approach is able to deal with different preventive-maintenance types. We borrow the Resource Task Network representation from the process-industry domain to represent our problem and facilitate its formulation as a mathematical model. In addition, we develop efficiency-improving constraints based on the characteristics of the preventive-maintenance activities. In numerical tests based on industry data, we show that the model generates high-quality schedules even without applying the inequalities, although the optimality gap is reduced only when including inequalities. We furthermore assess the trade-off between shutdowns and batch lead times. We compare our model’s schedule quality to (i) the simple industry practice of shutting down chambers permanently to reduce wear and tear and (ii) an approach that schedules maintenance and production sequentially. The numerical tests yield the following managerial insights. First, integrating maintenance and production scheduling has substantial advantages. Second, the practice of shutting equipment down permanently diminishes scheduling flexibility and solution quality. Third, shutdowns scheduling must also consider the impact on batch waiting times.
KW - maintenance scheduling
KW - optimisation
KW - preventive maintenance
KW - production scheduling
KW - robotic cells
KW - shutdown scheduling
UR - http://www.scopus.com/inward/record.url?scp=85043316175&partnerID=8YFLogxK
U2 - 10.1080/00207543.2018.1444809
DO - 10.1080/00207543.2018.1444809
M3 - Article
AN - SCOPUS:85043316175
SN - 0020-7543
VL - 56
SP - 3306
EP - 3325
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 9
ER -