A constraint programming model for makespan minimisation in batch manufacturing pharmaceutical facilities

•A novel constraint programming (CP) was introduced to minimise makespan in a batch pharmaceutical plant.•The model captured all the constraints of the overall production cycle and its features.•The makespan was minimised and productivity was increased compared to baseline schedule.•The model acts a...

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Veröffentlicht in:Computers & chemical engineering 2022-01, Vol.156, p.107565, Article 107565
Hauptverfasser: Awad, Mohamed, Mulrennan, Konrad, Donovan, John, Macpherson, Russell, Tormey, David
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Sprache:eng
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Zusammenfassung:•A novel constraint programming (CP) was introduced to minimise makespan in a batch pharmaceutical plant.•The model captured all the constraints of the overall production cycle and its features.•The makespan was minimised and productivity was increased compared to baseline schedule.•The model acts as a simulation optimisation tool by running what-if scenarios. This work introduces a constraint programming (CP) model to minimise the makespan of a large scheduling problem in batch pharmaceutical manufacturing facilities. The model included campaign-manufacturing, sequence-dependent changeover, forbidden product-equipment assignment, non-working periods, limited renewable resources, finite intermediate/non-intermediate storage policies and preemptive and non-preemptive operations. The model was tested by scheduling two real examples. Each example consisted of two cases. Case A used the actual number of workers per shift. Case B involved reorganising the shift pattern of the workers. The results from the model were qualitatively validated and compared with the baseline schedules. The makespan of the first example decreased by 24.35% for case 1.A and 38.63% for case 1.B. The second example reported a 2.17% decrease in makespan for case 2.A and 16.67% decrease for case 2.B. This demonstrates the success of the proposed model as a simulation tool to identify the manufacturing bottlenecks by running what-if scenarios.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2021.107565