An automated planning engine for biopharmaceutical production

Robert C. Leachman, Lenrick Johnston, Shan Li and Zuo-Jun Shen

European Journal of Operational Research, 2014, vol. 238, issue 1, 327-338

Abstract: We introduce an optimization-based production planning tool for the biotechnology industry. The industry’s planning problem is unusually challenging because the entire production process is regulated by multiple external agencies – such as the US Food and Drug Administration – representing countries where the biopharmaceutical is to be sold. The model is structured to precisely capture the constraints imposed by current and projected regulatory approvals of processes and facilities, as well as capturing the outcomes of quality testing and processing options, facility capacities and initial status of work-in-process. The result is a supply chain “Planning Engine” that generates capacity-feasible batch processing schedules for each production facility within the biomanufacturing supply chain and an availability schedule for finished product against a known set of demands and regulations. Developing the formulation based on distinct time grids tailored for each facility, planning problems with more than 27,000 boolean variables, more than 130,000 linear variables and more than 80,000 constraints are automatically formulated and solved within a few hours. The Planning Engine’s development and implementation at Bayer Healthcare’s Berkeley, CA manufacturing site is described.

Keywords: Biopharmaceutical production (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:238:y:2014:i:1:p:327-338

DOI: 10.1016/j.ejor.2014.03.002

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