Improving lead time of pharmaceutical production processes using Monte Carlo simulation

•Systematic approach for improving production lead time in pharmaceutical industry.•Monte Carlo simulation allowing flexible estimation of the production lead time.•Sensitivity analysis for identifying key contributors.•What-if analysis for simulating the effect of assessed improvements.•Industrial...

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Veröffentlicht in:Computers & chemical engineering 2014-09, Vol.68, p.255-263
Hauptverfasser: Eberle, Lukas Gallus, Sugiyama, Hirokazu, Schmidt, Rainer
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container_start_page 255
container_title Computers & chemical engineering
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creator Eberle, Lukas Gallus
Sugiyama, Hirokazu
Schmidt, Rainer
description •Systematic approach for improving production lead time in pharmaceutical industry.•Monte Carlo simulation allowing flexible estimation of the production lead time.•Sensitivity analysis for identifying key contributors.•What-if analysis for simulating the effect of assessed improvements.•Industrial case study for proving the effectiveness of the method. Reliable product supply is one of the most critical missions of the pharmaceutical industry. The lead time, i.e. the duration between start and end of an activity, needs to be well managed in any production facility in order to make scheduling predictable, agile and flexible. We present a method for measuring and improving production lead time of pharmaceutical processes with a primary focus on Parenterals (i.e. injectables) production processes. Monte Carlo simulation is applied for quantifying the total lead time (TLT) of batch production as a probability distribution and sensitivity analysis reveals the ranking of sub-processes by impact on TLT. Based on these results, what-if analyses are performed to evaluate effects of investments, resource allocations and process improvements on TLT. An industrial case study was performed at a production site for Parenterals of F. Hoffmann-La Roche in Kaiseraugst, Switzerland, where the presented method supported analysis and decision-making of production enhancements.
doi_str_mv 10.1016/j.compchemeng.2014.05.017
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Reliable product supply is one of the most critical missions of the pharmaceutical industry. The lead time, i.e. the duration between start and end of an activity, needs to be well managed in any production facility in order to make scheduling predictable, agile and flexible. We present a method for measuring and improving production lead time of pharmaceutical processes with a primary focus on Parenterals (i.e. injectables) production processes. Monte Carlo simulation is applied for quantifying the total lead time (TLT) of batch production as a probability distribution and sensitivity analysis reveals the ranking of sub-processes by impact on TLT. Based on these results, what-if analyses are performed to evaluate effects of investments, resource allocations and process improvements on TLT. An industrial case study was performed at a production site for Parenterals of F. 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Reliable product supply is one of the most critical missions of the pharmaceutical industry. The lead time, i.e. the duration between start and end of an activity, needs to be well managed in any production facility in order to make scheduling predictable, agile and flexible. We present a method for measuring and improving production lead time of pharmaceutical processes with a primary focus on Parenterals (i.e. injectables) production processes. Monte Carlo simulation is applied for quantifying the total lead time (TLT) of batch production as a probability distribution and sensitivity analysis reveals the ranking of sub-processes by impact on TLT. Based on these results, what-if analyses are performed to evaluate effects of investments, resource allocations and process improvements on TLT. An industrial case study was performed at a production site for Parenterals of F. 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source Elsevier ScienceDirect Journals
subjects Applied sciences
Biological and medical sciences
Chemical engineering
Computer simulation
Decision theory. Utility theory
Decision-making
Exact sciences and technology
General pharmacology
Impact analysis
Industrial application
Inventory control, production control. Distribution
Lead time
Logistics
Medical sciences
Monte Carlo methods
Monte Carlo simulation
Operational research and scientific management
Operational research. Management science
Pharmaceutical production
Pharmaceutical technology. Pharmaceutical industry
Pharmaceuticals
Pharmacology. Drug treatments
Resource allocation
Sensitivity analysis
Supply chain
title Improving lead time of pharmaceutical production processes using Monte Carlo simulation
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