Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study
Increasing regulatory demands are forcing the pharmaceutical industry to invest its available resources carefully. This is especially challenging for small- and middle-sized companies. Computer simulation software like FlexSim allows one to explore variations in production processes without the need...
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doaj-f5e4993baf154cccafe539f5131dfa612020-12-31T00:03:31ZengMDPI AGProcesses2227-97172021-12-019676710.3390/pr9010067Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case StudyStefanie Hering0Nico Schäuble1Thomas M. Buck2Brigitta Loretz3Thomas Rillmann4Frank Stieneker5Claus-Michael Lehr6Department of Pharmacy, Saarland University, 66123 Saarbrücken, GermanySW Pharma GmbH, 66578 Schiffweiler, GermanySW Pharma GmbH, 66578 Schiffweiler, GermanyHelmholtz Institute for Pharmaceutical Research Saarland (HIPS), 66123 Saarbrücken, GermanySW Pharma GmbH, 66578 Schiffweiler, GermanyFree Consultant and Qualified Person According to German Law, 79410 Badenweiler, GermanyDepartment of Pharmacy, Saarland University, 66123 Saarbrücken, GermanyIncreasing regulatory demands are forcing the pharmaceutical industry to invest its available resources carefully. This is especially challenging for small- and middle-sized companies. Computer simulation software like FlexSim allows one to explore variations in production processes without the need to interrupt the running process. Here, we applied a discrete-event simulation to two approved film-coated tablet production processes. The simulations were performed with FlexSim (FlexSim Deutschland—Ingenieurbüro für Simulationsdienstleistung Ralf Gruber, Kirchlengern, Germany). Process visualization was done using Cmap Tools (Florida Institute for Human and Machine Cognition, Pensacola, FL, USA), and statistical analysis used MiniTab<sup>®</sup> (Minitab GmbH, Munich, Germany). The most critical elements identified during model building were the model logic, operating schedule, and processing times. These factors were graphically and statistically verified. To optimize the utilization of employees, three different shift systems were simulated, thereby revealing the advantages of two-shift and one-and-a-half-shift systems compared to a one-shift system. Without the need to interrupt any currently running production processes, we found that changing the shift system could save 50–53% of the campaign duration and 9–14% of the labor costs. In summary, we demonstrated that FlexSim, which is mainly used in logistics, can also be advantageously implemented for modeling and optimizing pharmaceutical production processes.https://www.mdpi.com/2227-9717/9/1/673D simulation modeling and analysismodel implementationbottleneck analysisproduction costsresource conservation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Stefanie Hering Nico Schäuble Thomas M. Buck Brigitta Loretz Thomas Rillmann Frank Stieneker Claus-Michael Lehr |
spellingShingle |
Stefanie Hering Nico Schäuble Thomas M. Buck Brigitta Loretz Thomas Rillmann Frank Stieneker Claus-Michael Lehr Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study Processes 3D simulation modeling and analysis model implementation bottleneck analysis production costs resource conservation |
author_facet |
Stefanie Hering Nico Schäuble Thomas M. Buck Brigitta Loretz Thomas Rillmann Frank Stieneker Claus-Michael Lehr |
author_sort |
Stefanie Hering |
title |
Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study |
title_short |
Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study |
title_full |
Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study |
title_fullStr |
Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study |
title_full_unstemmed |
Analysis and Optimization of Two Film-Coated Tablet Production Processes by Computer Simulation: A Case Study |
title_sort |
analysis and optimization of two film-coated tablet production processes by computer simulation: a case study |
publisher |
MDPI AG |
series |
Processes |
issn |
2227-9717 |
publishDate |
2021-12-01 |
description |
Increasing regulatory demands are forcing the pharmaceutical industry to invest its available resources carefully. This is especially challenging for small- and middle-sized companies. Computer simulation software like FlexSim allows one to explore variations in production processes without the need to interrupt the running process. Here, we applied a discrete-event simulation to two approved film-coated tablet production processes. The simulations were performed with FlexSim (FlexSim Deutschland—Ingenieurbüro für Simulationsdienstleistung Ralf Gruber, Kirchlengern, Germany). Process visualization was done using Cmap Tools (Florida Institute for Human and Machine Cognition, Pensacola, FL, USA), and statistical analysis used MiniTab<sup>®</sup> (Minitab GmbH, Munich, Germany). The most critical elements identified during model building were the model logic, operating schedule, and processing times. These factors were graphically and statistically verified. To optimize the utilization of employees, three different shift systems were simulated, thereby revealing the advantages of two-shift and one-and-a-half-shift systems compared to a one-shift system. Without the need to interrupt any currently running production processes, we found that changing the shift system could save 50–53% of the campaign duration and 9–14% of the labor costs. In summary, we demonstrated that FlexSim, which is mainly used in logistics, can also be advantageously implemented for modeling and optimizing pharmaceutical production processes. |
topic |
3D simulation modeling and analysis model implementation bottleneck analysis production costs resource conservation |
url |
https://www.mdpi.com/2227-9717/9/1/67 |
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