Qualitative risk assessment in V-Blender using Bayesian Network

The development of solid dosage is very important in the production process, especially in powder blending. Moreover, the homogeneity of products can be influenced by the performance of powder blending operations that do not conform to the desired specifications and therapeutic effect as regulation...

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Main Authors: Nur Atikah, Md Azni, Nadiya, Abdul Halim, Wan Nurul Huda, Wan Zainal
Format: Conference or Workshop Item
Language:English
Published: 2022
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Online Access:http://umpir.ump.edu.my/id/eprint/36977/1/Qualitative%20risk%20assessment%20in%20v-blender%20using%20bayesian%20network.pdf
http://umpir.ump.edu.my/id/eprint/36977/
https://ncon-pgr.ump.edu.my/index.php/en/?option=com_fileman&view=file&routed=1&name=E-BOOK%20NCON%202022%20.pdf&folder=E-BOOK%20NCON%202022&container=fileman-files
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Institution: Universiti Malaysia Pahang
Language: English
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spelling my.ump.umpir.369772023-02-17T07:46:18Z http://umpir.ump.edu.my/id/eprint/36977/ Qualitative risk assessment in V-Blender using Bayesian Network Nur Atikah, Md Azni Nadiya, Abdul Halim Wan Nurul Huda, Wan Zainal QD Chemistry T Technology (General) TA Engineering (General). Civil engineering (General) TP Chemical technology The development of solid dosage is very important in the production process, especially in powder blending. Moreover, the homogeneity of products can be influenced by the performance of powder blending operations that do not conform to the desired specifications and therapeutic effect as regulation by the Food and Drug Administration (FDA) may be detrimental to consumers. In addition, the International Conference on Harmonization (ICH) has also taken initiatives to improve production standards by establishing ICH 9 for Quality Risk Management (QRM). This is why drugs must be manufactured with high quality, safety, and effectiveness to ensure the safety of drug manufacturers as well as consumers. The objective of this research work is to study and investigated the probabilistic relationship between process parameters that can affect the blender performance that led to blending inhomogeneity by using the Qualitative Risk Assessment (QRA) method. QRA method is performed in order to categorize the identification risk level exposed in powder blending with low, medium, and high levels. The method of QRA that has been applied in this study is the Bayesian Network (BN) model. Furthermore, the BN is one of the risk assessment tools that present the parameters and their conditional independence using a directed aversion plot (DAG). The BN was used to verify the process parameters that could cause the failure of blending unit operation are fill level, loading order, blending time, and blending speed. However, from the outcome, the critical process parameters (CPPs) that have a greater risk of affecting homogeneity are a combination of fill level, loading order, and blending speed with 0.62 while the highest probabilities value of failure was a combination of fill volume, loading order and blending time with 0.92. The medium probabilities value of failure was a combination of fill level, blending time, blending speed, and combination of loading order, blending time and blending speed, which was 0.77 and 0.69, respectively. Moreover, it can be concluded that the failure that caused by the related process parameter is 0.75 for a true statement while the false statement is 0.25. This can be concluded that not all of the process parameters can impact the blender operation on the degree of product homogeneity. For further studies, it is possible to address the limitation of the BN in combination with a quantitative risk assessment to confirm the results and minimize the risk of failure by practicing the preventive method. 2022-11-15 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/36977/1/Qualitative%20risk%20assessment%20in%20v-blender%20using%20bayesian%20network.pdf Nur Atikah, Md Azni and Nadiya, Abdul Halim and Wan Nurul Huda, Wan Zainal (2022) Qualitative risk assessment in V-Blender using Bayesian Network. In: The 6th National Conference for Postgraduate Research (NCON-PGR 2022), 15 November 2022 , Virtual Conference, Universiti Malaysia Pahang, Malaysia. p. 127.. https://ncon-pgr.ump.edu.my/index.php/en/?option=com_fileman&view=file&routed=1&name=E-BOOK%20NCON%202022%20.pdf&folder=E-BOOK%20NCON%202022&container=fileman-files
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QD Chemistry
T Technology (General)
TA Engineering (General). Civil engineering (General)
TP Chemical technology
spellingShingle QD Chemistry
T Technology (General)
TA Engineering (General). Civil engineering (General)
TP Chemical technology
Nur Atikah, Md Azni
Nadiya, Abdul Halim
Wan Nurul Huda, Wan Zainal
Qualitative risk assessment in V-Blender using Bayesian Network
description The development of solid dosage is very important in the production process, especially in powder blending. Moreover, the homogeneity of products can be influenced by the performance of powder blending operations that do not conform to the desired specifications and therapeutic effect as regulation by the Food and Drug Administration (FDA) may be detrimental to consumers. In addition, the International Conference on Harmonization (ICH) has also taken initiatives to improve production standards by establishing ICH 9 for Quality Risk Management (QRM). This is why drugs must be manufactured with high quality, safety, and effectiveness to ensure the safety of drug manufacturers as well as consumers. The objective of this research work is to study and investigated the probabilistic relationship between process parameters that can affect the blender performance that led to blending inhomogeneity by using the Qualitative Risk Assessment (QRA) method. QRA method is performed in order to categorize the identification risk level exposed in powder blending with low, medium, and high levels. The method of QRA that has been applied in this study is the Bayesian Network (BN) model. Furthermore, the BN is one of the risk assessment tools that present the parameters and their conditional independence using a directed aversion plot (DAG). The BN was used to verify the process parameters that could cause the failure of blending unit operation are fill level, loading order, blending time, and blending speed. However, from the outcome, the critical process parameters (CPPs) that have a greater risk of affecting homogeneity are a combination of fill level, loading order, and blending speed with 0.62 while the highest probabilities value of failure was a combination of fill volume, loading order and blending time with 0.92. The medium probabilities value of failure was a combination of fill level, blending time, blending speed, and combination of loading order, blending time and blending speed, which was 0.77 and 0.69, respectively. Moreover, it can be concluded that the failure that caused by the related process parameter is 0.75 for a true statement while the false statement is 0.25. This can be concluded that not all of the process parameters can impact the blender operation on the degree of product homogeneity. For further studies, it is possible to address the limitation of the BN in combination with a quantitative risk assessment to confirm the results and minimize the risk of failure by practicing the preventive method.
format Conference or Workshop Item
author Nur Atikah, Md Azni
Nadiya, Abdul Halim
Wan Nurul Huda, Wan Zainal
author_facet Nur Atikah, Md Azni
Nadiya, Abdul Halim
Wan Nurul Huda, Wan Zainal
author_sort Nur Atikah, Md Azni
title Qualitative risk assessment in V-Blender using Bayesian Network
title_short Qualitative risk assessment in V-Blender using Bayesian Network
title_full Qualitative risk assessment in V-Blender using Bayesian Network
title_fullStr Qualitative risk assessment in V-Blender using Bayesian Network
title_full_unstemmed Qualitative risk assessment in V-Blender using Bayesian Network
title_sort qualitative risk assessment in v-blender using bayesian network
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/36977/1/Qualitative%20risk%20assessment%20in%20v-blender%20using%20bayesian%20network.pdf
http://umpir.ump.edu.my/id/eprint/36977/
https://ncon-pgr.ump.edu.my/index.php/en/?option=com_fileman&view=file&routed=1&name=E-BOOK%20NCON%202022%20.pdf&folder=E-BOOK%20NCON%202022&container=fileman-files
_version_ 1758578266503905280