TY - GEN
T1 - Exploring the Impact of Advanced Manufacturing Technologies in South Africa's Pharmaceutical Industry
AU - Tshehla-Nkuna, Makope
AU - Sukdeo, Nita
AU - Mukwakungu, Sambil Charles
AU - Mbohwa, Charles
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This study investigates the impact of Advanced Manufacturing Technologies, especially Artificial Intelligence, on the operational efficiency and production quality in South Africa's pharmaceutical manufacturing sector. Utilizing a quantitative approach, data was gathered from 34 industry professionals to evaluate their understanding and attitudes towards Artificial Intelligence and related technologies. The findings indicate that Artificial Intelligence notably enhances production efficiency, quality, and compliance, while reducing human error and defects. However, challenges such as skill gaps and complexities in regulatory and Artificial Intelligence governance were identified. The study suggests diversifying the participant pool and incorporating qualitative methods for broader insights. Future research should expand to include more international perspectives and focus on specific technologies to better understand the industry's adaptation to technological advancements.
AB - This study investigates the impact of Advanced Manufacturing Technologies, especially Artificial Intelligence, on the operational efficiency and production quality in South Africa's pharmaceutical manufacturing sector. Utilizing a quantitative approach, data was gathered from 34 industry professionals to evaluate their understanding and attitudes towards Artificial Intelligence and related technologies. The findings indicate that Artificial Intelligence notably enhances production efficiency, quality, and compliance, while reducing human error and defects. However, challenges such as skill gaps and complexities in regulatory and Artificial Intelligence governance were identified. The study suggests diversifying the participant pool and incorporating qualitative methods for broader insights. Future research should expand to include more international perspectives and focus on specific technologies to better understand the industry's adaptation to technological advancements.
KW - Advanced Manufacturing Technologies
KW - Artificial Intelligence
KW - Operational Efficiency
KW - Pharmaceutical Manufacturing
KW - Regulatory Compliance
UR - http://www.scopus.com/inward/record.url?scp=85189929133&partnerID=8YFLogxK
U2 - 10.1109/ACDSA59508.2024.10467315
DO - 10.1109/ACDSA59508.2024.10467315
M3 - Conference contribution
AN - SCOPUS:85189929133
T3 - International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024
BT - International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 International Conference on Artificial Intelligence, Computer, Data Sciences, and Applications, ACDSA 2024
Y2 - 1 February 2024 through 2 February 2024
ER -