Artificial Intelligence as a Catalyst for Operational Excellence in Iraqi Industries: Implementation of a Proposed Model
محورهای موضوعی : فصلنامه ریاضی
Mayyadah Mohammed Ridha Naser
1
,
Mohammad Jalali Varnamkhast
2
,
Husam Jasim Mohammed
3
,
مجتبی آقاجانی
4
1 - Department of Industrial Management , Isfahan Branch (Khorasgan), Islamic Azad University, Isfahan, Iran
2 - Department of Industrial Management, Isfahan Branch (Khorasgan), Islamic Azad University, Isfahan, Iran,
3 - Al-Karkh University of Science, Baghdad, Iraq
4 - استادیار، گروه مدیریت، واحد مبارکه، دانشگاه آزاد اسلامی، اصفهان، ایران
کلید واژه: Artificial intelligence, Operational excellence, Iraqi industries, Implementation, Model. ,
چکیده مقاله :
This study explores the potential of artificial intelligence (AI) as a catalyst for achieving operational excellence in Iraqi industries, specifically targeting the textile and food processing sectors. The objective is to assess how AI can enhance efficiency, productivity, and decisionmaking. The research introduces an AI model that comprises five components: data collection, data processing, the implementation of AI algorithms, a decision support system, and a feedback mechanism for continuous improvement. Data is gathered from diverse sources, such as sensors and Enterprise Resource Planning (ERP) systems. This data undergoes cleaning and processing, followed by the application of machine learning and deep learning algorithms for predictive analytics and pattern recognition. The implementation of the AI model demonstrated significant improvements across both sectors. In the textile industry, production output increased by 100%, defect rates fell from 8% to 4%, and customer satisfaction improved from 85% to 92%. In the food processing sector, production output rose by 50%, spoilage rates decreased from 5% to 2.5%, and customer satisfaction reached 96%. These results highlight the successful integration of AI into traditional manufacturing processes. The results suggest that AI can transform conventional manufacturing practices, fostering a culture of continuous improvement and enhancing competitiveness in global markets. This research offers a novel approach to leveraging AI for operational excellence, underscoring its potential for driving growth and innovation in the Iraqi economy.
This study explores the potential of artificial intelligence (AI) as a catalyst for achieving operational excellence in Iraqi industries, specifically targeting the textile and food processing sectors. The objective is to assess how AI can enhance efficiency, productivity, and decisionmaking. The research introduces an AI model that comprises five components: data collection, data processing, the implementation of AI algorithms, a decision support system, and a feedback mechanism for continuous improvement. Data is gathered from diverse sources, such as sensors and Enterprise Resource Planning (ERP) systems. This data undergoes cleaning and processing, followed by the application of machine learning and deep learning algorithms for predictive analytics and pattern recognition. The implementation of the AI model demonstrated significant improvements across both sectors. In the textile industry, production output increased by 100%, defect rates fell from 8% to 4%, and customer satisfaction improved from 85% to 92%. In the food processing sector, production output rose by 50%, spoilage rates decreased from 5% to 2.5%, and customer satisfaction reached 96%. These results highlight the successful integration of AI into traditional manufacturing processes. The results suggest that AI can transform conventional manufacturing practices, fostering a culture of continuous improvement and enhancing competitiveness in global markets. This research offers a novel approach to leveraging AI for operational excellence, underscoring its potential for driving growth and innovation in the Iraqi economy.
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