The Role of Artificial Intelligence Technologies in Improving Production Process Performance: A Case Study of the Al-Mansour/Bejji Plant of the General Food Products Company in Salah al-Din Governorate

Maysam Riyadh Bahr

Авторы

Maysam Riyadh Bahr Tikrit University Department of Public Administration

Ключевые слова:

Artificial intelligence technologies, production process performance, Al-Mansour Factory

Аннотация

This study aims to identify the role of artificial intelligence (AI) technologies in improving the performance of production processes through an applied study at the Al-Mansour/Beiji factory, which is affiliated with the General Company for Food Products in Salah al-Din Governorate. The study was based on the main hypothesis that artificial intelligence technologies have a statistically significant impact on production process performance, in addition to testing the impact of each of the following technologies: machine learning, expert systems, intelligent forecasting and data analysis, computer vision, and intelligent automation. The study used a descriptive-analytical design, with a sample of 100 factory workers of different job level and specialization. A questionnaire was used to collect the data. In order to analyze the data and test the research hypotheses, the various types of statistical methods were applied, among which correlation coefficient, Cronbach alpha, descriptive statistics, linear regression analysis were used. The results indicated that the implementation of artificial intelligence (AI) technologies in the factory was relatively high with the arithmetic mean of 3.83 and relative importance of 76.60%, and the performance of the production processes in the factory was 3.8 with a relative importance of 76.00%. The regression results also indicated that there is an influence of the use of AI technologies on the performance of production processes, as can be seen by the correlation value R of 0.746 and R² of 0.557, which means that AI technologies can explain about 55.7% of the variation of the performance of production processes. All five dimensions of artificial intelligence studied also had a significant effect, with intelligent automation showing the greatest effect, followed by intelligent forecasting and data analysis, machine learning, expert systems, and computer vision.

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