OPTIMIZING PRODUCTIVITY IN METALWORK MANUFACTURING THROUGH TECHNOLOGICAL ADOPTION IN NIGERIA

This research examined the impact of Artificial Intelligence (AI) technologies on optimizing manufacturing processes in Nigeria's manufacturing industry, emphasizing critical outcomes such as efficiency, productivity, and product quality. Data were obtained using structured questionnaires from a sample of 342 respondents from Ajaokuta Steel Company Limited and Universal Steel Nigeria Ltd. The outcomes were examined using multiple regression models. The findings indicate a strong positive correlation between technological adoption and productivity optimization, with a regression coefficient of 0.583 and a statistically significant p-value of 0.000. Improved infrastructure and workforce skill levels were also found to significantly enhance productivity, with coefficients of 0.245 and 0.198, respectively. Furthermore, the study revealed that technological advancements contribute significantly to product quality improvements, as evidenced by a coefficient of 0.502 and a p-value of 0.000. Larger firms with greater financial resources demonstrated a higher capacity for technological integration, as indicated by a coefficient of 0.269 and a p-value of 0.002. These results align with existing literature highlighting the role of automation and digital technologies in enhancing efficiency and reducing defects in manufacturing. The study concludes that modern technology adoption is essential for productivity growth in Nigeria’s metalwork sector. However, challenges such as inadequate infrastructure and skill gaps persist. It recommends strategic investments in infrastructure, targeted workforce training, and supportive policies to strengthen the sector’s competitiveness and contribute to Nigeria’s industrialization.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-20
DOI
https://doi.org/10.5281/zenodo.15705774
Primary Topic
Digital Transformation in Industry
Type
article
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article

OPTIMIZING PRODUCTIVITY IN METALWORK MANUFACTURING THROUGH TECHNOLOGICAL ADOPTION IN NIGERIA

Zenodo (CERN European Organization for Nuclear Research)
Digital Transformation in Industry
article

OPTIMIZING PRODUCTIVITY IN METALWORK MANUFACTURING THROUGH TECHNOLOGICAL ADOPTION IN NIGERIA

article en

Abstract

This research examined the impact of Artificial Intelligence (AI) technologies on optimizing manufacturing processes in Nigeria's manufacturing industry, emphasizing critical outcomes such as efficiency, productivity, and product quality. Data were obtained using structured questionnaires from a sample of 342 respondents from Ajaokuta Steel Company Limited and Universal Steel Nigeria Ltd. The outcomes were examined using multiple regression models. The findings indicate a strong positive correlation between technological adoption and productivity optimization, with a regression coefficient of 0.583 and a statistically significant p-value of 0.000. Improved infrastructure and workforce skill levels were also found to significantly enhance productivity, with coefficients of 0.245 and 0.198, respectively. Furthermore, the study revealed that technological advancements contribute significantly to product quality improvements, as evidenced by a coefficient of 0.502 and a p-value of 0.000. Larger firms with greater financial resources demonstrated a higher capacity for technological integration, as indicated by a coefficient of 0.269 and a p-value of 0.002. These results align with existing literature highlighting the role of automation and digital technologies in enhancing efficiency and reducing defects in manufacturing. The study concludes that modern technology adoption is essential for productivity growth in Nigeria’s metalwork sector. However, challenges such as inadequate infrastructure and skill gaps persist. It recommends strategic investments in infrastructure, targeted workforce training, and supportive policies to strengthen the sector’s competitiveness and contribute to Nigeria’s industrialization.

Zenodo (CERN European Organization for Nuclear Research)
Federal College of Education, Kano (NG)
Industry, innovation and infrastructure
Openalex Percentile: Top 42%
Digital Transformation in Industry
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