A Comprehensive Review of Skill Development in the Petrochemical Industry: Opportunities, Challenges, and Strategic Directions

Authors

  • Steevan Pinto, Dr. Rashmi Uchil

Keywords:

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Abstract

The petrochemical industry plays a critical role in the global economy, driving innovation and contributing significantly to industrial and economic growth through the production of essential materials like plastics, fertilizers, and synthetic fibers. The industry’s evolution,
particularly in the context of automation, digitalization, and sustainability, has created unprecedented opportunities and challenges for workforce development. As global demand for petrochemical products grows, projected to reach $958.8 billion by 2025 (WalkWater Talent Advisors, 2023), the industry’s reliance on a highly skilled and adaptable workforce becomes increasingly evident. Technological advancements such as artificial intelligence (AI), machine learning, and the Internet of Things (IoT) have redefined operational processes, necessitating a workforce equipped with both technical expertise and interdisciplinary knowledge (Nurgaliev, et al., 2021; Shinkevich, et al., 2021). However, skill gaps, workforce redundancy due to automation, and disparities in access to training pose significant barriers to the industry’s growth and efficiency.

References

• Nurgaliev, R. (2021). Training of personnel in the conditions of innovative management of petrochemical production. European Proceedings of Social and Behavioural Sciences, ICEST 2021, 1802-1808.

• WalkWater Talent Advisors. (2023). Industry paper: Petrochemicals industry. WalkWater Talent. Retrieved from

• Khattab, W., & El Attar, I. (2013). Proposed advanced training & educational methodologies, for tanker & gas industry. International Journal of Materials Science and Applications, 2(1), 1-7.

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Published

2024-12-31

How to Cite

Steevan Pinto, Dr. Rashmi Uchil. (2024). A Comprehensive Review of Skill Development in the Petrochemical Industry: Opportunities, Challenges, and Strategic Directions . Journal of Computational Analysis and Applications (JoCAAA), 33(08), 1613–1639. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/1752

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