Contextual Intelligence: An AI Approach to Manufacturing Skills’ Forecasting

The manufacturing industry is skill-intensive and plays a pivotal role in South Africa’s economy, reflecting the nation’s progress and development. The advent of technology has initiated a transformative era within the manufacturing sector. Workforce skills are at the heart of ensuring the sustained growth of the industry. This study delves into the skill-related aspects of the occupational landscape of the South African manufacturing sector, with a particular focus on two important manufacturing sectors: the food and beverage manufacturing (FoodBev) sector and the chemical manufacturing (CHIETA) sector. Leveraging the forecasting prowess of Autoregressive Integrated Moving Average (ARIMA), this paper outlines a sectorial occupational forecasting modeling exercise to reveal which job roles are poised for expansion and which are expected to decline. The approach predicted future skills’ demand 80% accuracy for 473 out of 713 (66%) occupations for FoodBev and 474 out of 522 (91%) for CHIETA. These insights are invaluable for industry stakeholders and educational institutions, providing guidance to support the sector’s growth in an era marked by technological advancement.

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Publication Details

Journal
Big Data and Cognitive Computing
Published
2024-09-02
DOI
https://doi.org/10.3390/bdcc8090101
Citations
1
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.35
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Contextual Intelligence: An AI Approach to Manufacturing Skills’ Forecasting

Xolani Maphisa, Arnesh Telukdarie, Mpho Godfrey Nkadimeng
1 citations
Big Data and Cognitive Computing
Scheduling and Optimization Algorithms
0.35
article

Contextual Intelligence: An AI Approach to Manufacturing Skills’ Forecasting

Xolani Maphisa, Arnesh Telukdarie, Mpho Godfrey Nkadimeng
article en
1 citations

Abstract

The manufacturing industry is skill-intensive and plays a pivotal role in South Africa’s economy, reflecting the nation’s progress and development. The advent of technology has initiated a transformative era within the manufacturing sector. Workforce skills are at the heart of ensuring the sustained growth of the industry. This study delves into the skill-related aspects of the occupational landscape of the South African manufacturing sector, with a particular focus on two important manufacturing sectors: the food and beverage manufacturing (FoodBev) sector and the chemical manufacturing (CHIETA) sector. Leveraging the forecasting prowess of Autoregressive Integrated Moving Average (ARIMA), this paper outlines a sectorial occupational forecasting modeling exercise to reveal which job roles are poised for expansion and which are expected to decline. The approach predicted future skills’ demand 80% accuracy for 473 out of 713 (66%) occupations for FoodBev and 474 out of 522 (91%) for CHIETA. These insights are invaluable for industry stakeholders and educational institutions, providing guidance to support the sector’s growth in an era marked by technological advancement.

Big Data and Cognitive ComputingVol. 8(9)
University of Johannesburg (ZA)
Openalex Percentile: Top 37%
Scheduling and Optimization Algorithms
0.35
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