Industry 4.0 Technological Advancement in the Food and Beverage Manufacturing Industry in South Africa—Bibliometric Analysis via Natural Language Processing

Abstract

The food and beverage (FOODBEV) manufacturing industry is a significant contributor to global economic development, but it is also subject to major global competition. Manufacturing technology evolution is rapid and, with the Fourth Industrial Revolution (4IR), ever accelerating. Thus, the ability of companies to review and identify appropriate, beneficial technologies and forecast the skills required is a challenge. 4IR technologies, as a collection of tools to assist technological advancement in the manufacturing sector, are essential. The vast and diverse global technology knowledge base, together with the complexities associated with screening in technologies and the lack of appropriate enablement skills, makes technology selection and implementation a challenge. This challenge is premised on the knowledge that there are vast amounts of information available on various research databases and web search engines; however, the extraction of specific and relevant information is time-intensive. Whilst existing techniques such as conventional bibliometric analysis are available, there is a need for dynamic approaches that optimise the ability to acquire the relevant information or knowledge within a short period with minimum effort. This research study adopts smart knowledge management together with artificial intelligence (AI) for knowledge extraction, classification, and adoption. This research defines 18 FOODBEV manufacturing processes and adopts a two-tier Natural Language Processing (NLP) protocol to identify technological substitution for process optimisation and the associated skills required in the FOODBEV manufacturing sector in South Africa.