The application and benefits of emerging digital technologies for Industry 4.0

Abstract

Industry 4.0 technology advancement in recent years has enabled organizations to capitalize on new processes and tools towards making their businesses more profitable and efficient. 4IR Technologies such as Artificial Intelligence, Machine Learning, Condition Monitoring and Internet of Things have been at the forefront of the digital revolution and have transformed the way organizations do business. However, these complex technologies come with many challenges such as startup costs, lack of knowledge experts as well as the limited technology foundation for both business owners, as well as their employees. Therefore, this study looks at the current knowledge of Industry 4.0 from individuals in the industry, which will provide information on the current trends as well as possible knowledge gaps. The research also explores the benefits of Industry 4.0 technologies by using machine learning technology to elaborate on how we can enhance organizations’ efficiencies. The purpose of this study is to contribute towards the successful implementation of Industry 4.0 and provide encouragement for organizations to start their digital revolution. The research follows both a qualitative and quantitative analysis process. The qualitative data is analyzed from a survey of individuals which enables us to dissect and better identify the current trends, and possible knowledge gaps whilst the quantitative data is analyzed using machine learning software to highlight the potential that can be attained if organizations decide to implement these types of technologies. A content and grounded theory method was used to analyze the qualitative data, as the feedback from the interviewees was constantly reviewed and compared with each other whilst also comparing that to the initial hypothesis statements. It was seen that current trend is that individuals in the industry are excited and are aware of Industry 4.0, but there are still some challenges such as legacy machines, return of investment and knowledge gaps. For the quantitative data, a thematic analysis was used, in the form of machine learning software, to identify patterns in the results and interpret them in a way that can be understood better. From the analysis, it was seen that the machine learning software has a positive impact as the software was able to identify the highest points of failure as well as the type of failure which occurred for a machine. The timeline of failure was also deduced and therefore the organization would be able to put measures in place to restrict these failures from happening. The research provides great benefit for future researchers as well as organizations on topics relating to Industry 4.0 towards connecting the power of the technologies to create a smooth transition within the workplace. The survey analysis offers a better understanding of the current trends in the industry, and the research in general provides a foundation towards the understanding of Industry 4.0, and provides valuable insight on the greater role that new digital technologies play towards creating a better future for organizations.