Artificial intelligence system


to improve asset management program

in industry 4.0: Manufacturing case study



By Dr Lalamani Budeli

South Africa


As Industry 4.0 continues making media dominance, various associations are fighting with the genuine components of artificial intelligence (AI) use in Maintenance. For a machine to be on the lookout, it should have the choice to learn. Man-made intelligence is the cycle by which personal computer structures access data, run examines, and acquire truly a comparable way humans do. Development has been joined into asset the heads for a seriously long time with a grouping of livelihoods. The upsides of insightful help, which consolidate choosing the condition of stuff and envisioning when Maintenance ought to be performed, are unfathomably indispensable. Mechanical help experts grasp that the use of AI (ML) based game plans can incite huge costs, save reserves, higher consistency, and the extended plainness of the systems.

The inspiration driving this article is to inspect the use of artificial intelligence in asset maintenance programs and how this will assist companies with reducing their working and maintenance cost while improving asset availability, reliability, maintainability While extending the overall asset life. This will be a basic driver of capacities need for industry 4.0 to the extent of the sort of specialists, maintainers, and overseers required and the aptitudes they should need to play out their functions.

Keywords: Predictive maintenance, Industry 4.0, Artificial intelligence


Even though Maintenance designing and support have a similar end level headed or, the conditions under which they work vary altogether. Maintenance designing is a logical capacity that is conscious and deliberate whereas support is a capacity that should be performed under regularly antagonistic conditions and stress, and its fundamental goal is to quickly re-establish the equipment to its operational preparation state utilizing accessible assets. The contributing goals of Maintenance designing incorporate improving Maintenance activities, lessening the sum and recurrence of Maintenance, decreasing the impact of intricacy, diminishing the support abilities required, diminishing the measure of provider uphold, set up ideal recurrence and degree of preventive support to be done, improve and guarantee most extreme use of support offices, and improve the support association.

In industry 4.0, the kinds of advances to be used in support designing incorporate AI and ML expand on the current frameworks and innovation foundation isolating innovation into three fundamental classes which are (1) client experience and interfaces, (2) Operational productivity, and (3) venture measures. In industry 4.0, artificial intelligence and AI innovation can help organizations in every classification to improve productivity, oversee danger, and upgrade dynamic. These advancements include individuals (specialists) who give oversight and consider the yields of innovations for a more educated dynamic.

Research Method

According to Foresti, Rossi, Magnani, Bianco & Delmonte (2020:840), a research design is a blueprint for getting from the beginning to the end of a study. The beginning is an initial set of questions to be answered, and the end is some set of conclusions about those questions. According to Mushiri, Hungwe & Mbohwa (2017:1487), a research design is the string of logic that ultimately links the data to be collected and the conclusions to be drawn to the initial questions of the study. In this study, a case study research experiment will be followed to determine:

  1. A study’s hypothesis.
  2. A study’s propositions.
  3. A study’s units of analysis.
  4. The logic linking of the data to the propositions.
  5. The criteria for interpreting the findings.


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How to cite this paper: Budeli, L. (2021). Artificial intelligence project to improve asset management program in industry 4.0: Manufacturing case study, PM World Journal, Vol. X, Issue V, May. Available online at https://pmworldlibrary.net/wp-content/uploads/2021/05/pmwj105-May2021-Budeli-AI-to-improve-asset-management-in-industry-4-0.pdf

About the Author

Dr Lalamani Budeli

South Africa


Dr Lalamani Budeli obtained his degree in Electrical Engineering at the Vaal University (VUT), BSc honors in Engineering Technology Management at University of Pretoria (UP), Master in engineering development and Management at North West University (NWU), Master of business administration at Regent Business School (RBS) and a Doctor of Philosophy in Engineering Development and Management at North West University (NWU), Potchefstroom, South Africa. Currently, he is a managing director of BLIT, an engineering, research, and project management company based in South Africa.

His research interests include project portfolio management, agile project management, plant life cycle management, advanced systems analytics, project early warning system, and the use of artificial intelligence in project management. Currently, he is spending most of the time on research that is looking at the development of system and application that uses the latest technology like block chain, internet of things (IoT), Big data, and artificial intelligence. Lalamani Budeli can be contacted at budelil@blit.co.za.

To view other works by Dr. Budeli, visit his author showcase in the PM World Library at https://pmworldlibrary.net/authors/lalamani-budeli/