Industry 4.0 is evolving through technological advancements, leveraging information technology to enhance industry with digitalisation and intelligent activities. Whereas Industry 5.0 is the Age of Augmentation, striving to concentrate on human-centricity, sustainability, and resilience of the intelligent factories and synergetic industry. The crucial enhancer for the improvements accomplished by digital transformation is the notion of ‘digital triplet D3’, which is an augmentation of the digital twin with artificial intelligence, human ingenuity, and experience. digital triplet D3 encompasses intelligent activities based on human awareness and the convergence among cyberspace, physical space, and humans, in which Implementing useful reference hierarchy is a crucial part of instigating Industry 5.0 into a reality. This paper depicts a digital triplet which discloses the potency of retrofitting a conventional drilling machine. This hierarchy included the perceptive level for complex decision-making by deploying machine learning based on human ingenuity and creativity, the concatenated level for controlling the physical system’s behaviour predictions and emulation, the observing level is the iterative observation of the actual behaviour of the physical system using real-time data, and the duplicating level visualises and emulates virtual features through physical tasks. The accomplishment demonstrated the viability of the hierarchy in imitating the real-time functionality of the physical system in cyberspace, an immaculate performance of this paradigm. The digital triplet’s complexity was diminished through the interaction among facile digital twins, intelligent activities, and human awareness. The performance parameters of the digital triplet D3 paradigm for retrofitting were eventually confirmed through appraising, anomaly analysis, and real-time monitoring.

This study is carried out for determining the effect of coating thickness on Hardness which is used on the protective layer when polyester coating is applied on the aluminum coil. Total 120 samples with aluminum substrate and coated with polyester coating were used for Hardness test. For coating thickness six group were made (Group 1 = 73 μm), (Group 2 = 81μm), (Group 3 = 120 μm), (Group 4 = 150 μm), (Group 5 = 180 μm) and (Group 6 = 210μm), for each group Twenty samples were used. Hardness was investigated by using three methods: indentation hardness, damping hardness, and Scratch hardness; in addition we investigated their relationship and the effect of the coating thickness. Statistical analysis (ANOVA Test, Kruskal-Wallis Test& Bivariate Correlate Test) were used to compare mean effect of different thickness on Hardness, and to evaluate correlation between coating thickness and Hardness. According to the result of the study, an excellent correlation between Hardness (indentation hardness, damping hardness) and thickness of polyester coatings is obtained, which is fairly supported by the experimental and statistical data.