The Machine Condition Monitoring Service market, which in 2021 handled US$2,084 million, is expected to reach US$2,789.2 million by 2028, according to MarketWatch projections. Another study, from Future Market Insights, speaks of US$ 6.79 billion by the end of 2031. Machine condition monitoring refers to the process of monitoring and measuring temperature, humidity, and pressure in mechanical equipment. It is commonly used on pumps, rotary, and electric motors, internal combustion engines (ICEs), and presses. This involves vibration monitoring, corrosion monitoring, thermographic, oil analysis, ultrasonic emission, and motor current analysis. These processes help predict mechanical wear and diagnose the location of unwanted noise, vibration, and heat generation that can damage machine components. They also enable proper scheduling of maintenance programs, minimizing the severity of machine downtime and ensuring equipment safety. Increasing digitization along with significant growth in oil & gas, automotive, defense, aerospace, manufacturing, food & beverage, and marine industries is one of the major factors creating a positive outlook for the market. In addition, various technological advancements such as the use of secure cloud computing platforms, wireless technologies, and integration with the Internet of Things (IoT) are acting as other major growth-inducing factors. According to Future Market Insights, the portable machine diagnostics segment is shaping the condition monitoring services market revenue as portable equipment is used to analyze sensor data, saving operation time. Moreover, in the current scenario, the integration of condition monitoring software with computerized maintenance management services and process control software is noted as an emerging trend. To minimize asset downtime, it is necessary to monitor assets continuously or at regular intervals, especially in facilities such as power generation and petrochemical plants. Given the importance of highly accurate results in such facilities, manufacturers are striving to further develop condition monitoring software that can be integrated with services to record data. Demand for condition monitoring services is expected to gain momentum in South Asia in the coming years due to increasing investments in power generation and petrochemical industries. Governments in countries such as India and Indonesia are encouraging private sector players to minimize power deficit to meet maximum power requirements. This, in turn, is supporting the condition monitoring services market in the region. However, North America is a prominent market for condition monitoring services and is expected to maintain its hegemony owing to its strong industrial growth and high adoption of the services in the region. It is worth remembering that the main focus of industrial automation is centered on the capabilities of advanced technology, along with concerns about cybersecurity and the environment. And that among the automation trends for 2022, the advanced use of IIoT (Internet of Industrial Things) for condition monitoring has been unanimous. The IIoT enables several enhanced engineering strategies, such as root cause analysis, predictive maintenance (PM), big data analytics, and condition monitoring (CM). Industry experts are recording a definite shift in machine manufacturers towards CM as they begin to understand how it works and what key benefits it can deliver. Using a wide variety of IIoT sensors for CM covers the particular conditions of a machine and assists in immediately identifying any operational changes that may indicate the development of a fault, transmitting system alerts, and/or triggering corrective actions. It is very useful on things like motors, presses, pumps, and compressors, and the range of parameters that can be monitored is constantly expanding. Real-time CM data analysis can also extend to wider performance analysis, such as machine usage, cycles, and hours of operation. More advanced IIoT technologies mean the production of much more data, collected constantly and in real-time. This will continue as one of the key automation trends of 2022 as companies learn to exploit its full potential. Big data reflects every input and action of the automated production process, which can be studied or stored for further analysis. Data analysts can find faults in a process, gaps in procedure and assess the total lifecycle of their equipment. Big data allows businesses to see exactly what is happening in their company minute by minute. They can then produce better planning and forecasting models, which in turn will improve productivity and profits. In some cases, larger companies can aggregate the data from multiple production facilities to get a more comprehensive picture of their operations in SCADA dashboards designed to monitor, visualize, control, and regulate industrial production and IT. These processes can also be further enhanced by artificial intelligence (AI) and machine learning (ML). The digitalization of manufacturing is a critical factor in today's global competitive framework. Traditionally isolated factories and machines need access to the Internet for logistics, predictive maintenance, and individualized (on-demand) customer production. All this requires extended communication that is only possible through classical IT. The IT/OT convergence is the consequence of this new context.