February 21, 2024
Machine Condition Monitoring Market

Advanced Condition Monitoring Systems to Boost Growth of the Global Machine Condition Monitoring Market

The global Machine Condition Monitoring Market is estimated to be valued at US$ 3965.6 Mn in 2023 and is expected to exhibit a CAGR of 9.1% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.

Market Overview:

Machine condition monitoring systems are used to track and monitor equipment and its performance in a variety of industrial domains including manufacturing, mining, oil & gas, and energy & power among others. These systems monitor parameters like vibration, temperature, humidity, pollution levels, pressure and noise levels to detect anomalies, faults and predict malfunctions. They help maximize equipment uptime, reduce unplanned downtime and maintenance costs. They also enable condition-based and predictive maintenance through continuous monitoring and analysis of equipment health data.

Market key trends:

The global machine condition monitoring market is witnessing rapid adoption of wireless and portable devices for continuous vibration monitoring of rotating equipment like motors, pumps and compressors. Wireless systems facilitate installation and maintenance while offering enhanced mobility. Another major trend is the use of advanced analytics and artificial intelligence to analyze huge amounts of condition monitoring data and detect subtle changes indicating impending equipment faults. Integration of machine learning and predictive algorithms is enabling highly accurate equipment prognostics and prescriptive maintenance for improved asset utilization and productivity. Manufacturers are also offering customized monitoring solutions for specific industrial machines and processes. Standardization of data communication protocols is further expected to bolster the market growth over the forecast period.

Porter’s Analysis

Threat of new entrants: New entrants face high initial costs in establishing manufacturing units and developing monitoring technologies. Strict regulatory policies for machine safety also pose barriers.
Bargaining power of buyers: Buyers have high bargaining power as they can choose from various global and regional providers offering customized solutions.
Bargaining power of suppliers: Key suppliers include component and software providers. Their impact is moderate as machine condition monitoring solutions utilize standard components.
Threat of new substitutes: Alternatives like predictive maintenance pose threats. However, real-time monitoring provides greater control and visibility to address urgent issues.
Competitive rivalry: The market is moderately competitive with technology giants and startups vying for market share. Price wars are common to expand customer base.

Key Takeaways

The Global Machine Condition Monitoring Market Size is expected to witness high growth, exhibiting a CAGR of 9.1% over the forecast period 2023 to 2030, due to increasing demand for preventive maintenance of critical assets and growing emphasis on cost savings through efficient maintenance strategies.

Regional analysis: Asia Pacific is expected to dominate the market, growing at a CAGR of over 10% during the forecast period. This can be attributed to rapid industrialization in China and India and increasing adoption across sectors like oil & gas, metals & mining, and power generation in the region. Europe and North America are also significant markets with presence of global giants.

Key players analysis: Key players operating in the Machine Condition Monitoring Market are Meggitt Sensing Systems, SKF AB, Parker Kittiwake, Rockwell Automation Inc., Thermo Fisher Scientific Inc., GE Bently Nevada, Perkin Elmer Inc., Emerson Electric Co., Gastops Ltd, Nippon Avionics Co. Ltd, AMETEK Spectro Scientific, FLIR Systems Inc. and Fluke Corporation. The market is witnessing increased R&D investments by players to develop advanced data analytics and IoT-enabled solutions.

*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it