Europe Machine Condition Monitoring Market - Growth, Trends, Covid-19 Impact, and Forecasts (2023 - 2028)
The European machine condition monitoring market was valued at USD 834.4 million in the base year. It is expected to reach a value of USD 1,210.23 million, registering a CAGR of 7.72% in the next five years. An outlook toward low-cost mass production has led maintenance professionals to turn to condition monitoring. With active machine condition monitoring, multiple industries can prevent machine failures, which is an added capital investment.
Key HighlightsThe European machine condition monitoring market is moderately fragmented, with key players like Honeywell International Inc., Schaeffler Technologies AG & Co. KG, General Electric Company, Emerson Electric Co., and Fluke Corporation, among others. Players in the market are adopting strategies such as partnerships, innovations, mergers, and acquisitions to enhance their product offerings and gain sustainable competitive advantage.
In July 2022, GE announced plans to become three independent and publicly traded businesses focusing on healthcare, energy, and aviation, where new names also reflect a new beginning. GE’s healthcare business would be called GE HealthCare. GE’s existing portfolio of energy businesses, including renewable energy, power, digital, and energy financial services, would sit together under the brand name GE Vernova. GE Aerospace would be the name of GE’s aviation business.
In May 2022, NI announced the launch of ActiveUptime, its maintenance-as-a-service solution for condition monitoring and predictive maintenance of test equipment and facilities. This turnkey solution is tailored to the user’s environment and provides the information needed to proactively monitor system health and prevent critical test equipment from failing. As part of the ongoing service, a dedicated technician from NI’s maintenance team is expected to remotely monitor system health, provide support, and adapt the solution based on the customer’s needs. This solution advances the user’s capabilities to predict outages before they happen proactively.
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