Predictive maintenance is a technique designed to help determine the condition of in-service equipment in order to predict when maintenance should be performed. It includes regular monitoring of the actual mechanical condition, operating efficiency. Process systems will provide the data required to ensure the maximum interval between repairs and minimize the number and cost of unscheduled outages created by machine-train failures. In all the manufacturing companies and production plants, maintenance costs are a major part of the total operating cost. Depending on the specific industry, maintenance costs can be as high as 15% to 60% of the cost of goods produced. Maintenance cost for iron and steel, pulp and paper, and other heavy industries are comparatively higher than that of food related industries. One of the main reasons for the increasing usage of predictive maintenance is the ability of these software solutions to precisely predict asset failure, enabling enterprises to take the asset out of production just before it is to fail, thus ensuring production is not hampered in any way due to the failure of the asset.
The global predictive maintenance market size is expected to grow from US$ XXXX.X million in 2017 to US$ XXXX.X million by 2026, at a CAGR of XX.X% during the forecast period. Factors such as the lowering maintenance cost with reduced downtime, rising demand for better monitoring and predictive technology in developed countries, and widespread of Internet of Things (IoT) are fueling demand for predictive maintenance solutions & services. In addition, increasing popularity and rising adoption of predictive maintenance solutions across all the major verticals, such as government, aerospace & defense, manufacturing, energy & utilities, healthcare, and transportation & logistics are driving the growth of market. However, high cost, lack of training and trust for predictive maintenance are the major factors restraining the growth of the market.
North America is estimated to have the largest market share and is expected to dominate the predictive maintenance market during the forecast period. Asia-Pacific offers potential growth opportunities for the predictive maintenance market to grow in this region.
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The manufacturers are seeing maintenance as a strategic business function, as lowering the maintenance cost is expected to help increase profitability, thus manufacturing vertical segment has the largest market size in the predictive maintenance market. Also, rising adoption of advanced technology of cloud-based deployment, as it reduces enterprises“ dependency on IT, data mining specialist, and data integration, cloud-based predictive maintenance market is expected to grow at the highest CAGR.
The major vendors in the predictive maintenance market include IBM (U.S.), SAP SE (Germany), Software AG (Germany), General Electric (U.S.), Robert Bosch (Germany), Rockwell Automation (U.S.), PTC (U.S.), Warwick Analytics (U.K.), RapidMiner (U.S.), and SKF (Sweden).
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