Technavio, a leading provider of market research reports, has released its latest study on Predictive Maintenance (Pdm) Market. This report offers a comprehensive analysis of the current market trends, emerging opportunities, and key challenges. Predictive maintenance (PdM) is a proactive approach to equipment maintenance that utilizes data analysis and predictive modeling to anticipate equipment failures before they occur. By consuming data, applying advanced algorithms, and developing models for future events, PdM solutions enable businesses to address potential issues before they escalate into costly downtime. The increasing adoption of innovative technologies, including AI, machine learning, cloud computing, advanced analytics, IoT, is driving the widespread implementation of PdM across industries. With significant investments being made in research and development for these technologies, the demand for predictive maintenance solutions is expected to grow substantially during the forecast period.
The global predictive maintenance (pdm) market size is estimated to grow by USD 33.77 bn from 2024-2028, according to Technavio. The market is estimated to grow at a CAGR of 39% during the forecast period. Increased adoption of advanced analytics by SMEs owing to rise in cloud computing is driving market growth, with a trend towards proliferation of advanced technologies, ai, and iot However, lack of expertise and technical knowledge poses a challenge. Some of the key industry leaders include Augury Inc., Avnet Inc., C3.ai Inc, Dell Technologies Inc., Deutsche Telekom AG, Fortive Corp., General Electric Co., Hitachi Ltd., Honeywell International Inc., International Business Machines Corp., PTC Inc., RapidMiner Inc., Reliability Solutions sp. z o.o., Robert Bosch GmbH, Rockwell Automation Inc., SAP SE, SAS Institute Inc., Schneider Electric SE, Siemens AG, and Warwick Analytics Services Ltd..
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Major Findings
Predictive Maintenance (PDM) is transforming maintenance practices through technologies such as electromagnetic radio fields, NFC chips, and sensors. NFC technology, in particular, is reducing manual intervention and human error, further fueling market growth during the forecast period.
The major challenge impeding market growth is the lack of expertise and technical knowledge. Predictive Maintenance (PdM) leverages sensors and condition-monitoring devices to analyze real-time data from sources like electromagnetic radio fields and NFC chips to forecast equipment failure and preemptively address maintenance needs.
NFC technology enhances PdM by facilitating distance transactions and interactions with smart posters and work orders via mobile devices. PdM shifts from time-based to condition-based maintenance, but these advanced technologies may also pose barriers to market growth due to their complexity.
The IT software market encompasses businesses specializing in the creation and distribution of application and system software. Application software companies focus on developing specialized software for business and consumer use, including enterprise, technical, and cloud-based solutions. Technavio's IT software market analysis considers the consolidated revenue of organizations providing various IT software offerings, including cloud services. This assessment excludes companies producing interactive home entertainment software and those classified under systems software for database management.
The Predictive Maintenance (Pdm) Market is experiencing significant growth, fueled by the Increased adoption of advanced analytics by SMEs owing to rise in cloud computing. Businesses are leveraging the products belonging to the market for customer engagement, transactional notifications, and promotional offers.
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Predictive Maintenance (PDM) employs analytics tools and sensor data to foresee equipment failures before they happen. This proactive approach uses predictive algorithms to analyze both historical and real-time data, allowing fleet and building managers to address potential issues before they become significant problems. By leveraging wireless internet connections for real-time data transmission and insights, PDM surpasses traditional maintenance practices, driving market growth in North America.
Predictive maintenance (PDM) is revolutionizing the way maintenance is performed in industries such as coal preparation plants. Traditional reactive maintenance methods, which involve waiting for equipment failure before taking action, are being replaced by condition-based maintenance (CBM) strategies. CBM uses real-time data from sensors like vibration meters to monitor assets such as centrifugal pump motors. Machine operators and maintenance staff receive work orders when baselines are exceeded, allowing for timely intervention. PDM technologies include infrared analysis, acoustic analysis, and vibration analysis. Maintenance software and CMMS systems facilitate data collection and analysis. Sensor devices like NFC technology enable smart posters and pocket dials to provide real-time information. However, human error and distance can impact transactions, making it essential to minimize these factors through proper training and implementation. Electromagnetic radio fields from NFC chips in devices can provide additional data, enhancing PDM's capabilities. By focusing on condition-based maintenance, coal preparation plants can reduce downtime, increase efficiency, and extend the life of their assets.
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