Predictive Maintenance Market size was valued at USD 5.77 Billion in 2022 and is poised to grow from USD 7.57 Billion in 2023 to USD 66.46 Billion by 2031, at a CAGR of 31.2% during the forecast period (2024-2031).
The predictive maintenance market is a brand-new developed segment under the overlapping industrial and industrial maintenance. They use big-data analytics, where the company uses machine learning and IoT to predict when specific equipment or devices are likely to fail predictive maintenance using real-time data and historical data.
Pioneers in this market include IBM, Microsoft, SAP and General Electric. They provide end-to-end solutions to monitor the status of business assets and indicators that these assets require maintenance. The global predictive maintenance market is expected to witness a high growth rate in the coming year driven by increasing demand from manufacturing, energy and transportation sectors as they focus on cost savings, reliability and overall efficiency.
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Business Verticals: A Closer Look at the Competitive Landscape in Predictive Maintenance
Rapid technological advances and a growing number of competitors offering solutions. There is a mix of established technology giants in this market and mainstream companies focused on niche applications. Key players are leveraging artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) to tailor advanced predictive solutions. The competitive landscape is characterized by factors such as new developments, strategic partnerships, and mergers and acquisitions to increase capacity and expand markets.
In February 2024, the company will formally partner with Siemens as a service provider to facilitate the adoption of generative AI for businesses across all industries and scales. They appreciate the long-term collaboration of technology, manufacturing, logistics, insurance, or banking specialists who can do many effective new generative AI solutions.
In June 2023, Qatar Airways signed a partnership agreement with Google Cloud to provide data and artificial intelligence solutions to airlines. This engagement will primarily focus on areas such as predictive maintenance, passenger satisfaction and facilities, as these same objectives can be effective in streamlining customer-centric processes in the airline industry in the 19th century.
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Key Players and their Strategies
IBM Corporation
Strategy: IBM will focus on integrating AI and IoT to create robust predictive maintenance solutions. The company uses its Watson AI platform to analyze large amountsof data and predict device failures.
Example: IBM’s Maximo Asset Performance Management (APM) suite uses AI to track, monitor and manage assets in real-time, reducing downtime and maintenance costs.
General Electric (GE)
Strategy: GE leverages its expertise in engineering tools and software to provide predictive maintenance through its Predix platform. GE focuses on providing end-to-end solutions that integrate hardware and software.
Example: GE Digital’s Predix APM solution helps industries like aviation and energy optimize asset performance, predict failures, and ensure continuity.
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Future-Proofing Operations: The Rise of Predictive Maintenance
The competitive environment in the predictive maintenance market is dynamic, with established leaders and new entrants making breakthroughs in technologies and applications. Companies are investing heavily in AI, IoT and cloud computing to provide predictive maintenance edge products that reduce downtime, improve asset performance and reduce maintenance costs. Strategic partnerships and ongoing innovation are key to remaining competitive in this rapidly growing market, ensuring that companies can proactively meet their maintenance needs and achieve operational efficiencies.
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