Operational Predictive Maintenance Global Market Report 2024

The operational predictive maintenance market size has grown exponentially in recent years. It will grow from $5.78 billion in 2023 to $7.31 billion in 2024 at a compound annual growth rate (CAGR) of 26.5%. The growth observed during the historic period can be attributed to several factors, including cost savings resulting from reduced downtime and maintenance costs, improved asset reliability and performance, enhanced safety and risk mitigation measures, regulatory compliance requirements, and a growing awareness of the benefits of predictive maintenance.

The operational predictive maintenance market size is expected to see exponential growth in the next few years. It will grow to $18.62 billion in 2028 at a compound annual growth rate (CAGR) of 26.3%. The anticipated growth in the forecast period can be attributed to several factors, including expansion into new industries and applications, increasing demand for proactive maintenance solutions, market penetration in emerging economies, adoption of predictive maintenance practices, and a heightened focus on sustainability and energy efficiency initiatives. Major trends expected in the forecast period include the integration of IoT sensors and data analytics, adoption of machine learning algorithms, expansion of applications across various industries, development of cloud-based platforms, and integration with enterprise asset management systems.

The growth of the operational predictive maintenance market is expected to be driven by the increasing adoption of IoT (Internet of Things) devices in the foreseeable future. IoT devices, including sensors, actuators, and appliances, connect wirelessly to networks and transmit data, facilitated by widespread high-speed internet connectivity, industrial automation, supply chain management advancements, and data analytics capabilities. These devices are integral to operational predictive maintenance, enabling real-time monitoring, data analytics, early issue detection, condition-based maintenance, predictive insights, and continuous improvement. They help organizations optimize asset performance, reduce costs, and enhance operating efficiency. For example, Akamai Technologies Inc. predicts that IoT connections will rise from 15.1 billion in 2021 to 23.3 billion by 2025, illustrating the increasing prevalence of IoT devices driving the operational predictive maintenance market.

Leading companies in the operational predictive maintenance market are leveraging innovative AI technologies, such as AI-based predictive maintenance solutions, to enhance the accuracy, efficiency, and effectiveness of predictive maintenance processes. These solutions utilize AI or ML (machine learning) technology to monitor industrial equipment condition locally, without relying on internet-based cloud connections. QuickLogic Corporation, for instance, introduced an AI-based predictive maintenance solution in May 2021, leveraging the QuickLogic EOS S3 Platform and SensiML Analytics Toolkit. This solution integrates AI and ML technology to monitor manufacturing equipment, distinguishing between normal and abnormal operations. The platform, designed for mobile markets and IoT applications, offers low-power consumption and supports a wide range of open-source software and hardware, facilitating rapid and efficient solution development.

In March 2023, Schaeffler Group, a German automotive industry company, acquired ECO-Adapt SAS to bolster its presence in the growing predictive maintenance market. This strategic move aims to expand Schaeffler's service offerings, strengthen its market position, and contribute to its customers' sustainable future. ECO-Adapt SAS, based in France, specializes in energy monitoring and predictive maintenance services.

Major companies operating in the operational predictive maintenance market are Google LLC, Microsoft Corporation, Robert Bosch GmbH, Hitachi Ltd., Amazon Web Services Inc., The International Business Machines Corporation, General Electric Company, Schneider Electric SE, SAP SE, Svenska Kullagerfabriken AB, Rockwell Automation Inc., SAS Institute Inc., Micro Focus, Splunk Inc., PTC Inc., Software AG, TIBCO Software Inc., C3.ai Inc, Softweb Solutions Inc, Fiix Software, Uptake Technologies Inc., eMaint Enterprises LLC, Seebo Interactive Ltd., Asystom, Ecolibrium Energy.

North America was the largest region in the operational predictive maintenance market in 2023. The regions covered in the operational predictive maintenance market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the operational predictive maintenance market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Operational Predictive Maintenance (OPM) is a proactive maintenance strategy that leverages data analytics, machine learning, and predictive modeling techniques to forecast equipment failures or maintenance requirements before they occur. The objective of OPM is to minimize downtime, reduce maintenance costs, and optimize the efficiency and reliability of equipment and processes.

The primary types of Operational Predictive Maintenance include software and services. Software encompasses a collection of programs, instructions, and data that enable computers and other electronic devices to perform specific tasks, functions, or operations. It can be deployed in the cloud or on-premise and utilizes various technologies such as machine learning, deep learning, big data, and analytics. It is utilized by various end-users, including the public sector, automotive, manufacturing, healthcare, energy and utilities, transportation, and others.

The operational predictive maintenance market research report is one of a series of new reports that provides operational predictive maintenance market statistics, including operational predictive maintenance industry global market size, regional shares, competitors with an operational predictive maintenance market share, detailed operational predictive maintenance market segments, market trends and opportunities, and any further data you may need to thrive in the operational predictive maintenance industry. This operational predictive maintenance market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The operational predictive maintenance market includes revenues earned by entities by providing services such as data analytics and modeling, predictive maintenance modeling, condition monitoring, failure prediction and diagnostics, performance monitoring and optimization, and training and support. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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