predictive maintenance Market

The predictive maintenance market is projected to reach US$ 26,588.00 million by 2028 from US$ 5,316.99 million in 2021, growing at a CAGR of 27.4% from 2022 to 2028.

Advanced predictive maintenance solutions and services are increasingly being adopted by businesses to gain a competitive edge and minimize unexpected production delays. A number of macroeconomic factors have created challenging conditions for businesses globally. The COVID-19 pandemic, for instance, caused significant disruptions and resulted in substantial losses for several industry sectors. Furthermore, political factors in Europe, the Middle East, and South America negatively impacted various industry sectors. Additionally, severe economic downturns in numerous countries have decreased consumer spending on non-essential goods.

Enterprises are adopting measures to stay competitive in the face of factors such as economic downturns and political disruptions, which have made business environments unfavourable. One such measure is the adoption of technologies that can reduce production downtime and support continuous manufacturing activities. Predictive maintenance is one such technology that can aid organizations in reducing costs while staying competitive. According to studies, offshore oil and gas companies can use predictive maintenance solutions to reduce downtime by 20%, resulting in an increase in production of more than 500,000 oil barrels annually. The market for predictive maintenance is expected to experience growth during the forecast period due to these advantages.

Impact of COVID-19 Pandemic on Predictive Maintenance Market Growth

The outbreak of COVID-19 led to various restrictions imposed by governments to control its spread, which had adverse effects on the day-to-day operations of most enterprises. Companies faced supply chain disruptions, travel restrictions, and business shutdowns, causing revenue loss and reduced technological spending. As a result, many multinational enterprises had to reconfigure their manufacturing operations to continue functioning with reduced manpower. This sudden shift led to a surge in demand for predictive maintenance market players worldwide, as businesses increasingly adopted digital transformation to accommodate the changing business environment. Hence, both large enterprises and SMEs are expected to invest more money and energy in identifying intelligent management solutions to manage their plant machinery and equipment. However, the work-at-home modality is speculated to become the new normal for many people in the near future, creating a favorable outlook for the predictive maintenance market growth post-COVID-19.

China, Japan, and India dominate the Asia Pacific region's predictive maintenance market. China's market is growing rapidly and is among the fastest globally. Chinese companies are enthusiastic technology adopters in APAC, aiming to gain a competitive edge through digitalization and innovation. The increasing demand for predictive maintenance solutions from industries such as oil & gas, energy & utility, transportation, and logistics presents significant opportunities for market players to expand. For instance, in February 2022, Shentong Bombardier (Shanghai) Rail Transit Vehicle Maintenance Co., Ltd., a joint venture of Alstom in China, secured a contract worth US$ 44.85 million from Shanghai Shentong Metro Group Co., Ltd. (Shanghai Metro) to provide lifecycle maintenance services for 204 Movia metro cars and 34 trains, which further promotes the predictive maintenance market's growth in China.
The primary source of revenue in the predictive maintenance market has been the solutions segment. These solutions are tailored to meet the increasing demand from various industries for energy-efficient and cost-effective operations and data-driven decision-making supported by analytics tools. Market players in the predictive maintenance industry, such as Embitel and Cariad Group Company, provide solutions that integrate seamlessly with production systems and industrial assets.

Large enterprises are increasingly seeking application-specific predictive maintenance solutions to manage and collect data for uninterrupted production flows through maintenance scheduling. The segment growth is further propelled by the growing efforts of solution providers to enhance fleet management, HVAC controls, and remote diagnostics for buses, among others. For example, Continental AG has introduced ContiConnect 2.0, a predictive maintenance solution that includes standard and premium packages for tire pressure and temperature management and insights on tread depth and tire condition.

The utilization of drones equipped with sensors and cameras to detect corrosion in grid insulators and provide predictive maintenance solutions for various industries is driving the growth of the solutions segment and the overall predictive maintenance market. These drones transmit insights using AI through 5G, leading to an increased demand for these technologies.

General Electric Co.; Hitachi Ltd.; IBM Corporation; Microsoft Corporation; PTC, Inc.; SAS Institute Inc.; Schneider Electric SE; Software AG; Syncron AB; and TOSL Engineering Ltd. are a few key predictive maintenance market players.

The predictive maintenance market size has been determined using primary and secondary sources. The research process began with an extensive secondary research approach that involved collecting qualitative and quantitative information related to the market from internal and external sources. This process aimed to obtain an overview and forecast of the predictive maintenance market size across all market segments. Industry participants and commentators were also consulted through multiple primary interviews to validate the data and gain more analytical insights. The participants in this process included key personnel such as VPs, business development managers, market intelligence managers, national sales managers, external consultants like valuation experts, research analysts, and key opinion leaders specializing in the predictive maintenance market.