According to the report, the global predictive maintenance industry garnered $2.80 billion in 2018, and is estimated to reach $23.01 billion by 2026, growing at a CAGR of 30.2% from 2019–2026.
The report also provides a detailed analysis of the drivers & opportunities, top investment pockets, top winning strategies, market size & estimations, competitive landscape, and wavering market trends.
The need to improve uptime of equipment and increase in investment on predictive maintenance fuel the growth of the global predictive maintenance market. On the other hand, lack of skilled staff, difficulties in implementation, and data privacy & security concerns are some of the factors that restrain the growth to certain extent. However, integration of predictive maintenance with IIoT and use of machine learning are expected to create a number of lucrative opportunities in the near future.
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Impact of Covid-19 on Predictive Maintenance Market:
- Shortage of employees, disrupted supply chain, and increase in demand for various goods during the pandemic prompted organizations to take special care of their manufacturing equipment to escalate the output. This, in turn, led way to rise in demand for predictive maintenance solutions across the globe.
- Many enterprises have started using smart sensors, artificial intelligence systems, and other IIoT solutions to keep a tab on the efficiency of vital machinery used in their
manufacturing procedure to evade costly production downtimes.
Based on component, the solution segment accounted for more than two-third of the global predictive maintenance market share in 2019, and is anticipated to retain its dominance by 2027. Companies are looking for all-inclusive development solutions which integrate hardware sensor board and software environment created precisely for predictive maintenance requirements, which drives the segment growth.
The services segment, on the other hand, would register the fastest CAGR OF 31.4% from 2020 to 2027. This is attributed to the fact that companies are trying to achieve profit by implanting predictive analytics into their products and offering better maintenance services.
Based on technique, the vibration monitoring segment contributed to nearly one-fourth of the global predictive maintenance market revenue in 2019, and is projected to dominate by the end of 2027. The need for parts to be ordered more effectively increases the demand for this technique, thereby boosting the segment growth.
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Simultaneously, the shock pulse segment would manifest the fastest CAGR of 31.4% throughout the forecast period. Shock pulse technique specializes in defining precise information on the mechanical condition of the bearing surfaces along with the state of lubrication on the bearing. This factor drives the growth of the segment.
Based on region, North America held the major share in 2019, garnering more than one-third of the global predictive maintenance market, owing to the presence of a large number of solution and service vendors in this region. At the same time, the predictive maintenance market across Taiwan (Asia-Pacific) would cite the fastest CAGR of 30.3% from 2020 to 2027, due to rapid industrialization in this province.
The key players operating in the global predictive maintenance market analysis include IBM Corporations; Microsoft; SAP SE; General Electric; Schneider Electric; Hitachi; PTC; Software AG; SAS; Engineering Consultants Group, Inc.; Expert Microsystems, Inc.; SparkCognition; C3.Ai; Uptake Technologies Inc.; Fiix Inc.; Operational Excellence (Opex) Group Ltd, TIBCO Software Inc.; Asystom; Reliability Solutions Sp. zo.o. and Sigma Industrial Precision.
Key Benefits For Stakeholders
- This study includes the analytical depiction of the global predictive maintenance market forecast and trends to determine the imminent investment pockets.
- The report presents information related to key drivers, restraints, and Predictive Maintenance Market opportunity.
- The current market size is quantitatively analyzed from 2019 to 2027 to highlight the financial competency of the predictive maintenance industry.
- Porter’s five forces analysis illustrates the potency of buyers & suppliers in the predictive maintenance market.
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