Predictive maintenance solutions have the ability to precisely predict asset failure, which is one of the major reasons for the increasing adoption of these systems. This helps enterprises plan removal of the asset before it fails, thereby ensuring production is not affected due to action taken beforehand.
San Francisco, CA -- (SBWIRE) -- 04/09/2018 -- Predictive maintenance (PdM) solutions are designed to help predict when an in-service equipment might fail and to perform maintenance before the failure occurs. This approach enables convenient planning of corrective maintenance resulting in considerable cost savings as action is taken before the equipment failure occurs.
Other advantages of predictive maintenance include increased equipment longevity, increased plant safety, better spare parts handling, and fewer accidents that can be detrimental to the environment.
The predictive maintenance ecosystem constitutes vendors that provide predictive maintenance solutions to carry out the maintenance needs across several industry verticals.
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Predictive Maintenance Market: Key Trends
Predictive maintenance solutions are increasingly being adopted across several industry verticals such as aerospace and defense, energy and utilities, transportation and logistics, manufacturing, healthcare, and government. This is due to their ability to reduce operational and maintenance costs and minimize asset downtime. The adoption of predictive maintenance solutions enhances decision making capabilities of enterprises for planning production cycle and related aspects.
Predictive maintenance solutions have the ability to precisely predict asset failure, which is one of the major reasons for the increasing adoption of these systems. This helps enterprises plan removal of the asset before it fails, thereby ensuring production is not affected due to action taken beforehand.
The explosion of big data due to digitisation of processes across industry verticals is also favoring the adoption of predictive maintenance solutions for real-time monitoring of complex equipment.
Organizations that are trying to embrace predictive maintenance solutions face difficulties in terms of lack of training provided to operators and dearth of experts to provide guidance for best-suited predictive maintenance solutions. Furthermore, in predictive maintenance, technical personnel involved need to be well-versed to interpret data generated by predictive maintenance technologies. These factors are limiting the market's growth to some extent.
Nonetheless, the predictive maintenance market is expected to be benefitted from increasing demand from small and medium-sized enterprises and rising demand for real-time streaming analytics.
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Predictive Maintenance Market: Market Potential
Predictive maintenance solutions are spreading wings to rock excavation activities from their traditional use in the manufacturing sector. In a recent industry development, Sandvik Mining and Rock Technology and IBM have joined hands to develop technology for predictive maintenance services for rock excavation and data driven productivity. The terms of the agreement involve Sandvik and IBM to work together on advanced analytics solutions to for improving productivity, safety, operational services, and maintenance of rock excavation equipment.
The IBM-Sandvik alliance will employ the use of advanced analytics, cognitive technologies, and remote monitoring. The combination of services will assist in rock excavation by facilitating well-informed decisions regarding production cycles and maintenance schedules.
Predictive Maintenance Market: Regional Outlook
North America is expected to hold the leading market share and dominate the predictive maintenance market in the near future. However, Asia Pacific is expected to emerge as a significant market for predictive maintenance and display the fastest growth rate in the near future. Developing countries in Asia Pacific and the Middle East and Africa are investing heftily on predictive maintenance solutions to enhance their operational efficiency by minimizing machine downtime and operational costs.
Predictive Maintenance Market: Competitive Landscape
Key players in the predictive maintenance market include Software AG, IBM, Robert Bosch, PTC, RapidMiner, SAP SE, General Electric, Rockwell Automation, Warwick Analytics, and SKF.
These vendors are engaged in various types of organic and inorganic growth initiatives such as partnerships and collaborations, mergers and acquisitions, and new product launches to strengthen their position in the predictive maintenance market.
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