Press release
Operational Predictive Maintenance Market to Generate Heightened Revenue Prospects for Manufacturers in the Next Decade
Persistence Market Research (PMR) recently published a report titled “Predictive Maintenance Market for Manufacturing Industry – Global Industry Analysis 2013-2017 and Market Forecast 2018-2026.” The predictive maintenance market for manufacturing industry has witnessed an upsurge in the past four years with the introduction of advanced technologies such as Big Data & analytics, machine learning, deep learning, and artificial intelligence. As a result of the increasing adoption of these advanced technologies, a transition from the on-premise deployment models to the cloud is witnessed in the global predictive maintenance market for manufacturing industry.The global predictive maintenance market for manufacturing industry is expected to witness a double-digit growth rate during the forecast period. The predictive maintenance market for manufacturing industry was valued at US$ 741.1 Mn in 2017, and is projected to grow significantly to reach US$ 4,746.6 Mn by 2026, which can be attributed to the high demand for efficient output & management in the manufacturing industry and for minimizing the costs associated with the maintenance of the assets/products/machines.
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In this report, PMR has segmented the global predictive maintenance market for manufacturing industry on the basis of component type, deployment model, technology, and region. By component type, predictive maintenance market for manufacturing industry is subsegmented into software and services. Services subsegment of the global predictive maintenance market for manufacturing industry is further segmented into consulting, training, implementation & integration, and support. According to the PMR analysis of the global predictive maintenance market for manufacturing industry, as the adoption of software increases, a corresponding increase in the demand for services is expected to be witnessed, especially during the latter half of the forecast period. During the initial phase of the global predictive maintenance market for manufacturing industry, the consulting and implementation & integration segments are expected to witness higher demand. However, as time progresses, higher demand for the support and maintenance segment is expected in the global predictive maintenance market for manufacturing industry.
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Based on deployment model, the predictive maintenance market for manufacturing industry is subsegmented into on-premise and cloud. In 2017, the on-premise segment is expected to dominate the predictive maintenance market for manufacturing industry. However, the cloud segment is expected to exhibit a higher double digit-growth rate during the forecast period in the global predictive maintenance market for manufacturing industry owing to the increasing demand for adopting cloud technology across all the regions. The deployment of predictive maintenance market for manufacturing industry simplifies the integration of advanced technologies with the software and, furthermore, assists in the global advent of Industry 4.0. Increasing awareness about the advantages associated with the deployment of predictive maintenance over cloud is another factor expected to fuel the growth of the segment in the global predictive maintenance market for manufacturing industry, in terms of value, during the forecast period.
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Demand for Reduced Downtime & Low Maintenance Costs from Manufacturers Boosting Revenue Growth in the Predictive Maintenance Market for Manufacturing Industry
Moreover, the predictive maintenance market for manufacturing industry report also includes a qualitative analysis of the integration of machine learning, deep learning, and Big Data & analytics with predictive maintenance and an assessment of the opportunities in the future with an increase in the adoption of these solutions. At the global level, the maximum adoption of the aforementioned integrated solution is witnessed among the North American and European manufacturing companies.
Furthermore, on the basis of geography, North America predictive maintenance market for manufacturing industry is expected to dominate the global predictive maintenance market for manufacturing industry due to the large presence of solution providers, availability of resources for offering advanced solutions, and maximum penetration of Industry 4.0 in the region. Moreover, the predictive maintenance market for manufacturing industry has high potential in SEA & Others of APAC and China owing to the presence of numerous manufacturing companies in these regions and an increase in the adoption of advanced technologies to increase the efficiency associated with the same.
According to PMR analysis, initiatives undertaken by governments to enhance the efficiency of manufacturing plants/machines, transition from on-premise to cloud, increasing awareness among end-users, and high growth opportunities in developing countries are likely to boost the global predictive maintenance market for manufacturing industry. Some of the market participants in the global predictive maintenance market for manufacturing industry report include
• IBM Corporation
• Software AG
• SAS Institute Inc.
• PTC, Inc
• General Electric
• Robert Bosch GmbH
• Rockwell Automation
• Schneider Electric
• eMaint Enterprises LLC
• Others
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About us: Persistence Market Research (PMR) is a third-platform research firm. Our research model is a unique collaboration of data analytics and market research methodology to help businesses achieve optimal performance.To support companies in overcoming complex business challenges, we follow a multi-disciplinary approach. At PMR, we unite various data streams from multi-dimensional sources. By deploying real-time data collection, big data, and customer experience analytics, we deliver business intelligence for organizations of all sizes.Our client success stories feature a range of clients from Fortune 500 companies to fast-growing startups. PMR’s collaborative environment is committed to building industry-specific solutions by transforming data from multiple streams into a strategic asset.
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