FACTS AT A GLANCE
Editing: 8; Posted: November 2021
Executive pool: 6184
Companies: 115 – Players covered include eMaint Enterprises, LLC; General electricity company; IBM Corporation; PTC, Inc .; Robert Bosch GmbH; Rockwell Automation, Inc .; SAS Institute, Inc .; Schneider Electric SA; Software AG and others.
Blanket: All major geographies and key segments
Segments: Component (software, services); Deployment (on-site, in the cloud); Technology (Machine Learning, Deep Learning, Big Data & Analytics)
Geographies: World; United States; Canada; Japan; China; Europe (France; Germany; Italy; UK; and rest of Europe); Asia Pacific; Rest of the world.
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Global Predictive Maintenance Market For Manufacturing Industry To Reach 3.9 billion US dollars by 2026
Predictive maintenance is proactive and is designed to increase machine reliability and reduce downtime. As competition in the manufacturing industry intensifies and the challenges for successful survival increase in magnitude, companies are focusing on improving their financial performance by closely scrutinizing the manufacturing reliability of their operations. Effective management of asset performance is in this regard an absolute necessity. Legislation on strict occupational safety regulations also strengthens the focus on asset management. Occupational safety standards create the need for routine inspection of the condition of manufacturing facilities and assets. As a subset of asset management, predictive maintenance (PdM) is expected to benefit from increasing investments by manufacturers in asset management systems and the enterprise-wide implementation of management regimes. actives. Maintenance is undergoing a notable facelift due to the ongoing digital transformation, with the use of advanced data capture and analysis tools leading to the emergence of predictive maintenance. End-to-end integration of PdM with the entire industrial plant lifecycle is a key trend in vogue to enable the creation of more efficient workflows, achieve higher productivity and ensure better correlation. data between various sources.
In the midst of the COVID-19 crisis, the global predictive maintenance market for the manufacturing industry is estimated to be US $ 1.2 billion in 2020, is expected to reach a revised size of 3.9 billion US dollars by 2026, with a CAGR of 21.4% over the analysis period. Software, one of the segments analyzed in the report, is expected to grow at a CAGR of 19.6% to reach US $ 2.5 billion at the end of the analysis period. After a thorough analysis of the business implications of the pandemic and the induced economic crisis, the growth of the Services segment is readjusted to a revised CAGR of 23.6% for the next 7-year period. This segment currently represents a 41.8% share of the global predictive maintenance market for the manufacturing industry. Predictive maintenance software accesses big plant data to gain additional information about the plant’s operating environment and other external factors that influence machine operation. Maintenance and repair services are essential to the proper functioning of business assets while being essential to the continuity and efficiency of business operations. The growing deployment of sensing systems and advanced digital technologies such as IoT, AI and Big Data will boost the dynamics of predictive maintenance.
The US market is estimated at $ 409.6 million in 2021, when China is expected to reach $ 634.8 million by 2026
The predictive maintenance market for the manufacturing industry in the United States is estimated at US $ 409.6 million in 2021. The country currently represents 29.2% of the world market. China, the world’s second-largest economy, is expected to reach an estimated market size of US $ 634.8 million during the year 2026, with a CAGR of 26.4% during the analysis period. Other notable geographic markets include Japan and Canada, each projects growth of 17.9% and 17.5% respectively during the analysis period. In Europe, Germany is expected to grow by around 18.2% CAGR while the rest of the European market (as defined in the study) will reach US $ 417.6 million at the end of the analysis period. Following
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