Global Predictive Maintenance for Manufacturing Industry Industry

Global Predictive Maintenance for Manufacturing Industry Industry

  • February 2022 •
  • 482 pages •
  • Report ID: 5896244 •
  • Format: PDF
Abstract:

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Global Predictive Maintenance for Manufacturing Industry Market to Reach US$3.9 Billion by the Year 2026

Predictive maintenance is proactive and is designed to increase reliability of machine and decrease their 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 scrutinizing closely the manufacturing reliability of their operations. Effective asset performance management is this regard represents an absolute necessity. Also strengthening the emphasis on asset management is the legislation of stringent workplace safety regulations. Occupational safety norms create the need for routine inspection of the condition of plant and manufacturing assets. As a subset of asset management, predictive maintenance (PdM) is forecast to benefit from the growing manufacturer investments in asset management systems and corporate wide implementation of asset management regimes. Maintenance is getting a notable makeover due to ongoing digital transformation, with the use of advanced data capturing and analytics tools leading to emergence of predictive maintenance. End-to-end integration of PdM with the entire lifecycle of the industrial plant is a key trend in vogue to enable the creation of more efficient workflows, elicit higher productivity and ensure better correlation of data among various sources.

Amid the COVID-19 crisis, the global market for Predictive Maintenance for Manufacturing Industry estimated at US$1.2 Billion in the year 2020, is projected to reach a revised size of US$3.9 Billion by 2026, growing at a CAGR of 21.4% over the analysis period. Software, one of the segments analyzed in the report, is projected to grow at a 19.6% CAGR to reach US$2.5 Billion by the end of the analysis period. After a thorough analysis of the business implications of the pandemic and its induced economic crisis, growth in the Services segment is readjusted to a revised 23.6% CAGR for the next 7-year period. This segment currently accounts for a 41.8% share of the global Predictive Maintenance for Manufacturing Industry market. Predictive maintenance software accesses the plant`s big data to gain additional insights about the operating environment in the plant and other extraneous factors that influence machine operation. Maintenance and repair services are vital for the proper functioning of enterprise assets while being key to the continuity and effectiveness of business operations. The proliferating deployment of sensing systems and advanced digital technologies such as IoT, AI and Big Data will spur the momentum for predictive maintenance.

The U.S. Market is Estimated at $409.6 Million in 2021, While China is Forecast to Reach $634.8 Million by 2026

The Predictive Maintenance for Manufacturing Industry market in the U.S. is estimated at US$409.6 Million in the year 2021. The country currently accounts for a 29.2% share in the global market. China, the world`s second largest economy, is forecast to reach an estimated market size of US$634.8 Million in the year 2026 trailing a CAGR of 26.4% through the analysis period. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 17.9% and 17.5% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 18.2% CAGR while Rest of European market (as defined in the study) will reach US$417.6 Million by the end of the analysis period.

Select Competitors (Total 115 Featured) -
  • Accenture Plc
  • Cisco Systems, Inc.
  • eMaint Enterprises
  • General Electric Company
  • Hitachi, Ltd.
  • Honeywell International Inc.
  • International Business Machines Corporation
  • Microsoft Corporation
  • Mitsubishi Electric Corporation
  • Oracle Corporation
  • PTC, Inc
  • Robert Bosch GmbH
  • Rockwell Automation, Inc.
  • SAP SE
  • SAS Institute Inc.
  • Schneider Electric SE
  • Siemens AG
  • Software AG