Predictive maintenance (PdM) is a process for monitoring equipment during operation with the purpose of identifying any deterioration, allowing maintenance to be planned, and reducing the operational costs. In this, data about previous breakdowns is used to model when failures are likely to occur and arbitrate at the same time as sensors detect the same conditions. PdM techniques are used to identify the time the in-service equipment requires maintenance to avoid expensive operational disruptions caused due to equipment failures.
Increase in adoption of industry 4.0, booming manufacturing industry are driving the demand for predictive maintenance solutions.
Factors such as increase in need to improve the uptime of asset and reduce cost, growing investment on predictive maintenance due to adoption of IoT drives the growth of the global predictive maintenance market. Further, increase in need to gain insights from the adoption of new technologies boosts the growth of the predictive maintenance market.
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However, difficulty in implementation and data security concerns hamper the market growth. Furthermore, adoption of advanced technologies such machine learning and integration of predictive maintenance with IIoT is anticipated to fuel the growth of the predictive maintenance market.
The global predictive maintenance market is segmented into component, deployment model, technique, stakeholder, industry vertical, and region. Based on component, it is bifurcated into solution and service. According to deployment, the market is classified into cloud and on-premise segments. Further, based on technique the market is divided into vibration monitoring, electrical testing, oil analysis, ultrasonic leak detectors, shock pulse, infrared, and others. Based on stakeholder, the market is segmented into MRO, OEM/ODM, and technology integrators.
Based on industry vertical, it is classified into manufacturing, energy & utilities, aerospace & defense, transportation & logistics, government, and others. Based on region, it is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
The report analyzes the profiles of key players operating in the market. These include IBM Corporation, Microsoft Corporation, SAP SE, General Electric, Schneider Electric, Hitachi, Ltd., PTC Inc., Software AG, SAS Institute Inc., Engineering Consultants Group, Inc., Expert Microsystems, Inc., SparkCognition, C3.ai, Inc., Uptake Technologies Inc., Fiix Inc., Operational Excellence (Opex) Group Ltd, TIBCO Software Inc., Asystom, and Sigma Industrial Precision.
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KEY BENEFITS FOR STAKEHOLDERS
• The study provides an in-depth analysis of the global predictive maintenance market along with the current & future trends to elucidate the imminent investment pockets.
• Information about key drivers, restrains, and opportunities and their impact analyses on the market size is provided in the report.
• Porter’s five forces analysis illustrates the potency of buyers and suppliers operating in the industry.
• The quantitative analysis of the global predictive maintenance market from 2018 to 2026 is provided to determine the market potential.
KEY MARKET SEGMENTS
• Vibration Monitoring
• Electrical Testing
• Oil Analysis
• Ultrasonic Leak Detectors
• Shock Pulse
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• Technology Integrators
By Industry Vertical
• Energy & utilities
• Aerospace & Defense
• Transportation & Logistics
• North America
o Rest of Europe
o South Korea
o Rest of Asia-Pacific
o Latin America
o Middle East
KEY MARKET PLAYERS
• IBM Corporation
• Microsoft Corporation
• SAP SE
• General Electric
• Schneider Electric
• Hitachi, Ltd.
• PTC Inc.
• Software AG
• SAS Institute Inc.
• Engineering Consultants Group, Inc.
• Expert Microsystems, Inc.
• C3.ai, Inc.
• Uptake Technologies Inc.
• Fiix Inc.
• Operational Excellence (Opex) Group Ltd
• TIBCO Software Inc.
• Sigma Industrial Precision
This post was originally published on Downey Magazine