Predictive Maintenance Market Grow with New Opportunities & Developments by 2026

Press Release

KD Market Insights, a market research and consultancy firm, has announced the release of its Global Predictive Maintenance Market research reportThe report offers an exhaustive analysis of the market trends, opportunities, growth areas and industry drivers which would help the stakeholders to devise and align their market strategies according to the current and future market dynamics.

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.

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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. 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,, Inc., Uptake Technologies Inc., Fiix Inc., Operational Excellence (Opex) Group Ltd, TIBCO Software Inc., Asystom, and Sigma Industrial Precision.

– 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.

By Component
– Solution
– Service

By Deployment
– Cloud
– On-premise

By Technique
– Vibration Monitoring
– Electrical Testing
– Oil Analysis
– Ultrasonic Leak Detectors
– Shock Pulse
– Infrared
– Others

By Stakeholder
– Technology Integrators

By Industry Vertical
– Manufacturing
– Energy & utilities
– Aerospace & Defense
– Transportation & Logistics
– Government
– Healthcare
– Others

North America
– U.S.
– Canada
– Germany
– France
– UK
– Italy
– Rest of Europe
– Japan
– China
– India
– South Korea
– Rest of Asia-Pacific
– Latin America
– Middle East
– Africa

– IBM Corporation
– Microsoft Corporation
– General Electric
– Schneider Electric
– Hitachi, Ltd.
– PTC Inc.
– Software AG
– SAS Institute Inc.
– Engineering Consultants Group, Inc.
– Expert Microsystems, Inc.
– SparkCognition
–, Inc.
– Uptake Technologies Inc.
– Fiix Inc.
– Operational Excellence (Opex) Group Ltd
– TIBCO Software Inc.
– Asystom
– Sigma Industrial Precision.

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Table of Contents:

Chapter 1: Introduction
1.1. Report Description
1.2. Key Market Segments
1.3. Research Methodology
1.3.1. Primary Research
1.3.2. Secondary Research
1.3.3. Analyst Tools & Models

Chapter 2: Executive Summary
2.1. Cxo Perspective

Chapter 3: Market Landscape
3.1. Market Definition And Scope
3.2. Key Findings
3.2.1. Top Investment Pockets
3.2.2. Top Impacting Factors
3.2.3. Top Winning Strategies
3.3. Porter’S Five Forces Analysis
3.3.1. Bargaining Power of Suppliers
3.3.2. Threat of New Entrants
3.3.3. Threat of Substitutes
3.3.4. Competitive Rivalry
3.3.5. Bargaining Power Among Buyers
3.4. Key Player Positioning
3.5. Market Dynamics
3.5.1. Drivers The Need To Improve Uptime of Equipment And Maintenance Cost Reduction Increase In Investment On Predictive Maintenance
3.5.2. Restraints Lack of Skilled Staff Difficult To Implement Data Privacy And Security Concerns
3.5.3. Opportunity Integration of Predictive Maintenance With Iiot And Use of Machine Learning Real-Time Condition Monitoring To Assist In Taking Prompt Actions
3.6. Value Chain Analysis
3.7. Robotics Adoption In Manufacturing
3.8. Ai Implementation Analysis Across Industry Verticals
3.9. Qualitative Insights (Detection And Diagnosis)
3.9.1. Case Studies
3.9.2. Mueller Industries
3.9.3. Deutsche Bahn Ag
3.9.4. Vaalco Energy, Inc.
3.9.5. Israel Electric Corporation (Iec)
3.10. Models And Approaches
3.10.1. Statistical Pattern Classification: Bayesian Network Neural Networks Linear Classification Hybrid Models
3.10.2. Pattern Classification: Phases And Components Training Phase Testing Phase
3.10.3. Sub Problems Pattern Classification Feature Extraction Over Fitting Model Selection Prior Knowledge Missing Features Mereology Segmentation Context Invariance’S Evidence Pooling Costs And Risks Computational Complexity

Chapter 4: Predictive Maintenance Market, By Component
4.1. Overview
4.2. Solution
4.2.1. Key Market Trends, Growth Factors And Opportunities
4.2.2. Market Size And Forecast, By Region
4.2.3. Market Analysis By Country
4.3. Service
4.3.1. Key Market Trends, Growth Factors, And Opportunities
4.3.2. Market Size And Forecast, By Region
4.3.3. Market Analysis By Country
4.3.4. Professional Service Market Size And Forecast Support And Maintenance Deployment And Integration Training And Education
4.3.5. Managed Service

Chapter 5: Predictive Maintenance Market, By Technique
5.1. Overview
5.2. Vibration Monitoring
5.2.1. Key Market Trends, Growth Factors And Opportunities
5.2.2. Market Size And Forecast, By Region
5.2.3. Market Analysis By Country
5.3. Electrical Testing
5.3.1. Key Market Trends, Growth Factors, And Opportunities
5.3.2. Market Size And Forecast, By Region
5.3.3. Market Analysis By Country
5.4. Oil Analysis
5.4.1. Key Market Trends, Growth Factors, And Opportunities
5.4.2. Market Size And Forecast, By Region
5.4.3. Market Analysis By Country
5.5. Ultrasonic Leak Detectors
5.5.1. Key Market Trends, Growth Factors, And Opportunities
5.5.2. Market Size And Forecast, By Region
5.5.3. Market Analysis By Country
5.6. Shock Pulse
5.6.1. Key Market Trends, Growth Factors, And Opportunities
5.6.2. Market Size And Forecast, By Region
5.6.3. Market Analysis By Country
5.7. Infrared
5.7.1. Key Market Trends, Growth Factors And Opportunities
5.7.2. Market Size And Forecast, By Region
5.7.3. Market Analysis By Country
5.8. Others
5.8.1. Key Market Trends, Growth Factors And Opportunities
5.8.2. Market Size And Forecast, By Region
5.8.3. Market Analysis By Country

Chapter 6: Predictive Maintenance Market, By Deployment Type
6.1. Overview
6.2. Cloud
6.2.1. Key Market Trends, Growth Factors And Opportunities
6.2.2. Market Size And Forecast, By Region
6.2.3. Market Analysis By Country
6.3. On-Premise
6.3.1. Key Market Trends, Growth Factors And Opportunities
6.3.2. Market Size And Forecast, By Region
6.3.3. Market Analysis By Country

Chapter 7: Predictive Maintenance Market, By Stakeholder
7.1. Overview
7.2. Mro
7.2.1. Key Market Trends, Growth Factors And Opportunities
7.2.2. Market Size And Forecast, By Region
7.2.3. Market Analysis By Country
7.3. Oem/Odm
7.3.1. Key Market Trends, Growth Factors And Opportunities
7.3.2. Market Size And Forecast, By Region
7.3.3. Market Analysis By Country
7.4. Technology Integrators
7.4.1. Key Market Trends, Growth Factors And Opportunities
7.4.2. Market Size And Forecast, By Region
7.4.3. Market Analysis By Country
7.4.4. Pure Play
7.4.5. End-To-End

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