; Predictive Maintenance Market Trends, Share, Forecast, 2030

Predictive Maintenance Market

Predictive Maintenance Market Segments: By Component (Software and Service); By Deployment Type (Cloud and On-premise); By Organization Size (Large Enterprises and Small & Medium-sized Enterprises (SMEs); By Application (Manufacturing, Energy and Utility, Healthcare, Government) and Region - Global Analysis of Market Size, Share & Trends for 2019 - 2030 and Forecasts to 2030

Published on: Jan-2021
Report Code: FG HC 00436
No. of Pages: 170-350
Report Format: PDF

[ 170 + Pages Research Report ] Predictive Maintenance Market to surpass USD 55.34 billion by 2030 from USD 4.42 billion in 2020 at a CAGR of 28.74% in the coming years, i.e., 2020-30.

Product Overview

Predictive Maintenance (PdM) solutions are installed to detect and monitor anomalies or failures in equipment, it is a maintenance strategy determined by the application of predictive analytics technology. Predictive maintenance enhances quality and supply chain processes, maximizes device uptime, deploys limited resources, and advances the overall satisfaction of all the stakeholders involved. Machine learning and artificial intelligence in predictive maintenance aid the organizations in the collection of data of the components of the machine which helps them to understand and analyze the extent of workability of the machine and take preventive measures and schedule maintenance procedures in advance. There is a high demand for predictive maintenance in manufacturing industries such as oil and gas, where various machines work together. Predictive maintenance helps to optimize the production process by significantly reducing the costs and time required for machine maintenance. It also helps to analyze the efficiency of the entire engine by analyzing the efficiency of each part.

Market Highlights

The global Predictive Maintenance Market is expected to project a notable CAGR of 28.74% in 2030.

Global Predictive Maintenance Market to surpass USD 55.34 billion by 2030 from USD 4.42 billion in 2020 at a CAGR of 28.74% in the coming years, i.e., 2020-30 owing to the benefits provided by predictive maintenance such as a decrease in the cost of maintenance, the decline in machine failures, enhanced operator safety a reduction in downtime for repairs, reduction of spare parts stock, a surge in production, and confirmation of upkeeps. The growth of technologies such as data analytics and the internet of things has also contributed to the growth of the global predictive maintenance market as with the help of these technologies predictive maintenance has inclined towards complete automation leading to increased accuracy and efficiency.

Global Predictive Maintenance Market: Segments

Energy and utility segment to grow with the highest CAGR during 2020-30

The global Predictive Maintenance Market is segmented by application into Manufacturing, Energy and Utility, Healthcare, and Government. The energy and utility segment held the largest market share of XX.X% in the year 2019 owing to the mounting demand for power-usage analytics applications. The standalone solutions can identify asset monitoring problems in advance which notifies the organizations to perform repairs that minimize disruption in energy production. Also, the global predictive maintenance market is anticipated to rise as the government is investing in the expansion and production of the distribution networks of energy resources like oil & gas, and electricity.

A cloud-based segment to grow with the highest CAGR during 2020-30

Global Predictive Maintenance Market is divided by deployment into Cloud-based and On-premise. The cloud-based segment held the largest market share of XX.X% in the year 2019 and will continue to dominate the market in the coming years because of various factors such as cost-effectiveness, easy maintenance of data, effective management, and scalability. Most vendors offer cloud-based maintenance solutions to earn maximum profits and for the efficient automation of the equipment maintenance process.

Market Dynamics

Drivers

Developments in technology

Companies are leveraging AI and ML technologies to achieve accuracy and speed over traditional business intelligence tools to analyze data. With the use of predictive maintenance, companies can make operational predictions 20 times faster and more accurately than threshold-based monitoring systems. The rising adoption of real-time streaming analytics technology is driving the growth of the predictive maintenance market. It involves analytic computing of real-time data streamed from applications, sensors, devices, and others. Provides timely information and language integration for specialized applications. It is one of the pillars of predictive maintenance as it provides real-time data to automated monitoring systems for maintaining asset health or personnel to perform maintenance operations when required.

Reduction in maintenance costs and downtime

With rising awareness about the increasing maintenance costs and downtime caused by unexpected machine failures, predictive maintenance solutions are gaining even more traction. Predictive maintenance-based solutions help businesses identify patterns in constant streams of data to predict equipment failure.

Restraint

Lack of skilled workforce

Trained workers are required to operate the latest software systems to deploy AI-based IoT technologies and skillsets. As a result, existing workers are needed to be trained to operate new and modernized systems. Moreover, industries are dynamic towards the adoption of new technologies; however, there is a shortage of skilled workers. As most global vendors organize predictive maintenance projects, the demand for a highly skilled workforce is expanding. Companies need to gain expertise in areas such as cybersecurity, networking, and applications.

Global Predictive Maintenance Market: Key Players
  • IBM Corporation

Company Overview, Business Strategy, Key Product Offerings, Financial Performance, Key Performance Indicators, Risk Analysis, Recent Development, Regional Presence, SWOT Analysis

  • Microsoft Corporation
  • Schneider Electric SE
  • Hitachi, Ltd
  • TIBCO Software, Inc.
  • Uptake Technologies, Inc
  • Sigma Industrial Precision
  • Google
  • PTC, Inc.
  • SAP SE
  • Other Prominent Players

Global Predictive Maintenance Market: Regions

The global Predictive Maintenance Market is segmented based on regional analysis into five major regions. These include North America, Latin America, Europe, Asia Pacific, the Middle East, and Africa. Global Predictive Maintenance Market in North America held the largest market share of XX.X% in the year 2019 owing to the presence of well-established end-user industries as well as high awareness among organizations to adopt the latest technologies that help them to improve efficiency and lower operational costs. Asia Pacific is projected to grow with the highest CAGR due to rapid digitalization, urbanization, and growth of the end-use industries like Energy & Utility, Healthcare Services, and Manufacturing.

Global Predictive Maintenance Market is further segmented by region into:

  • North America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – the United States and Canada

  • Latin America Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – Mexico, Argentina, Brazil, and Rest of Latin America

  • Europe Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – United Kingdom, France, Germany, Italy, Spain, Belgium, Hungary, Luxembourg, Netherlands, Poland, NORDIC, Russia, Turkey, and Rest of Europe
  • Asia Pacific Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – India, China, South Korea, Japan, Malaysia, Indonesia, New Zealand, Australia, and Rest of APAC
  • the Middle East and Africa Market Size, Share, Trends, Opportunities, Y-o-Y Growth, CAGR – North Africa, Israel, GCC, South Africa, and Rest of MENA

The global Predictive Maintenance Market report also contains an analysis on:

Predictive Maintenance Market Segments:

  • By Component
    • Software
    • Service
  • By Deployment Type
    • Cloud
    • On-premise
  • By Organization Size
    • Large Enterprises
    • Small & Medium-sized Enterprises (SMEs)
  • By Application
    • Manufacturing
    • Energy and Utility
    • Healthcare
    • Government 
  • Predictive Maintenance Market Dynamics
  • Predictive Maintenance Market Size
  • Supply & Demand
  • Current Trends/Issues/Challenges
  • Competition & Companies Involved in the Market
  • Value Chain of the Market
  • Market Drivers and Restraints

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