Global Predictive Maintenance Market Size Study & Forecast, by Component (Solutions, Services), By Deployment Model (Cloud, On-premise), By Organization Size (Large Enterprises, Small and Medium-sized Enterprises), By Industry Vertical (Government & Defense, Manufacturing, Energy & Utilities, Transportation & Logistics, Healthcare & Life Sciences), and Regional Analysis, 2023-2030
Global Predictive Maintenance Market is valued approximately at USD 5.45 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 30.90% over the forecast period 2023-2030. Predictive Maintenance is a proactive maintenance strategy employed by organizations to anticipate and mitigate equipment failures before they occur, thereby optimizing operational efficiency and reducing downtime. This approach relies on advanced data analytics, machine learning algorithms, and sensor technologies to monitor the condition of machinery and predict potential faults or failures based on historical performance data and real-time operational parameters. The application of Predictive Maintenance spans various industries, including manufacturing, transportation, energy, and healthcare, among others. By continuously monitoring equipment health and performance metrics, organizations can identify patterns and anomalies indicative of impending failures or degradation in asset condition. This enables timely intervention through scheduled maintenance activities, part replacement, or corrective actions, thereby preventing costly breakdowns, minimizing production disruptions, and extending the lifespan of critical assets. Moreover, the growing adoption industrial internet of things (IIoT), increasing focus on asset performance management, and rising shift from reactive to proactive maintenance are anticipated to create the lucrative demand for the market during forecast period 2023-2030.
Additionally, the proliferation of IIoT devices and connectivity solutions in industrial settings has facilitated the collection of vast amounts of real-time data from equipment and machinery. This data can be leveraged for predictive analytics and condition monitoring, enabling proactive maintenance actions, driving the growth of the Predictive Maintenance market. In 2021, the global industrial internet of things (IIoT) market was valued USD 263.52 billion and it is anticipated to reach USD 2,188.73 billion by 2028. Aa a result, the growing adoption of IIoT is anticipated to support the market growth. Moreover, the growing advancement in sensor technology, IoT devices, cloud computing, and machine learning algorithms, and growing industrialization are anticipated to create lucrative opportunity for the market growth. However, the high initial implementing costs, and inadequate availability of skilled workforce stifles market growth throughout the forecast period of 2023-2030.
The key regions considered for the Global Predictive Maintenance Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 with largest market share owing to the increasing adoption of IOT and sensor technologies, growing awareness of predictive maintenance, rise of industry 4.0 and digital transformation initiatives, and advancement in data analytics and machine learning. Whereas, the Asia Pacific region is expected to grow with the fastest growth rate during the forecast period, owing to factors such as the rapid adoption of industrial IoT and sensor technologies across various industries such as manufacturing, energy, transportation, and healthcare, government initiatives promoting industry 4.0, growing advancements in data analytics and ai technologies, and expansion of manufacturing and infrastructure sectors in the region.
Major market players included in this report are:IBM Corporation
Microsoft Corporation
SAP SE
Schneider Electric SE
Hitachi, Ltd.
SAS Institute, Inc.
Oracle Corporation
Siemens AG
Axiomtek Co., Ltd.
Banner Engineering Corp.
Recent Developments in the Market: In April 2023, TrendMiner has unveiled an upgraded version of its predictive maintenance software, named the Digital Twin Manager. This latest version boasts improved compatibility with cloud data sources from leading providers like AWS and Microsoft. Additionally, it introduces interactive search capabilities, empowering users to glean insights from data swiftly and make informed decisions with heightened efficiency.
In May 2023, Cisco Systems, Inc. and NTT, a leading provider of telecom infrastructure services, have joined forces to co-create a suite of solutions aimed at delivering real-time data insights, bolstering decision-making processes, and fortifying security measures. Leveraging predictive maintenance, supply chain management, and asset tracking capabilities, this collaboration aims to empower organizations with advanced tools for optimizing operations and safeguarding critical assets.
Global Predictive Maintenance Market Report Scope: Historical Data – 2020 - 2021
Base Year for Estimation – 2022
Forecast period - 2023-2030
Report Coverage - Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered - Component, Deployment Model, Organization Size, Industry Vertical, Region
Regional Scope - North America; Europe; Asia Pacific; Latin America; Middle East & Africa
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.
The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players.
The detailed segments and sub-segment of the market are explained below:By Component:
Solutions
Services
By Deployment Model:
Cloud
On-premise
By Organization Size:
Large Enterprises
Small and Medium-sized Enterprises
By Industry Vertical:
Government & Defense
Manufacturing
Energy & Utilities
Transportation & Logistics
Healthcare & Life Sciences
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa
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