Predictive Maintenance Market Size, Share & Industry Analysis, By Component (Solution, Services), By Techniques (Power System Assessments, Infrared thermography, Temperature Monitoring, Fluid Analysis, Circuit Monitor Analysis, Vibration Monitoring, and Others), By Deployment (On-Premises and Cloud), By Organization Size (Small and Middle Enterprises (SMEs) and Large Enterprises), By End-User (Manufacturing, Government, Energy and Utilities, Transportation, Healthcare, Aerospace and Defence, and Others) and Regional Forecast, 2019-2026

The global predictive maintenance market size was valued at USD 2,387.6 million in 2018 and is projected to reach USD 18,551.0 million by 2026, exhibiting a CAGR of 29.8% during the forecast period. North America market size was worth USD 774.3 Million in 2018. Predictive maintenance is the technique that is used to track the performance of crucial machine components in real-time to minimize downtime needed for repairs. 

It helps enterprise owners determine the working conditions of the equipment and machines that assist in maximizing uptime and increasing efficiency. Predictive maintenance tools prevents costly operational interruptions and equipment failures by providing maintenance arrival alerts.

Predictive maintenance has always been very essential in factories to improve productivity.  The adoption of predictive maintenance solutions is increasing rapidly among both large enterprises and SMEs, owing to various benefits including reduced downtime, extended equipment life, improved plant safety, optimized maintenance schedules, reduced maintenance costs, and improved yield rate.

The predictive maintenance system deals with routine and scheduled check-ups of equipment by collecting and analyzing real-time data on the conditions of the in-service equipment. The growing organizational focus on improving operational efficiency to gain more profit is propelling the growth of predictive maintenance market. Furthermore, the rapid industrialization across the globe is expected to fuel the market growth during forecast period.  

MARKET DRIVERS

“Adoption of Technologies such Internet of Things (IoT), Cloud Computing, Artificial Intelligence (AI) and Machine Learning in Predictive Maintenance Solutions to Drive Market Growth.”

Predictive maintenance utilizes technologies such as the internet of things (IoT), cloud computing, artificial intelligence (AI), and machine learning to increase the operational efficiency of the machines. The integration of AI in predictive maintenance tools helps in collecting massive amounts of data and translate that data into meaningful insights and data points, which further helps avoid data overloading. 

Additionally, the implementation of the data sensor and machine learning models in predictive maintenance solutions provides quick and easy extraction of more valuable information from large volumes of unstructured data. The predictive maintenance solution providers are upgrading the organization’s existing maintenance systems by incorporating advanced technologies to ensure peak performance of in-service equipment.

“Rising Demand for the Maintenance Solutions to Reduce Cost and Downtime across Various Industries to Boost the Growth of the Market.”

The demand for predictive maintenance solutions is increasing rapidly across various industrial verticals, including manufacturing, energy and utilities, transportation, healthcare, and aerospace and defense. In the energy and utility industries, the equipment manufacturers, operators, and plant owners usually face challenges regarding the efficient working of their machinery and other assets. The predictive maintenance solutions help the plant owners to schedule a maintenance program before any probability of failures. 

Similarly, in the manufacturing industry, it is very crucial to identify the causes of failures and potential faults before their occurrence. Thus, the companies are deploying predictive maintenance solutions and services more effectively to improve equipment uptime by proactively detecting potential issues in real-time without disturbing the ongoing process.

SEGMENTATION

By Component Analysis

“Solution Segment is Expected to Augment the Predictive Maintenance Market During the Forecast Period”

Based on the component, the market is classified into solution and services segment. Among these, the solution segment held the largest market share in 2018 and is expected to continue during the forecast period owing to the rising demand for IoT-based predictive maintenance solutions and the growing awareness among industries to implement cost-effective solutions.

The solution segment is further bifurcated into integrated and standalone solutions. Among these, the integrated solutions segment is anticipated to dominate the market over the forecast period owing to the uprising need for customized solutions and rising demand for application-specific solutions across various industry verticals.

Similarly, the services segment is further segmented into deployment and installation, support and maintenance, and consulting. Among these, the deployment and installation services segment is anticipated to dominate the market in the forthcoming years, owing to the growing demand for predictive maintenance services across various industry verticals such as automotive and transportation, energy and utilities, and aerospace and defense.

By Techniques Analysis

“Vibration Monitoring Segment Accounted for the Largest Market Share”

By techniques, the predictive maintenance market has been diversified into the power system assessments, infrared thermography, temperature monitoring, fluid analysis, circuit monitor analysis, vibration monitoring, and other segments. The vibration monitoring segment held the largest share in the global predictive maintenance market, owing to its ability to detect and diagnose problems and provide details regarding the life span and possible failure mode of the machine.

The fluid analysis segment exhibited the highest CAGR during the forecast period owing to its ability to monitor liquid contamination and reduce uncertainty, risk, and reactive work for a maintenance department.

By Deployment Analysis

“On-Premise Segment to Augment the Market During the Forecast Period”

Based on the deployment, the market is classified into the cloud and on-premise. Among these, on-premise deployment held the largest market share in 2018 and is expected to continue during the forecast period, owing to the rising data privacy concerns associated with cloud infrastructure. Therefore, most of the organizations prefer to have their servers and data centers for running their internal and external software solutions effectively, thereby increasing the demand for on-premises solutions.

The cloud-based solutions segment is expected to exhibit the fastest CAGR over the forecast period, owing to the rising awareness regarding the benefits associated with the cloud solutions including faster data processing, direct IT control, efficient resource utilization, and cost-effectiveness. Moreover, prominent vendors operating in the global market are offering cloud-based solutions for effective automation of the equipment maintenance as well as to gain maximum associated profits.

By Organization Size Analysis

“Large Enterprises Segment Accounted for the Largest Market Share”

By organization size, the predictive maintenance market has been diversified into small and middle enterprises (SMEs) and large enterprises. Small and medium enterprises (SMEs) segment is projected to register the fastest CAGR during the forecasted period, owing to the growing investments for new establishments and a rising number of small and medium-sized enterprises across the globe.

Large enterprises segment holds a significant share in the global predictive maintenance market, owing to the growing inclination of enterprises towards optimizing and automating their operational maintenance process by using predictive maintenance solutions. Additionally, in large enterprises, the cost associated with downtime and assets is very high. Thus, demand for predictive maintenance solutions is increasing rapidly in large enterprises across the globe.

By End-User Analysis

“Manufacturing Segment Accounted for the Largest Market Share”

Based on end-user, the predictive maintenance market has been segmented into manufacturing, government, energy and utilities, transportation, healthcare, aerospace and defence, and other segments. The manufacturing segment held the largest share in the global predictive maintenance market, owing to the rising need for maintenance of manufacturing equipment such as machinery, elevators, industrial robots, and pumps for reducing the overall downtimes. Furthermore, the emergence of Industry 4.0 is expected to drive the demand for predictive maintenance in coming years.

The energy and utilities segment is projected to exhibit the fastest CAGR over the forecast period, owing to the increasing need to monitor and maintain assets, as well as to increase the efficiency and reliability levels of machines. Additionally, the growing demand to predict prior failure of aged components in the energy and utility infrastructure is supporting the segment growth.

REGIONAL ANALYSIS

The predictive maintenance market has been analyzed across five major regions, which are North America, Europe, Asia Pacific, the Middle East & Africa, and Latin America. These regions are further categorized into countries.

North America is projected to augment the market during the forecast period. In 2018, North America generated a revenue of USD 774.3 Million and is expected to reach up to USD 5,454.0 Million by 2026. North America will be the dominant region in the global predictive maintenance market during the forecast period owing to the rising adoption of predictive maintenance solutions that leverage advanced technologies including IoT, cloud computing, machine learning, and artificial intelligence (AI). 

Organizations in the region are using predictive maintenance solutions to identify operational performance factors and improve maintenance practices and reliability. The US holds the largest market share in the North America predictive maintenance market, owing to the presence of prominent players operating in the predictive maintenance market.

Europe is expected to hold a second leading position in the market and is expected to grow at a remarkable CAGR till 2026. The demand for predictive maintenance solutions is increasing in Europe, owing to the increasing organizational investments and awareness regarding the importance of predictive maintenance technology to gain competitive advantage.

Asia Pacific is positioned to be the fastest-growing region in the global predictive maintenance market in terms of CAGR, owing to massive potential in the untapped market such as India, and Singapore where various industries are growing rapidly. In the Asia Pacific region, providers of predictive maintenance solutions are developing AI and IoT-enabled predictive maintenance systems to enhance predictive maintenance services across the region. 

The Middle East and Africa are anticipated to witness a steady growth rate in the predictive maintenance market. Increasing demand for more cost-efficient predictive maintenance solutions and inclination towards reducing machine breakdowns will cultivate the growth of the predictive maintenance market across the region.

INDUSTRY KEY PLAYERS

“Key players such as IBM Corporation, Banner Engineering Corp. and Axiomtek Co., Ltd. to Strengthen their Market Position”

IBM Corporation has been actively providing predictive maintenance solutions for various industries including transportation, manufacturing, energy and utilities, and chemical, and petroleum. IBM Maximo is a fully integrated predictive maintenance platform that uses advanced analytic tools and IoT data to reduce risk and improve operational availability. IBM Maximo comprises configurable dashboards, alerts, and analytics.

Banner Engineering Corp. provides predictive maintenance solutions such as  QM30VT Series, Wireless Solutions Kit, and DXM Series. QM30VT is a series of vibration and temperature sensors used to detect changes in machine vibration and temperature for prior identification of potential problems. The company also provides wireless solutions kit designed to collect remote data, and create visualization tools, warnings, and alarms. It offers DXM Series of wireless controllers designed to facilitate ethernet connectivity and Industrial Internet of Things (IIoT) applications.

Axiomtek Co., Ltd. is actively participating in the predictive maintenance market by offering various types of predictive maintenance solutions for steel plant operations, CNC machine operations and robotic arm management. The company provides predictive maintenance technology, which offers valuable insights about in-service equipment and helps the client to make better business decisions. It also includes middleware solutions that enhance customers' ability to quickly respond to demand spikes and emergency situations by offering visual data over IoT and critical operational alerts.    

LIST OF KEY COMPANIES PROFILED: 

• IBM Corporation


• Microsoft Corporation


• SAP SE


• Schneider Electric SE


• Hitachi, Ltd.


• SAS Institute, Inc.


• Oracle Corporation


• Siemens AG


• SparkCognition


• Axiomtek Co., Ltd.


• Banner Engineering Corp.


• Sigma IT


• RFMicron, Inc. d/b/a Axzon


• Larsen & Toubro Infotech Ltd.


• Predictive Maintenance Solutions, LLC


• Fujitsu Ltd.


• Software AG


• Engineering Consultants Group, Inc.

REPORT COVERAGE

The report offers an elaborative analysis of numerous factors affecting the global predictive maintenance market. These include opportunities, growth drivers, threats, key developments, and restraints. In addition to this, it further helps in analyzing, segmenting, and defining the market based on different segments such as component, techniques, deployment, organization size, and end-user. It strategically analyzes several strategies such as product innovations, mergers, alliances, joint ventures, and acquisitions adopted by players in the industry.

Report Scope & Segmentation

INDUSTRY DEVELOPMENT:

• August 2019 – Cisco systems, Inc. acquired Cloudcherry, a predictive analytics based customer experience management company, to enhance its cognitive contact center solutions using predictive maintenance and analytics capabilities


• June 2018 – IBM Corporation acquired Oniqua Holdings Pty Ltd., one of the leading providers of maintenance, repair, and operations optimization software, to expand its asset optimization practice, while helping clients to reduce and optimize maintenance repair and operations (MRO) Inventories.