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Predictive maintenance Companies

Predictive maintenance companies, provide solutions that leverage data and analytics to predict equipment failures and optimize maintenance schedules. Predictive maintenance is crucial for preventing unplanned downtime and reducing maintenance costs in industries such as manufacturing, energy, and transportation. Predictive maintenance companies play a vital role in maximizing asset reliability and efficiency.

Predictive Maintenance Companies


Competitive Landscape of Predictive Maintenance Market:


The global predictive maintenance market is experiencing explosive growth, fueled by the increasing adoption of Industry 4.0 technologies and the need to optimize operational efficiency and asset uptime. This rapid growth presents a lucrative opportunity for established players and new entrants alike to capitalize on this burgeoning market.


Key Players:



  • Axiomtek Co. Ltd (Taiwan)

  • Oracle Corporation (US)

  • Microsoft Corporation (US)

  • XMPro (US)

  • IBM Corporation (US)

  • RapidMiner (US)

  • Hitachi Ltd (Japan)


Key Players Dominating the Landscape:


The current landscape of the predictive maintenance market is characterized by a mix of established industry giants and dynamic young companies. Some of the key players include:



  • Industrial giants: General Electric, Siemens, Schneider Electric, ABB, Honeywell International, Bosch Rexroth, Emerson Electric, IBM, SAP, Microsoft.

  • IT giants: Amazon Web Services, Google Cloud, Microsoft Azure, Oracle Cloud.

  • Predictive maintenance specialists: Uptake Technologies, C3.ai, Predix, AspenTech, OSIsoft, Baker Hughes, GE Aviation, SKF, Emerson Automation Solutions, PTC.


Strategies for Success:


In this competitive environment, companies are adopting various strategies to gain a foothold and expand their market share. Some of the key strategies include:



  • Product Innovation: Continuous development of advanced predictive maintenance solutions incorporating cutting-edge technologies like AI, machine learning, and big data analytics.

  • Industry Focus: Specialization in specific industry verticals to cater to the unique needs of different industrial sectors.

  • Partnership and Collaboration: Strategic partnerships with technology providers, data analytics companies, and sensor manufacturers to leverage complementary capabilities and expand reach.

  • Subscription-based Model: Transitioning from traditional licensing models to subscription-based models for recurring revenue and better customer engagement.

  • Cloud-based Solutions: Offering cloud-based predictive maintenance solutions for scalability, affordability, and easier deployment.


Factors for Market Share Analysis:


To understand the competitive landscape effectively, several factors need to be considered for market share analysis:



  • Market Size: Share of the market captured by a particular company in terms of revenue or installed base.

  • Product Portfolio: Breadth and depth of the product portfolio, encompassing different industries, functionalities, and deployment models.

  • Geographical Reach: Global presence and penetration into different regional markets.

  • Technology Expertise: Depth of expertise in AI, ML, cloud computing, and other key technologies.

  • Customer Base: Number and size of customers, including prominent industry leaders.

  • Financial Performance: Revenue growth, profitability, and market capitalization.


Emerging Companies and Trends:


Several new and emerging companies are disrupting the traditional landscape by offering innovative solutions and competitive pricing models. These companies are focusing on niche areas like predictive maintenance for specific equipment types or industries. The emergence of these companies is pushing established players to innovate and adapt to remain competitive.


Current Investment Trends:


Companies are investing heavily in research and development to enhance their predictive maintenance capabilities and stay ahead of the curve. This includes investments in:



  • Advanced algorithms: Developing more sophisticated AI and ML algorithms for accurate anomaly detection and predictive maintenance.

  • Data integration: Building robust data integration platforms to collect and analyze data from various sources, including sensors, historical records, and operational data.

  • Cybersecurity: Strengthening cybersecurity measures to protect sensitive data and ensure the integrity of predictive maintenance systems.

  • User experience: Enriching the user experience through intuitive interfaces, robust data visualization, and actionable insights.


Latest Company Updates:


A new artificial intelligence (AI) predictive maintenance tool called Asset Risk Predictor was introduced by Rockwell Automation in 2023. Fiix is the company's cloud-based computer maintenance management system (CMMS) division. The most recent product to be released under the Fiix by Rockwell Automation brand is Asset Risk Predictor (ARP). With the integration of AI sensor data, machine learning, and operational settings, Fiix's second product predicts asset health, enabling customers to identify and fix problems before they arise.

Predictive Maintenance (PdM) Market Overview


Predictive Maintenance (PdM) Market Size was valued at USD 17.3 billion in 2021. The Predictive Maintenance (PdM) market industry is projected to grow from USD21.83 Billion in 2022 to USD 111.30 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 26.20% during the forecast period (2024 - 2030). Increasing demand for maintenance cost reduction and growing use of real-time streaming analytics technology are the key market drivers enhancing the market growth.

 

Figure 1: Predictive Maintenance (PdM) Market Size, 2022 - 2030 (USD Billion)

Predictive Maintenance (PdM) Market Overview

 

Predictive Maintenance (PdM) Market Trends


The rising adoption of PdM solutions in various rapidly growing sectors to boost market growth


Businesses are utilising AI and ML technology to evaluate loT data with extraordinary precision, accuracy, and speed compared to traditional business intelligence solutions. PdM proactive maintenance strategies offer solutions to minimise time and money spent on repairs and maintenance while reducing unplanned downtime of equipment that is essential for production. PdM solutions also guarantee that assets are always available and in top functioning condition.


Further, One of the best alternatives for asset-heavy firms that offers lower expenses and a higher ROI is predictive maintenance tactics. Solution providers skilled in AI and ML can gather a sizable amount of customer-related data and turn it into insightful information. due to loT's massive data production from linked devices. Real-time condition monitoring is made possible by the ongoing improvements in big data and cloud testing. A wealth of data is made available by the widespread use of loT devices with industrial equipment.


Additionally, Machine learning and artificial intelligence are now more frequently combined. A growing number of clients are embracing these AI-powered solutions to assist in the transition from a reactive to a proactive strategy. New AI-enabled solutions are being aggressively introduced by market participants.has enhanced the Predictive Maintenance (PdM) market CAGRacross the globe in the recent years.


However  the expanding utilization of predictive maintenance in the logistics and transportation industries is another factor driving the growth of the Predictive Maintenance (PdM) marketrevenue.


Predictive Maintenance (PdM) Market Segment Insights


Predictive Maintenance (PdM) Component Insights


The Predictive Maintenance (PdM) market segmentation,based on component, includes Hardware, Solution, Services. The market was dominated by the solution sector. In order to predict an anomaly in the operation of the essential equipment, the solution makes use of the data accumulated by various IoT sensors and does an in-depth data analysis. Hence, is a great contributor in Predictive Maintenance (PdM) market revenue. In some circumstances, businesses directly prefer to adopt managed services for their operations in accordance with their needs. Additionally, the increasing demand for employee training, efficient application of these solutions, and help with integration & implementation are anticipated to boost the expansion of the services sector.


On June 2022: Siemens Digital Industries announced the acquisition of Senseye, a Southampton-based provider of machine data, to broaden its range of cutting-edge predictive maintenance and asset intelligence. 


Predictive Maintenance (PdM) Testing Type Insights


The Predictive Maintenance (PdM) market segmentation,based on testing type, includes Vibration Monitoring, Electrical Insulation, Infrared Detector Thermography, Temperature Monitoring, and others. Among these, the vibration monitoring segment accounts for the largest market share. Additionally, Regular motor testing, or testing at the first hint of trouble, allows for accurate problem prediction, prevention, and resolution with the least amount of service interruption. It is possible to do this motor winding test without actually attaching the test apparatus to the motor. The test apparatus is typically linked to the motor starter's load side. A voltage pulse is applied to the other two windings while one of the three windings is grounded during the test. The segment is anticipated to have the greatest CAGR throughout the assessment period. positively impacts the market growth.


Predictive Maintenance (PdM) Deployment Mode Insights


Theglobal Predictive Maintenance (PdM) market data based on deployment includes Cloud, and On-premise. The on-premises market category represents the biggest market share of these. Additionally, the segment is anticipated to have the greatest CAGR throughout the assessment period. Its modular sensors and simpler deployments in existing equipment are credited with this. However, due to direct IT control, remote accessibility, internal data delivery & handling, faster data processing using advanced predictive analytics, efficient resource utilisation, and cost-effectiveness, cloud-based predictive maintenance solutions are expected to exhibit the highest growth rate during the forecast period.


Figure 2: Predictive Maintenance (PdM) Market, by Deployment, 2021 & 2030 (USD Billion)Predictive Maintenance (PdM) Market, by Deployment, 2021 & 2030Source: Secondary Research, Primary Research, MRFR Database and Analyst Review


Predictive Maintenance (PdM) Technique Insights


Based on Techniques, the Predictive Maintenance (PdM) industry has been segmented into Traditional Technique, Advanced Technique. The market share that belongs to traditional procedures is the largest. Additionally, the segment is anticipated to have the greatest CAGR throughout the assessment period. Traditional maintenance techniques are simple. They include planned maintenance on a regular basis and emergency maintenance. This means that equipment is taken out of the manufacturing cycle until the broken or worn-out components are fixed.


Predictive Maintenance (PdM) Vertical Insights


Based on Vertical, the Predictive Maintenance (PdM) industry has been segmented into Manufacturing, Healthcare, Energy & Utility, Automotive, Aerospace & Defense, Transportation, and Others. The manufacturing sector holds the biggest market share of these. Additionally, the segment is anticipated to have the greatest CAGR throughout the assessment period. Companies are concentrating on increasing their financial performance by thoroughly examining the manufacturing reliability of their operations as competition in the manufacturing business grows and the obstacles for successful survival become more significant. In this context, effective asset performance management is a must-have.


Predictive Maintenance (PdM) Regional Insights


By Region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. North AmericaPredictive Maintenance (PdM) market accounted for USD 7.47 billion in 2021 and is expected to exhibit a significant CAGR growth during the study period. Key developments in technology are among the main drivers of the predictive maintenance industry in this region.


Further, the major countries studiedin the market reportare: The U.S, Canada, Germany, France, UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.


Figure 3: PREDICTIVE MAINTENANCE (PDM) MARKET SHARE BY REGION 2021 (%)PREDICTIVE MAINTENANCE (PDM) MARKET SHARE BY REGION 2021Source: Secondary Research, Primary Research, MRFR Database and Analyst Review


Europe Predictive Maintenance (PdM) market accounts for the second-largest market share due to the increase in awareness towards the benefits of predictive maintenance in all sectors. Further, the Germany Predictive Maintenance (PdM) marketheld the largest market share, and the UK Predictive Maintenance (PdM) market was the fastest growing market in the European region


The Asia-Pacific Predictive Maintenance (PdM) Market is expected to grow at the fastest CAGR from 2022 to 2030. A number of businesses are currently introducing next-generation, complete cloud-based solutions. Industry expansion has been assisted by the rising use of new and developing technologies to get insightful knowledge into decision-making. Various vertical end-users are looking for downtime and cost savings more and more. Moreover, China Predictive Maintenance (PdM) market held the largest market share, and the India Predictive Maintenance (PdM) market was the fastest growing market in the Asia-Pacific region


Predictive Maintenance (PdM) Key Market Players & Competitive Insights


Major market players are spending a lot of money on R&D to increase their product lines, which will help the Predictive Maintenance (PdM) market grow even more. Market participants are also taking a range of strategic initiatives to grow their worldwide footprint, with key market developments such as new product launches, contractual agreements, mergers and acquisitions, increased investments, and collaboration with other organizations. Competitors in the Predictive Maintenance (PdM) industry must offer cost-effective items to expand and survive in an increasingly competitive and rising market environment.


One of the primary business strategies adopted by manufacturers in the Predictive Maintenance (PdM) industry to benefit clients and expand the market sector is to manufacture locally to reduce operating costs. In recent years, Predictive Maintenance (PdM) industry has provided efficiency in terms of providing many solutions ahead of time. The Predictive Maintenance (PdM) market major player such as Axiomtek Co. Ltd (Taiwan), Oracle Corporation (US), Microsoft Corporation (US), XMPro (US) and others are working to expand the market demand by investing in research and development activities.


Axiomtek is a well-known industry pioneer who is steadfastly committed to the research, development, and production of a variety of cutting-edge, dependable, and industrial computer products with high efficiency. Over the past 30 years, Axiomtek has grown dramatically. Software, hardware, firmware, and application engineers are all part of Axiomtek's expanding team of engineers. In December 2022: Axiomtek, a company with experience in both software and hardware integration, recently introduced the AMR Builder Package. The package comes with DigiHub for AMR, sensor kits, a controller, and development support services.


Senseye is a industrial analytics software company providing outcome-oriented predictive maintenance solutions for manufacturing and industrial companies. Its predictive maintenance technology offers a significant decrease in unplanned machine downtimes and greater productivity of maintenance personnel. Through extended asset lifetimes and waste reduction, Senseye products help businesses enhance their sustainability. On June 2022 Siemens Digital Industries announced the acquisition of Senseye, a Southampton-based provider of machine data, to broaden its range of cutting-edge predictive maintenance and asset intelligence. 


Key Companies in the Predictive Maintenance (PdM) market includes




  • Axiomtek Co. Ltd (Taiwan)




  • Oracle Corporation (US)




  • Microsoft Corporation (US)




  • XMPro (US)




  • IBM Corporation (US)




  • RapidMiner (US)




  • Hitachi Ltd (Japan) among others




Predictive Maintenance (PdM) Industry Developments


The purpose of the partnership between Optibus and Stratio, which will begin in March 2023, is to advance and enhance predictive maintenance solutions through the application of artificial intelligence.


In order to provide predictive maintenance solutions that forecast vehicle needs with greater precision and notify users in advance of when a vehicle may break down or require repair, the Optibus-Stratio partnership will quicken the integration of historical data, artificial intelligence, and vehicle health monitoring. The agreement represents the first time a predictive maintenance company and a planning and operations platform have worked together.


To improve occupant comfort and raise building value, Schneider Electric, the world leader in the digital revolution of energy management and automation, today announced the launch of EcoStruxureTM Building Operation for the Indian market in March 2023. Buildings in India use 30% of the total electricity produced there, which has resulted in an increase in demand for energy.


November 2022: Persistent and Software AG will work on go-to-market initiatives, including as the creation of industry solutions and accelerators for the banking, financial services, and insurance, telecommunications, and healthcare and life sciences sectors. The recently established Professional Services Center of Excellence will bring the domain and technical capabilities required to deliver these solutions to meet client business goals. It will be supported by a strong talent base of Persistent-trained engineers.


June 2022: GlobalLogic Japan, Ltd. ("GlobalLogic Japan") is a Japanese affiliate of GlobalLogic Inc., which will be bought by Hitachi, Ltd. (TSE:6501, "Hitachi") in July 2021. Today, Nojima Corporation (TSE:7419, "Nojima") announced their alliance. The collaboration aims to hasten Nojima's Digital Transformation ("DX") strategy's creation and application.


Predictive Maintenance (PdM) Market Segmentation


Predictive Maintenance (PdM) Component Outlook




  • Hardware




  • Solution




  • Services




Predictive Maintenance (PdM) Testing Type Outlook




  • Vibration Monitoring




  • Electrical Insulation




  • Infrared Thermography




  • Temperature Monitoring




  • Ultrasonic Leak Detector




  • Oil Analysis




Predictive Maintenance (PdM) Deployment Mode Outlook




  • Cloud




  • On-premise




Predictive Maintenance (PdM) Technique Outlook




  • Traditional Technique




  • Advanced Technique




PdM Vertical Outlook




  • Manufacturing




  • Healthcare




  • Energy & Utility




  • Automotive




  • Aerospace & Defense




  • Transportation




  • Others




Predictive Maintenance Regional Outlook




  • North America



    • US

    • Canada






  • Europe



    • Germany

    • France

    • UK

    • Italy

    • Spain

    • Rest of Europe






  • Asia-Pacific



    • China

    • Japan

    • India

    • Australia

    • South Korea

    • Australia

    • Rest of Asia-Pacific






  • Rest of the World



    • Middle East

    • Africa

    • Latin America



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