Predictive maintenance is also known as condition-based maintenance. It monitors the performance and maintenance, condition of machines and equipment during operations to avoid failure. It depends on condition monitoring. The three facets of condition monitoring include online, periodic, and report. In addition, there are several advantages of predictive maintenance which include cost savings, decreasing planned downtime, maximizing the lifespan of equipment, optimizing employee productivity, and more. Besides, the disadvantage is the amount of time it takes for assessing and implementing PDM schedules.
Predictive maintenance offers a great ability to make a prediction 20 times faster than threshold-based monitoring systems to organizations. In industries such as oil & gas and industrial manufacturing, downtime costs a large amount of money, caused by machine failures. Thus, industrial customers are becoming more conscious of predictive maintenance. Additionally, organizations are taking support of AI and ML technologies for precision accuracy and speed over traditional tools to examines the data. All these factors are escalating the demand for predictive maintenance, which is boosting the growth of the global Predictive Maintenance market.
On the downside, data produced by devices used in predictive maintenance are increasing in volume as connected devices are rising in number. This causes misuse of data such as to determine the strategies of competing companies, and take control of machines. Similarly, an increase in privacy issues is seen due to the unavailability of resources for the implementation of AI on IoT devices. These factors may restrain the growth of the predictive maintenance market.
Covid-19 Impact on Predictive Maintenance Market
Like many other industries, COVID-19 badly knocked the electronic and semiconductor industries. This unprecedented event has impacted nearly 230 countries in just a few weeks, resulting in the forced shutdown of manufacturing and transportation activities within and across the countries. This has directly affected the overall sector's growth. It is estimated that COVID-19 to leave more than USD 30 billion impacts on the electronics and semiconductor industry. The sector is majorly affected due to transport restrictions on major electronics and semiconductor raw material providers. However, the emerging need for semiconductors in several industries will offer rapid market recovery over the future period.
Predictive Maintenance Market Segment Overview
Based on Deployment Mode, the Cloud segment is expected to grow at a rapid pace in the forecast period. Most of the vendors in the predictive maintenance market offer cloud-based maintenance solutions to gain maximum profits and efficiently automate the equipment maintenance process. In addition, the adoption of cloud-based predictive maintenance solutions is anticipated to grow, primarily due to their benefits, such as easy maintenance of generated data, cost-effectiveness, scalability, and effective management. According to Industry Vertical, the Energy and Utilities segment is the fastest-growing segment in the predictive maintenance market. This is due to the increasing demand for power-usage analytics applications.
Predictive Maintenance Market, By Component
· Software
· Services
Predictive Maintenance Market, By Deployment Mode
· Cloud
· On-premise
Predictive Maintenance Market, By Industry Vertical
· Government and Defense
· Manufacturing
· Energy and Utilities
· Transportation and Logistics
· Others
Predictive Maintenance Regional Overview
In terms of region, North America and Europe are expected to witness significant growth in the predictive maintenance market. This is due to increasing competition among players. Similarly, the market in the Asia Pacific is projected to expand at a high growth rate during the forecast period. This growth is attributed to an extensive range of applications, the adoption of advanced technologies, the benefits of predictive maintenance, and the increasing manufacturing industry in developing countries such as Japan, Taiwan, and China. Hence, these factors are anticipated to upsurge the demand for predictive maintenance products. As well, the market in Middle East & Africa is also expected to show high growth owing to growing demand from the oil & gas industry.
Predictive Maintenance Market, By Geography
· North America (US & Canada)
· Europe (UK, Germany, France, Italy, Spain, Russia & Rest of Europe)
· Asia-Pacific (Japan, China, India, Australia, & South Korea, & Rest of Asia-Pacific)
· LAMEA (Brazil, Saudi Arabia, UAE & Rest of LAMEA)
Predictive Maintenance Market Competitor overview
Some key developments and strategies adopted by manufacturers in Predictive Maintenance are highlighted below.
· In September 2021, Infineon recently developed the XENSIV™ Predictive Maintenance evaluation kit to enable their customers to easily and quickly evaluate predictive maintenance functionalities in their system. Thanks to the evaluation kit, customers can reduce their time to market and engineering efforts.
Predictive Maintenance Market, Key Players
· IBM
· Microsoft
· SAP
· Hitachi
· Schneider Electric
· PTC
· GE
· Software AG
· SAS
· TIBCO
· C3 IoT
· Uptake
· Softweb Solutions
· Asystom
· Others
1. Introduction
- 1.1. Research Scope
- 1.2. Market Segmentation
- 1.3. Research Methodology
- 1.4. Definitions and Assumptions
2. Executive Summary
3. Market Dynamics
- 3.1. Market Drivers
- 3.2. Market Restraints
- 3.3. Market Opportunities
4. Key Insights
- 4.1. Key Emerging Trends – For Major Countries
- 4.2. Latest Technological Advancement
- 4.3. Regulatory Landscape
- 4.4. Industry SWOT Analysis
- 4.5. Porters Five Forces Analysis
5. Global Predictive Maintenance Market Analysis (USD Billion), Insights and Forecast, 2020-2027
- 5.1. Key Findings / Summary
- 5.2. Market Analysis, Insights and Forecast – By Component
- 5.2.1. Software
- 5.2.2. Services
- 5.3. Market Analysis, Insights and Forecast – By Deployment Mode
- 5.3.1. Cloud
- 5.3.2. On-premise
- 5.4. Market Analysis, Insights and Forecast – By Industry Vertical
- 5.4.1. Government and Defense
- 5.4.2. Manufacturing
- 5.4.3. Energy and Utilities
- 5.4.4. Transportation and Logistics
- 5.4.5. Others
- 5.5. Market Analysis, Insights and Forecast – By Region
- 5.5.1. North America
- 5.5.2. Europe
- 5.5.3. Asia Pacific
- 5.5.4. Latin America, Middle East and Africa
6. North America Predictive Maintenance Market Analysis (USD Billion), Insights and Forecast, 2020-2027
- 6.1. Key Findings / Summary
- 6.2. Market Analysis, Insights and Forecast – By Component
- 6.2.1. Software
- 6.2.2. Services
- 6.3. Market Analysis, Insights and Forecast – By Deployment Mode
- 6.3.1. Cloud
- 6.3.2. On-premise
- 6.4. Market Analysis, Insights and Forecast – By Industry Vertical
- 6.4.1. Government and Defense
- 6.4.2. Manufacturing
- 6.4.3. Energy and Utilities
- 6.4.4. Transportation and Logistics
- 6.4.5. Others
- 6.5. Market Analysis, Insights and Forecast – By Country
- 6.5.1. U.S.
- 6.5.2. Canada
7. Europe Predictive Maintenance Market Analysis (USD Billion), Insights and Forecast, 2020-2027
- 7.1. Key Findings / Summary
- 7.2. Market Analysis, Insights and Forecast – By Component
- 7.2.1. Software
- 7.2.2. Services
- 7.3. Market Analysis, Insights and Forecast – By Deployment Mode
- 7.3.1. Cloud
- 7.3.2. On-premise
- 7.4. Market Analysis, Insights and Forecast – By Industry Vertical
- 7.4.1. Government and Defense
- 7.4.2. Manufacturing
- 7.4.3. Energy and Utilities
- 7.4.4. Transportation and Logistics
- 7.4.5. Others
- 7.5. Market Analysis, Insights and Forecast – By Country
- 7.5.1. UK
- 7.5.2. Germany
- 7.5.3. France
- 7.5.4. Italy
- 7.5.5. Spain
- 7.5.6. Russia
- 7.5.7. Rest of Europe
8. Asia Pacific Predictive Maintenance Market Analysis (USD Billion), Insights and Forecast, 2020-2027
- 8.1. Key Findings / Summary
- 8.2. Market Analysis, Insights and Forecast – By Component
- 8.2.1. Software
- 8.2.2. Services
- 8.3. Market Analysis, Insights and Forecast – By Deployment Mode
- 8.3.1. Cloud
- 8.3.2. On-premise
- 8.4. Market Analysis, Insights and Forecast – By Industry Vertical
- 8.4.1. Government and Defense
- 8.4.2. Manufacturing
- 8.4.3. Energy and Utilities
- 8.4.4. Transportation and Logistics
- 8.4.5. Others
- 8.5. Market Analysis, Insights and Forecast – By Country
- 8.5.1. China
- 8.5.2. India
- 8.5.3. Japan
- 8.5.4. Australia
- 8.5.5. South East Asia
- 8.5.6. Rest of Asia Pacific
9. Latin America, Middle East and Africa Predictive Maintenance Market Analysis (USD Billion), Insights and Forecast, 2020-2027
- 9.1. Key Findings / Summary
- 9.2. Market Analysis, Insights and Forecast – By Component
- 9.2.1. Software
- 9.2.2. Services
- 9.3. Market Analysis, Insights and Forecast – By Deployment Mode
- 9.3.1. Cloud
- 9.3.2. On-premise
- 9.4. Market Analysis, Insights and Forecast – By Industry Vertical
- 9.4.1. Government and Defense
- 9.4.2. Manufacturing
- 9.4.3. Energy and Utilities
- 9.4.4. Transportation and Logistics
- 9.4.5. Others
- 9.5. Market Analysis, Insights and Forecast – By Country
- 9.5.1. Brazil
- 9.5.2. Saudi Arabia
- 9.5.3. UAE
- 9.5.4. Rest of LAMEA
10. Competitive Analysis
- 10.1. Company Market Share Analysis, 2018
- 10.2. Key Industry Developments
- 10.3. Company Profile
- 10.4. IBM
- 10.4.1. Business Overview
- 10.4.2. Segment 1 & Service Offering
- 10.4.3. Overall Revenue
- 10.4.4. Geographic Presence
- 10.4.5. Recent Development
- 10.5. Microsoft
- 10.6. SAP
- 10.7. Hitachi
- 10.8. Schneider Electric
- 10.9. PTC
- 10.10. GE
- 10.11. Software AG
- 10.12. SAS
- 10.13. TIBCO
- 10.14. C3 IoT
- 10.15. Uptake
- 10.16. Softweb Solutions
- 10.17. Asystom
Data Library Research are conducted by industry experts who offer insight on industry structure, market segmentations technology assessment and competitive landscape (CL), and penetration, as well as on emerging trends. Their analysis is based on primary interviews (~ 80%) and secondary research (~ 20%) as well as years of professional expertise in their respective industries. Adding to this, by analysing historical trends and current market positions, our analysts predict where the market will be headed for the next five years. Furthermore, the varying trends of segment & categories geographically presented are also studied and the estimated based on the primary & secondary research.
In this particular report from the supply side Data Library Research has conducted primary surveys (interviews) with the key level executives (VP, CEO’s, Marketing Director, Business Development Manager and SOFT) of the companies that active & prominent as well as the midsized organization
FIGURE 1: DLR RESEARH PROCESS
Extensive primary research was conducted to gain a deeper insight of the market and industry performance. The analysis is based on both primary and secondary research as well as years of professional expertise in the respective industries.
In addition to analysing current and historical trends, our analysts predict where the market is headed over the next five years.
It varies by segment for these categories geographically presented in the list of market tables. Speaking about this particular report we have conducted primary surveys (interviews) with the key level executives (VP, CEO’s, Marketing Director, Business Development Manager and many more) of the major players active in the market.
Secondary ResearchSecondary research was mainly used to collect and identify information useful for the extensive, technical, market-oriented, and Friend’s study of the Global Extra Neutral Alcohol. It was also used to obtain key information about major players, market classification and segmentation according to the industry trends, geographical markets, and developments related to the market and technology perspectives. For this study, analysts have gathered information from various credible sources, such as annual reports, sec filings, journals, white papers, SOFT presentations, and company web sites.
Market Size EstimationBoth, top-down and bottom-up approaches were used to estimate and validate the size of the Global market and to estimate the size of various other dependent submarkets in the overall Extra Neutral Alcohol. The key players in the market were identified through secondary research and their market contributions in the respective geographies were determined through primary and secondary research.
Forecast Model
