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The plant asset management market size is expected to increase by USD 2.40 billion, at a CAGR of 7.8% from 2023 to 2028. The market is experiencing significant growth, driven by the incorporation of advanced technologies such as 3D modeling in real-time asset management and the use of prescriptive analytics for proactive analysis. PAM involves real-time asset management incorporating 3D modeling, smart sensor adoption, and advanced technologies such as smart factory in various industries. Key growth drivers include the rise of wireless monitoring systems and the integration of industrial IoT, enhancing system reliability and reducing maintenance costs. These innovations enable organizations to optimize their maintenance operations, reduce downtime, and enhance operational efficiency. However, the PAM market also faces challenges from substitutes, including the increasing adoption of cloud-based solutions and the integration of Internet of Things (IoT) sensors for predictive maintenance. As the industry continues to evolve, the focus on data-driven insights and automation will be crucial to remaining competitive.
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The PAM market plays a crucial role in helping manufacturing organizations effectively manage their long-term assets, including fixed assets and capital equipment investments. These beneficial assets, such as property, machinery, and manufacturing equipment, contribute significantly to business operations and generate sales by producing products and services. Properly managing plant assets is essential for maintaining asset health, ensuring plant safety, optimizing plant performance, and adhering to regulations. Plant managers rely on workflow processes to organize and plan for maintenance records, upgrades, repairs, and life cycle replacements. IT asset management software (AMS) is a strategic tool used to collect, analyze, and report data on plant assets. Advanced data analytics, IoT solutions, and automated reporting provide valuable insights into asset health, plant utilization, and environmental footprints, enabling turnaround times to be reduced and business intelligence to be maximized.
Effective PAM involves identifying and categorizing assets, understanding their contributions to business operations, and tracking their progress throughout their life cycle. This includes data collection on maintenance history, asset condition, and performance metrics. Properly managing plant assets leads to improved plant safety, increased plant utilization, and reduced downtime, ultimately contributing to total earnings for the organization. Examples of plant assets include factory-related resources such as machinery, HVAC systems, pumps, and tanks. The industrial revolution brought about a significant increase in the use of plant assets, and their importance has only grown since then. Effective PAM is essential for any manufacturing organization seeking to remain competitive and profitable in today's market
The plant asset management market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD Billion" for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.
The cloud segment is estimated to witness significant growth during the forecast period. There has been an increase in demand for cloud storage services across different industries including PAM. One of the main reasons fuelling the high demand for this segment is its numerous advantages including scalability and accessibility.
The cloud segment was the largest segment and was valued at USD 2.41 billion in 2018. Scalability is one of the main advantages of this segment as it allows several enterprises to accommodate the needs of growing businesses. This is essential for industries where assets and operations may expand over time. Additionally, this segment offers real-time data and analytics, enabling better decision-making and proactive maintenance which is essential in PAM, where timely insights can prevent costly downtime. Furthermore, it is easy to integrate with other cloud-based services and emerging technologies, including Internet of Things (IoT) platforms, allowing more comprehensive and connected asset management strategies. Hence, such factors are expected to fuel the growth of this segment, which in turn will drive plant asset management market growth during the forecast period.
Based on end-user, the segment is classified into the power industry, pulp and paper industry, oil and gas industry, refining industry, petrochemical, and others. There is an increasing shift towards renewable sources of energy, such as solar and wind power, for electricity production due to factors such as increasing demand for green fuel and increasing environmental concerns across the world. There is an increasing adoption of PAM systems across power industries as it enable to maintenance of a record of the equipment and machinery in power generation plants. Such insights and records help to increase efficiency by preventing system failure. Hence, such factors are expected to fuel the growth of this segment which in turn will drive plant asset management market growth during the forecast period.
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North America is estimated to contribute 53% to the growth by 2028. Technavio's analysts have elaborately explained the regional trends, drivers, and challenges that are expected to shape the market during the forecast period. One of the main countries that is significantly contributing to the growth of the PAM market in North America is the US as it is the largest producer and consumer of crude oil. Additionally, there are significant fluctuations in crude oil prices across the world which has fuelled the adoption of PAM across these industries. Several mid-sized oil firms are adopting PAM systems in their processes for effective operations.
Furthermore, there has been significant growth in the power industry across the US over the last few years, which has resulted in a rise in demand for renewable sources of energy. Some of the key assets in power industry plants comprise piping, mechanical structures, instrumentation, steel structures, electrical equipment, and process automation systems. Therefore, there is an increase in the adoption of PAM systems across these power industries as the operators need to access the details of the lifecycle of the assets. Hence, such factors are expected to drive PAM market growth in North America during the forecast period.
The PAM market is witnessing significant growth driven by manufacturing firms' increasing focus on equipment inspections and efficient plant asset management systems, including asset performance management. Leveraging field technicians and real-time location tracking technologies, companies are optimizing operations and ensuring the reliability of critical assets such as construction equipment and generators. Location-based technology enhances visibility and control over assets in manufacturing and utility plants, minimizing resource wastage and maximizing productivity. Digitalization plays a key role, enabling stakeholders to adopt lean manufacturing practices and capitalize on the advantages of digitalization in manufacturing processes. Cloud-based PAM solutions, real-time data analytics, and automation assets streamline asset lifecycle management, catering to industries like aerospace, defense, and energy & power.
Our researchers studied the data for years, with 2023 as the base year and 2024 as the estimated year, and presented the key drivers, trends, and challenges for the market.
Incorporation of 3D modeling in real-time asset management is notably driving the market growth. The Plant Asset Management (PAM) market is experiencing significant growth due to the increasing adoption of advanced technologies such as Acoustic technology, Computer vision, Machine learning (ML), and the Internet of Things (IoT)/Industrial Internet of Things (IIoT). These technologies are revolutionizing the way organizations manage their equipment and infrastructure. For instance, acoustic sensors are used for predictive maintenance in industries like aerospace and defense, automotive, and energy & power, where regular inspections are crucial for safety and efficiency. Similarly, Computer vision and Machine learning solutions are used for automating workflows in industries like construction and healthcare, enabling real-time monitoring and analysis of equipment and environmental risks. Moreover, the use of IoT sensors, including cheap sensors, is making it possible to collect vast amounts of data from assets and infrastructure in real-time.
This data is then analyzed using AI and ML algorithms to identify patterns and anomalies, enabling predictive maintenance and reducing downtime. The adoption of cloud deployment models and cloud services is also facilitating the digitalization of asset management, enabling remote monitoring and control of assets and infrastructure. The use of automation assets, such as generators and automation systems, is also increasing in various industries, including manufacturing and industrial automation. Location-based technology and 3D modeling are also being used to enhance asset management, with applications in areas like commissioning, decommissioning, and content creation processes. The focus on lean manufacturing practices and reducing carbon emissions is also driving the adoption of asset management software and solutions. Data security is a critical concern in asset management, and organizations are investing in developing IT infrastructure to ensure the security of their data. Overall, the PAM market is expected to continue growing as organizations seek to optimize their asset utilization, reduce downtime, and improve operational efficiency.
One of the main tools which are extensively used in PAM is the prescriptive analytics tool. The main function of prescriptive analytics is that it leverages historical data trends to forecast changes to showcase what impact each task on the system can have on the process. There is an increasing adoption of prescriptive analytics across several organizations. Moreover, prescriptive analytics enables the organization to schedule its maintenance based on distinct scenarios created through these tools.
Additionally, several prominent market players including Rockwell Automation, ABB, and IBM offer services that use prescriptive analytics for asset management and offer data on factors that can positively or negatively affect plant operations. Hence, such factors are positively impacting the market. Therefore, it is expected to drive the market growth during the forecast period.
Threat from substitutes is a key challenge hindering growth. The PAM system witnesses a high threat from substitutes from solutions such as manufacturing execution system (MES) software. An MES is an information technology-based manufacturing system that provides control and management operations for manufacturing plants. The system also helps in execution, automation, and operations management, including lot tracking, operation scheduling, resource allocation, plant maintenance, planning of labor, data acquisition and collection, process control, and quality assurance. For example. Schneider Electric offers Wonderware MES Software which provides real-time data on work orders, compares planned and actual production rates, and monitors operational activities. The data collected can be used to evaluate key performance indicators such as overall equipment effectiveness and analysis and track the effectiveness of the equipment in the production process.MES provides accurate real-time data, which is used for running the manufacturing process. MES system also helps in tracking orders and scheduling tasks. Thus, such substitutes will pose a challenge to the market in focus which will hamper the market growth during the forecast period.
Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.
AB SKF: The company offers plant asset management services that help plants reduce inventory costs and machinery problems.
We also have detailed analyses of the market's competitive landscape and offer information on 20 market companies, including:
ABB Ltd., Aspen Technology Inc., AVEVA Group Plc, Emerson Electric Co., Endress Hauser Group Services AG, Hitachi Ltd., Honeywell International Inc., IFS World Operations AB, International Business Machines Corp., Novo Solutions Inc., Oracle Corp., Petrofac Ltd., Ramco Systems Ltd., Rockwell Automation Inc., S and T Deutschland GmbH, SAP SE, Schneider Electric SE, Siemens AG, and Yokogawa Electric Corp.
Technavio report provides an in-depth analysis of the market and its players through combined qualitative and quantitative data. The analysis classifies companies into categories based on their business approaches, including pure-play, category-focused, industry-focused, and diversified. Companies are specially categorized into dominant, leading, strong, tentative, and weak, based on their quantitative data analysis.
The plant asset management market is experiencing significant growth driven by advancements in industrial automation and the adoption of smart technologies. With industries such as aerospace & defense, automotive, energy & power, and healthcare investing in advanced technologies like IoT, machine learning, and robotics, the demand for efficient asset management solutions is rising. PAM solutions enable companies to automate workflow, manage and map production assets, and optimize maintenance requirements through predictive and preventive maintenance strategies. Supported by supportive government initiatives and developed IT infrastructure, the PAM market offers software solutions for real-time data analytics, location-based technology, and real-time monitoring. From small- & medium-sized businesses to large manufacturing firms, PAM solutions play a crucial role in enhancing productivity, minimizing resource wastage, and ensuring sustainability in production environments.
Additionally, the market is experiencing significant growth, driven by the increasing digitalization in manufacturing processes and investments in advanced technologies across the energy and industrial sectors, driving the growth of smart manufacturing. PAM solutions enable efficient management and mapping of production assets, including equipment and infrastructure, in industries such as aerospace & defense, construction, and manufacturing & utility plants. With the deployment of cloud-based facilities and IoT sensors, PAM systems offer real-time location tracking and predictive maintenance capabilities, optimizing asset performance and reducing downtime. Key players provide industrial asset management (IAM) solutions incorporating machine learning and computer vision for enhanced efficiency. As stakeholders in the sustainability solution, PAM solutions play a vital role in monitoring carbon emissions and mitigating environmental risks, ensuring a proactive approach towards asset management in today's smart factory environments.
Market Scope |
|
Report Coverage |
Details |
Base year |
2023 |
Historic period |
2018 - 2022 |
Forecast period |
2024-2028 |
Growth momentum & CAGR |
Accelerate at a CAGR of 7.8% |
Market growth 2024-2028 |
USD 2.40 billion |
Market structure |
Fragmented |
YoY growth 2023-2024(%) |
7.2 |
Regional analysis |
North America, Europe, APAC, Middle East and Africa, and South America |
Performing market contribution |
North America at 53% |
Key countries |
US, Germany, China, Japan, and Italy |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
Key companies profiled |
AB SKF, ABB Ltd., Aspen Technology Inc., AVEVA Group Plc, Emerson Electric Co., Endress Hauser Group Services AG, Hitachi Ltd., Honeywell International Inc., IFS World Operations AB, International Business Machines Corp., Novo Solutions Inc., Oracle Corp., Petrofac Ltd., Ramco Systems Ltd., Rockwell Automation Inc., S and T Deutschland GmbH, SAP SE, Schneider Electric SE, Siemens AG, and Yokogawa Electric Corp. |
Market dynamics |
Parent market analysis, Market forecasting, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, Market growth and Forecasting, COVID-19 impact and recovery analysis and future consumer dynamics, Market condition analysis for the forecast period |
Customization purview |
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1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by Deployment
7 Market Segmentation by End-user
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Opportunity/Restraints
11 Competitive Landscape
12 Competitive Analysis
13 Appendix
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