While operating, predictive maintenance software monitors the performance and condition of any equipment or machine. The software monitors the equipment using advanced techniques, allowing maintenance to be scheduled before the occurrence of any failure.
Predictive maintenance software is used to identify motor amperage spikes, and overheating caused by bad bearings, detect three-phase power imbalances caused by harmonic distortion and insulation breakdowns, and locate potential overloads or degradation in electrical panels.
The global predictive maintenance market was worth $4.32 billion in 2021 and is expected to be worth $45.75 billion by 2030, with a CAGR of 29.98% from 2021 to 2030.
Reduced Maintenance costs to drive the Market Growth
The primary reason for using predictive maintenance systems is to increase machine efficiency and, secondly, to ensure lower maintenance costs. The data analyzed by encryption software and electronics indicate the need for timely maintenance to prevent the machinery from breaking down. Breakdowns result in longer and more expensive repairs and a halt in production. According to one study, US manufacturing units spend more than USD 50 billion annually on maintenance and repair. Another study discovered that using predictive maintenance can reduce maintenance costs by about 20% while increasing production capacity by about 10%. Organizations will always look to improve process efficiency, reduce costs, optimize resources, and maximize profits by analyzing predictive maintenance statistics, so we will see an increase in demand for predictive maintenance systems.
Furthermore, businesses that used big data and data analytics in their operations saw an average 8% increase in profits. With an astounding 97% of companies in North America alone investing in AI and big data, we will see an increase in the use of artificial intelligence (AI), machine learning (ML), and analytics in the field of predictive maintenance, leading to its exceptional growth.
Deployment Mode Insights
By deployment, the on-premises mode had the largest market share, accounting for approximately 68% of the total. The ease with which the systems can be enabled in a plant setup, followed by the relatively lower capital expenditure in this mode, explains the dominance. However, due to the increased adoption of cloud-based technologies across sectors, the cloud deployment mode will grow rapidly during the forecast period.
There are two major categories in the component segment: solutions and services. The solutions category dominated the segment, with its sub-categories of integrated and standalone solutions. The integrated solutions dominated the solution segment due to their holistic approach to standalone solutions. As a result of organizations’ customer-centric policies, the solutions category will dominate the market, while the services market will grow at a relatively high CAGR.
Organization Size Insights
Large enterprises ruled the market, while small and medium enterprises (SMEs) grew rapidly. Large enterprises dominated the segment due to their higher overall requirement than SMEs. Downtime for machinery and production lines results in extremely high costs for organizations without predictive maintenance systems. According to studies, an hour of machine downtime can cost a manufacturing company up to USD 260,000, and a minute of downtime on an automobile production line can cost anywhere between USD 22,000 and USD 50,000.
North America dominated the market. The high level of investment in the industry by the companies and the availability of supporting infrastructure in the area are the causes of the dominance. According to a US Department of Energy report, putting predictive maintenance systems in place can produce returns on investment up to ten times the systems’ capital cost. Data from the World Bank show that the US manufacturing value addition in 2020 was significantly higher than USD 2,337 billion. The US also has the largest defense budget in the world, estimated at USD 2,021 billion in FY 2022. According to the Government of Canada statistics, the manufacturing sector contributed close to 174 billion CAD to the GDP, and the sector’s exports were roughly 354 billion CAD annually. North America will continue to rule the intelligent maintenance systems market segment shortly due to the region’s strong manufacturing and healthcare sectors.
To strengthen their market offerings, predictive maintenance market vendors have implemented a variety of growth strategies, such as product upgrades, partnerships and agreements, new product launches, business expansions, and mergers and acquisitions.
Major players in the market are:
- Hitachi Ltd
- Oracle Corporation
- Microsoft Corporation
- SAP SE
- Engineering Consultants Group, Inc
- General Electric
- IBM Corporation
- Sigma Industrial Precision
- Spark Cognition
- TIBCO Software Inc
- Uptake Technologies Inc
- SAS Institute
- Other players