Global Predictive Maintenance Market is valued around USD 5.56 Billion in 2021 and expected to reach USD 32.36 Billion by 2028 with the CAGR of 28.6% over the forecast period.
Predictive maintenance techniques are proposed to support to determine the condition of in-service equipment so as to estimate when maintenance should be performed. This approach promises cost savings over monotonous or time-based preventive maintenance due to tasks are performed only when essential. Thus, it's measured condition based maintenance managed as recommended by approximations of the squalor state of an item. The main potential of predictive maintenance is to license suitable scheduling of corrective maintenance, and to stop unforeseen equipment failures. Predictive maintenance varies from preventive maintenance because it relies on the specific condition of kit, instead of average or predictable life statistics, to predict when maintenance is going to be obligatory.
Some of the main mechanisms that are necessary for applying predictive maintenance are data collection and pre-processing, early fault discovery, fault detection, time to failure prediction, maintenance preparation and resource optimization. Predictive maintenance has also been measured to be one between the driving forces for refining productivity and one with the ways to recognize just-in-time in manufacturing.
COVID-19 has shown a positive impact on the growth of global predictive maintenance market. The COVID-19 pandemic encouraged companies to take extra care of their manufacturing equipment and machinery to raise output because of worldwide supply chain disruption and high demand for different goods. Predictive maintenance solutions have permitted organizations to reimburse for restricted accessibility of labourers during the COVID-19 pandemic as they can deal with simple machinery troubleshooting, periodic monitoring and different tasks. Many organizations have begun to utilize advanced artificial intelligence systems, smart sensors, and other Industry Internet of Things (IoT) solutions for track health and productivity of important apparatus utilized in their fabricating process to stay away from expensive production downtimes.
Global predictive maintenance market is segmented into components, deployment mode, organization size, industry verticals and regions & country level. Based on components, the predictive maintenance market is segmented into solutions and services. Based on deployment mode, the predictive maintenance market is segmented into cloud and on-premise. Based on organization size, the predictive maintenance market is segmented into large enterprises and small and medium-sized enterprises (SMEs). Based on vertical, the market is segmented into government and defence, manufacturing, energy and utilities, transportation and logistics, healthcare and life sciences and others.
The regions covered in this global predictive maintenance market report are North America, Europe, Asia-Pacific and Rest of the World. Based on country level, market of predictive maintenance is sub divided into U.S., Mexico, Canada, U.K., France, Germany, Italy, China, Japan, India, South East Asia, GCC, Africa, etc.
Global predictive maintenance market report covers prominent players like
On April 20th, 2021; Koenig and Bauer launched its predictive maintenance services for print machine proprietors. Different work processes have been explained and executed in close collaboration with in excess of 20 pilot clients from the paper and business fragments. Customer utilizes the data contained in previously existing press information for automated investigations. This makes it conceivable to distinguish and redress possible problems before they happen. It is feasible to survey a wide scope of press parts like the reel stands, the plate changers, or lubrication systems and the hydraulic clamping. Predictive maintenance applies artificial intelligence techniques, like rule mining or AI, to empower exact and computerized real-time investigation of the press information.
One of the major factors driving the growth of global predictive maintenance market is increasing requirement to decrease the maintenance cost and downtime. In different verticals, like modern assembling or seaward oil and gas, unplanned downtime emerging from equipment breakdown can cost cash. AI-based based IoT arrangements offer ventures predictive maintenance applications to anticipate hardware disappointment early. Organizations are utilizing AI and ML advances to accomplish accuracy, incredible precision, and speed over customary business insight devices to analyse IoT information. As industrial clients become progressively aware of the developing maintenance expenses and unexpected apparatus failures, predictive maintenance solutions are gaining much more footing. Predictive maintenance based solutions assist ventures with recognizing designs in constant streams of information to forecast apparatus failure downtime caused.
For instance; in May 2019, Microsoft worked together with NXP Semiconductors to bring AI and ML abilities for oddity detection to Azure IoT clients. The two organizations together launched another Anomaly Detection Solution for Azure IoT. The arrangement included predictive maintenance features for rotating parts, presence discovery, and interruption recognition for avoiding failures and decreasing downtime to upgrade efficiency and system safety.
In addition, another major factor for the growth of global predictive maintenance market is rising IoT adoption. The reception of predictive maintenance addresses a huge business opportunity for ventures that wish to take benefits of the advanced technologies of digitization. Predictive analytics has gained importance growing adoption of IoT devices. As prescient analytics uses similar IoT information as utilized by IoT gadgets and refines it to produce predictions and inferences. IoT Analytics has the capacity to deal with IoT information and foster constant dashboards mapped on varied parameters. For instance; in June 2020, PTC upgraded ThingWorx Industrial IoT stage to speed up Industrial IoT arrangements across the endeavour value chain. ThingWorx 9.0 would convey new and extended features to assist industrial organizations implement, create, customize and scale their answers. Furthermore, growing investments in predictive maintenance and increasing importance of data in equipment management decisions are also fostering the market growth.
However, lack of skilled workforce and data privacy & security concern may hamper the global predictive maintenance market growth. In spite of that, increasing adoption of advanced technology such as machine learning, integration of predictive maintenance with IIoT can provide various opportunities for the further growth of the global predictive maintenance market.
North America is expected to dominate the global predictive maintenance market due to the rising number of predictive maintenance vendors and growing concern regarding cost saving & safety. For instance; in February 2019, IBM launched another arrangement of IoT solutions that group AI and advanced analytics to help resource serious associations, like the Metropolitan Atlanta Rapid Transit Authority (MARTA), to further develop maintenance strategies. The solution was intended to help associations with bringing down costs and diminish the risk of disappointment from actual resources like vehicles, fabricating robots, turbines, mining gear, lifts, and electrical transformers. The arrangement named IBM Maximo Asset Performance Management (APM) arrangements were intended to gather information from actual resources in close to real-time and give experiences on current working conditions, anticipate possible issues, identify issues and offer repair suggestions. Predictive maintenance procedures have been intended to help in surveying the state of in-administration hardware to estimate the time for maintenance. Such a methodology offers cost savings over daily schedule or preventive support dependent on time, as works are done just whenever justified.
Asia Pacific is expected to witness a lucrative growth in the global predictive maintenance market due to the increasing concern to improve maintenance & repair time of industrial equipments and rising investment by public & private sectors or more innovative maintenance solution in this region.
|2015 - 2022
|2021 - 2028
|Market Size in 2021:
|USD 5.56 Billion
|Base year considered
|Forecast Period CAGR %:
|Market Size Expected in 2028:
|USD 32.36 Billion
|Tables, Charts & Figures:
|Syncron AB, Hitachi, Ltd, Software AG, Microsoft Corporation, PTC Inc., IBM Corporation, TIBCO Software Inc, Schneider Electric SE, SAS, General Electric and others.
|By Component, By Deployment Mode, By Enterprise Size, By Industry Vertical
|North America, U.S., Mexico, Canada, Europe, UK, France, Germany, Italy, Asia Pacific, China, Japan, India, Southeast Asia, South America, Brazil, Argentina, Columbia, The Middle East and Africa, GCC, Africa, Rest of the Middle East and Africa
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