Predictive maintenance for manufacturing industry market is estimated to grow with a high CAGR during the forecast period, i.e., 2020-2029. Extensive research associated with predictive maintenance for manufacturing industry in western countries, along with growing need to reduce maintenance cost and downtime are expected to fuel the progress of this market. The growth of the market can also be attributed to factors such as increase in investments in predictive maintenance in industries as a result of IoT adoption. Moreover, lack of employees and personnel, coupled with global supply chain disruption as well as high demand for various goods during the COVID-19 pandemic encouraged companies to take extra care of their manufacturing equipment and machinery to increase output. This resulted in a surge in demand for predictive maintenance solutions across the globe. However, many companies have started to use smart sensors, advanced artificial intelligence systems, and other Industry Internet of Things (IIoT) solutions to track health and efficiency of vital machinery used in their manufacturing process to avoid costly production downtimes.
Predictive maintenance techniques are formed to determine the condition of in-service equipment in order to estimate when maintenance should be performed. This approach confirms cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted. It is likely to be influenced by a range of political, economic, social, technical, and industry-specific factors.
The market is segmented based on component into software and services, out of which, the software segment is anticipated to grab the largest share by the end of 2020, improvement of safety in factories is one of the primary concerns of the manufacturing industry. Furthermore, machine breakdowns are also causing severe production loses in the manufacturing industry. Demand for better safety, reduction of costs and machine utilization are driving the global market for manufacturing predictive analytics.
On the basis of Technology, the market is segmented into machine learning, deep learning, big data and analytics. Out of which machine learning is estimated to grab the largest market share during the forecast period 2020-2029. Manufacturers are adopting machine learning based predictive maintenance. It depends on large amount of historical or test data, along with tailored machine-learning algorithms, to test different scenarios and predict the errors in the system. Then it generates the alerts accordingly. When properly designed and implemented, a machine learning algorithm will learn the typical data’s behavior and identify deviation in real-time. A machine monitoring system will comprise input about diverse temperatures, engine speed, and others. The system can then predict the time of the breakdown. Additionally, big data analytics is projected to grab the substantial market share owning to the increasing technological advancement and dealing with the large data securely. As, the data security is one of the major concern for any organisation. Today the adoption big data technology is high because it is cost efficient, provide accurate results, and facilitates to analyse the large data set innovatively .Moreover, the interpretation helps the organisations in booting their sales and retaining customer loyalty.
Geographically, the market is segmented into North America, Latin America, Europe, Asia Pacific and the Middle East & Africa region. North America is expected to hold the largest market size in the global predictive maintenance for manufacturing industry market. North America is estimated to be the leading region in terms of adopting and developing predictive maintenance. The rising investments in emerging technologies such as IoT, AI, ML, the increasing presence of predictive maintenance vendors, and growing government support for regulatory compliance are the major factors expected to contribute to the market growth during the forecast period, while Asia Pacific is expected to grow at the highest CAGR during the forecast period. In APAC, the highest growth rate can be attributed to the massive investments made by private and public sectors for enhancing their maintenance solutions, resulting in an increased demand for predictive maintenance solutions used for automating the maintenance and plant safety process.
The predictive maintenance for manufacturing industry market is further classified on the basis of region as follows:
Our in-depth analysis of the Predictive Maintenance for Manufacturing Industry market includes the following segments:
FREQUENTLY ASKED QUESTIONS
Growing need to reduce maintenance cost and downtime and increase in investments in predictive maintenance in industries as a result of IoT adoption are the key factors driving market growth.
The market is anticipated to attain a high CAGR over the forecast period, i.e., 2021-2029.
Lack of skilled workforce and data security & privacy issue are estimated to hamper market growth.
The market in Asia Pacific region will provide ample growth opportunities owing to the increased demand for predictive maintenance solutions used for automating the maintenance and plant safety process.
The major players dominating the market are Robert Bosch GmbH, Rockwell Automation, Inc., Siemens AG, Schneider Electric, SAS Institute, PTC Inc., General Electric Company, and Software AG among others.
The company profiles are selected on the basis of revenues generated from the product segment, geographical presence of the company which determine the revenue generating capacity as well as the new products being launched into the market by the company.
The market is segmented by product type and technology, and region.
With respect to type, solutions segment to hold the largest market share due to the increase demand of predictive mantainence and rise in awareness of the cost efficiency in the industry verticals.
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