Tools commonly used in the Predictive Maintenance Service industry for day-to-day tasks and operations.

• Vibration analysis equipment
• Infrared thermography cameras
• Ultrasonic testing equipment
• Oil analysis equipment
• Motor current analysis equipment
• Laser alignment tools
• Acoustic emission testing equipment
• Visual inspection tools
• Temperature sensors
• Pressure sensors

Common products and services typical of NAICS Code 238990-31, illustrating the main business activities and contributions to the market.

• Manufacturing equipment maintenance
• HVAC system maintenance
• Power plant maintenance
• Oil and gas equipment maintenance
• Mining equipment maintenance
• Transportation equipment maintenance
• Medical equipment maintenance
• Food processing equipment maintenance
• Water treatment equipment maintenance
• Building automation system maintenance

The specific certifications, permits, licenses, and regulatory compliance requirements within the United States for this industry.

• Certified Maintenance and Reliability Professional (CMRP): This certification is offered by the Society for Maintenance and Reliability Professionals (SMRP) and is designed for professionals who demonstrate knowledge and skills in maintenance, reliability, and physical asset management. The certification requires passing an exam and meeting specific education and experience requirements.
• Certified Reliability Engineer (CRE): This certification is offered by the American Society for Quality (ASQ) and is designed for professionals who demonstrate knowledge and skills in reliability engineering. The certification requires passing an exam and meeting specific education and experience requirements.
• Certified Maintenance Manager (CMM): This certification is offered by the Association for Maintenance Professionals (AMP) and is designed for professionals who demonstrate knowledge and skills in maintenance management. The certification requires passing an exam and meeting specific education and experience requirements.
• Certified Maintenance Technician (CMT): This certification is offered by the Association for Facilities Engineering (AFE) and is designed for professionals who demonstrate knowledge and skills in maintenance and reliability. The certification requires passing an exam and meeting specific education and experience requirements.
• Certified Reliability Leader (CRL): This certification is offered by the Association of Asset Management Professionals (AMP) and is designed for professionals who demonstrate knowledge and skills in reliability leadership. The certification requires passing an exam and meeting specific education and experience requirements.

A concise historical narrative of NAICS Code 238990-31 covering global milestones and recent developments within the United States.

• The Predictive Maintenance Service industry has its roots in the early 1990s when the concept of predictive maintenance was first introduced. The industry has since grown to become a critical component of the maintenance and repair sector, with the development of advanced technologies such as machine learning, artificial intelligence, and the Internet of Things (IoT). In recent years, the industry has seen significant growth due to the increasing demand for predictive maintenance solutions across various sectors, including manufacturing, healthcare, and transportation. For instance, in 2019, General Electric launched a predictive maintenance solution for the aviation industry, which uses machine learning algorithms to predict engine failures before they occur. In the United States, the Predictive Maintenance Service industry has experienced steady growth over the past decade, driven by the increasing adoption of predictive maintenance solutions by various industries. The industry has also benefited from the growing demand for real-time monitoring and predictive analytics solutions, which help companies optimize their maintenance schedules and reduce downtime. For example, in 2018, IBM launched a predictive maintenance solution for the manufacturing industry, which uses IoT sensors and machine learning algorithms to predict equipment failures and optimize maintenance schedules. Overall, the Predictive Maintenance Service industry is expected to continue growing in the coming years, driven by the increasing adoption of advanced technologies and the growing demand for predictive maintenance solutions across various industries.

The anticipated future trajectory of the NAICS 238990-31 industry in the USA, offering insights into potential trends, innovations, and challenges expected to shape its landscape.

• Growth Prediction: Growing

  The predictive maintenance service industry in the USA is expected to grow in the coming years due to the increasing adoption of predictive maintenance techniques by various industries. Predictive maintenance helps in reducing downtime, increasing equipment efficiency, and reducing maintenance costs. The industry is also expected to benefit from the increasing use of IoT devices and sensors, which help in collecting real-time data and predicting equipment failures. The COVID-19 pandemic has also highlighted the importance of predictive maintenance in ensuring business continuity, which is expected to drive the demand for predictive maintenance services in the future.

Recent groundbreaking advancements and milestones in the Predictive Maintenance Service industry, reflecting notable innovations that have reshaped its landscape.

• Augury, an AI-based predictive maintenance platform, raised $55 million in Series D funding in 2020 to expand its offerings and accelerate its growth.
• Senseye, a UK-based predictive maintenance software provider, launched a new version of its software in 2020 that includes new features such as anomaly detection and root cause analysis.
• Uptake, a predictive analytics software provider, partnered with Rolls-Royce in 2020 to provide predictive maintenance services for the aviation industry.
• SKF, a Swedish bearing and seal manufacturer, launched a new predictive maintenance platform in 2020 that uses AI and machine learning to predict equipment failures.
• GE Digital, a subsidiary of General Electric, launched a new predictive maintenance software in 2020 that uses AI and machine learning to predict equipment failures and optimize maintenance schedules.