Predictive Maintenance Industry Overview

The global predictive maintenance market size was valued at USD 7.85 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 29.5% from 2023 to 2030.

Integrating AI and ML into predictive maintenance prevents unplanned downtime and asset failures. AI-based preventive maintenance solutions include IoT hardware components that connect physical assets and an advanced analytics platform that helps predict failures and avoid unplanned downtime. IoT sensors, which are embedded in the equipment, collect various data, including environmental and manufacturing operations data, to determine component failure before breakdown. AI models can also predict patterns for failure modes of certain components. AI's major benefits in predictive maintenance include preventing production losses owing to faulty equipment, eliminating manual inspection, and enhancing workplace safety by automatically collecting data from machines in hard-to-reach places.

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Digital twin technology offers a replica of the actual proof in digital format by collecting real-world data of the physical system or objects. It provides simulated output, for example, determining how various inputs would affect business equipment systems. Some major applications include visualization of products in real-time, troubleshooting remote equipment, connecting disparate systems and promoting traceability, and managing complexities and system-level linkages. For the use of digital twin in predictive maintenance, generally, certain criteria need to be considered, such as predictive problem, meaning there should be a target or an outcome to predict; recorded data must be appropriate and sufficient for supporting use cases; operational history, which includes both good and bad outcomes of problems, is required, and the businesses should have domain expertise.

Some industrial machines used currently are not compatible with smart sensors used for predictive maintenance, which has been a major factor restraining the market growth. Compatibility concerns of the assets have resulted in assets being altered for system integration, which could result in additional costs, restraining businesses from adopting predictive maintenance technology.

Predictive Maintenance as a Service (PdMaaS) offers easy access to manufacturing plants at an affordable price. Several startups offer PdMaaS solutions, which help reduce infrastructure costs and maximize asset utilization. PdMaaS solutions also offer on-demand access to predictive maintenance, helping improve scalability and eliminating infrastructure and development costs. Other benefits include improving asset life, remaining useful life, machine uptime, and reliability by tracking issues concerned with assets before their breakdown.

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Key Companies Market Share Insights

Prominent Predictive Maintenance (MVNO) market players are Cisco Systems, Inc., General Electric Company, SAP SE, Schneider Electric SE, and Siemens. Industry players are also adopting various strategic initiatives such as partnerships, mergers acquisitions, collaborating with other firms to gain a competitive edge, and deploying better customer services. For instance, in May 2023, Cisco Systems, Inc. and NTT, a telecom infrastructure services company, collaborated to develop and offer real-time data insights, improved decision-making, and enhanced security with the help of predictive maintenance, supply chain management, and asset tracking capabilities.

In June 2023, Accenture plc acquired Nextira, an Amazon Web Services (AWS) premier partner that leverages AWS services to deliver predictive analytics, cloud-native innovations, and an immersive experience to its client base. These AWS services and solutions help boost the engineering capabilities of Accenture Cloud First and provide full-scale cloud capabilities to clients. Nextira offers cloud-based services with cutting-edge artificial intelligence, machine learning, engineering skills, and data analytics to facilitate consumers to build, design, launch, and improve high-performance computing settings. Some of the prominent players operating in the global predictive maintenance market are:

• Accenture plc
• Cisco Systems, Inc.
• General Electric
• Honeywell International Inc.
• Hitachi, Ltd.
• IBM Corporation
• Microsoft
• PTC
• Robert Bosch GmbH
• Rockwell Automation
• SAP SE
• SAS Institute
• Schneider Electric SE
• Siemens
• Software AG

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