Manufacturers are turning to the Industrial Internet of Things for smarter ways to continuously acquire behavioral data to provide actionable insights to predict product failures, increase uptime, and improve asset efficiency. Maintenance is a strategic consideration when developing and manufacturing 名媛直播, but one-third of maintenance activities are too frequent, and half are ineffective. For machine operators and plant managers, preventive maintenance and asset repairs waste unnecessary resources, eat up operating costs and undermine efficient operations. In this case, predictive maintenance may help.
Maintenance and repair operations (MRO) are essential to the normal operation of corporate assets, because maintenance is the key to the continuity and effectiveness of corporate operations. Maintenance and repair operations (MRO) involve a wide range of activities, such as inspecting industrial equipment, repairing machinery, and replacing damaged or malfunctioning parts.
The difference between preventive maintenance and predictive maintenance
In the past, companies passively maintained their assets. After the asset collapsed, the company repaired or replaced the asset. The asset has been restored to its original state. Reactive maintenance is problematic because it is associated with equipment failures, which cause interruptions in activities and cause large losses.
In order to reduce the inefficiency of passive maintenance, industrial organizations have transitioned to a preventive maintenance model. Preventive maintenance will regularly schedule repairs and service operations to prevent equipment failures. In short, preventive maintenance considers the expected life of assets to proactively inspect and maintain them. In this way, it will reduce unexpected downtime and stimulate the continuity of business operations.
Predictive maintenance strategy
Currently, preventive maintenance is dominant in corporate maintenance methods. However, it is far from optimal because it usually maintains assets earlier than their lifespan. Therefore, it leads to sub-optimal overall equipment efficiency (OEE). Companies must plan maintenance activities based on factual information about the state of assets rather than hypothetical EoL values to achieve the best overall equipment efficiency (OEE).
Compared with traditional reactive and preventive models, predictive maintenance can bring many business benefits. These measures include improving asset utilization and overall equipment efficiency (OEE), avoiding unplanned downtime, and optimal planning of maintenance activities.
Predictive maintenance as an industry 4.0 application
The benefits of predictive maintenance can save a lot of costs and increase revenue for commercial enterprises managing large deployments. Nevertheless, given that it is very difficult to obtain timely detailed information about asset conditions, predictive maintenance is still not widely used.
In the past few years, this situation is gradually changing due to the widespread deployment of advanced digital technologies such as the Internet of Things (IoT), big data, and artificial intelligence (AI) in the production facilities of large organizations. The deployment of these technologies is called the Fourth Industrial Revolution (Industry 4.0).
Industry 4.0 is deploying sensors and cyber-physical systems to digitize physical processes and realize IT-based data-driven automation and control operations. It supports a variety of industrial applications, such as flexible automation, predictive maintenance, digital twins, and various supply chain management optimizations.
In order to maintain the enterprise, Industry 4.0 promotes the collection of large amounts of digital data on the condition of machinery and equipment. The ability to collect this data can be enhanced by deploying different sensors (such as vibration sensors, acoustic sensors, temperature sensors, power sensors, and thermal imaging cameras).
