Predictive Maintenance and IoT: A Perfect Pairing for Enhanced Performance

Eseye

IoT Hardware and Connectivity Specialists

LinkedIn

While it’s easy to only think about innovations like IoT in terms of commercialization and the generation of new revenue streams, arguably IoT’s greatest potential is its capability for predictive maintenance.

While predictive maintenance isn’t necessarily a ‘revenue generator’, the potential for IoT to put a sensor on pretty much anything you can think of provides ample opportunity for enterprises to avoid unplanned downtime that could affect revenues.

In the manufacturing sector this could be the failure of a key piece of production equipment right at the start of the seasonal busy period. Or for a utility it could be a catastrophic supply chain failure putting thousands of customers’ services at risk.

Benefits of IoT in predictive maintenance

Reduced maintenance cost

IoT-based predictive maintenance uses sensors and analytics software to monitor the status and performance of a machine or piece of equipment and predict when it will require maintenance. This approach avoids catastrophic failure and unplanned downtime, reducing maintenance costs overall.

Reduced equipment downtime

An extension of the above benefit, keeping equipment in optimal condition ensures it runs at maximum efficiency and reduces the time it is out of action, especially for unplanned maintenance. All equipment and machines need some maintenance and will likely see downtimes as worn parts are replaced or upgraded, but being able to control when that happens is advantageous for the company and prolongs the lifespan of the equipment.

Increased asset utilization

Again this is more an extension of the above, but well-maintained equipment tends to perform better and more efficiently. This means squeezing more value of the equipment cost and keeping production at peak efficiency.

Increased human efficiency

Humans tend to be more expensive than machines and IoT monitoring can help human technicians keep equipment running better and make the best use of their time. IoT sensors can provide real-time information about equipment that can help identify potential issues that need to be fixed by a human. This helps technicians stay on top of tasks and gives them the opportunity to perform more tasks.

Improved safety and compliance

In hazardous environments or segments such as manufacturing that rely heavily on machinery, IoT predictive maintenance can be essential from a health and safety perspective – helping ensure machinery is in good working order and alerting human managers to any potential risks. This could be a part or machine overheating or pressure levels outside of normal operating parameters.

Key IoT technologies in predictive maintenance

Sector-specific IoT sensors, each with their own long life battery and cellular or wireless connectivity, can monitor and measure a wide range of data points, including operating temperature, supply voltage and current, vibration, fluid levels, chemical components, and location among others.

Collected data could then be sent real time or in batches to a cloud-based centralized data analytics and storage platform, where AI and ML models can access and manipulate it to provide actionable insights.

Key technical components for predictive maintenance include:

• Sensors: To collect data from machines, devices, or the local environment.

• Actuators: To perform remote-controlled or automated actions on the machine.

• Data analytics and storage platforms: Tools that aggregate, store and analyze data to provide insights, often in the cloud.

• IoT platforms: Management software for status and inventory management of IoT devices and for managing commands sent to actuators.

Smart manufacturing specifically may also use an Industrial Control System (ICS) – an industrial operating system and set of devices that regulate the behavior of the machinery and equipment used in the production process. This includes mechanical, hydraulic and pneumatic devices, as well as electronics.

Many of these manufacturing or industrial systems are based on the SCADA (supervisory control and data acquisition) architecture for high-level supervision of machines and processes.

Industries that can benefit from predictive maintenance

Manufacturing

Industrial manufacturing, especially smart manufacturing and Industrial IoT, is one of the most obvious segments that can benefit from predictive maintenance.

Instrumentation for industrial sensors, actuators and machines, and providers of industrial network equipment increasingly offer solutions to enable customers to monitor and control devices wirelessly in parts of the plant that are normally not connected to the control room due to accessibility or wiring costs. This can mean reduced machine downtime, increased worker safety, and better quality control.

Pharmaceutical and chemical

Pharmaceutical companies can leverage predictive maintenance to optimize manufacturing and improve quality control. Automated processes and robotics can enhance the production of chemicals while ensuring compliance with regulatory standards and worker safety.

Sensors connected to predictive maintenance software helps pharmaceutical manufacturers detect signs of equipment malfunction and act accordingly during the production process or chemical and liquid storage.

Utilities

For energy and water utilities, predictive maintenance solutions open up new possibilities for utilities to make enhancements in operational efficiency, reduce non-revenue water (NRW), and greatly improve water and energy conservation. Leaky pipes can also allow contaminants to enter, such as bacteria and viruses, making the water unsafe for consumption.

Transportation

IoT sensors can be installed on traffic lights, cameras, and roadway sensors to collect data on traffic patterns, congestion, and accidents. In some cases additional data can also be collected from connected cars or the mobile devices of the occupants.

For fleet vehicles, predictive maintenance means the avoidance of time-consuming and costly repairs, avoiding vehicles being taken off the road unexpectedly.

Smart cities, campuses and building

Just as the brain and nervous system govern how the human body regulates its functions, technologies enable cities to respond to changes in their local environments on a city-wide, campus or estate level, all the way down to individual buildings.

Smart city and smart building IoT architecture encompasses a complex network of sensors, devices, and data processing systems, connecting back to multiple management ‘brains’ that work together to enhance urban living and working.

IoT connectivity means cities can achieve real-time data collection and analysis and improve everything from traffic management and public safety to energy efficiency and environmental monitoring. Smart cities encompass a lot of other ‘smart’ segments, including but not limited to smart water management, smart energy, smart mobility, smart buildings, and smart campuses, but all linked back to a centralized system.

Predictive maintenance in action

Costa Coffee

The Costa Express coffee vending machine aggregates over 90 sensors including health monitoring, local time synchronization and data route information. The coffee vending machines report problems directly to Costa Express, making diagnosis and problem solving quick and easy.

In the event of a malfunction, such as a disrupted water flow or when coffee beans and milk run out, the IoT solution immediately triggers the appropriate alerts. Detailed reports on downtimes and troubleshooting times also enable Costa Express to communicate optimization suggestions to operators and service partners, making the machines more profitable in the long term.

Zero Motorcycles

The electric motorcycle manufacturer needed reliable connectivity uptime to support the mission-critical features so customers can depend on full, real-time visibility of their bike’s status and performance.

The system combines GPS technology and cellular GSM technology to monitor and protect the bikes, while allowing Zero to offer advanced information and security features to its customers. These include real-time data on location, speed, power consumption, and battery status, as well as safety alerts.

Martin Engineering

The engineering firm manufactures conveyor belt cleaners, air cannons and dust control products for making bulk materials handling cleaner, safer, and more productive.

Eseye helped Martin Engineering to improve governance, security, and compliance with local data protection laws and with the new solution in place, Martin Engineering’s mining customers can reduce safety risks, increase uptime, improve budgeting, and save time and effort.

IoT solutions for optimizing predictive maintenance

Integrating real-time status and performance data with predictive analytics, predictive maintenance can help enterprises improve productivity, reduce unplanned or untimely downtime, and maximize the value of production assets across the entire lifecycle.

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Eseye

IoT Hardware and Connectivity Specialists

LinkedIn

Eseye brings decades of end-to-end expertise to integrate and optimise IoT connectivity delivering near 100% uptime. From idea to implementation and beyond, we deliver lasting value from IoT. Nobody does IoT better.

In this article

• Benefits of IoT in predictive maintenance
• Key IoT technologies in predictive maintenance
• Industries that can benefit from predictive maintenance
• Predictive maintenance in action