How to implement predictive maintenance and asset optimization with IIOT

IIoT helps collect and analyze real-time data from machines and equipment in an organization. Understanding this data helps organizations create a highly connected ecosystem of devices and firmware where information is passed quickly and smoothly. With predictive maintenance and asset optimization working together, organizations can benefit from zero equipment downtime, lower maintenance costs, higher asset productivity, and enhanced employee safety.

The Industrial Internet of Things (IIoT) is a value-capturing technology. Its implementation becomes successful depending on the right execution. To harness its capabilities, organizations across the globe are including IIoT in their operations. The motive is to bring factory intelligence, smart operations, and digital manufacturing systems into play.

According to Microsoft IoT Signals Report, around 56% of organizations implement IIoT services to optimize operations. 46% of them use it to increase productivity and 44% for the safety and security of their assets. Given the multiple use cases of IIoT, let’s find the ones that fit into predictive maintenance and asset optimization.

How IIoT, Asset Optimization, and Predictive Maintenance are Connected?

Predictive maintenance and asset optimization are important goals for a manufacturing unit. With the help of IIoT, they can gather real-time data about the machines and equipment. With this information, the machines and equipment can be better monitored. Essentially, IIoT delivers an insider report about the machines under question. Due to this, they perform better and get timely maintenance, which increases their performance and productivity.

What IIoT does is share the key performance indicators about the machines and equipment. It can share bearing speed, lubrication, and temperature, diagnose issues, detect slow-performing parts, and identify faulty parts. Using this information, companies can either schedule timely maintenance or replace the parts. As a result, there is no sudden shutdown.

Organizations with IIoT implemented can monitor and manage their assets from on-site or remote locations. They can get alerts and notifications about them and schedule repairs or maintenance during off hours to save time. The next two sections will clearly show how an organization with IIoT works more efficiently.

IIoT for Predictive Maintenance

IIoT is a key player in Industrial Revolution 4.0. Where organizations are looking to have record-breaking performances, they are also investing in the technologies that help them transition into the new revolution. With almost every organization eyeing predictive maintenance, they will gain the following benefits if executed correctly:

No Equipment Downtime

As a machine runs, hundreds of parts work in synchronization to deliver the result. But if even a single part does not perform as intended, the machine’s performance takes a dip. IIoT predicts equipment health and its maintenance needs before any of the parts fail.

Consistent Monitoring

Constant monitoring means that at no point can the machine stop working or fail suddenly. As the organizations will have continuous reports about their assets, they can plan things accordingly.

For larger orders that require the machines to run 24*7, the organizations can make changes to the machines accordingly.

Increased Productivity

When a logistics company uses IIoT for its work, it can monitor the vehicles in their fleet at all times. They can send route updates in real-time, making sure that the vehicles change in advance and reach their destination on time.

Everything is connected to having prior information about the assets and machines. With this information, the organizations will have enough time to ensure that their assets don’t come as surprises.

Reduced Costs

Everyone connected to the assets under predictive maintenance in an organization can benefit from higher productivity. Higher productivity means more output from the same quantity of resources.

From reducing field service costs to in-house operational costs, IIoT-enabled predictive maintenance increases asset utilization. A reduction in operational costs also comes from anticipating maintenance and upgrades.

Higher Worker Safety

Any sort of unexpected anomaly with the assets in an organization can lead to an unwanted disaster. Predictive maintenance and IIoT can help ensure that no workers in an organization are at risk of getting injured from their assets.

Because all the assets are connected to an IIoT-enabled master program, the administrators receive updates about the health in real time. Even if there is some issue, the sensors can detect it before the situation gets out of control and the works happen.

Organizations can use the time they get to take the workers to safety. They can also ask the technicians to start the repair work.

All of these aspects help with and come from predictive maintenance. When you combine all these benefits, they will result in predictive maintenance. Also, because IIoT leads to predictive maintenance, we have implemented predictive maintenance activities.

IIoT for Asset Optimization

IIoT does not work in a vacuum, rather, it is a part of the large nexus of technologies building a smarter world. IIoT takes the help of cloud computing, big data, advanced analytics, and other similar technologies to deliver the results we need. Benefits like asset longevity, predictive maintenance, asset optimization, etc., are some of the best ones out so far.

Here are some aspects of IIoT for asset optimization to help you gain a better understanding.

Increase In Asset Performance

Higher asset performance is linked with higher efficiency, lower risk, and higher agility. Given higher data collection, analysis, and monitoring, organizations can implement measures to achieve all three goals, which can deliver higher asset performance.

Higher Returns on Assets (ROA)

Generating higher returns implies that machinery and other types of equipment perform better than expected. Organizations use the digital capabilities provided by IIoT to build monitoring and performance-enhancing frameworks for their assets. Better monitoring is related to higher asset reliability.

Reduced Asset Maintenance Costs

Asset maintenance is a significant component of IIoT and is set to bring multiple benefits. IIoT supplies information that helps with predictive maintenance, condition-based maintenance, remote monitoring, and higher asset performance. When you know exactly when to change the engine oil of your vehicle, the only cost you have to worry about is changing the oil.

Consistent Feedback to Asset Manufacturers

Manufacturers of machines and equipment can use real-time data to identify performance issues. They can use this data to make better equipment while addressing the concerns the previous owner had about it.

IIoT-enabled predictive maintenance can help organizations optimize asset performance. By conducting efficient maintenance exercises and practically bringing unplanned downtime and maintenance to zero, they can considerably improve asset performance.

How to Implement IIoT for Asset Optimization and Predictive Maintenance?

Industrial Internet of Things implementation can be completed in five steps;

1. Project Goals: Begin the process by setting IIoT implementation goals. Get everyone involved and agree on the common goals. Based on the goals, finalize the team required for the project, resources, and extent of training.
2. Identify Work Champions and Success criteria. As you set goals, also set milestones for the project. Identifying champions of success means getting onboard experts who understand IIoT and can help you overcome obstacles along the way while taking responsibility for project implementation.
3. Set Roles and Responsibilities: For the team working on IIoT implementation, clearly define the roles and responsibilities of each member. You can use the RACI (Responsible, Accountable, Consulted, and Informed) model.
4. Run Pilot Projects: IIoT implementation is a resource-intensive project and taking small steps can help validate the project’s success. Divide the entire project into small segments, use these segments as pilot projects to test their viability. Once the pilot projects are successful, move on to full-scale implementation.
5. Make Adjustments and Start Automating: Based on the results of pilot projects, fine-tune the operations and implement the IIoT at full-scale. During implementation, you might face some challenges, but rest assured that these challenges can be overcome with due diligence.
6. Connectivity Issues: IIoT requires uninterrupted connectivity to the internet, and no one can guarantee 100% network availability. Gaps in connectivity can cause the entire system to stop functioning and cause performance issues. To tackle this issue, get the best possible internet connection, use high-quality cables, and use a system that guarantees zero data loss.
7. Data Storage and Analysis: Devices in the IIoT network generate tremendous amounts of data, and storing, processing, and analyzing the same is a big challenge. However, any amount of data can be processed and stored on the required platforms. You can choose cloud-based data storage solutions, which save on-premise storage costs.
8. Security Risks: Every type of device and connection in the IIoT network can pose a security risk, as hackers can use loopholes in these gateways to access the main network.

However, with best-in-class encryption systems, access control features, and authentication protocols, you can safeguard the network from unauthorized access.

Examples of Predictive Maintenance and Asset Optimization with IIoT Implementation

• Volvo Group uses IIoT predictive maintenance to predict spindle damages, identifying cracking, and spalling in the equipment. Using this information, they run checkups and repairs before the spindles stop working abruptly. With this approach, they are able to save both time and money.
• BNSF Railways has IIoT enabled force detectors, acoustic sensors, vision cameras, etc. used to identify cracks and defects in the freight car braking systems.

They also get real-time data on excessive friction in the car wheels and brakes, including the rail curves. Using this data, which is run through machine learning algorithms, the system is able to identify unhealthy data patterns that can cause breakage in the system.

Using similar patterns and principles, other industries like construction, oil and gas, process manufacturing, electric power generation, etc. use IIoT for predictive maintenance and asset optimization.

Conclusion

IIoT is quickly becoming an integral part of the modern economy. A McKinsey study finds that IIoT can become a $500 billion market by 2025. This can happen with further advances in this technology and its implantation. IIoT for predictive maintenance and asset optimization are two of the major benefits organizations desire.

Bringing IIoT into an organization can deliver considerable benefits, including lower maintenance costs, higher productivity, zero downtime, predictive maintenance, and asset optimization. To better understand how IIoT fits into your organization, get in touch with Intuz as we build the firmware for the IIoT hardware you can install in your organization.