IIoT is changing the game for manufacturers. IIoT-connected machines capture and communicate real-time data more accurately and consistently than previously possible. IIoT allows organizations to break open data silos and gain access to information at every level.
The benefits of this actionable data are far-reaching. Operators, supervisors, and engineers can gain visibility into production. Engineers can take cues from the process, operator, and machine data to achieve continuous improvement and improve efficiency on the plant floor. Also, management can make informed business decisions backed by data. Overall, personnel at all levels can detect problems and inefficiencies sooner and optimize their operations. This data-driven decision-making takes the guesswork out of solving problems.
9 key benefits of IIoT
1. Increased machine utilization
Industrial IoT enables manufacturers to connect their machines to the internet. Connected machines give manufacturers insight into machine health and important KPIs in real-time. These can include overall equipment effectiveness (OEE) and overall process effectiveness (OPE). This data helps manufacturers identify and fix causes of unplanned downtime. They can also increase machine utilization by highlighting need for preventive equipment maintenance.
2. Predictive maintenance
Real-time data from IIoT-connected systems can help predict defects in machinery. This allows manufacturers to take preventative measures against the issues before they occur, ultimately resulting in higher machine uptime and greater overall productivity. Preventing equipment failures reduce process time, rework, scrap, and unplanned downtime. These improvements help manufacturers save on associated costs.
3. Asset tracking
Manufacturers can track products throughout the supply chain and alert stakeholders of damage or possible damage to goods.
4. Facility management
IoT-connected environmental sensors can monitor conditions such as vibrations, temperature, humidity, and more. They can detect conditions that negatively impact operations or cause excessive wear and tear to equipment.
5. Just in Time Manufacturing
Real-time data reporting makes Just in Time manufacturing possible. Processes can be adjusted in real-time to eliminate waste and allow for production to finish on time and in sync with materials in process and raw materials. This helps bring planned production closer to actual production.
6. Connecting remote assets
Connecting devices means that data from remote assets are now accessible from a central location. These assets can be monitored and controlled remotely, allowing for a greater degree of control.
7. Easier-to-use interfaces
Connected software allows operators, engineers, and managers to monitor data through HMIs (human-machine interfaces). HMIs are much more intuitive, especially for personnel without a high level of IT proficiency. These interfaces also centralize data from different sources. As a result, personnel can master tools without extensive training or needing to rely on IT staff.
8. Sharing knowledge across plants
Institutionalizing knowledge keeps critical knowledge within the workforce over time. Centralized knowledge can also help standardize processes. This is critical to continuous improvement efforts within an organization. Finally, having standardized, centralized knowledge allows experts to respond to issues no matter where they are.
Data silos and tribal knowledge, (knowledge that is gained over years of experience and passed down orally but not standardized or documented), are a significant cause of inefficiency for manufacturers. Sharing knowledge is more critical for manufacturers now than ever, as baby boomers are retiring from the workforce at a rate of 10,000 a day. If the retiring workforce’s knowledge is not preserved, it will need to be re-learned by later generations.
9. Process and behavior monitoring
The data collected from IoT-enabled devices and software allows managers to gain insight into employees’ performance. With this data, they can identify bottlenecks and areas for improvement. For example, they could learn that employees consistently make mistakes or produce defects during a given step. Using this information, process engineers can perform root cause analysis to determine what improvements can be made (and use this data as a benchmark to measure improvement).
These benefits translate to significant business impacts based on cost savings, quality improvement, and increased efficiency.
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