Working with industrial machinery comes with inherent risks that can lead to accidents, injuries, and even fatalities if not properly safeguarded. Preventive control systems utilize various sensor technologies and automated controls to proactively monitor equipment operations and worker behavior in real time, identify potential hazards, and take appropriate actions to prevent incidents from occurring. In this blog, we will explore some common types of preventive control systems and their applications in improving workplace safety.

Proximity Detection Systems

One of the most basic yet critical types of safety systems uses proximity sensors to detect when a worker enters a hazardous zone defined around industrial machinery in motion. Common proximity sensors include light curtains, laser scanners and area scanning safety sensors. These continuously monitor the danger areas and can immediately stop or slow down moving parts if a breach is detected, preventing the worker from coming into contact with machinery components. Proximity detection is commonly used around robotic arms, presses, conveyor belts, and rotary equipment.

Vision-Based Safety Systems

With advances in computer vision and AI, video cameras are increasingly being used for real-time people and object detection near operating industrial machinery. These vision-based safety systems process live video feeds to identify any worker, tool, or obstruction entering a safety zone. They provide location and distance data that integrated machinery controls can leverage for automated stopping or slowing responses. Some vision systems also analyze activities to detect unsafe behaviors. These find wide applicability across various equipment types in manufacturing facilities, shipyards, construction sites, etc.

Environmental Monitoring Systems

Sensors also help monitor critical environmental conditions in industrial workspaces that impact safety if not maintained appropriately. These include sensors to detect factors like temperature, vibration, noise pollution, and airborne contaminants like smoke or toxic fumes. Exceeding thresholds in such conditions can increase accident risks. The data helps personnel take preemptive actions like zone evacuations, machinery shutdowns, or hazard remediation tasks before dangerous situations arise. Common deployment areas include welding/cutting areas, heavy machinery rooms, dry docks, etc.

Preventive Maintenance Systems

Equipment failures or improper maintenance frequently contribute to industrial accidents. IoT sensor modules for vibration, thermal imaging, lubricant quality, and motor/circuit conditions can continuously transmit telemetry to cloud/mobile dashboards. Advanced analytics on this maintenance data helps reliability engineers predict issues before failures occur to plan repairs. This preventively reduces risks during maintenance work. Applications involve rotating machinery, pressing machines, cranes, boilers, etc. that benefit from condition-based predictive maintenance.

Motion Control and Lockout Systems

These systems automatically disable or restrict the movement of mechanical components based on sensor triggers. Common configurations use safety controllers integrated with motors/actuators to lock out dangerous motions through electrical or mechanical means when a human presence is detected. Manual lockout-tagout features let workers isolate energy sources before service entry. This type of protective motion control goes a long way in guaranteeing zero-energy states for presses, conveyor lines, assembly robots, and other sequencing machinery.

Collaborative Robot Safety Systems

As robotic technologies get smarter and tasks become more complex, industries are deploying collaborative robots (cobots) designed to operate safely alongside workers. Integrated e-stop controls, safety-rated monitored stops, speed, and separation monitoring help ensure cobot motions adapt based on proximity detection sensors. Advanced intent recognition based on computer vision helps cobots yield to human movements for safer hand-over-hand interactions. This enables higher productivity use-cases like mobile material handling, piece part manipulation, box packing, palletizing, etc.

Wearables for Safety Analytics

Exoskeletons, smart vests, and other wearable technologies incorporate sensors to monitor biometric and location data that feeds into hazard assessments. When integrated with wider factory systems, they help track lone workers, enforce safe social distances, detect early physical stress/fatigue signals, and provide haptic alerts for on-body risks. Used along with situational safety dashboards, the data helps facility managers ensure safe work practices and prevent over-exertion injuries due to tasks like materials lifting.

The Preventech

Debilitating industrial injuries causes irreparable damage to the organs. Industrial accidents occur in a very short time and are usually caused by fatigue and reduced accuracy. Some advanced industrial equipment is equipped with safety tools and the risk of damage is reduced, but older devices are usually not equipped with smart devices.

The main problem is the lack of integrated safety methods. Methods that can also be implemented on older technology devices

What’s our solution?

Our idea is to use modular control processors. The processor, based on sensor information, detects the position and movement of the worker and immediately disables the device if the worker passes the permitted range.

The occurrence of an industrial accident has not only one cause, but it has been a chain of factors. For this reason, all useful reports for analyzing ergonomic conditions are collected. Such as reporting the time and duration of “Proximity within the Danger Zone” for each device. Reports are sent to the factory safety center.

Analysis of these data can be effective in improving the ergonomic layout of equipment and improving environmental engineering factors.

How does our system work?

1. With the help of factory safety experts and ergonomist mentors startup, we monitor and analyze the worker’s movement and how he works with devices.
2. We divide the equipment into two parts: “low-risk” and “high-risk”.
3. For the workers’ proximity and contact with the devices, we define four areas: safe, risky, high-risk, and forbidden zones.
4. We equip workers with wearable equipment with sensors.
5. Devices are equipped with processors and programmed.
6. If necessary, we will equip some peripheral equipment such as cameras or lights with auxiliary sensors.
7. We train the workers.
8. 8- Analyze feedback and report to the factory safety office.

Special Features

1. Using microprocessors to detect and analyze essential data
2. Ability to sink with a variety of industrial devices
3. Using an independent energy source to reduce the risk of technical manipulation and vandalism

4. Allow setting of technology only with a digital card of the manager and qualified persons

Based on the information provided, here are some key advantages of the Preventech preventive control system over other types of industrial safety systems:

Comprehensive Risk Assessment and Monitoring:

By evaluating worker movements, and equipment risks and defining safe/risk zones with experts, it takes a holistic ergonomic approach to safety, unlike basic sensor-based systems.

Worker-Wearable Sensors:

The use of wearable sensors on workers provides a more direct way to monitor proximity, activity, and biometrics compared to static ambient sensors alone. This enables more accurate risk detection.

Integration with Peripheral Sensors:

The ability to integrate additional sensors like cameras, and lighting aids in more robust safety inspection capabilities beyond just equipment monitoring.

Custom Configuration:

The flexibility to divide equipment into risk zones and train tailored to specific workflows/tasks allows for optimized safety protocols unique to each assembly line/machine.

Independent Power Source:

This ensures uninterrupted operation without relying on factory power and reduces the chances of technical sabotage compared to non-isolated systems.

Secure Access Controls:

Digital authentication for technology access and adjustment elevates security against accidental or malicious parameter changes over open-access preventive controls.

Data Analytics and Reporting:

Statistical analysis of safety data helps gain deeper operational insights to continuously enhance risk management compared to non-data-driven approaches.

So in summary, Preventech takes a comprehensive, configurable, and secure risk-focused approach with integrated human and equipment monitoring for optimizing industrial safety.

conclusion

In conclusion, leveraging different types of preventive control systems based on sensing, analytics, and actuation helps industrial operations transition from reactive to proactive safety approaches. By continuously monitoring worker behaviors and equipment statuses, analyzing for anomalies, and enabling automated responses, these systems significantly reduce the likelihood of injuries through early risk detection and prevention.