By Eric Whitley, L2L from CONTROL AUTOMATION
Data has become the currency that enables operational excellence. Sensors are the key links, acting as the eyes and ears of modern manufacturing units by providing real-time data on machine performance.
Reason 1: Monitoring Equipment
Monitoring equipment is no longer a matter of routine checks and reactive maintenance. With sensors, we've moved into the realm of predictive and even prescriptive maintenance. Vibration sensors, temperature monitors, and acoustic sensors can predict mechanical wear and tear, allowing you to schedule maintenance before a catastrophic failure occurs.
These sensors work by continuously monitoring various parameters like vibration frequencies, temperature variations, and acoustic patterns. This data is then fed into machine learning algorithms that can predict when a machine part is likely to fail. Real-time monitoring not only prevents downtime but optimizes machine performance and extends asset life.
Consider this example of a CNC machine in a metal fabrication unit. By using a combination of temperature and vibration sensors, the unit could predict spindle failures up to two weeks in advance, reducing unplanned downtime by 60%.
If you're still relying on calendar-based maintenance, it's time to upgrade. Start with critical assets and gradually expand your sensor-based monitoring system. Make sure to integrate it with your Manufacturing Execution System (MES) for seamless data flow and analytics.
Reason 2: Quality Control
Quality control has evolved from a post-production activity to an integrated part of the manufacturing process. With real-time sensors like vision systems, laser scanners, and spectrometers, you can achieve near-perfect inspection rates.
These sensors can identify defects ranging from dimensional inaccuracies to material inconsistencies. For example, vision systems use high-resolution cameras coupled with machine learning algorithms to identify even the most minute defects.
For example, in a semiconductor manufacturing unit, the implementation of laser scanning sensors reduced the defect rate by 40%. This not only improved product quality but also significantly reduced waste.
Integrate real-time quality control sensors into your production line, but remember — the sensor is only as good as the algorithm behind it. Invest in quality software and regular calibration.
Figure. Example of a force-torque sensor on a robot arm. Image used courtesy of Robotiq
Reason 3: Facilitating Complex Tasks
Complex manufacturing tasks, such as multi-axis machining or additive manufacturing, require a level of precision that's humanly impossible. Sensors provide the feedback loop for real-time adjustments, making these tasks feasible and efficient.
Force-torque sensors in robotic arms, for instance, ensure that the arms are applying the right amount of pressure during assembly. Similarly, optical sensors in 3D printers adjust the laser's focus in real time, ensuring high-resolution outputs.
Force-torque sensors enabled robotic arms in an aerospace manufacturing unit to assemble turbine blades with a precision of 0.01 mm, something unachievable by human operators.
When implementing sensors for complex tasks, precision is key. Opt for high-resolution sensors and make sure they are compatible with your existing systems. Also, invest in training your team to interpret and act on the sensor data.
Reason 4: Safety Measures
Safety in manufacturing has evolved from being reactive to proactive, and we owe that to sensors in many ways. Reactive safety measures require manufacturers to respond to incidents after they occur, while proactive safety measures aim to prevent incidents from happening in the first place through predictive analysis and monitoring.
Gas sensors, infrared cameras, and even wearable sensors for workers are making workplaces safer than ever. These sensors continuously monitor environmental conditions and machine operations. For example, gas sensors can detect hazardous leaks, and infrared cameras can identify hot spots in electrical systems.
The implementation of gas sensors reduced hazardous incidents by 70% in a chemical manufacturing plant, as they could detect gas leaks well before they reached critical levels.
Safety sensors should be non-negotiable in any manufacturing setup. Prioritize them based on the risk profile of your operations and make sure you integrate them into your emergency response protocols.
Figure. Example of a wearable safety sensor package. Image used courtesy of Strongarm Technologies
Reason 5: Data-Driven Insights
Data-driven insights are the pinnacle of modern manufacturing. Internet of Things (IoT)-enabled sensors take this a step further by making this data instantly actionable.
These sensors feed data into analytics platforms that can make real-time decisions. For example, organizations can optimize energy consumption patterns based on real-time machine performance data.
A food processing unit used IoT sensors to monitor the temperature and humidity in their storage units. They used this data to dynamically adjust the HVAC settings, reducing energy costs by 20%.
If you're not already harnessing the power of IoT in your manufacturing operations, start now. But remember, data security is paramount: make sure your IoT network is secure to prevent any potential breaches.
