Successful continuous improvement initiatives require manufacturers to understand everything happening across all of their shop floor activities. This requires significant investment in data collection to track the various machines and operator actions taking place.
Over recent years, the fourth industrial revolution has provided manufacturers with various tools to get more visibility into their on-floor operations. For example, technological advancement in the form of the Industrial Internet of Things (IIoT) has led to the proliferation of different types of manufacturing sensors.
These sensors draw data directly from machines and equipment on the shop floor, allowing operators and supervisors to know more about the equipment's performance. This approach significantly differs from the traditional methods of data collection relying on manual measurement of equipment output by workers.
In this post, we’ll explore the various types of manufacturing sensors and their vital role in tracking production on the shop floor.
What are manufacturing sensors?
Manufacturing sensors are technological instruments used to collect various data types from machines on the factory floor. This kind of data informs operators and supervisors about the machines’ physical condition and output when in operation.
Modern sensors give an additional layer of context to the collected data, enabling supervisors and managers to monitor machine performance. For example, they can determine the machine’s typical baseline performance by examining data over a prolonged period of time.
Deviations from this baseline alert personnel to reduced machine performance, prompting further investigation. Robust, real-time analysis allows managers to initiate preventive maintenance, reducing costly unplanned downtime significantly.
As a result, most sensors found in a production environment are internet-enabled and connect to analytic tools, providing manufacturers with more comprehensive, actionable insights.
And because industrial machines have various operational characteristics, businesses install different types of manufacturing sensors throughout the factory. Doing so enables more visibility into shop floor operations and facilitates further improvements.
Connect machines to Tulip and easily track Overall Equipment Effectiveness
Monitor machines, track status, and visualize performance across your facilities in real-time.
Types of manufacturing sensors
Machines on the factory floor have various physical properties when in operation. As such, manufacturers deploy different manufacturing sensors, enabling them to collect comprehensive data from the equipment.
Here are the common types of manufacturing sensors used:
Tri-axial accelerometers: Manufacturing equipment comprises several moving parts vital for proper function. Tri-axial accelerometers monitor vibrations across these various moving parts.
In addition, these manufacturing sensors keep track of velocity, acceleration, and displacement, providing a clear view into the machine’s operating condition. Fluctuations and deviations from the norm alert supervisors to potential breakdowns, allowing them to service the machine more quickly.
Temperature sensors: Factory machines generate significant heat when the various rotating parts are in operation. These machines operate at an optimum temperature and within set boundaries when working normally.
Temperature sensors identify damaged sections by tracking overheating or fluctuations from the baseline. This enables operators and supervisors to intervene, implementing maintenance protocols to prevent unplanned downtime.
Pressure sensors: Some machines use fluids like oil or water when running. In addition, some equipment utilize gases like nitrogen to function. Manufacturers deploy pressure sensors to track fluid and gas levels, ensuring that the machine is able to function properly.
Additionally, some businesses are producers of various chemical or liquid products. Such manufacturers use pressure sensors to keep track of product flow through their systems.
Torque sensors: Rotating machinery or components exert powerful turning forces. Operators and supervisors use torque sensors to monitor these forces, allowing them to keep track of equipment performance and health.
Unexpected fluctuations in torque sensor readings might point to component wear and tear. This allows maintenance crews to service the machine, preventing costly downtime.
Micro-electromechanical system (MEMS) sensors: MEMS are high-precision sensors that monitor movements within a manufacturing machine. These compact sensors can be fitted to various machinery because of their tolerance to intense temperatures.
Furthermore, manufacturers use MEMS sensors because of their robust resistance to the high-vibration and shock-rich manufacturing environment.
Connecting manufacturing sensors to an operations platform
As mentioned earlier, modern manufacturing sensors are capable of extracting significant quantities of data from machinery on a continuous, ongoing basis.
Analyzing this data provides insights and potential considerations that might impact other areas of the manufacturing operation. Therefore, it’s imperative to link manufacturing sensors to an operations platform for a more comprehensive, actionable view of the production data.
Connecting sensors to manufacturing systems gives businesses end-to-end visibility into their operations, enabling supervisors to more easily identify areas of inefficiency and identify opportunities for improvement.
Using Tulip’s Edge IO, manufacturers are able to connect analog sensors to Tulip’s Frontline Operations Platform to collect data and gain new insights into machine performance.
In the following video, we provide an in-depth overview of what this would look like in practice:
If you’re interested in learning how Tulip can help you improve the way you monitor machine performance, reach out to a member of our team today!
Connect and monitor machine performance with Tulip
Learn how you can automate data collection to track machine performance and overall equipment effectiveness.