Five Steps to Choosing the Right Manufacturing Sensors

In the United States, 98% of manufacturers employ fewer than 500 employees — more than 70% employ less than 20. These small to mid-size companies typically lag behind larger businesses in their implementation of manufacturing sensors, which gather data from the physical world and convert it into a format that can be read digitally.

Adding sensors is often the first step on a factory’s digital journey, and they don’t require a huge investment. Sensors can cost as little as 60 cents each and can be added to legacy machines. 

Sensors are ubiquitous in everyday life. A sensor detects the interior temperature of your oven when you are cooking, for example, allowing you to heat food at a set temperature.

Thousands of sensors in manufacturing measure such things as proximity, light, pressure, sound, speed, vibration, flow and temperature, which can help companies manufacture better products more efficiently and cost-effectively.

MxD offers five pieces of advice to manufacturers who are just starting their digitization efforts and need help choosing the right sensors.  

1. Research what needs to be monitored.  

The Pareto Principle holds that 80% of problems stem from 20% of the possible causes. You can’t fix a problem if you don’t know what’s causing it.

Every industry is unique. Every manufacturer is unique. Every problem is unique. The critical first step is to investigate what’s going on so you know where you need to make changes. 

Start by mapping, or charting, every step of the production process. Drilling down will let you pinpoint where failures are occurring in the order of operations and help you better understand what data you need to collect. That will tell you where you may need to add sensors.

2.  Figure out what you should be measuring.

Once you have pinpointed the problem, you need to determine what to measure to obtain the right data. Is it temperature? Vibration? Number of parts passing through a particular piece of equipment?

“Take the time to study the problem and figure out what you’re trying to measure,” says Tony Del Sesto, Digital Manufacturing Technical Fellow at MxD. “What you learn will point you in the right direction for the type of sensor you should be using.”

Let’s say a food company is trying to figure out why large amounts of a product have to be discarded for being substandard. The manufacturer might suspect that the amount of liquid ingredients stored in one of its tanks varies unacceptably. And if process mapping reveals an issue in the containment tanks, the problem that needs measuring could be the liquid levels in those tanks.

3. Choose a sensor from the right category.

Once you know what you want to measure, you will be pointed in the direction of a sensor category. 

In the food company example above, the manufacturer could decide on a level sensor to test the idea that liquid amounts are inconsistent during a particular stage of the production process. A level sensor can detect how much liquid there is, much like a sensor in your car communicates via a dashboard gauge how much gas is in the tank.

Or if you need to know how many parts pass through a particular production station in the manufacturing process, you would consider a sensor that counts each of the pieces.

If batches of beer at a brewery don’t meet standards and process mapping indicates that temperature could be an issue, you might consider a sensor that can measure brewing temperatures over time.

4. Use sensor data for analysis.

Sensor data can be used to continuously improve the production process. Companies planning to remain in business must commit to continuous improvement, Del Sesto says. Continuous improvement requires collecting and analyzing data, learning from it, and then implementing changes that improve the process. 

For example, data from sensors can help create a history of how different parts of the production process are working so you can make the necessary adjustments to prevent problems in the future. 

Sensors can alert you to incorrect settings, defective equipment parts, or machines that are about to fail, which is known as predictive failure or predictive maintenance.

5. Use sensors to build every part better than the last.

What are you going to do with all of that data you collect? How are you going to communicate it? How are you going to store it?

Those are important questions to consider, even before you install sensors. Sensors on their own will take you only so far; you also must select systems to communicate, analyze, and store the data.

MxD’s vision is for production lines to be embedded with software that communicates with sensors and connects to the cloud — a Future Factory, if you will. 

Only with this ability to send and receive data can the equipment learn from every part produced in real time, and then improve itself before the next parts are made.

MxD helps U.S. manufacturers adopt the digital tools and expertise they need to begin building every part better than the last. Learn more about becoming an MxD partner.