IO-Link vs. Analog in Measurement Applications

IO-Link is well-suited for use in measurement applications that have traditionally used analog (0…10V or 4…20mA) signals. This is thanks in large part to the implementation of IO-Link v1.1, which provides faster data transmission and increased bandwidth compared to v1.0. Here are three areas where IO-Link v1.1 excels in comparison to analog.

1

Fewer data errors, at lower cost

By nature, analog signals are susceptible to interference caused by other electronics in and around the equipment, including motors, pumps, relays, and drives. Because of this, it’s almost always necessary to use high-quality, shielded cables to transmit the signals back to the controller. Shielded cables are expensive and can be difficult to work with. And even with them in place, signal interference is a common issue that is difficult to troubleshoot and resolve.

2

With IO-Link, measurements are converted into digital values at the sensor, before transmission. Compared to analog signals, these digital signals are far less susceptible to interference, even when using unshielded 4-wire cables which cost about half as much as equivalent shielded cables. The sensor and network master block (Ethernet/IP, for example) can be up to 20 meters apart. Using industry-standard connectors, the possibility for wiring errors is virtually eliminated.

3

Less sensor programming required

An analog position sensor expresses a change in position by changing its analog voltage or current output. However, a change of voltage or current does not directly represent a unit of measurement. Additional programming is required to apply a scaling factor to convert the change in voltage or current to a meaningful engineering unit like millimeters or feet.

It is often necessary to configure analog sensors when they are being installed, changing the default characteristics to suit the application. This is typically performed at the sensor itself and can be fairly cumbersome. When a sensor needs to be replaced, the custom configuration needs to be repeated for the replacement unit, which can prolong expensive machine downtime.

IO-Link sensors can also be custom configured. Like analog sensors, this can be done at the sensor, but configuration and parameterization can also be performed remotely, through the network. After configuration, these custom parameters are stored in the network master block and/or offline. When an IO-Link sensor is replaced, the custom parameter data can be automatically downloaded to the replacement sensor, maximizing machine uptime.

Diagnostic data included

A major limitation of traditional analog signals is that they provide process data (position, distance, pressure, etc.) without much detail about the device, the revision, the manufacturer, or fault codes. In fact, a reading of 0 volts in a 0-10VDC interface could mean zero position, or it could mean that the sensor has ceased to function. If a sensor has in fact failed, finding the source of the problem can be difficult.

With IO-Link, diagnostic information is available that can help resolve issues quickly. As an example, the following diagnostics are available in an IO-Link magnetostrictive linear position sensor: process variable range overrun, measurement range overrun, process variable range underrun, magnet number change, temperature (min and max), and more.

4

This sensor level diagnostic information is automatically transmitted and available to the network, allowing immediate identification of sensor faults without the need for time-consuming troubleshooting to identify the source of the problem.

To learn about the variety of IO-Link measurement sensors available, read the Automation Insights post about ways measurement sensors solve common application challenges. For more information about IO-Link and measurement sensors, visit www.balluff.com.

RFID in the Manufacturing Process: A Must-Have for Continuous Improvement

There is quite an abundance of continuous improvement methodologies implemented in manufacturing processes around the globe. Whether it’s Lean, Six Sigma, Kaizen, etc., there is one thing that all of these methodologies have in common, they all require actionable data in order to make an improvement.  So, the question becomes: How do I get my hands on actionable data?

All data begins its life as raw data, which has to be manipulated to produce actionable data. Fortunately, there are devices that help automate this process. Automatic data collection (ADC), which includes barcode and RFID technology, provides visibility into the process. RFID has evolved to become the more advanced method of data collection because it doesn’t require a centralized database to store the data like barcode technology. RFID stores the data directly on the product or pallet in the process, which allows for much more in-depth data collection.

rfid

RFID’s greatest impact on the process tends to be improving overall quality and efficiency. For example, Company X is creating widgets and there are thirty-five work cells required to make a widget. Between every work cell there is a quality check with a vision system that looks for imperfections created in the prior station. When a quality issue is identified, it is automatically written to the tag.  In the following work cell the RFID tag is read as soon as it enters the station. This is where the raw data becomes actionable data. As soon as a quality issue has been identified, someone or something will need to take action. At this point the data becomes actionable because it has a detailed story to tell. While the error code written to the tag might just be a “10”, the real story is: Between cells five and six the system found a widget was non-conforming. The action that can be taken now is much more focused. The process at cell five can be studied and fixed immediately, opposed to waiting until an entire batch of widgets are manufactured with a quality issue.

Ultimately, flawless execution is what brings success to organizations.  However, in order to execute with efficiency and precision the company must first have access to not only data, but actionable data. Actionable data is derived from the raw data that RFID systems automatically collect.

Learn more about RFID technology at www.balluff.com.