IO-Link Changeover: ID Without RFID – Hub ID

When looking at flexible manufacturing, what first comes to mind are the challenges of handling product changeovers. It is more and more common for manufacturers to produce multiple products on the same production line, as well as to perform multiple operations in the same space.

Accomplishing this and making these machines more flexible requires changing machine parts to allow for different stages in the production cycle. These interchangeable parts are all throughout a plant: die changes, tooling changes, fixture changes, end-of-arm tooling, and more.

When swapping out these interchangeable parts it is crucial you can identify what tooling is in place and ensure that it is correct.

ID without RFID

When it comes to identifying assets in manufacturing today, typically the first option companies consider is Radio-Frequency Identification (RFID). Understandably so, as this is a great solution, especially when tooling does not need an electrical connection. It also allows additional information beyond just identification to be read and written on the tag on the asset.

It is more and more common in changeover applications for tooling, fixtures, dies, or end-of-arm tooling to require some sort of electrical connection for power, communication, I/O, etc. If this is the case, using RFID may be redundant, depending on the overall application. Let’s consider identifying these changeable parts without incurring additional costs such as RFID or barcode readers.

Hub ID with IO-Link

In changeover applications that use IO-Link, the most common devices used on the physical tooling are IO-Link hubs. IO-Link system architectures are very customizable, allowing great flexibility to different varieties of tooling when changeover is needed. Using a single IO-Link port on an IO-Link master block, a standard prox cable, and hub(s), there is the capability of up to: 

    • 30 Digital Inputs/Outputs or
    • 14 Digital Inputs/Outputs and Valve Manifold Control or
    • 8 Digital Inputs/Outputs and 4 Analog Voltage/Current Signals or
    • 8 Analog Input Signals (Voltage/Current, Pt Sensor, and Thermocouple)

When using a setup like this, an IO-Link 1.1 hub (or any IO-Link 1.1 device) can store unique identification data. This is done via the Serial Number Parameter and/or Application Specific Tag Parameter. They act as a 16- or 32-byte memory location for customizable alphanumeric information. This allows for tooling to have any name stored within that memory location. For example, Fixture 44, Die 12, Tool 78, EOAT 123, etc. Once there is a connection, the controller can request the identification data from the tool to ensure it is using the correct tool for the upcoming process.

By using IO-Link, there are a plethora of options for changeover tooling design, regardless of various I/O requirements. Also, you can identify your tooling without adding RFID or any other redundant hardware. Even so, in the growing world of Industry 4.0 and the Industrial Internet of Things, is this enough information to be getting from your tooling?

In addition to the diagnostics and parameter setting benefits of IO-Link, there are now hub options with condition monitoring capabilities. These allow for even more information from your tooling and fixtures like:

    • Vibration detection
    • Internal temperature monitoring
    • Voltage and current monitoring
    • Operating hours counter

Flexible manufacturing is no doubt a challenge and there are many more things to consider for die, tooling and fixture changes, and end-of-arm tooling outside of just ID. Thankfully, there are many solutions within the IO-Link toolbox.

For your next changeover, I recommend checking out Non-Contact Inductive Couplers Provide Wiring Advantages, Added Flexibility and Cost Savings Over Industrial Multi-Pin Connectors for a great solution for non-contact connectivity that can work directly with Hub ID.

Condition Monitoring & Predictive Maintenance: Machine Failure Indicators & Detection Methods

In our previous blogs, we discussed the basics of the P-F (Potential – Functional Failure) curve and the cost-benefit tradeoffs of various maintenance approaches. We’ll now describe the measures that can be taken to discover failure indicators along the P-F curve.The basic concept of the P-F curve is that as a machine or asset deteriorates, various symptoms/indicators emerge. The early-stage indicators may be harder to detect and may require more sophisticated and expensive systems to analyze, but they give you more time to take action to prevent a catastrophic failure. They allow users to choose times to service a machine when it’s less disruptive to the manufacturing process and when only minor maintenance actions, such as changing lubricant, replacing a filter or balancing a fan, are needed rather than major parts repair/replacement. The later-stage indicators may be more obvious and simpler to notice, but they may require extensive and expensive maintenance since greater deterioration has taken place.

Some monitoring methods can be done on a continual basis by using a permanently mounted sensor that takes samples at intervals of once an hour or more often. Others can only be done on a one-time or periodic basis, as when a sensor is brought in for special analysis, perhaps once a month or less often.

Common indicators and detection methods

This version of the P-F curve lists several common indicators and detection methods, in rough order of when they might start to reveal deterioration in an asset:

    • Ultrasonic Spike Energy. Ultrasonic condition monitoring sensors are often expensive and used in portable systems to take one-time readings, but they can provide very early potential failure detection.
    • Vibration Analysis. Sensors and evaluation tools can range from very simple and low cost to sophisticated and expensive. The vibration analysis is done on either a one-time, periodic, or continual basis and often gives an early insight into emerging problems.
    • Oil Analysis. An oil analysis may signal the need for additional, relatively simple maintenance actions, such as lubricating bearings, changing lubricant, or scheduling maintenance. This can usually be done on a one-time basis, but perhaps periodically, such as monthly or annually.
    • Temperature Analysis. This analysis can indicate emerging “hot spots” on a machine, such as bad bearings or excessive friction that signal a future failure. Depending on the measurement system and asset, it can be an early or a late indicator of impending failure.
    • Pressure & Flow. These indicators can fall into either the predictive or the fault domain, depending on implementation. If a proactive approach is taken, they might be condition indicators that can provide an early indication of potential failure; if a reactive approach is taken, they might be indicators of a functional failure (failure already occurring).
    • Audible Noise. Noise is often an indicator of deterioration moving into the fault domain, and requiring more immediate action than vibration, temperature, or ultrasonic indicators.
    • Hot to Touch. Generally, once bearings, motors, or shafts become hot to the touch, failure is imminent and quick action is needed to avoid catastrophic failure.
    • Mechanically Loose. This indicator may fall into preventative maintenance (maintenance performed at time-based intervals rather than based on need) and may not catch impending failures until it is too late. Parts, which are obviously loose, can indicate a deeper problem, often close to failure.
    • Ancillary Damage. This detects when other parts of the machine/assets are being damaged prior to a catastrophic failure (for example, a damaged belt due to belt misalignment caused by a failing bearing). Generally, when this is found, it is too late to prevent the failure of the asset.

This list does not cover all possible indicators. Machine users and builders may have others depending on their unique application – other potential methods to detect asset deterioration include monitoring of current, corrosion, or leaks.

The “best” indicator and approach will depend on each user’s and each asset’s unique risk/cost/benefit profile. Machine builders and users should work closely with an experienced condition monitoring solution provider who provides multiple solutions to help consider and assess the tradeoffs associated with various approaches.