IO-Link Safety: What It Is and Isn’t

Comparing “IO-Link” and “Safety” to “IO-Link Safety”

There are many I/O blocks that have “IO-Link” and “Safety” in their descriptions, which can cause some confusion about which safety features they include. Here’s an overview of different safety-named blocks and how they compare to IO-Link Safety.

Safety Network Blocks

These blocks have I/O ports that use Pin 4 and Pin 2 as OSSD signals (safety ports). OSSD—output switching signal devices—send 24-volt signals over two wires to confirm that a device is operating in a safe condition. If 0 volts are detected in either signal, besides their safety-checking 0-volt pulses, it’s read as a safety event that signals the machine to go into a safe state. Safety network blocks are only for standard (non-network) safety devices. These blocks communicate directly back to a Safety Controller over safety protocols like CIP Safety, PROFIsafe, etc. These blocks typically can monitor between 8-16 standard safety devices. There is no intelligence built into the safety devices.

Safety Network Blocks with IO-Link

Blocks in this category usually have a mixture of I/O ports on them. The ports can range from standard I/O to standard IO-Link communication, and in addition, include ports that use Pin 4 and Pin 2 as OSSD signals (safety ports). These blocks communicate over the safety protocols with only a few ports to connect standard (non-network) safety devices. There is some versatility with these blocks since you can wire standard sensors, IO-Link devices, and safety devices to it. The drawback is, you will always run short of the port style you need and, in the end, use more blocks to cover either the safety or IO-Link needs of the application. There is no intelligence built into the safety devices.

Safety over IO-Link Blocks

In this system/architecture, there are standard IO-Link Masters communicating to the Safety PLCs/Controllers over standard protocols like EtherNet/IP, PROFINET, etc. Connected to the IO-Link Ports of these Masters are Safety over IO-Link devices, currently limited to only Safety over IO-Link hubs. The Safety PLCs/Controllers communicate via safety protocols like PROFIsafe to the standard IO-Link Master, and then using the IO-Link communication channel, they bridge the gap to the Safety over the IO-Link hub via the “black channel.” These Safety over IO-Link hub’s ports use Pin 4 and Pin 2 as OSSD signals (safety ports), so standard (non-network) safety devices can be connected. This system provided a “gap filler” while IO-Link Safety was being developed. In this system/architecture, the standard IO-Link Masters allowed standard IO-Link devices and Safety over IO-Link hubs to be connected to any ports. This brought even more versatility to an application and the beginnings of the benefits of IO-Link. Still, there is no intelligence built into the safety devices.

IO-Link Safety

IO-Link Safety adds a safety communication layer to IO-Link. The difference between this and Safety over IO-Link is that this safety layer applies to both the IO-Link Master and IO-Link Safety devices. Within a CIP Safety or PROFIsafe network, the safety communication protocol has top priority over standard EtherNet/IP or PRIFONET data if both are existing on the same physical network. The same is true for IO-Link Safety: both standard and safety IO-Link protocols can exist on the same physical cable between the IO-Link Master ports and IO-Link Safety devices, with IO-Link Safety carrying the top priority. For a deep dive into the IO-Link Safety protocol, I suggest visiting the IO-Link Consortium’s website at io-link.com. In this system/architecture, you have IO-Link Safety Masters, which communicate to the Safety PLCs/Controllers over safety protocols like CIP Safety, PROFIsafe, etc. The ports on the Masters can utilize Pin 4 and Pin 2 as OSSD signals (safety ports), so standard (non-network) safety devices can be connected. Pin 4 can also be used to carry standard IO-Link and IO-Link Safety communication to standard IO-Link devices and IO-Link Safety devices, respectively. This allows for the most versatile safety solution in the market–IO-Link Safety Masters that can accept standard (non-network) safety devices, standard IO-Link devices, and IO-Link Safety devices. Intelligence in the IO-Link Safety devices is now available.

Benefits of IO-Link Safety

    • IO-Link Safety devices are fieldbus neutral: you just need to specify the IO-Link Safety Master to match the Safety PLCs/Controllers protocol.
    • IO-Link Safety Master port versatility: standard (non-network) safety devices, standard IO-Link devices, and IO-Link Safety devices can be connected.
    • Parameter storage: standard IO-Link and IO-Link Safety device’s parameters can be stored for ease of device replacement.
    • Smart IO-Link Safety device data: more data available, like internal temperature, humidity, number of cycles, power consumption, diagnostics, etc.
    • Simplified wiring: IO-Link Safety devices are still connected to the IO-Link Master port with a standard 3 to 4 conductor cable.
    • IIoT fit: IO-Link Safety gives more visibility to upper-level systems like SCADA, allowing safety device-level monitoring.

I am looking forward to seeing how quickly IO-Link Safety will be accepted, with how IO-Link numbers have skyrocketed over the last few years. The future looks great for IO-Link with IO-Link Safety, IO-Link Wireless and in the future, Single-Pair Ethernet (SPE). With all these new capabilities, what application can’t IO-Link support?

Maximize the Benefits of Open-Source Code in Manufacturing Software

The rise of many players in manufacturing automation, along with factories’ growing adoption of Industrial Internet of Things (IIoT) and automation solutions, present a suitable environment for open-source software. This software is a value-adding solution for manufacturers, regardless of their operation technology and management requirements, due to the customization, resiliency, scalability, accessibility, cost-effectiveness, and quality it allows.

Customization

Software developers who use open-source code provide software with a core code that establishes specific features and allows users to access it and make changes as necessary. The process is much like being able to complete an author’s writing prompt or change the end of a story. Unlike a closed system that locks users in, open-source allows them to adapt and modify the code to meet a particular need or application.

This add-on coding system provides endless customization. It enables communities (i.e., users) to add or remove features beneficial in an integration phase, such as features for user testing or to find the best solution for a machine.

Customization is also valuable regarding data visualizations; users can develop dashboards and visuals that best describe their operations. Suppose a sensor provides real-time condition monitoring data over a particular machine. In that case, it’s possible to customize the code supporting the software that gathers and processes the data for specific parameters or to calculate specific values.

Resiliency

Additionally, open-source code is resilient to change because it can be modified quickly. The ability to quickly add or remove features and adapt to cyber environments or specific applications also makes it volatile. Like exposure to pathogens can help strengthen an immune response to said pathogens, so can an open-source code be made stronger by its exposure to different environments and applications to be ready to face cybersecurity threats. Implementing an open code isn’t any less risky (cybersecurity-wise) than closed codes due to the testing and enhancements made by so many coders or programmers. However, it is up to the implementer to use the same rules that apply to other closed source software. The implementer must be aware of the code’s source and avoid code from non-reputable sources who could have modified it with negative intentions. Overall, the code is resilient, adaptable, and agile to adapt given a new environment.

Scalability

The add-on and customization aspects of open-source also allow the code to be highly scalable. This scalable implementation happens in two dimensions: adoption timeline and application-based. Both are important to guarantee user acceptance and that it meets the operation and application requirements. Regarding the adoption timeline, scalability allows modification of the software and code to meet users’ expectations. Open-sourced code enables the implementation of features for user testing and feedback. The ultimate solution will include multiple iterations to meet the users’ needs and fulfill operation expectations.

On the other hand, this code is scalable based on the application(s), such as working on different machines, multiples of the same machine with different purposes, or adding/dropping features for specific uses. Say, for example, there are three of the same machine (A, B, and C), but they are in different environments. Machine A is in an environment that is 28°F , B is at room temperature, and C is exposed to constant wash-down. In this case, the condition monitoring software defines the acceptable parameters for each scenario, avoiding false alarms from erroneous triggers. In this example, the base code is adapted to include specific features based on the application.

Accessibility

In general, cost-effective and high-quality open-source code is available online. There are additional resources such as free coding tutorials that don’t require any licenses as well. Moreover, when programmers update an open code, they must make the new version available again, ensuring that the code is accessible and up to date.

Cost-effectiveness and quality

Regarding cost-effectiveness, using community open-source code significantly reduces the cost of developing, integrating, and testing software built in-house. It also reduces the implementation time and makes for better production operations. Essentially, it is high-quality, reliable code created by trusted sources for multiple coders and users.

“The application drives the technology” mantra is at the heart of open-source software development—a model where source code is available for community members to use, modify, and share. IIoT enablers and providers in the manufacturing industry own a particular solution that is then available for manufacturers to adapt to their specific operational requirements. With the increasing adoption of data-collecting technologies, it is in manufacturers’ best interest to seek software providers who grant them the flexibility to adjust software solutions to meet their specific needs. Automation is a catalyst for data-driven operation and maintenance.

Start Condition Monitoring With Vibration Sensors

IIOT (Industrial internet of things) has gained much traction and attraction in past years. With industries getting their assets online for monitoring purposes and new IO-Link sensors providing a ton of information on a single package, monitoring machines has become economically feasible.

Vibration is one of the most critical metrics regarding the health of machines, providing early detection of potential faults – before they cause damage or equipment failure. But since this is a relatively new field and use case, there is not much information about it. Most customers are confused about where to start. They want a baseline to begin monitoring machines and then finetune them to their use case.

“Vibration is one of the most critical metrics regarding the health of machines…”

One approach to solve this is to hire a vibration expert to determine the baseline and the best location to mount the vibration measuring sensor. Proper setup increases the threshold of getting into condition monitoring as a new user figures out the feasibility of such systems.

I direct my customers to this standardized baseline chart from ISO, so they can determine their own baselines and the best mounting positions for their sensors. The table shows the different standards for severity for different machine classes. These standards detail the baseline vibration and show the best place to mount the sensor based on the machine type.

Click here for more information on the benefits of condition monitoring.

 

Manufacturing Insights: Top Blogs From 2021

While last year was filled with challenges and unexpected changes for many industries, including manufacturing, it was not without positive achievements and insights. As we look forward to 2022, let’s not forget some topics that shaped 2021, including our five most-read blogs.

1. 5 Manufacturing Trends to Consider as You Plan for 2022

 

 

 

 

It’s that time of year again where we all start to forget the current year (maybe that’s OK) and start thinking of plans for the next – strategy and budget season! 2022 is only a few weeks away! I thought I’d share 5 insights I’ve had about 2022 that you might benefit from as you start planning for next year.

READ MORE>>

2. The Pros and Cons of Flush, Non-Flush and Semi-Flush Mounting


Inductive proximity sensors have been around for decades and have proven to be a groundbreaking invention for the world of automation. This type of technology detects the presence or absence of ferrous objects using electromagnetic fields. Manufacturers typically select which inductive sensor to use in their application based on their form factor and switching distance. Although, another important factor to consider is how the sensor will be mounted.

READ MORE>>

3. IO-Link Wireless – IO-Link with Even Greater Flexibility



In a previous blog entry, I discussed IO-Link SPE (Single-Pair Ethernet). SPE, in my opinion, has two great strengths compared to standard IO-Link: cable length and speed. With cable lengths of up to 100 meters and speed of 10 Mbps, compared to 20 meters and max baud rate of 230.4 Kbps, what could be out of reach?

READ MORE>>

4. How Condition Monitoring has Evolved and Its Role in IIoT

In recent years, as IIoT and Industry 4.0 have become part of our everyday vocabulary, we’ve also started hearing more about condition monitoring, predictive maintenance (PdM) and predictive analytics. Sometimes, we use these terms interchangeably as well. Strictly speaking, condition monitoring is a root that enables both predictive maintenance and predictive analytics. In today’s blog we will brush up a little on condition monitoring and explore its lineage.

READ MORE>>

5. Lithium Ion Battery Manufacturing – RFID is on a Roll



With more and more consumers setting their sights on ‘Drive Electric,’ manufacturers must prepare themselves for alternative solutions to combustion engines. This change will no doubt require an alternative automation strategy for our electric futures.

READ MORE>>

Honorable Mention: Top 5 Insights From 2020

And, finally, for the sake of comparison, we can’t help but honorably mention last year’s look-back blog. The top five insights from 2020 include buying a machine vision system; data provided by IO-Link; changes in electrostatic sensing field by capacitive sensors; reducing the number of ethernet nodes on your network using IO-Link; and adding a higher level of visibility to older automation machines.

Read more>>

We appreciate your dedication to Automation Insights in 2021 and look forward to growth and innovation in 2022!

3 Easy Options to Get Started With IIoT in 2022

The Industrial Internet of Things (IIoT) may seem large, intimidating, and challenging to implement; however, new systems and solutions will eliminate the perceived barriers for entry. As we wrap up the year and make plans for 2022, now is a great time to resolve to modernize your facility.

Do you have a process, system or machine that has outlived its life expectancy for many years or even decades and isn’t up to current IIoT standards? Great news: you have several options for updating.

Traditional approach

The traditional approach allows you to use your current controller to output your information to your existing database. If you want to try IIoT on your current setup and your controller cannot be modified, a self-contained system will allow for ultimate flexibility. It will provide you with access to the data based off an extra layer of sensing with a focus on condition monitoring. This approach is the least expensive route, however, if database access is restricted the following options may be better choices.

Cloud-based current industry standard

A second option is to use a portable monitoring system that has a condition monitoring sensor. It is essentially five sensors in one package that can hook up to a system using the cellular network to report data to a secure cloud database. This approach is useful in remote locations or where local network access is limited. If you have a problem area, you can apply this temporarily to collect enough data, enabling you to implement predictive maintenance.

Local-based current industry standard

A local self-contained system is a great solution if a cloud database is not desired or allowed. Systems such as a Condition Monitoring Toolkit allow for recording of devices onto the local memory or USB drive. Additionally, multiple alarm set points can be emailed or extracted locally. This approach is best for testing existing machines to help with predictive maintenance, to improve a process, or even to prevent a failure.

All three of these options require data management and analysis to improve your processor and to remedy problematic areas. Using any of them is an opportunity to test the IIoT waters before fully diving in. Extrapolating the results into problem-solving solutions can allow you to expand IIoT to the rest of your facilities in a cost-effective manner.

Getting Condition Data From The Shop Floor to Your Software

IIoT (Industrial Internet of Things)  is becoming more mainstream, leading to more vendors implementing innovative monitoring capabilities in the new generation of sensors. These sensors are now multifunctional and provide a host of additional features such as self-monitoring.

With these intelligent sensors, it is possible to set up a system that enables continuous monitoring of the machines and production line. However, the essential requirement to use the provided data for analysis and condition monitoring for preventative and predictive maintenance is to get it from the shop floor to the MES, ERP, or other analysis software suites.

There are a variety of ways this can be done. In this post we will look at a few popular ways and methods to do so.

The most popular and straightforward implementation is using a REST API(also known as RESTful API). This has been the de facto standard in e consumer space to transport data. It allows multiple data formats to be transferred, including multimedia and JSON (Javascript Object Notation)

This has certain disadvantages like actively polling for the data, making it unsuitable for a spotty network, and having high packet loss.

MQTT(Message Queuing Telemetry Transport) eliminates the above problem. It’s very low bandwidth and works excellent on unreliable networks as it works on a publish/subscribe model. This allows the receiver to passively listen for the data from the broker. The broker only notifies when there is a change and can be configured to have a Quality of Service(QoS) to resend data if one of them loses connection. This has been used in the IoT world for a long time has become a standard for data transport, so most of software suits have this feature inbuilt.

The third option is to use OPCUA, which is the standard for M2M communication. OPCUA provides additional functionality over MQTT as it was developed with machine communication in mind. Notably, inbuilt encryption allows for secure and authenticated communication.

In summary, below is a comparison of these protocols.

A more detailed explanation can be found for these standards :

REST API : https://www.redhat.com/en/topics/api/what-is-a-rest-api

MQTT : https://mqtt.org/

OPCUA : https://opcfoundation.org/about/opc-technologies/opc-ua/

RFID Gaining Traction in Tire Manufacturing

RFID is one of the hottest trending technologies in the tire industry. It has the potential to increase efficiency in tire production and logistics processes and gather large amounts of data for IIoT.

This technology will:

  • Reveal transparency deep in the processes
  • Minimize the number of rejected tires
  • Improve production processes for fewer failures
  • Increase control of materials
  • Improve the overall quality of individual tires

The challenge of using RFID in the tire industry is dealing with the harsh environments of some of the production areas in automotive plants. But the benefits of RFID to the tire industry are becoming more and more a reality. Suppliers of RFID are talking to tire manufacturing engineers, automation teams, material handling teams and R&D development engineers to develop better tools. For now, here are some examples of where RFID can be implemented in the tire creation process to improve efficiency, quality and cost.

In the mixing process, RFID “labels” are applied to all the chemicals and rubber compounds to assure the mixing of the right recipe of materials. RFID readers can be mounted on TBMs (Tire Build Machines), which are located before the curing press process, to assure the right material reels, parts and tools are in place before the expensive tire build process occurs.

There is also a growing need for RFID in the curing and mold processes. It important to manage the molds and the parts of the mold, like the bead rings, mold containers and mold segments. These are very expensive and there are hundreds in the average plant. Tags need to be able to sustain temperatures above 300 °F continuously for 8 hour shifts with little to no cooling down time.

RFID is an excellent tool to monitor material flow throughout the whole manufacturing process. RFID can be added to a trolly, AGV, conveyors and hook-chain conveyors.

While RFID is already being implemented by some tire manufacturers, there is much room for much growth in this conservative industry. As more manufacturers lean into IIoT and the need for data, RFID will surely be used more and more often.

The tire industry is excited to roll in RFID technology and pumped up to implement it where it makes the most sense and ROI dollars.

For more information about the tire industry, visit https://www.balluff.com/local/us/industries-and-solutions/industry/mobility/tire-industry/

How Condition Monitoring has Evolved and Its Role in IIoT

In recent years, as IIoT and Industry 4.0 have become part of our everyday vocabulary, we’ve also started hearing more about condition monitoring, predictive maintenance (PdM) and predictive analytics. Sometimes, we use these terms interchangeably as well. Strictly speaking, condition monitoring is a root that enables both predictive maintenance and predictive analytics. In today’s blog we will brush up a little on condition monitoring and explore its lineage.

Equipment failures have been around since the beginning of time. Over the years, through observation (collecting data) and brute-force methods, we learned that from time-to-time every piece of equipment needs some TLC. Out of this understanding, maintenance departments came to existence, and there we started having experts that could tell based on touch, smell and noise what is failing or what has gone wrong.

Figure 1: Automation Pyramid

Then we started automating the maintenance function either as a preventative measure (scheduled maintenance) or through some automated pieces of equipment that would collect data and provide alerts about a failure. We proudly call these SCADA systems – Supervisory Control and Data Acquisition. Of course, these systems did not necessarily prevent failures, but help curtail them.  If we look at the automation pyramid, the smart system at the bottom is a PLC and all the sensors are what we call “dumb sensors”. So, that means, whatever information the SCADA system gets would be filtered by the PLC. PLCs were/have been/ and are always focused on the process at hand; they are not data acquisition equipment. So, the data we receive in the SCADA system is only as good as the PLC can provide. That means the information is primarily about processes. So, the only alerts maintenance receives is when the equipment fails, and the process comes to a halt.

With the maintenance experts who could sense impending failures becoming mythological heroes, and  SCADA systems that cannot really tell us the story about the health of the machines, once again, we are looking at condition monitoring with a fresh set of eyes.

Sensors are at the grass root level in the automation pyramid, and until the arrival of IO-Link technology, these sensors were solely focused on their purpose of existence; object detection, or measurement of some kind. The only information one could gather from these sensors was ON/OFF or a signal of 4-20mA, 0-10V, and so on. Now, things are different, these sensors are now becoming pretty intelligent and they, like nosy neighbors, can collect more information about their own health and the environment. These intelligent sensors can utilize IO-Link as a communication to transfer all this information via a gateway module (generally known as IO-Link master) to whomever wants to listen.

Figure 2: IO-Link enabled Balluff photo-eye

The new generation of SCADA systems can now collect information not only from PLCs about the process health, but also from individual devices. For example, a photo-eye can measure the intensity of the reflected light and provide an alert if the intensity drops beyond a certain level, indicating a symptom of pending failure. Or a power supply inside the cabinet providing an alert to the supervisory control about adverse conditions due to increase temperature or humidity in the cabinet. These types of alerts about the symptoms help maintenance prevent unplanned downtime on the plant floor and make factories run more efficiently with reduced scrap, reduced down-time and reduced headaches.

Figure 3: The Next Generation Condition Monitoring

There are many different condition monitoring architectures that can be employed, and we will cover that in my next blog.

Improve OEE, Save Costs with Condition Monitoring Data

When it comes to IIOT (Industrial Internet of Things) and the fourth industrial revolution, data has become exponentially more important to the way we automate machines and processes within a production plant. There are many different types of data, with the most common being process data. Depending on the device or sensor, process data may be as simple as the status of discrete inputs or outputs but can be as complex as the data coming from radio frequency identification (RFID) data carriers (tags). Nevertheless, process data has been there since the beginning of the third industrial revolution and the beginning of the use of programmable logic controllers for machine or process control.

With new advances in technology, sensors used for machine control are becoming smarter, smaller, more capable, and more affordable. This enables manufacturers of those devices to include additional data essential for IIOT and Industry 4.0 applications. The latest type of data manufacturers are outputting from their devices is known as condition monitoring data.

Today, smart devices can replace an entire system by having all of the hardware necessary to collect and process data, thus outputting relative information directly to the PLC or machine controller needed to monitor the condition of assets without the use of specialized hardware and software, and eliminating the need for costly service contracts and being tied to one specific vendor.

A photo-electric laser distance sensor with condition monitoring has the capability to provide more than distance measurements, including vibration detection. Vibration can be associated with loose mechanical mounting of the sensor or possible mechanical issues with the machine that the sensor is mounted. That same laser distance sensor can also provide you with inclination angle measurement to help with the installation of the sensor or help detect when there’s a problem, such as when someone or something bumps the sensor out of alignment. What about ambient data, such as humidity? This could help detect or monitor for moisture ingress. Ambient pressure? It can be used to monitor the performance of fans or the condition of the filter elements on electrical enclosures.

Having access to condition monitoring data can help OEMs improve sensing capabilities of their machines, differentiating themselves from their competition. It can also help end users by providing them with real time monitoring of their assets; improving overall equipment efficiency and better predicting  and, thereby, eliminating unscheduled and costly machine downtime. These are just a few examples of the possibilities, and as market needs change, manufacturers of these devices can adapt to the market needs with new and improved functions, all thanks to smart device architecture.

Integrating smart devices to your control architecture

The most robust, cost effective, and reliable way of collecting this data is via the IO-Link communication protocol; the first internationally accepted open, vendor neutral, industrial bi-directional communications protocol that complies with IEC61131-9 standards. From there, this information can be directly passed to your machine controller, such as PLC, via fieldbus communication protocols, such as EtherNET/Ip, ProfiNET or EtherCAT, and to your SCADA / GUI applications via OPC/UA or JSON. There are also instances where wireless communications are used for special applications where devices are placed in hard to reach places using Bluetooth or WLAN.

In the fast paced ever changing world of industrial automation, condition monitoring data collection is increasingly more important. This data can be used in predictive maintenance measures to prevent costly and unscheduled downtime by monitoring vibration, inclination, and ambient data to help you stay ahead of the game.

Injection Molding: Ignore the Mold, Pay the Price

Are you using a contract molding company to make your parts? Or are you doing it in house, but with little true oversight and management reporting on your molds? As a manufacturer, you can spend as much on a mold as you might for an economy, luxury or even a high-performance car. The disappointing difference is that YOU get to drive the car, while your molder or mold shop gets to drive your mold. How do you know if your mold is being taken care of as a true tooling investment and not being used as though it were disposable, or like the car analogy, like the Dukes of Hazzard used the General Lee?

What steps can you take in regard to using and maintaining a mold in production that can help guarantee your company’s ROI? How can you ensure your mold is going to produce the needed parts and provide or exceed the longevity required?

It is important for any manufacturer to understand the need for the cleaning and repair required for proper tool maintenance. The condition of your injection mold affects the quality of the plastic components produced. To keep a mold in the best working order, maintenance is critical not only when issues arise, but also routinely over time.

In the case of injection molds specifically, there are certain checks and procedures that should be performed regularly. An example being that mold cavities and gating should be routinely inspected for wear or damage. This is as important as keeping the injection system inspected and lubricated, and ensuring all surfaces are cleaned and sprayed with a rust preventative.

Figure 1 An example of the mold usage process.

The unfortunate reality is that some molders wait until part quality problems arise or the tool becomes damaged to do maintenance. One of the biggest challenges with injection molders is being certain that your molds are being run according to the maintenance requirements. Running a mold too long and waiting until problems arise to perform routine maintenance or refurbish a mold can result in added expense, supply/stock issues, longer time to market and even loss of the mold. However, when molders have a clear indication of maintenance and production timing, and follow the maintenance procedures in place, production times and overall costs can decrease.

Figure 2 Balluff add-on Mold ID monitoring and traceability system.

Creating visibility and accuracy into this maintenance timing is something today’s automation technology can now address. With todays modern, industrial automation technology, visibility and traceability can be added to any mold machine, regardless of machine age, manufacturer and manufacturing environment.

With the modern networked IIoT (industrial internet of things)-based monitoring and traceability system solutions available today, the mold can be monitored on the machine in real-time and every shot is recorded and kept on the mold itself using, for example, an assortment of industrial RFID tag options mounted directly on the mold. Mold shot count information can be tracked and kept on the mold and can be reported to operations or management using IIoT-based software running at the molder or even remotely using the internet at your own facility, giving complete visibility and insight into the mold’s status.

Figure 3 Balluff IIoT-based Connected Mold ID reporting and monitoring software screens.

Traceability systems record not only the shot count but can provide warning and alarm shot count statuses locally using visual indicators, such as a stack light, as the mold nears its maintenance time. Even the mold’s identification information and dynamic maintenance date (adjusted continuously based on current shot count) are recorded on the RFID tag for absolute tracability and can be reported in near real-time to the IIoT-based software package.

Advanced automation technology can bring new and needed insights into your mold shop or your molder’s treatment of your molds. It adds a whole new level of reliability and visibility into the molding process. And you can use this technology to improve production up-time and maximize your mold investments.

For more information, visit https://www.balluff.com/en/de/industries-and-solutions/solutions-and-technologies/mold-id/connected-mold-id/