How to choose the perfect Industrial IoT platform for your factory

You're probably no stranger to the increased demands present in day-to-day factory operations, the constant pressure to increase efficiency, the need to reduce downtime, and the want to improve product quality. From the top down and the bottom up, chances are you're getting it from all angles.

It's hard to know where to turn your attention in order to make the biggest impact. But luckily with the rise of what is considered to be 'smart factory' technologies such as Industrial IoT, it's easier than ever to pin-point exactly where you need to spend your time and attention in order to improve the efficiency and profitability of your operations.

Understanding Industrial IoT (IIoT)

What is IIoT, and why does it matter?

If you're already familiar with IIoT, then feel free to skip to the next paragraph. But for those of you who aren't, let's start with the basics. Industrial IoT refers to the network of connected devices, sensors, and software used in industrial settings to collect and analyse data in real-time. Unlike consumer IoT, which connects everyday devices like smart thermostats or fitness trackers, IIoT is all about improving industrial processes, often with significant financial implications.

For instance, did you know that predictive maintenance, a common IIoT application, can reduce maintenance costs by up to 30% and eliminate breakdowns by up to 70%? That’s according to a study by Deloitte. These are the kinds of stats that make IIoT a must-have for modern factories.

Key components of an IIoT platform

Now we are all familiar with the terms. Let's begin to understand what you should be looking for in an IIoT platform, here are some key components:

• Sensors and Devices: The "eyes and ears" of your operation, these collect the data.
• Data Analytics: Where the magic happens. Analytics turn raw data into actionable insights.
• Cloud Computing: Provides the muscle for data storage and complex computations.
• Machine Learning: Allows the system to learn and improve over time, making predictions and optimising processes.

Next, let's get more specific and start assessing your business needs:

What are your pain points?

Before diving into the features and technical specs of IIoT platforms, take a step back and assess your current challenges. Are you struggling with unexpected downtime? Do you need to improve production quality? Maybe your maintenance costs are through the roof.

Identifying your pain points is the first step to finding an IIoT platform that addresses them. This clarity of purpose helps guide the selection process and ensures you get the most out of your investment.

Common pain points we see regularly from our customers include:

• The downtime of their operations is way too high
• They have inefficient resource utilisation
• They are slow to react due to lack of real-time visibility

Setting clear objectives

Once you’ve pinpointed your pain points, the next step is setting clear objectives. What do you want to achieve with an IIoT platform? Are you looking to cut costs, boost productivity, or improve product quality? Maybe all three?

Defining these goals will help you prioritise features when evaluating different platforms. It also gives you a benchmark to measure success after implementation.

Scalability and future-proofing

In the fast-paced world of manufacturing, what works today might not work tomorrow. That’s why it’s crucial to choose an IIoT platform that can grow with your business. Look for a solution that can handle more devices, more data, and more complexity as your operations expand.

According to a Gartner report, nearly 80% of manufacturing leaders consider scalability a top priority when choosing an IIoT platform. After all, the last thing you want is to invest in a system that becomes obsolete in a few years.

Let's consider the key features you might want to look for in an IIoT platform

Integration capabilities

One of the most important factors to consider is how well the IIoT platform integrates with your existing systems. Whether it's your PLCs, SCADA, or MES, the platform should seamlessly connect with what you already have in place.

Why is this important? Because integration issues can lead to data silos, where critical information is stuck in one system and can't be accessed by others. This can result in inefficiencies and missed opportunities for optimisation. Look for platforms that offer robust APIs and support a wide range of industrial protocols.

Data management and analytics

Data is at the heart of IIoT, but it’s not just about collecting data—it’s about making sense of it. A good IIoT platform should offer strong data analytics capabilities, turning raw data into actionable insights.

For example, let’s say you’re collecting temperature data from various points in your production line. Advanced analytics can help you identify patterns that lead to product defects, allowing you to address issues before they become costly problems.

Security

With great data comes great responsibility. Cybersecurity is a significant concern in industrial settings, and your IIoT platform should have robust security measures in place.

This includes encryption of data both in transit and at rest, user authentication, and regular security updates. According to IBM’s "Cost of a Data Breach" report, the average cost of a data breach in the industrial sector is $4.24 million. So, this is definitely an area where you don’t want to cut corners.

User-friendliness

Let’s face it—an IIoT platform is only as good as the people using it. While advanced features are important, the platform should also be user-friendly.

Consider the varying levels of tech-savviness among your team. If the platform is too complicated, it could lead to low adoption rates and, ultimately, a failed implementation. Look for a system with a clean, intuitive interface and plenty of training resources.

Real-time monitoring and alerts

Real-time monitoring is one of the biggest advantages of IIoT. The ability to see what’s happening in your factory as it happens can be a game-changer, especially when combined with instant alerts for critical issues.

For example, if a sensor detects that a machine is overheating, the platform can send an alert to the maintenance team before it leads to a costly breakdown. This proactive approach can save time, money, and headaches.

Support for edge computing

Edge computing processes data closer to where it's generated rather than sending it all to the cloud. This can significantly reduce latency, which is crucial for applications that require real-time responses.

If your operations involve complex processes or need instant feedback loops, look for an IIoT platform that supports edge computing. According to a study by MarketsandMarkets, the edge computing market is expected to grow from $36.5 billion in 2021 to $87.3 billion by 2026, underlining its growing importance in industrial applications.

Customisation and flexibility

Every factory is different, and a one-size-fits-all IIoT platform might not meet all your needs. Look for a platform that allows for customization and flexibility, whether that means tailoring the user interface, adding new modules, or integrating third-party apps.

Customizable dashboards, for example, can help you focus on the metrics that matter most to your operation, making it easier to track performance and spot trends.

Evaluating Vendors and Solutions

Vendor reputation and experience

When it comes to choosing an IIoT platform, the vendor’s reputation and experience should weigh heavily in your decision. Look for vendors with a proven track record in your industry. They should have a deep understanding of the unique challenges you face and offer solutions that have been tried and tested in similar environments.

Don’t be afraid to ask for case studies or customer testimonials. Seeing how other companies have successfully implemented the platform can give you confidence that you’re making the right choice.

Case studies and references

Speaking of case studies, they’re an invaluable resource when evaluating IIoT platforms. A good case study will provide detailed insights into how the platform was implemented, the challenges faced, and the outcomes achieved.

Customer support and SLAs

Even the best IIoT platform is only as good as the support that comes with it. Ensure the vendor offers robust customer support, including 24/7 availability if your operations run around the clock.

Check the Service Level Agreements (SLAs) carefully. They should clearly outline the vendor’s commitments regarding uptime, response times, and issue resolution. Remember, downtime in your IIoT system can directly translate to downtime in your production, so this is critical.

Total cost of ownership (TCO)

Finally, consider the total cost of ownership (TCO). This includes not just the upfront cost of the platform but also ongoing expenses like maintenance, updates, and potential downtime.

While a lower-cost solution might seem attractive initially, it’s essential to consider the long-term costs and potential savings from increased efficiency, reduced downtime, and lower maintenance costs.

Let's look at what you should consider when implementing an IIoT solution:

Pilot programs and testing

Once you’ve chosen a platform, it’s wise to start with a pilot program. This allows you to test the platform in a controlled environment before rolling it out across your entire operation.

Use this time to iron out any kinks and gather feedback from the team. If the pilot is successful, you’ll have a much smoother experience when you scale up.

Take a look at our recent blog on implementing an IIoT pilot programme.

Change management

Implementing a new IIoT platform is not just a technical challenge—it’s a cultural one. Change management is crucial to ensure that your team is on board and ready to make the most of the new system.

Provide training, communicate the benefits clearly, and involve key stakeholders in the process to foster a sense of ownership and commitment.

Timeline and phased rollout

A phased rollout is often the best approach, especially for larger operations. Start with a single line or department, gather data, and learn from the experience. Then, gradually expand the implementation across the factory.

This method reduces risk and allows you to make adjustments as needed, ensuring a smoother transition.

Measuring success

Finally, it’s essential to measure the success of your IIoT platform post-implementation. This is where those clear objectives you set earlier come into play. Use key performance indicators (KPIs) to track the impact of the IIoT platform on your operations. Common KPIs might include machine uptime, production output, defect rates, and maintenance costs. It’s also important to gather feedback from your team on how the platform is affecting their day-to-day work. Are processes running more smoothly? Are there areas where the system could be improved?

Regularly reviewing these metrics will help you gauge the return on investment (ROI) of the IIoT platform and identify any areas where further optimization might be needed. Remember, the implementation of an IIoT platform is not a one-time event but an ongoing process of continuous improvement.

Overcoming common challenges:

Technical hurdles

Integrating an IIoT platform with your existing systems can present technical challenges. Compatibility issues with older equipment or network connectivity problems are common. You can address these hurdles by working closely with an IIoT implementation consultant such as CAD-IT, along with your existing IT team. Also consider consider conducting a thorough infrastructure assessment before implementation.

Cultural resistance

Employees may resist new technology due to concerns about job security or added complexity. Overcome this by clearly communicating the benefits of the IIoT platform, providing adequate training, and involving employees in the process. This builds trust and helps ensure a successful transition.

Data overload

IIoT platforms generate vast amounts of data, which can be overwhelming. To avoid data overload, focus on collecting and analysing the data most relevant to your business objectives. Use analytics tools within the platform to filter and prioritise data, helping you make more informed decisions.

Future trends in IIoT to look out for:

Artificial Intelligence and Machine Learning

AI and machine learning are becoming increasingly integrated into IIoT platforms, enhancing their ability to predict maintenance needs, optimise processes, and automate decision-making. As these technologies advance, they will provide even deeper insights and more sophisticated automation capabilities.

5G and Its Impact on IIoT

The rollout of 5G networks is set to revolutionise IIoT even further by enabling faster, more reliable communication between devices. This will support real-time data transfer and analysis, particularly in applications requiring immediate feedback, such as remote monitoring and control.

Sustainability and IIoT

Sustainability is a growing priority in manufacturing, and IIoT can help factories reduce their environmental footprint. By providing real-time insights into energy usage, material consumption, and waste, IIoT platforms enable more efficient and sustainable operations.

How do we know all of this? Well, we help business on a daily basis to implement smart factory solutions, including Industrial IoT, that will enhance the efficiency of their operations. That is why we are perfectly positioned to help you to choose and implement a platform that meets your current needs, and supports your future growth. Find out more about CAD-IT's IIoT offering here , or contact us via [email protected] .