A Strategic Approach to Connecting Your Legacy Machines

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Click to learn more about author Bernard Brode.

If you work in the manufacturing or production sectors, it’s likely you’ve spent the last few years reading endless articles about the fourth industrial revolution and the massive benefits it can bring in terms of efficiency and agility. Unfortunately most of the literature on how to implement industry 4.0 machinery assumes that you are either building a factory from scratch or have an unlimited budget for upgrades.

In the real world, most companies upgrade their legacy machines piecemeal, one part at a time. There are good reasons for doing so – one recent study showed that 76% of decision-makers admit that legacy systems trap their data. Connecting these machines would greatly improve automation and operational efficiency. But companies need to proceed carefully in order to realize these benefits. In this article, we’ll show you how to do that.

1. Create a Digital Transformation Road Map

First and foremost, you need a strategic plan as to how and when you are going to upgrade your legacy machines. This strategic plan is generally referred to as a “digital transformation roadmap,” and contains details of the type of data you will collect and what you will use it for.

Creating a plan like this can be challenging. The IIoT technology available is constantly changing. That’s why it’s important to start with a list of desired outcomes – even if these aren’t possible at the moment – and work backward to what can actually be achieved. This way, you can design a framework that outlines the hardware, software, and computing infrastructure that you are working towards thus avoiding the cost of upgrading machines that will be obsolete as you develop other systems.

2. Analyze Your System Holistically

Alongside building a strategic plan to connect legacy machines into an integrated whole, you should undertake detailed and holistic analysis of all of your systems. The reasons for doing this are two-fold.

One is to avoid the same problem we’ve already mentioned. There’s no point in spending time and money updating major parts of a machine that allow it to integrate into the IIoT if the entire assembly that the machine forms part of is eventually going to be replaced by a “smarter” alternative. It’s better, in that case, to work around the legacy system until you have the investment capital to do the entire upgrade.

The second reason to look at your systems holistically is that many machines, even those produced years ago, have data collection facilities that simply haven’t been used up until now. Some companies find that, after this kind of analysis, they have far more sensing capability than they thought. In this case, they can greatly improve the efficiency of their plant by merely making better use of the systems already in place.

3. Select the Right IIoT Hardware

With this analysis and strategic plan in place, you can begin to choose the IIoT devices needed to connect the legacy machines. At this point, some engineers look to the systems used in smart cities as they dream of impressive, highly integrated networks of sensing and action devices.

Unfortunately, few industrial engineers are able to achieve this. Instead, they find that the majority of IIoT devices are limited by the conditions they will be exposed to. Today, most IIoT devices are built around a diverse set of ingress protection codes (IPs) that protect them when used in manufacturing facilities. This means that you need to know the operating conditions of each part of your plant before purchasing smart devices.

There are a number of specific questions to ask for every location of your planned IIoT infrastructure:

  • How will the heat, steam, grease, dust or water produced in my facility affect IIoT devices?
  • Do the systems and equipment in my shop floor need custom-designed hardware to ensure it fits into or on the machines complex structure?
  • Do shop floor technicians, order pickers, or assistants need to communicate with the IIoT devices?

4. Choose a Computing Solution

In the same way that you should analyze existing systems holistically, you should also envision your future IIoT system at the plant level. Though you will likely be connecting and upgrading the components of your shop floor individually or in groups, ensure there is sufficient computing power to handle the entire future demand.

There will essentially be two models for this computing – Cloud or Edge – and a number of hybrid approaches that seek to deliver the advantages of both. With cloud computing, it’s possible to achieve a centralized computing solution that handles data analysis – but at the cost of processing latency challenges. Edge computing brings compute resources to the deployed IIoT device or legacy system using a decentralized model. This allows you to make data-driven decisions immediately. The challenge in this scenario is to integrate systems across the entire production line.

5. Integrate Security Systems

Last but definitely not least, build security into the plan at every stage. As hack attempts continue to soar, this is not the place to skimp. Some legacy machines were likely designed long before hacking and the present world of data privacy even existed. The chance they can deliver a modern level of security on their own is not high.

You will likely need to implement security at the level of your IIoT network rather than relying on the software used to connect each legacy machine. And it’s cheaper and easier to include adequate security in the beginning of your upgrade cycle than try to crowbar it in later.

The Bottom Line

Ultimately, you should also remember that no machinery is eternal. Connecting legacy machines is largely a way of extending their useful life rather than setting them up for the future. At the same time, it’s important to take advantage of each new technology as it arises to get the most out of your legacy hardware. So while today this might mean connected old machines, tomorrow it might well include catchy terms like blockchain and artificial intelligence.

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