Best Practices for Industry 4.0 Implementation

Posted by Brian Hoey on Dec 17, 2019 9:00:00 AM

Make the mostFrom 2018 to 2019, Gartner’s outlook on Industry 4.0 adoption seemingly became a little less sanguine. It’s certainly not the case that their opinion of the potential of this massive industrial paradigm shift has lessened in any way, but the focus of their Industry 4.0 predictions for 2018 was how CIOs could find useful models of successful digitization, while for 2019 their focus was on dealing with the gap between expectations and reality that numerous industrial businesses are encountering with new technology. Again, it’s not that the outlook on Industry 4.0 itself is any less rosy than it was a year ago, but it seems like we’re reaching the point where real implementation hurdles are beginning to show themselves.

Of course, we’re still in the early stages of the Industry 4.0 era, and the world of manufacturing is gaining new wisdom and insight into these challenges every day. As that wisdom accumulates, we’ll get closer and closer to a set of relatively universal best practices for Industry 4.0-readiness. For any companies who are impatient to begin their digital transformations, however, there are a few best practices that we can already lay out with relative confidences:

 

1. Perform a Technology Audit

Industry 4.0 will completely change the nature of your technology and IT ecosystem—but how it does so will depend in large part on what that ecosystem already looks like. This is why your first step is to audit the technology you’re already using. This should obviously include things like software solutions you might already have in place (APS or S&OP systems, e.g.), but also any physical hardware like servers, other computers, and even factory floor machinery. This should give you insight on two fronts: how far along your digitization efforts already are, and how well-positioned your are for further technology integration. If you have a lot of modern computer hardware being used to store customer orders and production data, for instance, you’re likely in a position where new technologies can access that data without too much in the way of retrofitting or otherwise monkeying around. Conversely, if you’re still operating with a bunch of pre-1990s servers that don’t have ethernet or USB connections, you’re going to need something to bridge the gap.

 

2. Put Industry 4.0 in Context

While the best practice above may have appeared technological, in reality it was more about operational visibility than anything else. That’s going to be something of a leitmotif on this list. Why? Because the biggest hurdles to real operational change usual emanate from the operation itself, rather than the technology being proposed. That’s why one of the most important steps you can take is to develop a company-wide understanding of what Industry 4.0 is, why you’re adopting it, and what your goals are. You may have noticed that not every definition of Industry 4.0 is identical—some are most focused on machine-to-machine communication, while others lean heavily on machine learning and cloud technology—and this is okay, as long as your company is working with one definition that’s suited to your industry and your needs. For instance, if you manufacture complex products like automobiles, your vision of Industry 4.0 might focus more heavily on advances in data-driven product design and increases in supply chain visibility. The trick is to make sure that everyone’s on the same page about what this new paradigm means for you and how it fits into your broader corporate goals.  

 

3. Focus on Connectivity

While there will be plenty of variation in how technology deployment shakes out depending the exact needs of your organization, there’s one element of Industry 4.0 that should be non-negotiable: increased connectivity across the entire value chain. If you’re evaluating a software solution that helps you to optimize the use of space in your warehouses, for instance, you need to make sure that it does so in such a way as to promote data visibility and integration up and downstream. Thus, if the solution can’t integrate nicely with the solution being used by your logistics partners—meaning that they can’t figure out where things are warehoused so that they can get them loaded efficiently—then you’ve effectively sacrificed connectivity. By the same token, if you’re looking at GPS tracking devices or RFID chips, you need to ask whether they can provide data in any software environment, or if you’re stuck using proprietary applications. If it’s the latter, you might be better off looking elsewhere for your devices.

 

4. Find Some Quick Wins

Often, adopting a big, scary technology suite can seem daunting, and your team might begin to feel like they’ll be in the weeds for years trying to get a handle on everything. That’s why it’s crucial that your implementation strategy include some quick wins for your company and the various teams that comprise it. If the long term goal is complete digitization and tracking of every moving part within your supply chain, start by tracking factory floor machines themselves, and make sure that planners can integrate this visibility with software that helps schedule maintenance to reduce downtime. In this way, you immediately increase uptime and thus throughput, giving your production planners an immediate value boost and helping to keep them engaged and excited about the rest of the deployment. This is just one example, of course, but it should give a sense of what we mean.

 

5. Don’t Neglect Advanced Analytics

Again, Industry 4.0 means different things to different people. But just as connectivity is non-negotiable, you should also be sure that any choice you make puts you in a position to leverage advanced analytics—whether that’s in the form of machine learning-derived forecasting, real-time traffic and pricing analysis, or automatic network optimizations. Why is this so crucial? Because the more you implement new technology and the more you integrate with supplier and even customer IT, the more data your operations will produce. Though much of it might seem opaque to a human planner, advanced analytics workflows can ensure that this data translates into real value in the form of better predictions and decreased waste. Again, whatever your definition of Industry 4.0, these will be important elements of your push towards an improved ROI.

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Topics: Industry 4.0, Advanced Analytics