What Toothbrushes Can Teach Us about Industrial IoT Innovation Integration

April 27, 2021

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A simple example of how disparate parts need to connect to make IoT-enabled projects and products work is well demonstrated by what companies like Colgate-Palmolive are doing. In an industry where the functions of R&D and IT are historically siloed, the global consumer products giant has united each domain’s skills to work on a smarter toothbrush, the Wall Street Journal recently reported — coupling product design and technology expertise to make a smart toothbrush talk.

What Colgate-Palmolive’s Smart Toothbrush Teaches Us About IoT Integration

Colgate-Palmolive’s smart toothbrush offers some lessons for IoT-enabling plant and factory operations. Just as making a toothbrush talk involved connecting previously siloed domains — each doing the job they were best at — so does making machines, equipment and enterprise systems on the factory and plant floor talk to enable Industry 4.0.

Industry 4.0, a term that the Industrial Internet Consortium (IIC) defines as “IoT, machines, computers and people enabling intelligent industrial operations using advanced data analytics for transformational business outcomes.” The IIC defines an IoT system as one in which “the components are connected via a computer network, and one or more of those components interact with the physical world.”

Central to those definitions is not the word platform or unified technology, but the word connection. For decades, factories and plants have been trying to surface data from equipment, machines and vehicles by connecting them to enterprise systems. There are, by some counts, as many as 800 IoT platforms to that end. However, end-to-end IoT enablement can’t be achieved by implementing a single platform or vendor’s solution. Instead, we must orchestrate data from many different systems and move it along the network according to what needs to be analyzed in the cloud and what can be best handled at the edge for optimal cost and speed.

Consider how many different systems are in place on the shop floor governing plant or factory operations. There can be PLCs, robots, RFID barcode scanners, CNC machines, torque tools, operators and more. Then, layer on the enterprise systems running operations and making sense of all that data from the supply chain or the manufacturing process.

The nuts and bolts of IoT are about getting data from places you couldn’t before to improve or automate a process. Every company leveraging some industrial IoT technology works in a heterogenous domain and pulling things together in a symphony of motion. Companies don’t want to touch the underlying programming in the equipment but still want to create workflows with minimal coding. Connecting to the equipment in a highly optimized way — and enabling management of the data on the edge — is crucial. For instance, a machine that needs recalibration or support will automatically generate a support ticket directly into a system like SAP, trigger a request for parts and feed that data into an AWS system for machine learning to improve the process and enable predictive maintenance.

How to Integrate IIoT for Your Factory

Getting the data where it needs to go — from equipment to an IoT platform for analytics or an enterprise system for collaboration, closed-loop controls, simulations and digital threads — demands strong device management, connectivity management and data delivery capabilities.

To that end, choosing what technology to use to integrate all these technologies involves several considerations.

  1. Costs. While 5G networks have brought the capability to move all of the raw data, no one can afford the cost of moving all of it. Therefore, it’s essential to have a solution to manage data at the edge and decide what needs to be transferred upstream. Can it be dealt with locally, or does it need to go to a cloud-based IoT platform for analysis? There’s much innovation in this regard — including machine learning to enable better decision-making at the edge of IoT networks.
  2. Configuration vs. customization. Integration shouldn’t require costly customization. The integration platform should have built-in IT connectors and plug-ins that automatically discover and exchange information. All adapters should be built-in and deployed when installed, and there should be no need to touch the IT system or make any customizations. In turn, the software agent should be able to be installed across many different operating system platforms.
  3. Use case and change management. Technology is no longer the roadblock — things can be connected very quickly for data consumption. It takes businesses much longer to figure out what they’re going to do with the data — how it will change the business process, what it can enable and more. Perhaps the business is looking to surface data from operational technology in its enterprise applications or enable chargeable services to the dealer network, predictive maintenance or secure remote access for monitoring and maintenance. Also, consider how often the equipment needs to transmit data around a certain parameter. Perhaps the temperature around a piece of equipment is being monitored. Does the air temperature need to be transmitted every five seconds, or could it be done every 30 minutes or even every hour? It all boils down to getting the right data at the right time in the right amount to the right person.

Consider that the toothbrush in the recognizable form we know it today dates to 1938. While we don’t have equipment on the factory floor that is quite that old, some of the equipment we’re trying to enable with IoT hasn’t changed that much in decades. In many cases, we’re trying to get data from older equipment, see it on newer devices and push it to enterprise software to take actions or make decisions. Letting everything do the job it’s best at — and taking a data-centric view — will help achieve this vision of Industry 4.0.