10 Takeaways about the Industrial Internet of Things
What will it look like for manufacturing to embrace and make use of interconnected hardware? Here are some clues.
Here is the Internet of Things as applied to manual assembly. Instructions are projected onto the table surface while motion sensors time each step. Motion sensing also drives alerts for when the worker makes a wrong move, such as reaching for the incorrect tool or fastener for the step that is next. This scene is part of a demo at the Digital Capability Center.
Steven Jones of Steelcase describes the key concepts of Industry 4.0 as represented by the German “Industrie 4.0” initiative. The list of enabling technologies does not include robotics, but does include additive manufacturing.
Why IoT? For Vibco President Karl Wadensten, the answer is responsiveness. The company expects to compact total lead time in the future into an amount of time consumed by order entry and scheduling today. A data-driven process will provide the means for realizing this efficiency. Both this photo and the one previous were taken at the Smart Manufacturing Experience recently held in Boston.
Conceptually, what is meant by the "Internet of Things" (IoT) is clear. Objects can interact with one another to drive automatic decision-making the same way that apps, websites and other information tools interact now. The Industrial Internet of Things (IIoT) is this idea applied to manufacturing. What this will mean in practical terms, what it will really mean for manufacturers, is harder to grasp—but I am starting to get it.
At two recent conferences, the Smart Manufacturing Experience and the FT Future of Manufacturing Summit, manufacturers just beginning to succeed with the IIoT shared their experiences. From these accounts, I drew 10 takeaways about the industrial use and value of the Internet of Things:
1. Malware is a major concern. Security has to be step one. Otherwise, interconnecting machines creates the risk of malicious code causing an epidemic.
2. Everyday objects become smart. For furniture maker Steelcase, the IIoT instructs production staff. For example, a power screwdriver outfitted with sensors means torque is monitored and the operator is alerted when the optimum number of turns is met.
3. Everyday inefficiencies become clear. For this same manufacturer, data showed one manufacturing step took 20 percent longer for one style of a particular part compared to parts that are otherwise identical. The reason is that this particular style fits tighter in its fixture and the hardware needed to work on this style sits just slightly farther from the operator’s reach. Every operator knew that this particular style was “the hard one,” but the IIoT quantified the effect and made it plain.
4. IIoT guides kaizen. The proven means of looking for process improvements still happen, but now data directs the search.
5. Tools are free. Azure, IFTTT, Amazon Web Service IoT: just of few of the tools or tool kits for programming how a physical event produces a response, all free.
6. No special distinction for robots. The IoT is automation, but not as we commonly imagine it. Robots are no more and no less appropriate to IoT than other devices.
7. Additive manufacturing (AM) and IoT connect. Because AM enables direct digital part making without intervening steps for setup or tooling, AM is an enabler for IoT-driven production.
8. The "things" include people. The Digital Capability Center in Chicago, Illinois, shows a striking example of this point. Motion sensors (think Xbox) monitor the work of assembly employees to gather data and even alert them when they make the wrong move.
9. The payoff is productivity. To account for why it had embraced IoT, Rhode Island manufacturer Vibco explained that only by mapping and mastering its process using data will the company be able to improve its efficiency enough to meet leadtime goals.
10. Transformative progress is the promise. At the FT summit, Patrick Bass, CEO of Thyssenkrupp North America, described the path he has seen for advancing with the IIoT. First comes digitization, or capturing the data. Then comes digitalization: using it. The third step, the goal, is the digital transformation.
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