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OEE, IIoT, and Production lines: 3 Use Cases

How can the Industrial Internet of Things (IIoT) improve operational efficiencies on production lines in manufacturing? Let's look at saving time, quality control, and safety as use cases. 

 

INTRODUCTION: IoT VS. IIoT 

Overall Equipment Effectiveness (OEE) is a metrics system that measures the success of manufacturing operations. Typically, manufacturers pull data from IIoT (Industrial Internet of Things) logistics and multiply availability with performance and quality to determine and establish OEE.

 

A production line is a set of operations that occurs in factories, both local and abroad. Materials are put through refining processes to produce end-products that can be used by mass consumers.

 

Now, you’re probably wondering how all these things work and connect with each other. In previous articles, we discussed what the Internet of Things can do for industries such as retail and transportation, but in looking at the world of manufacturing, we see how much untapped potential there is.

 

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First, let’s discuss a few differences. The Internet of Things consists of physical devices working together through smart technology. Vehicles, buildings, and other products are embedded with sensors and connectivity software, allowing data to be the exchanged and collected accordingly. The Industrial Internet of Things is virtually the same thing, but reserved for manufacturing, and all IIoT technology is used to ensure accuracy and industrial productivity in factory networks.

 

IIoT has shown great promise in the areas of quality control, green practices, and overall supply chain efficiency, and its general purpose is to produce quality products during primary production runs. It is estimated that approximately 82 percent of businesses will incorporate the IIoT by mid-2017, and that its international market will grow to $7.1 trillion by 2020.

 

As businesses adapt to meet changing consumer demands, product operations are shifting more towards creating variations in products, leading to shorter production runs. Companies no longer have time to produce all the materials they need, so the goal is to build as many quality products as possible during initial manufacturing.

 

Download the FREE whitepaper: IoT Enables Predictive Maintenance 

 

CASE #1: SAVING TIME

 

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In the production of stamped metal parts for example, surface value cannot be measured by sensors, and flaws in paint jobs and exterior appearances lead to premature stops in production. Operators retrace their steps to examine the products that have already been produced. These items must then be stamped, sheared, or painted all over again manually to ensure mistakes and inaccuracies are fixed before the products head to stores.

 

Naturally, this process can be very time consuming, but the IIoT is designed to make these kinds of issues vanish quickly. By monitoring factory networks, the IIoT can gather performance data from machines to find the root of a problem. As these machines are likely interconnected through sensors, larger amounts of data can be obtained to ensure issues are discovered faster. Thus, manufacturing becomes more efficient.

 

CASE #2: QUALITY CONTROL 

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Now, let’s examine quality control. As factory productivity rises, production lines will be “facing the pressure” to work swiftly and smoothly. This can be accomplished through virtual connectivity to the cloud. The smart technology employed in an operation can decipher the specific belt or line a faulty product may have stemmed from, along with the employee who was operating it at the time. Being connected to the cloud allows production line issues to be recorded in real time, thus improving a product and guaranteeing greater accuracy.

 

CASE #3: SAFETY 

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Here’s a third scenario – safety. The IIoT has birthed wearable technology that connects employees and manufacturers to plant and factory information, giving them access to machine data and improving safety standards. This technology includes smart vests and Bluetooth beacons, which allow staffers and forklift operators to see past corners. Traffic is ultimately cleared, along with obstacles that pose danger to floor hands by sounding alert systems and braking incoming vehicles and factory mechanisms.

 

When it comes to IIoT benefits, the facts speak for themselves, and as time goes by, the choice is becoming relatively clear. Businesses would be smart to integrate IIoT technology into their systems early to improve operations from an initial start before it becomes too complicated or too expensive to handle.

 

Download the FREE whitepaper: IoT Enables Predictive Maintenance 

WORKS CITED

Bond, Jackson. “IIoT and OEE in Car Manufacturing.” Blog.relayr.io. Relayr, Inc. Web. 29 Mar. 2017. 

Spoda, Sal. “IIoT’s Role in Production Line Diagnostics.” Viewpoints. Industrial IoT/Industrie 4.0 Viewpoints, 20 Aug. 2015. Web. 29 Mar. 2017.

White, Glen. “4 Ways IoT Tech is Revolutionizing Production Lines.” Manufacturing Global. Manufacturing Global, 16 Apr. 2015. Web. 29 Mar. 2017.

Bennett, Jennifer. “5 Reasons Why Collaboration is Crucial for IIoT Success.” Plant Services. Plant Services, 17 Mar. 2016. Web. 29 Mar. 2017.