<b>Smarter manufacturing is now about predicting potential problems and finding workarounds - before they become a crisis.</b> The quest for greater manufacturing efficiency is not new. What is new is the need to be able to react - successfully - to an environment where circumstances are less predictable. The last two years have highlighted the need to not only be more efficient but to be able respond when the unexpected happens. Traditional automation has focused on faster and more consistent production. The next step focuses on not only greater efficiency, but also the ability to be more predictive. This includes seeing not only potential problems, but also possible solutions or alternatives in case those issues arise. <h3><b>From IoT to Industry</b></h3> Industrial Internet of Things (IIoT) is part of the more comprehensive digital transformation we are seeing in manufacturing. While IoT refers to the ability of devices to be interconnected over the internet, ‘IIoT’ focuses on adding sensors to processes and parts or materials for the purpose of collecting critical production data. <ul> <li>Roughly 60 percent of manufacturers across multiple industries are applying IoT on projects within their facilities, while 57 percent are using it with supply chain and other partners, according to a study by PwC. </li> <li>Their top focus areas are logistics (50%), supply chain (47%) and employee and customer operations (46%).</li> <li>Most agree it has been a good investment, with 93 percent believing that the benefits of IoT exceed the risks, with 68 percent planning to increase their investment over the next two years, per PwC.</li> <li>IIoT has its roots in heavy industry but is making its weight into light industry as manufacturers face greater pressure to reduce costs, be more flexible and have greater transparency.</li> </ul> It also plays a key role in creating digital twins, a predictive modeling method that creates a real time control tower, showing multiple scenarios, for global supply chains. <b>Key Advantage:</b> Cloud software analyzes the data to provide important insights, often in real time. Management can get a minute-by-minute view of what’s happening on the factory floor. IIoT can provide both an overview of the entire factory as well as data on the performance of individual pieces of machinery - at every point in the production process. <ul> <li>Most (81%) industrial manufacturers are making operations more efficient through the use of IoT, according to a survey by PwC. Nearly 43 percent said that they have already benefited from using IoT-based asset management, and 41 percent expect to do so within two years.</li> </ul> <b>CORE USE CASES </b> <h3><b>Driving Manufacturing Efficiency and Flexibility </b></h3> The ability to identify glitches in real time gives factories greater agility and faster solutions. The data collected through IIoT can help factories identify areas where they are less efficient. <b><i>How It Works: </i></b>Sensors are placed on equipment to provide continual data feed showing a machine’s performance (or overall factory performance) compared with specific KPIs (key performance indicators). <b><i>Key Benefits:</i></b> More accurate forecasting and greater adaptability. <ul> <li aria-level="1">Cost reduction through more efficient inventory management.</li> <li aria-level="1">Support greater customization and smaller order size.</li> <li aria-level="1">Can dramatically reduce lead times - especially on complex products.</li> <li aria-level="1">Provides factory floor agility.</li> </ul> <b><i>Outlook:</i></b> IoT applications for monitoring machine utilization can increase manufacturing productivity by 10 to 25%, according to research from ITIF. <h3><b>Inventory Tracking</b></h3> Being able to more tightly control inventory can have huge impacts on cost savings, as well as that now all-important transparency and traceability. <b><i>How It Works: </i></b>The solutions for the manufacturing sector are based on IoT and RFID technologies. Each inventory item gets labeled with a passive RFID tag. RFID readers scan these tags as inventory moves through the system providing real time location and status tracking. <b><i>Key Benefits:</i></b> More accurate forecasting and greater adaptability. <ul> <li aria-level="1">Cost reduction through more efficient inventory management.</li> <li aria-level="1">IoT also can optimize delivery routes, reduce errors and minimize fraud.</li> <li aria-level="1">Dashboards can provide deep visibility within a partner ecosystem and supply chain.</li> </ul> <b><i>Outlook:</i></b> Smart inventory management solutions can help save 20% to 50% of an enterprise’ inventory carrying costs. <h3><b>Predictive Machinery Maintenance </b></h3> Predictive maintenance relies on the insights gained with continuous equipment condition monitoring. <b><i>How It Works:</i></b> A piece of equipment gets sensors, which collect data on a wide range of parameters determining its health and performance. <ul> <li aria-level="1">The data is analyzed and factory managers can see potential problems on a dashboard.</li> <li aria-level="1">The key is that it can not only show the current status of each piece of equipment, but can predict potential problems.</li> <li aria-level="1">To enable prediction, the combined data set is run through machine learning algorithms to pinpoint abnormal patterns that may lead to equipment failures.</li> <li aria-level="1">In ‘smart factories’ managers receive an alert about potential problems - along with suggested solutions for mitigating the resulting impact on production. </li> </ul> This can predict when a machine is likely to fail and pinpoint operating conditions and machine usage patterns that lead to failures. <b><i>Outlook</i></b>: Predictive maintenance solutions based on the Industrial IoT are expected to reduce factory equipment maintenance costs by 40%, according to Deloitte. <h3><b>Developing Use Cases </b></h3> IIoT still is less developed for apparel manufacturing than for other industrial sectors. There are some additional benefits that it can provide, with some limitations. <h4><b>Quality Control</b></h4> <b><i>How It Works: </i></b>Monitoring product quality by monitoring the condition and calibration of machines on which a product is manufactured. <ul> <li aria-level="1">Currently, this involves establishing some kind of parameters for a machine’s performance and setting a threshold that would indicate that goods produced after that threshold has been reached are more likely to be defective.</li> </ul> <b><i>Where It Could Apply: </i></b>Clearly this applies to those processes that are already highly automated. For a lot of apparel production, manual inspection of work in progress is still necessary. <h3><b>Other Use Cases</b></h3> <h4><b>Worker Safety</b></h4> <ul> <li aria-level="1">RFID tags are frequently used in heavy industry to monitor workers’ safety. Typically they monitor movement, body temperature, heart rate, blood oxygen and more. Through using IoT solutions, a worker’s supervisor is alerted when any of these metrics reach a specified threshold. </li> </ul>