Internet of Things: Meeting the Demands of the Next Generation
The future is full of exciting challenges, and meeting the demands of the next generation is possibly the most important issue. Consumers want personalization, and manufacturers want to increase productivity and create new revenue opportunities. Overcoming the skills gap is another challenge we will have to face in the next few years. The Internet of Things (IoT) has the potential to equip manufacturers with real-time visiblity into plant operations, and the ability to predict and anticipate trends and patterns, giving them greater flexibility to respond to a dynamically changing industry.
A manufacturer's IoT strategy is unique to their specific operating system, their position in the value chain, and the consumers they serve. However, all manufacturers should consider the following to ensure their IoT strategy provides the information and resources needed to succeed now and in the future.
Automation has existed for many years in most manufacturing facilities, and many manufacturers can easily monitor the flow of parts and goods on their factory floors. The IoT allows manufacturers to leverage the information available inside, beyond the walls of the factory floors. IoT-driven automation enables granular visibility into manufacturing operations. In order to completely monitor oprations, manufacturers are required to deploy many more sensors throughout their facilities, incuding material handling equipment, to capture all equipment performance parameters in real time. This data would include information about ambient conditions like temperature, humidity, and air quality. This information, coupled with the workstation data collected through a Manufactuering Execution System, provides core level visibility and the impact of conditions on overall production performance. All systems and devices that affect performance should be instrumented, from maintenance equipment to robots and automated vehicles.
Predictive analytics are a vital part of IoT programs, enabling manufacturers to view real-time insights and make data-driven decisions. Predictive analytics provide a thorough analysis of all data generated by the IoT. With real-time analysis, analytics can predict issues and problems before they ever occur. Custom algorithms can reocgnize patterns of an overheating microchip and predict delays down to the millisecond. With this knowledge, technicians can make the repair and correct the issue before the costly delays ever occur. Predicting issues and problems can also create supply chain transparency. Detailed insight about how supplier delay will affect operations across the network can help a manufacturer make adjustments and coordinate with other suppliers to minimize the impact of the shortage. Most manufacturers will need to store more data for longer periods of time to get the maximum benefit from predictive analytics. More data equals better and smarter algorithms. Additionally, manufacturers must connect IoT insights and predictions with plant control functions. When the IoT reports a malfunction, it may trigger an automatic shut down, and dispatch an order to a technician for repairs. This requires seamless interaction between IT and IoT.
Semantic data is generated in multiple ways; from email exchanges to calendar invitations to social media tags. This data must be integrated with manufacturing systems and machine data to create a smart, comprehensive view of factory operations. Analytics tools can correlate semantic data with machine data to create a stronger context for accurately identifying patterns.
Manufacturers will get the most value from the IoT by using it to drive business strategy and foster innovation. They should be creative in augmenting and accelerating their IoT programs, which will help organizations build what's necessary to meet the demands and challenges in existing markets, and the markets of the future.