The Internet of Things, or more specifically machine-to-machine communication, may currently make headlines for innovations such as the self-driving car of the future, but, in reality, IoT-driven processes are making much bigger headway in the supply chain right now. In fact, Gartner recently reported that a 30X increase in Internet-connected physical devices by the year 2020 will “significantly alter how the supply chain operates.”
Among the top concerns of supply chain managers list inventory management and planning, in addition to demand management and forecasting. Coordination between vendor and OEM, and OEM to customer is vital. Lack of such coordination in the supply chain is a root cause of failure, which can aggravate nearly every other issue in the process of getting a product produced and delivered.
That's where connected devices come into play. Smart technology provides information on where products are, how long delivery will take, when and where they were manufactured, in ways much more quickly and accurately than in the not-so-distant past. However, to obtain such supply chain insight, a number of connections are necessary.
Machine to Dashboard
Imagine a clear line of sight onto the plant floor of a supplier, from many hundreds of miles away. To facilitate such transparency, manufacturing sites install sensors on machinery, and that data is sent to a dashboard. Should a process go awry, the sensors will signal certain systems to respond and correct the problem. Manufacturing issues are thereby identified before the product gets to the end customer, reducing delays in OEM production and, ultimately, preventing recalls.
Dashboards can be viewed not only at the plant site, but also at the partner's, and adjustments to delivery schedules can be made accordingly. In addition, because the data is monitored in real-time, catastrophes can frequently be prevented in the first place, by paying close attention to patterns that generally precede common problems. Sensors connected via the cloud can identify the precise factory conditions, e.g. temperatures, humidity, etc., necessary for high quality production.
Machine To Data
IoT enables the real-time analysis of data points, which create automated responses for machinery, and that provides a foundation for successful production processes.
However, it soon becomes an enormous challenge to analyze that information for real-time insights that can be acted upon to improve performance, so hard-core data analytics systems are mandatory for success. Those systems must be fast, accurate and easy to use, while providing intelligible and actionable intelligence.
One high profile company that puts its data where its products are is engine manufacturer Rolls Royce. Big Data processes are used in design, manufacture and after-sales support. Paul Stein, the company’s chief scientific officer, told Forbes:
We have huge clusters of high power computing which are used in the design process. We generate tens of terabytes of data on each simulation of one of our jet engines. We then have to use some pretty sophisticated computer techniques to look into that massive data set and visualize whether that particular product we've designed is good or bad. Visualizing Big Data is just as important as the techniques we use for manipulating it. It decreases development time and improves the quality and performance.
Machine To Processes
In the end, all the sensors, which then generate data, which in turn gets analyzed, are working toward a single goal: the creation of a more efficient workplace process. Procurement and manufacturing processes will be connected to eliminate any kink in the supply chain. So, a truck may be full of automotive parts headed to an assembly facility. Those parts might have a tag chip that has an integrated circuit, which delivers performance, memory and extended features to the tag. The chip is pre-programmed with a tag identifier, a unique serial number assigned by the chip manufacturer, and includes a memory bank to store the items' unique tracking identifier (EPC). That tag uses its sensors to transmit delivery information based on the exact time the parts left, traffic, route, and vehicle information rather than just an estimate based on when the parts were produced.
Connected devices allow OEMs to plan on a real-time basis rather than, for example, seasonally, using variable predictive algorithms. A supplier can sense and manage inventory based on actual shelf movement. Companies are using IoT technologies to transform their businesses. Yes, all the components will one day soon be “smart.” But it's the way that information is communicated, and used that will streamline the supply chain. That efficiency will result in saved costs and time, resulting in a bigger bottom line — something appealing to suppliers, manufacturers, and, ultimately, the customer.