IoT Coupled with Big Data can make Manufacturing ‘Smarter’

By Kamal Brar, Vice President and General Manager of APAC, Hortonworks

Towards the end of 2017, we at Hortonworks had predicted that Industrial Internet of Things (IIoT) will impact the manufacturing sector further through Big Data technologies. Mid-way through the year, it is a good time to delve further into this prediction and talk about the role of Big Data in making manufacturing ‘smarter’. Through low-cost sensors and IoT devices, manufacturers are creating a connected shop floor. But what about the data that is gathered across the manufacturing supply chain? This data needs to be stored in an inexpensive and secure manner. And more importantly, how can this data create more efficiencies? After all, manufacturing is all about efficiency at scale.

By using a combination IoT and Big Data technologies, players in the manufacturing sector can create better efficiencies and better products while improving speed-to-market and customer satisfaction. And reduce their costs of course. So, how can IoT and Big Data make manufacturing smarter? Here are some use cases:

By Reducing Supply Chain Costs

 Manufacturers always want to keep their inventories at minimum possible levels and prefer just-in-time delivery of raw materials. The danger with this model is that lack of raw material supplies can lead to production delays. By using sensors, RFID tags, supply chain data can be easily captured. Such historical data will lead to patterns which will enable manufacturers to follow a just-in-time model thereby reducing supply chain costs and improve their margins.

By Maximizing First-time Yield

 Every manufacturer wants to maximize the first-time yield for a production run. First-time yield is basically a measure of the number of products that are made correctly the first time they come through the production line. However, the key challenge that manufacturers face today is the lack of visibility into operations. Sensors can provide raw data for improving that visibility, if the sensor data can be integrated with other existing data stores. Hortonworks has increased yields in drug manufacturing for Merck Research Laboratories through its Hortonworks Data Platform.

By Improving Process and Product

 Sometimes, manufacturers face situations of product malfunction after the product is sold. If manufacturers can deploy sensors to capture data at various stages in the manufacturing process, they can detect the issue which caused the malfunction. This, by combining the forensic data with the original sensor data from when the product was manufactured. Thus, a manufacturer can improve the process and product across the product range.

Another way, IoT and Big Data can improve efficiencies and reduce costs is by creating maintenance schedules based on real-time and historical data drawn from machinery and equipment in the factory. Machine learning algorithms can compare maintenance events and machine data for each piece of equipment to its history of malfunctions. Manufacturers will also soon look beyond the shop floor and leverage IoT and Big Data across the value chain. For instance, they can fit sensors on their trucks or on those of their vendors to collect data like location of the truck, weather, and even incidents like speeding, or lack of lane discipline. Such data can be streamed back to the manufacturers’ servers in real time. This way, they can make sure the goods in the truck are safe and no major traffic violations happen through analytics. Real-time sensor data-in-motion would also find use on the shop floor in connected factories soon.

Interestingly, few of these use cases have started being deployed in the manufacturing sector in a few countries and in India too, they will be utilized in connected factories soon. With the push on manufacturing through initiatives like Make in India, the need for improving efficiencies at scale will arise. For manufacturers, the key will be choosing the right solutions to build successful enterprise grade IoT platforms.

Another important factor, manufacturers need to consider is interoperability. Sadly, standards of connectivity between the various devices were not in place at the start of the IoT boom. However, open source software offers a cohesive mechanism for data exchange. With open source software, the developer community can work together to create solutions that will allow data to flow across IoT networks. In the next few years, the ecosystem will mature and we will see greater adoption of IoT and Big Data in the manufacturing sector. ‘Smart’ will be the way forward.