What you think about an opportunity to use analytics to envisage the forthcoming events before they happen. What about using real-time insights to increase productivity and help the operations to make the right decision at the right time?
Now, Industrial IoT or IIoT is making all these imaginative things possible. By offering unparalleled levels of operational efficiency to the manufacturing units, performance and productivity are not taken care of more than ever before. The industry experts now predict IIoT may be a $230 billion market by the year 2023. It may have a big impact on manufacturing, including the increased efficiency, better productivity, streamlined maintenance, automated asset monitoring, etc.
Many of the top manufacturing industry giants now invest largely in IIoT and enjoying many benefits of it. IoT comes into play to increase productivity and efficiency by offering custom-built solutions. It is also very crucial to note that IIoT use cases may progressively expand in the future. Further, we will present a compilation of top industrial use cases of IoT in the manufacturing sector.
1. Asset Monitoring at Real-time
IoT assets are used in manufacturing companies to connect systems and machines. This can be viewed as a paradigm shift that enables asset monitoring in real-time. This can provide an opportunity to do equipment monitoring in real-time and ensure optimum safety. This approach is used largely in remote manufacturing, in which the sensors will help track the production process and send this to the reporting personnel. It can also offer a standard platform to control and manage all the assets remotely for increased production and operations.
Enabling timely and proactive manufacturing decisions, asset monitoring through IoT can take your manufacturing unit to the next level. When it comes to the manufacturing industry, asset tracking will make status monitoring very easy. It can also work to augment logistics, reduce overheads, sustain the inventory to eradicate quality issues, etc.
As a real-time example, you can see how the AMR manufacturer in the US deploys the Smart Metering and MDM solution for the water utilities to monitor the smart meters. This smart solution was architected by IoT consultants of Saviant on the Azure platform, which can now connect 50000 smart meters by handing billions of data. Smart metering now helps save billions of gallons of water and ensures accurate billing to avoid water wastage, theft, and good meter health for more operational efficiency.
2. Digital Transformation with Big Data
By connecting the equipment, manufacturers also generate intelligent networks which can communicate with each other autonomously. With this approach, organizations can also contextualize data from remote manufacturing and convert those into actionable applications. It can also provide proactive views to KPIs and enable quicker identification of problems and measures to improve operational performance.
IIoT companies can also connect to various operational data centers and then unify those to enable live data visibility across many manufacturing systems. IoT also enables machinery which enables connected operational intelligence and transmits these live insights to the manufacturing stakeholders and enables these to manage the industrial units remotely.
Digital transformation using big data now brings forth many secured and scalable industrial platforms on Azure. Therese can handle various enterprise gateways that connect many end-devices that can record the pressure, temperature, humidity, and other kinds of environmental data. All these can be utilized to derive timely business insights to practice actionable intelligence for the operational team to improve efficiency.
For IIoT related data management, it is essential to get a reliable and secured database administration service. For this, you may rely on the solutions offered by RemoteDBA.com, which is now a leading player in the IIoT remote data management sector.
3. Predictive Maintenance
We can see that millions of dollars now go into the operational cost for troubleshooting. However, if the equipment maintenance is done promptly, this can prevent any pauses in production. If you succeed in predicting a downtime before it occurs, the manufacturing units can significantly reduce their operations overheads. With IoT, by using sensors, cameras, data analytics, etc., we can almost accurately predict the possibility of a failure before it occurs. Such a detection will help create timelines for strategic maintenance to be performed only as needed if there is a chance for a glitch.
Manufacturers now largely leverage IoT to incorporate vibrant components in automated manufacturing to have autonomous maintenance schedules. Rather than relying on the intuitions of maintenance personnel, this autonomous approach will help you build a solid mechanism in place with zero maintenance overheads.
As a real-time, we can see how this technology is incorporated in standalone wind farms. Each wind farm tends to generate humongous volumes of WTG data in structured and unstructured forms. This can be used to trigger a warning sign in case of any error or a chance of failure. With many intelligent solutionsdeveloped for the same, the operations team can take quick and insightful actions to minimize any failure and prevent any operational errors in the future.
These types of smart approaches in manufacturing automation with IIoT data analytics are slowly gaining momentum. Industrial IoT now has the capability to transform the manufacturing sector radically. As the global market is quickly changing, the shift in industry dynamics no pushes the manufacturers to reconsider their operational approaches. The truth here is that there is a gigantic volume of valuable data being generated from each point, and effective gathering and processing of the same can bring in some unexpected results in terms of cost-saving.
The giants in the manufacturing industry are now largely investing in IIoT and started reporting significant benefits for their different operations. They are seeing streamlined operations and better results with the use. This includes increased efficiency, better productivity, and huge cost saving in terms of maintenance, etc giving them better results in different business aspects. There are many crucial developments in this sector, which will make the IIoT application more capable of making the predictions more accurate and giving better insights for timely decision making.
