Industrial Internet Of Things (IIOT)/Smart Factory Technology For Breweries
What is it & How Your Brewery Can Benefit
Industrial Internet of Things
(IIoT)/Smart Factory for Breweries
What is it & How Your Brewery Can Benefit
Industrial Internet of Things (IIoT)/Smart Factory for Breweries
What is it & How Your Brewery Can Benefit
Industrial Internet of Things (IIoT)/Smart Factory for Breweries
What is it & How Your Brewery Can Benefit
What is IIoT/Smart Factory Technology.
The Industrial Internet of Things (IIoT) is the application of the Internet of Things (IoT) in an industrial setting which applies smart technology (smart sensors), data collection/storage, and cloud-based analytic connections using the internet’s infrastructure to achieve value-added performance within an industry’s enterprise.
IoT is the interconnection of smart devices that monitor, inform, and enhance personal aspects of everyday life. IIoT, in a similar way, builds on the same technology and concepts as IoT to provide the ability to connect businesses, people, machines, data, and devices within an industrial setting specifically targeted to enhance performance across the manufacturing value chain.
For example, the motor and drive in a conveyor system on a bottling line, a temperature controller on a cooler or a pump that provides freshwater are connected, producing and sharing data to make informed real-time data-driven decisions that better control the process they are part of.
IIoT/Smart Factory technology can be applied to solve complicated logistics, manufacturing, and supply chain issues that benefit both the manufacturer and consumer. Leveraging IIoT in an existing enterprise is a mutually beneficial aspect of IIoT implementation and will reduce operational costs while ensuring the highest quality possible in a wide variety of an industry’s processes.
Four Parts to Applying IIoT/Smart Factory Technology to any Facility.
Before a process, system, mill or plant can qualify to be part of the Industrial Internet of Things (IIoT), they must fit into four categories:
Interconnection
Normalization
Analysis
Systems Automation
Step 1
Interconnection
The first category is interconnection. There must be an interconnection between sensors/algorithms and the operators themselves. This means there must be a human-machine interface (HMI) or a supervisory control and data acquisition (SCADA) system that monitors and allows the operators to interact with the process or equipment. This interaction can range from merely monitoring and recording values to complete control and (AI) decision making for the process.
Step 2
Normalization
The second category is the normalization of data, meaning the reorganization of data into something that models the process from where the data is being acquired — for example, monitoring a trend on an HMI to understand the performance of a system over time. This data could even come raw from the sensor/algorithm directly to the operator.
Step 3
Data Analysis
The analysis of data is the third category. Analyzing data can be broken down into different categories, such as descriptive analytics, which tell us what is happening or why it happened while predictive analytics tells us what is likely to occur in the future. Lastly, prescriptive analytics help guide us by telling us what should be done to prevent or control things that may be detrimental to the process or personnel. For example, these connected systems will assist in decision making to keep the operators safe from tasks that may not be safe. The introduction of an automated process using IIoT, adequately analyzed, controlled remotely, can enhance the safety of the operators and remove them from a potentially dangerous situation.
Step 4
Systems Automation
Lastly, the systems must become self-reliant over time. This will come from their data acquisitions and established protocols so that the operation can work smarter. A more reliable and automated system makes for a more productive process.