In the era of digital transformation, smart technologies are revolutionizing most industries, and the manufacturing industry has not escaped the revolution. If you work in the manufacturing sector, it is likely that you are aware of the upcoming innovations that, smart manufacturing which will hold the largest technology market that will transform the way manufacturing operates.
Internet of Things (IoT) is spreading like a wildfire across the market today and transforming how organizations and customers approach their workday around the globe. There no arguing the fact that the smart manufacturing sector provides a lot of scope of IoT.
Many manufacturing businesses are focusing on new and exciting technologies using IoT to create an intelligent, decision-making ecosystem of connected devices and things with proactive, autonomous and analytics capabilities, with the end goal of improving efficiency and productivity across the business. The sheer scale at which IoT is being implemented across the industry has led to the coining of a new term: IIoT (Industrial Internet of things).
Efficiency problems plague even the best manufacturing facilities leading to supply chain issues, productions losses, accidents, and more. With the advent of IIoT and related new technologies, it is possible to overcome these issues. Powered by the cloud, IIoT is already driving improved efficiencies within factories and throughout the supply chain by collecting the vast quantities of data from sensors in just moments.
However, gathering large chunks of data is just one part of smart manufacturing – smartness in this context is the ability to use that data effectively to improve efficiency. It is the ability to make accurate predictions by analyzing data and take automated decisions in real time. This is where Edge Intelligence holds the potential for transforming manufacturing.
How is edge intelligence making smart manufacturing possible?
The term ‘Edge’ is used for computing infrastructure that resides closer to the sources of data. This includes a range of connected devices, including sensors, motor drives, alarms and more. The term ‘IoT gateway’ refers to devices that are placed between the edge and the cloud – the IoT gateway serves as a connection point between the smart devices and sensors on one end, and the cloud and controllers on the other.
With more intelligence being shifted from the cloud to the edge, the role of the industrial IoT gateway will expand from being just a gateway to becoming an edge server integrated solution.
Edge Intelligence helps manufacturers to smartly process huge data sets generated by the sensors and turn it into actionable data which can be used for reducing commissioning time as well as accidents on site. Essentially, instead of sending all the data to the cloud, the edge device sensors process the data right at the source. This makes it possible for the sensors to enable real-time actions – incredibly useful in situations where even a delay of a few milliseconds can cause serious damage.
How can bringing AI and ML to the Edge benefit the manufacturing sector? Let’s take a look at a few examples.
1) Pipeline Safety
Pipeline safety is a primary concern for Oil and Gas manufacturers. IoT and edge computing technologies can help the industry deal with a number of challenges such as volatility of oil prices, pipeline safety, ensuring the safety of workers in the hazardous environment, monitoring remote assets and more.
Let’s consider the issue of pipeline safety. Pipelines are one of the most efficient ways of transporting large quantities of crude oil or natural gas. A number of factors can impact pipeline safety – human error, corrosion, metal loss, leakage or tiny cracks – which can lead to major breakdowns. Even a pinhole leakage, which can be easily missed during a virtual inspection, could become a serious issue over time.
To inspect and detect the corrosion on the surface of the pipe carrying oil & gas, a high-speed robotic scanner works as a great solution. It uses ultrasonic sensors and P.I.G (pipe inspection gauges), which notify the system about corrosion related defects. Cameras on the robot scanner identify and capture the details of defects such as corrosion, cracks or dents. The analysis of this data at the edge provides insights that are used to prevent future breakdowns.
2) Smart Warehouse
The management can improve warehouse efficiency by tracking assets in real time; assets include a range of equipment (e.g. forklifts) as well as staff. With the real-time availability of up to date information about the items’ location and nearest available forklift, the order-picking process can be improved. An analysis of the information about forklift movements in the warehouse can provide insights into how the material should be placed to minimize the travel time of forklifts.
But that’s not all – edge intelligence can also help make warehouse safer. For example, every year around 34,900 workers are seriously injured while 85 lose their lives in forklift accidents. In this case, not only are the operators are in danger, other people working near the forklifts are at risk too.
Operator inattention is the common cause of forklift accidents and it is a preventable issue. Wearable wireless sensors can be used to monitor fatigue levels of operators, suggesting rest periods. All this data can be processed at the edge in real time and can help trigger actions to prevent accidents.
Wearable sensors and data transmitters can also track employee movement around the warehouse, which displays the distance and the number of people in a given work area. Wearable tag scans the signals from employees and when this signal is closer to a forklift, and the driver gets notified when someone is close to his or her work area. So with edge analytics, hazardous situations can be identified before they happen by providing alerts to equipment operators.
3) Smart fleet management
Fleet (vehicle) management can include speed management, driver management, fuel management, vehicle financing, vehicle maintenance, vehicle telematics (tracking and diagnostics) and health and safety management. Fleet management companies, using IoT and edge computing, can remove or minimize the risks associated with vehicle investment, which further improves productivity and efficiency by reducing their overall transportation and staff costs.
In this case, using real-time data generated by edge devices which are fixed into vehicles – dashboard cameras, for example – can help the operator to monitor driver’s behavior in real time. This enables them to know where vehicles and drivers are at all times. By analyzing this data, potential problems can be identified/predicted and resolved before they become larger issues.
4) Smart metering
Traditional meters only measure total energy consumption but smart meters, which are internet-capable devices, record when and how most of the energy is consumed. Autonomous monitoring of electricity consumption needs a metering platform to record and process electric data.
Smart metering benefits utility companies by improving the customer satisfaction. Smart meters make it possible, both for the provider and the consumers, to automate and improve energy conservation. As consumers get more control over their energy usage and are able to save more money, they are happier with the utility providers.
By using edge intelligence, smart meters also give power consumption visibility all the way to the meter and back. This allows the utility companies to optimize energy distribution and take real-time actions to shift demand loads. Complex event processing is also possible in this scenario – it can be achieved by grouping the appliances.
As these examples demonstrate, edge intelligence is making it possible to deploy a range of smart factory solutions. Companies that are able to successfully implement such solutions will have an advantage over the competition. eInfochips is helping to develop analytical and engineering solutions for a wide range of domains, including Industrial IoT solutions, Energy Generation Equipment, and Actuation Systems.
To learn how we can help you with your edge intelligence project, contact us.
