One of the biggest challenges in running industries is optimizing efficiency in each production process. Efficiency is critical in this fourth industrial revolution (industry 4.0) because it keeps production and running costs as low as possible. This, in turn, helps keep the output (products) highly competitive in the market (low pricing) to maximize profits.
HMI (Human Machine Interface) automation and IoT are important aspects of industrial optimization because they provide real-time monitoring and control of different machine metrics.
IoT sensors collect massive amounts of data from different points along the production process and introduce task automation. On the other hand, HMI gives operators control and access to this data, including warnings/alarms, operational performance, fuel level, etc. Here’s how this combination is effective in industrial applications.
The Role of HMI in IIoT
The industrial Internet of Things creates a network incorporating sensors to collect data for analytics purposes. It can also have controllers in the network that users can control manually or the edge device can run autonomously based on sensor input.
However, operators need to have an eye on the internal machine operations, and HMIs provide this access in the following ways.
- Providing dashboards with curated data visualizations
- Contextualizing insights into various KPIs, such as production yield and quality
- Analyzing trends and performance stats across connected machines
- Alerting users/technicians on possible upcoming issues based on IoT predictive analytics and AI (machine learning)
- Enabling remote machine configuration and control to modify the production processes based on IoT analytics
HMI (Human Machine Interfaces) vs. PLC (Programmable Logic Controllers) vs. SCADA (Supervisory Control & Data Acquisition)
HMIs, PLCs (Programmable Logic Controllers), and SCADA (Supervisory Control & Data Acquisition) systems are closely related but are different components in industrial control systems.
Human Machine Interfaces convey data from the machine to the user and back. They provide an interface for information output and user inputs for control or configurations, but they do not collect or record information, nor do they connect to databases to store the data.
On the other hand, SCADA refers to industrial control systems that handle the complex backend processes involved with controlling and capturing data from sensors. Therefore, HMIs can operate alongside or as part of SCADA, providing analytics from SCADA and user feedback (manual controls) back to the system.
However, HMIs operate more effectively with PLCs because they lack sufficient processing power. These controllers receive sensor data, process it, provide outputs, and transmit data to the HMI. PLCs also execute the complex control algorithms that come from the user via the HMI.
Typical HMI Automation and IoT Setup
You might be wondering where IoT comes into the industrial control system when HMIs, PLCs, and SCADA systems seem to handle everything. Well, IoT works together with SCADA to acquire data specifically for analytics purposes.
Analytics shows you how you can enhance operational efficiency without using guesswork. IoT also introduces automation when using powerful edge computing hubs. SCADA, on the other hand, provides real-time monitoring and control, with HMIs providing an interface into these operations.
In this HMI and IoT setup, we’ll use a Dusun Modbus gateway, which provides half-duplex serial communication to implement the Modbus protocol via an RS485 interface. This half-duplex communication creates the SCADA system network to control and gather data from different end nodes.
A hub like the DSGW-081 NXP i.MX6 ULL industrial edge computing gateway can convert serial data in the industrial automation and control network provided by the Modbus protocol (RTU) into Modbus TCP packets to transmit data to the HMI and back.
The gateway also provides easy and secure access to PLCs via Modbus to enable the HMI to operate more effectively. Since it is an edge computing hub, you can use this power to automate some of the industrial processes based on sensor data. On the WAN side, the gateway sends data to the cloud for analytics, and it supports industrial cloud platforms like AWS and Azure.
The HMIs you can use in this industrial IoT solution can be either of the following.
- Centralized control panels
- Computers
- On-machine control panels (built-in screens)
- Mobile device interfaces (usually tablets)
Importance of HMI Automation in IIoT
Introducing automation functions in the edge device sort of automates the HMI because it provides control instructions if the sensor data indicates conditions have exceeded the threshold. This automation eliminates some human control and has several benefits, including.
Scaling Optimization
HMIs make it easy to manage multiple machines and industrial processes from a single point. Introducing automation via edge computing makes it possible to include and control more machines to optimize their operations. IIoT can identify idle resources and scale production appropriately based on the demand data to reduce time and resource wastage.
Increasing Employee Productivity
Automatic reconfiguration/recalibration of industrial processes ultimately increases productivity because fewer people will be required to man the machines. Some gateways even provide AI computing, which enhances data processing and analytics on the edge to make more intelligent optimization decisions on the fly.
Helping Reduce Maintenance-Related Costs
HMI automation via IoT edge computing can shut off machines if they are operating roughly or outside the recommended parameters. For instance, if pumps vibrate excessively or engines are running low on oil due to leakages, the gateway can initiate shutdown sequences to avoid costly damages and alert the relevant technicians to check out the issue. Without automation, technicians must access the HMI physically to turn off the machine.
Improving Safety
When hazardous conditions occur in factories, such as fuel and chemical leaks, HMI automation using IIoT can shut off the fluid flow immediately to keep the issue under control, making the workplace safer. This response is better than waiting for an operator to shut off things like pumps manually from the traditional HMI.
The Future of HMI Automation and IoT
Tighter AI integration
HMI and IoT combine to provide insights into key performance indicators in industrial processes. AI boosts this performance to augment operators with better insights and more accurate predictions. Additionally, AI improves automation to make the industrial processes run optimally without the need for human input for recalibration every now and then.
Modbus IIoT gateways can provide AI computing at the edge to reduce latency when automating tasks or providing data insights. A classic example is the DSGW-380 RK3588 industrial AI edge computing gateway, which is compatible with various neural network models and offers 6 TOPS of computing power.
Embedded VNC Server For Opening Up Traditional HMIs
Traditionally HMI are pretty basic and feature closed systems that limit the available operating options. Instead of spending loads of money to upgrade these Human Machine Interfaces, it is cheaper and less labor-intensive to link them to VNC (Virtual Network Console) smart boxes.
These boxes are embedded with a VNC server service, which enables HMIs to be VNC viewers. HMIs access them via TCP/IP (ethernet).
VNC boxes introduce more hardware interfaces to the HMI for peripheral connections to meet emerging user needs. They also allow in-depth secondary development and users to transplant applications in them without affecting the HMI’s system resources.
In a nutshell, these boxes make HMI devices smarter, and you should consider the DSGK-060 IoT VNC smart box for this task. This enhancement features a built-in 1 TOPS NPU to enable lightweight AI computing on the edge and a quad-core ARM Cortex-A55 RK3568, which you can use to implement HMI automation.
The box supports WiFi and ethernet backhauls for cloud connections to enable remote device control and data viewing. This feature is quite useful because users can use it for off-site system control to manage critical installations after working hours.
Direct Integration with Mobile Devices and Wearables
Modern mobile devices, wearables, and other personal devices like tablets carry immense processing power and have intuitive touchscreen interfaces. These can provide off-site system control using software applications.
Cloud HMIs
Cloud-based HMIs are basically web-based HMIs, and they provide the same remote monitoring and control benefits as mobile-based HMIs. But cloud computing has the advantage of having superior processing power and analytics based on technologies like machine learning.
Edge HMIs
Even as cloud HMIs become popular, edge interfaces are in high demand because machine operators want to access data visualizations directly from the machines in the field. Therefore, control and analytics capabilities will be kept both at the local and cloud levels.
Augmented Reality and Virtual Reality
HMIs in the current era are mostly touchscreens, but AR and VR are bound to change that. These technologies free up the operator’s hands, provide better contextual guidance to reduce the chances of making mistakes, and eliminate distractions that can cause safety risks when making adjustments.
AR is better as an onsite HMI because it can augment the projections with the industrial equipment and machines on the ground. But VR is more suitable for off-site HMIs because it can project the virtual industrial environment to show users the telemetry data for each machine and the effect of adjusting the parameters as if they are onsite.
Conclusion
HMI automation and IoT are critical in the modern industry because they introduce efficiencies that lower costs and make the price of the outputs more competitive in the market.
When selecting an IoT gateway that is ideal for this solution, there are 4 key factors to consider. The first is SCADA support via RS485 or RS232 for machine monitoring and control. IIoT hubs should also convert the Modbus protocol from RTU on the sensor network to TCP on the HMI side, provide edge computing power to enable automation, and have backhauls for cloud connection for analytics purposes.
AI computing power is necessary, as well, to make the edge provide analytics and better decision-making.
Considering these requirements, the DSGW-380 RK3588 industrial AI edge computing gateway ticks all the boxes, but you can also check out these other Modbus hubs for comparison purposes. In addition to the gateway, you can make HMIs smarter and increase their hardware interfaces using our DSGK-060 VNC box, which is programmable and has 1 TOPS of neural processing power.
Developing this solution needs lots of technical considerations, and we have a team ready to help you build an all-round solution at the lowest cost. Get in touch with us to get started today.
