A digital transformation begins by leveraging IoT and Industry 4.0 technologies to collect and analyze data automatically. This approach helps you make better decisions and optimize and automate production, making your factory smart.
In this article
You'll learn about Industry 4.0 and see an ideal example of a smart factory. We'll discuss:
If you want to learn more about smart manufacturing as a concept, read our article on Transforming Factory Floors for Smart Manufacturing. Otherwise, let's explore smart factories as they exist in the real world.
The fourth industrial revolution (aka Industry 4.0) is the digital transformation of any field, such as manufacturing or agriculture. It's characterized by implementing modern technologies, including IoT, cloud computing and analytics, AI, machine learning, and so on.
Simply put, the main goal of Industry 4.0 is to improve the efficiency of the production and quality of the product by using the most innovative technologies.
A smart factory equipped with these technologies gives you an unprecedented insight into what's actually going on. It creates a connected system of machines that feeds data into the cloud for analysis, unlocking all kinds of possibilities, from process optimization and predictive maintenance to factory automation, monetary savings, and even easy scalability for the entire operation.
We've identified four main technology groups leading the charge in creating smart factories. The list is by no means exclusive, but it will give you a general idea of what each technology does and why you should apply it on your factory floors.
IoT devices collect data from machines, such as cameras or robot arms, connect them to the network, and send information to the cloud. It's the backbone of any smart factory because it links all the pieces into one connected ecosystem. It also opens two-way communication with the machines, enabling their remote settings and management.
The main keywords here are real-time scalability, easy operation, and no upfront costs. The IIoT devices send a large amount of valuable data to the cloud that needs to be stored and analyzed. The cloud also nullifies the need to keep up with hardware costs and requirements, especially with such a large and variable volume of data.
Autonomous systems relying on AI and ML sift through the data, providing visibility into the processes and valuable insights. These systems can also send instructions to the IoT device without the need for human interaction.
Running advanced analytics on your data sets allows the data analysts to increase the effectiveness of the whole operation, decrease costs, and improve the final product.
Applying the principles and technologies of Industry 4.0, we can create an ideal smart factory. So, here is our vision of smart manufacturing in the near future.
Picture a factory floor for the manufacturing of solar panels. There are plenty of production lines equipped with robotic arms working autonomously. Several human operators are also present. They spend most of their working hours monitoring the processes and intervene only when a malfunction occurs or when the system recommends an inspection to prevent any issues down the line.
New parts for the panels, such as cover glass, electronics, or cables, are automatically ordered from the supplier based on the actual stock inventory and production plans. The IoT solution ensures that the warehouses always have enough inventory so the production line does not stop. Suppliers deliver the parts to the exact locations around the complex, where the new inventory is handed over to moving robots and taken to their assigned spots in the warehouses. The inventory is equipped with RFID tags or other technology that allows robots to identify it quickly. After the handover, the system's stock inventory is updated with the exact number of new parts. All this is done by autonomous robots that send information about the latest stock into the cloud with relevant data like timestamps or item codes.
Moving robots supply individual workstations with the required parts for assembling solar panels. Robotic arms take one part at a time and scan each item code to monitor the quality of the new batch and send feedback to the warehouse that this particular part has been used, meaning there's one less in stock.
An automated quality control (QC) solution checks every part before it's used in production. This particular solution is a set of AI-powered cameras with a built-in quality model that detects any deviations in the part's quality, including everything from its dimensions to structural issues like cracks. If a problem is detected, a notification is sent to the cloud, and the part moves to a scrap position for manual inspection. One system that runs in the cloud is a solution that monitors the scrap_rate. If the value exceeds the normal range, it sends a warning to the factory's control center and notifies the operator.
Every machine on the factory floor collects domain-specific (e.g., whether the part is OK or DAMAGED) and diagnostic data about the machine's performance (e.g., the temperature of the operating fluids). This data is sent to the cloud to be analyzed, classified, and sorted in real time according to its severity, ranging from INFO and WARNING to CRITICAL. By viewing the system dashboard, the operators see the actual state of the whole production as well as high-level metrics that serve as benchmarks. By comparing the two, the operators can identify trends and answer questions like: “Do we have more or fewer quality issues today than usual?”
If any problem is detected, the operators first try to solve it remotely because all machines are connected to the network. They can try to change the machine settings while it's in use, restart it, or get a complete set of diagnostics for a detailed analysis.
The last step in the process is an automated inspection of the assembled solar panels by the camera systems. These perform a visual and structural inspection to find any issues with the final product. If something is amiss, a picture is sent to the cloud for a remote inspection by the operators, who will decide if the solar panel gets a pass or is moved to the defect pile.
Finally, robots automatically pack, label, and move the finished solar panels to the expedition warehouse. And, if everything goes well, no human intervention is necessary during the whole process.
Let's answer the important question—how do you actually start creating a smart factory? Well, you can either recruit a team and give them a decade or two to develop an expert understanding of all those technologies, or we can get on board and start implementing the Industry 4.0 approach immediately.
Our expert team has years of experience executing similar projects, and Spotflow's offer includes:
Contact us today for a detailed proposal, and we'll introduce you to the future of smart manufacturing!
