Yesterday was analog - the future is digital
Yesterday was analog - the future is digital
The cloud is usually the first thing people think about when they hear the term Industry 4.0. However, the cloud is just the tip of the iceberg. The real strength of Industry 4.0 stems from digitization, which begins with connectivity. SICK has devised a five-step process to allow existing machines to become significantly more intelligent with very little effort.
Step One: Connectivity
Here is the truth of the matter: without sensors and connectivity, there is no data. Without data there is no visualization and transparency, and without digitization, there is no Industry 4.0. Therefore, thinking about future manufacturing should not start with the cloud, but with the sensors that enable everything else to run smoothly.
Sensors are at the forefront of collecting data from your processes. Keeping these networkable components connected and in tune with each other should be the primary goal of any company trying to reach Industry 4.0.
Step Two: Visibility
Once the sensors have gathered enough data, it must be compiled to determine what the machines are seeing. But this does not always have a clear answer. This step of digitization reveals new information that was initially unavailable.
An example of a visualization device is the FieldEcho Dashboard. Equipped with a modern, web-based graphical user interface, it can be displayed via a browser or integrated into the HMI of a machine. FieldEcho visualizes all configured IO-Link masters and connected IO-Link sensors or actuators and offers a detailed insight into the data, including alarm functions.
Step Three: Transparency
Once data has been gathered and visualized, transparency must be considered. Why did something happen? Why did the data form in such a way? When asking these questions, well thought-out software solutions will enable a greater understanding of the interrelations found in the data. With a tool like the FieldEcho, you can quickly draw conclusions from data records and events.
Here is an example of transparency in action: a sensor changes its signal. This is a sudden occurrence, and it immediately alerts workers that the sensor is in need of maintenance. Thus, the sensor can be cleaned quickly and sent back to work. Noticing too late that a component of production is in disrepair will become a thing of the past.
Step Four: Predictive Capacity
SICK’s application-oriented software packages make it possible to predict what will happen through the use of advanced analytics. Worried that a component might fail in the future? Plan regular maintenance intervals so they can always be kept up to date. We see airports utilizing predictability a lot with luggage.
Baggage Analytics ensures that luggage is accurately identified at the appropriate operating points, which makes identifying and correcting the path of misdirected luggage easier. Overall, this allows for an acceleration of the decision-making process, higher system performance, and improved supplier compliance… all thanks to simple data and visualization exchanges!
Step Five: Adaptability
The final step asks, “What autonomous responses are available?” The goal of adaptability is the self-optimizing of a business through the automated implementation of reactions or measures. This calls for innovative software solutions, like artificial intelligence (AI), which can continuously monitor and optimize a machine.
Although AI is still a long way off from taking over this step, SICK has developed several applications available today. Sensor intelligence relies on deep learning in image processing. Deviations from a learned image or process can be recognized by a machine without these errors having to be defined or characterized beforehand. This avoids time-consuming programming and opens the door for completely new possibilities.
Advice for Companies Interested in Industry 4.0
Jumping from analog to digital is not done in a snap. It takes time and careful consideration. This is why the cloud isn’t the central focus of this article.
Instead of looking at the clouds above the mountain, look at what makes up the base. It all begins with your machines’ sensors. Once step one is achieved, the next is easier to take. A small investment today will contribute significantly to the efficiency of your company.
