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Description
The first and most essential phase of digital transformation is informatization. In this phase, different IT technologies, stand-alone devices, and other systems are used separately within the company. This phase is characterized by IT being already well advanced and is mainly used to perform repetitive tasks more efficiently.
Benefits
Informatization brings significant benefits that are now taken for granted. Computerization makes it possible to produce cheaper products that offer a higher standard and a certain level of precision, without which it is impossible to have the kind of products we know today.
Features
In the phase of informatization, many machines can be found without a digital interface. This is especially true for devices with long cycles or manually operated machines. Computer numerical control machines characterize the first phase of digital transformation. Still, CAD data must, in the vast majority of cases, be manually entered into the machine system or uploaded manually to the system.
Example
The central computer numerical control allows the CNC machine exact machining of the piece. The CAD documents contain information describing the path and use of the tool. The machines are not connected to a network, there is no connection to the device, and there is no possibility to automatically upload CAD data to the machine.
Description
The second phase of the digital transformation is, as the name implies, focused on the deployment of components that provide connectivity between different IT technologies. In this way, the company's applications and systems are interconnected but still not fully integrated.
Benefits
As the Internet Protocol allows standardized communication, sensor technology can enable data capture and information transfer between different systems. This way, remote maintenance, monitoring of production status, obtaining data on product usage by the end-user are available.
Features
In the connectivity phase, it can be seen that part of the operational technology (OT) is linked to the information technology (IT). The primary technology used in this phase is IIoT technology, which integrates different systems, devices, and machines.
Example
At this stage, it is possible to send the CAD document to the CNC machine for processing directly from the application that is intended for the development of the new product. Once the operation is completed, it is recorded in an automated way via the MES system, and the final work order data is sent to the ERP system.
Description
In this phase, sensors capture data from the entire process, from start to finish. The falling prices of sensors, microchips, and network technology mean that all events can be recorded in real-time at this stage.
Benefits
Real-time data allows the digital data model of the factory to be updated or aligned with the actual state of the factory at any time. This combination brings significant benefits where information is available at the right time in the right place.
Features
Before the visibility phase, it is acknowledged that the company has some data available, but this data is not fully collected and is mainly decentralized in individual silos. Only a few employees have access to these silos, and broader use of this data is restricted or even prohibited. To achieve the agility offered by technology, it is undoubtedly characteristic of this phase that information is made available to a broader group of employees when they need it, in the form they need it.
Example
The CNC machine operator has selected information, documentation, and files available when he needs them for his work. On the other hand, the development staff can monitor the machine parameters through simulations and thus design an optimized product without initial test runs.
Description
If the main purpose of the previous phase is to create a data digital twin, the main purpose of phase 4 is transparency.
This understanding is based on verifiable data, where sophisticated analysis can be used to identify the causes of a condition or to answer why something is happening.
Benefits
Real-time data and advanced analytical tools allow employees to obtain critical information for further decision-making. And these advanced analytics deliver significantly faster response times to external and internal production events.
Features
We are talking about big data and extensive data analysis at this stage.
This mass of data is impossible to process with conventional business analytics, which is why "big data" encompasses large volumes of data and new innovative technologies and applications that enable fast and efficient analysis of this data.
Example
Applications and technology for monitoring big data are used in parallel with ERP and MES systems.
These applications thus provide comprehensive data analysis that can be used to monitor and analyze the condition of the machine and equipment or to monitor in detail various parameters on the device (for example, spindle load in a CNC machine, tool consumption monitoring, pressure monitoring).
Description
In the anticipation phase, the stage of predicting specific events in advance is a reality that can be implemented with the help of advanced simulations and artificial intelligence.
Benefits
Event forecasting can optimize the production process to the extent that unexpected bottlenecks are properly avoided. Artificial intelligence can predict expected outcomes based on the data collected and suggest different scenarios to optimize.
Features
This phase is characterized by the ability to anticipate certain events that could drastically affect the production process, thereby damaging the final business results.
Example
AI can be used to analyze the data collected from the CNC machine. This data includes detailed parameters on the machine's operation and the functioning of critical machine components. Predictions can predict when a part of the CNC machine will need to be replaced, thereby shifting the proportion of unexpected downtime to a balance of planned downtime.
Description
The flexibility phase is a fundamental requirement for automating activities and automated decision-making. Continuous adaptation allows a company to hand over certain decisions to artificial intelligence so that the system can adapt more quickly to changing business environments and market demands.
Benefits
The degree of flexibility is determined by the complexity of the decisions, which may be sufficiently automated with sophisticated technology so that the system adjusts to changes on the fly. In this way, production plants will become supercomputers that convert primary material into the product through autonomous decision-making.
Features
If manufacturing companies want to maintain their competitive edge, they will have to adapt to market demands, becoming more flexible. The only way to achieve this is to embark on a digital transformation process, which involves the introduction of new technologies and changes in the way we think and see what manufacturing is.
Example
The central computer numerical control allows the CNC machine exact machining of the piece. The CAD documents contain information describing the path and use of the tool. The machines are not connected to a network, there is no connection to the device, and there is no possibility to automatically upload CAD data to the machine.
Why choose us?
Explore what digital transformation makes possible
With extensive experience, numerous references, and in-depth knowledge in engineering, automation, computerization, and integration of various solutions, we help you build the infrastructure for an efficient digital transformation of your manufacturing company.
Capturing data
Automatic data capture from machines, lines and devices.
Digital production
Advanced visualization of standard procedures.
Paperless production
Digitization of the production process and documentation.
Predictive manufacturing
Predictive analytics and intelligent scheduling.
Your partner on the digital transformation journey
Embark on a digital transformation of your processes
Process transformation means moving from traditional processes to more efficient digital systems that can dramatically increase efficiency and improve all aspects of operations.
A leading methodological approach to complex digital transformation processes is phased to make it more manageable and transparent.
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We have integrated more than 1 million signals into various production management systems MES and IIoT implementations.
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