General definition What does process automation mean?
Process automation refers to the use of technologies for the extensive or complete automation of recurring procedures and tasks within business processes. The aim is to increase efficiency, reduce errors and save resources. Automation is becoming increasingly important in manufacturing in particular, as production processes are complex and often place high demands on precision, speed and quality.
Automation in production
The automation of manufacturing tasks involves the use of machines, robots, control systems and sensor technology to optimise production processes. Manual activities are replaced by automated processes that are able to precisely process, assemble, inspect or transport workpieces. A key advantage is the improvement in productivity thanks to shorter cycle times and the ability to carry out complex and repetitive tasks around the clock.
Modern production lines are often equipped with PLCs (programmable logic controllers) that control and coordinate process steps. They are supplemented by robots that can flexibly perform various tasks. The integration of IoT sensors also enables real-time monitoring and control of production processes, which leads to greater process reliability.
Three main types of process automation can be distinguished: Types of process automation
Simple process automation
In this variant, a clearly defined process already exists before the automation, which provides either only one possible or one optimum path. A typical example of this is the conveying of components or palletising with a robot.
Control-based process automation
In this case, there is no fixed sequence, but the individual process steps and their order depend on various conditions and decisions. One example of this is the production of different vehicle derivatives, where the procedure varies depending on the vehicle type (convertible, saloon, estate car, etc.).
Intelligent process automation
This form is used for particularly complex processes with many exceptions. Artificial intelligence (AI) is often used here to make automated decisions even when the previously defined rules are no longer sufficient. The use of robotic process automation (RPA) with machine learning processes significantly expands and improves automation.
Advantages of process automation in production
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Increased efficiency: Automated systems can work continuously and with consistent quality.
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Cost reduction: Production costs are reduced due to lower personnel costs and the minimisation of errors.
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Quality improvement: Automated processes are less susceptible to human error and ensure consistently high product quality.
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Flexibility: Modern automation solutions can often be quickly adapted to new product variants or process changes.
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Safety: Dangerous or unhealthy activities can be avoided through automation.
Automate your production Process automation with FFT
Process automation requires careful planning, as it involves both technical and organisational adjustments. We at FFT have over 50 years of experience and are happy to support you in automating your production.
the FFT DataBridge solution Automation of digital processes
In addition to production, the automation of digital business processes is also becoming increasingly important. IT-supported processes, for example in personnel administration, accounting or customer management, are automated using software (robotic process automation, RPA). This type of automation is particularly suitable for recurring and complex tasks.
The FFT DataBridge solution enables manufacturing companies to transfer production data to the cloud securely, scalably and efficiently. This solution is aimed at production managers, data engineers and IT managers and addresses common challenges such as data silos, limited transparency and inefficient analyses.
With a standardised interface architecture, it connects manufacturing systems directly to the Snowflake AI Data Cloud. Customers benefit from real-time analyses, AI-based forecasts and reduced downtime. The solution delivers measurable added value through faster decision-making, higher data quality and optimised IT costs - an important factor for data-driven intelligent manufacturing.
Challenges and future prospects
Implementing process automation in companies is often a complex task that goes beyond mere technical realisation. Thorough preparation is essential to ensure long-term success.
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Organisational adjustments:
Automation changes existing processes and work roles. Processes often have to be redesigned so that they can be optimally automated. This requires close co-operation between specialist departments and IT. -
Employee training:
The workforce must be prepared for dealing with new technologies. This includes both the operation of automated systems and the adaptation of working methods to changed processes. -
Cost factors:
In addition to the acquisition costs for hardware and software, ongoing maintenance and support costs also need to be considered. Investments in automation technology should therefore be carefully planned and calculated. -
Change management:
Acceptance by employees plays an important role. Changes can cause uncertainty, so transparent communication and employee involvement are crucial.
As technology advances, new opportunities are opening up to make process automation even more efficient and flexible.
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Artificial intelligence (AI) and machine learning:
These technologies enable automated systems to learn from experience, recognise patterns and make decisions even in unforeseen situations. As a result, complex and varied processes can be better mapped. -
Advanced robotics:
Modern robots are becoming ever more flexible and are increasingly able to take on complex tasks in addition to standardised tasks. This leads to even higher productivity and process quality. -
Real-time data analysis:
The combination of automation with real-time monitoring and analysis of process data enables a rapid response to deviations and optimisation potential. This increases efficiency and reduces downtime. -
Integration in Industry 4.0 and smart factory concepts:
Networked production plants in which machines, people and IT systems work together intelligently represent the next evolutionary stage of production automation.
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Send us your concept idea, your automation requirements or a description of your production process that we can support you with.
We look forward to presenting our standardized portfolio to you, but also to developing new solutions together with you.
