1. Determine the status quo — based on data and in real time The basis of any successful optimization is an accurate analysis of the current situation. Traditional methods such as value stream analysis, which visually depicts the flow of materials and information in a production process, provide important initial insights - but they are usually based on static or historical data.
True visibility, however, comes from the continuous collection of real-time data that instantly identifies variances and bottlenecks, enabling data-driven decision making.
Here aiomatic plays a central role: Our
Predict package makes it easy to identify patterns and anomalies that are hidden from the human eye. This provides a deep understanding of how machines are actually performing. As a result, companies can make informed decisions to reduce downtime, speed up processes and better utilize resources - without major changes or new IT infrastructure.
Another option is our
Retrofit & Predict package with our partner KSB: Existing machines can be quickly and easily retrofitted with the latest sensors - regardless of manufacturer or year of manufacture. We automatically collect data on cycle times, downtimes, temperature curves and vibrations in real time.
2. Define goals — rely on data With this visibility, measurable goals can be derived. These can include, for example, increasing production speed, reducing the scrap rate or reducing energy consumption. Clear objectives make it easier to measure success and focus on the most important areas of optimization.
In a customized
Workshop we help you to clearly define your requirements and develop an individual strategy. Together, we will clarify the technical integration of our software into your existing infrastructure and prepare the implementation and project plan. This workshop lays the
foundation for a clearly structured project process that ensures all objectives are met efficiently and on time. In addition, our intelligent
Dashboard the basis for fact-based decisions and clear priorities for further process optimization.
3. Derive measures — targeted, scalable and future-oriented Depending on the status quo and defined goals, concrete measures for process optimization are developed:
In addition to improving production processes, the solution also contributes to more efficient resource management. By accurately predicting maintenance needs and downtime, companies can deploy resources in a more targeted and efficient manner, reducing costs and making better use of existing capacity, while improving internal communication through intelligent process analysis.
With all relevant data available in real time, teams can make decisions faster and more transparently, leading to better collaboration across all departments. "Successful process optimization is based on a structured approach - from initial analysis to sustainable implementation.
Digital technologies such as those from aiomatic help to make each phase efficient and data-driven.
.avif)
