Leistungen
Conception and Implementation of Digital Products
We provide our clients with comprehensive support in developing digital products, from strategic consulting on data-driven business models to industrial implementation.
At the heart of our service is the identification and implementation of data-driven use cases: Predictive Maintenance, alarm sequence analysis, Predictive Quality and smart assistance systems are the key to developing innovative digital business models.
In addition, added value such as time and cost savings, waste reduction, process transparency and improved planning are already being generated along the way.
We meet you where your company currently stands on the path to the digital future:
- Do you want to start with a consultation on what is sensible and feasible in terms of data?
- Would you like us to drive forward your generation of ideas via Design Thinking?
- Can we support your data collection?
- Do you require an assessment of potential for your project?
- Should we tackle your specific use case directly?
Give us the go-ahead!
Data-based Business Models
Your data has added value. Which use case is yours?
Optimized Maintenance Intervals
Predictive Maintenance prevents unplanned downtimes, optimizes maintenance intervals as a maintenance strategy, and enables the efficient provision of the required spare parts.
Predictive Maintenance for High-Performance Pumps
ABEL Pump Technology
After evaluating the use case based on an exploratory analysis of existing data samples, physical and technical models were developed for condition and efficiency monitoring of the pumps, which already provide usable added value, such as detailed alarm emails or automatically generated performance reports.
Subsequently, AI models were developed for live condition monitoring, which differentiate between perfect pump operation and frequently occurring error patterns in the field and also recognize the actual extent of a defect. This allows maintenance intervals to be postponed by up to 30%.
Bleeding edge AI processes are being used to detect the development of a fault pattern even before this is possible during operation or through visual evaluation of the data by experts. This makes it possible, for example, to predict the failure of a component in the future.
Replacing wear parts can therefore be carried out at a time that is favorable for operation: Unplanned downtime of a critical component and the associated high downtime costs are avoided. Operators benefit from significantly more operational safety and reliability.
Avoid Machine and Plant Downtimes
Alarm sequence analysis is based on alarm data that is often overlooked but can help classify downtime. As a result, unwanted machine and plant downtime can be avoided.
Alarm sequence analysis enables a wide range of insights, which we visualize and make usable, e.g. by way of dashboards. The demo illustrates the possible look of such dashboards.
Setting Recommendations for Machine Operators
Smart assistance systems guide machine or plant operators based on the respective operation. These smart assistants give recommendations to optimize recipe or production settings and enable live monitoring.
Data-based Assistance System for Film Extrusion
Windmöller & Hölscher
Situation
Film extrusion is a complex process with numerous parameters and various influences. Setting up stable production is not trivial.
Goal
Users should be ideally supported during production in order to increase quality and reduce rejects.
Challenges
- Setting up a stable production process requires a lot of experience and intuition.
- There is not one obviously ideal setting for any product.
- Some customers manufacture a vast variety of products.
- Due to the wide variety of material and production parameters, it is difficult to identify identical products.
Solution
An AI-based assistance system analyzes correlations in the production process. Parameter settings are simplified and waste is reduced. This project was implemented in an agile manner from PoC to productive solution in around one year.
Reveal Bottlenecks in Processes
Process mining enables the analysis and visualization of processes and individual process steps. We use it to uncover bottlenecks and optimization potential. This way, optimizations may initially be implemented as simulations and tested digitally.
Exemplary process visualization
Anomaly detection
Increasing Production Quality and Output
Predictive Quality allows to draw conclusions on the final quality of the product already during the manufacturing process and prevents the recurrence of known quality defects. If necessary, operators can intervene in the process at an early stage, take countermeasures and minimize rejects in the long term.
Making Process Data Visible and Tangible
Condition monitoring provides insight into processes and machines and can be offered as a service to customers via the store floor. The relevant data is made available to the user both live and historically and forms the basis for further use cases.