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German provider of cutting-edge solutions for AI driven digitalization is looking for partners from the manufacturing industry using aluminium die casting to further develop the technology under a technical cooperation agreement

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TODE20210315002
Publicado:
29/03/2021
Caducidad:
30/03/2022
Resumen:
A German start-up specialised in artificial intelligence (AI) driven digitalization of manufacturing companies has developed a cutting-edge AI solution for visualization, monitoring, and predictive analytics in real-time. The company is looking for manufacturing companies which are using aluminium die casting as a process to jointly finalize the solution for a market entry. Partners for this technological cooperation agreement should be based especially in the DACH region.

Details

Tittle:
German provider of cutting-edge solutions for AI driven digitalization is looking for partners from the manufacturing industry using aluminium die casting to further develop the technology under a technical cooperation agreement
Summary:
A German start-up specialised in artificial intelligence (AI) driven digitalization of manufacturing companies has developed a cutting-edge AI solution for visualization, monitoring, and predictive analytics in real-time. The company is looking for manufacturing companies which are using aluminium die casting as a process to jointly finalize the solution for a market entry. Partners for this technological cooperation agreement should be based especially in the DACH region.
Description:
The German start-up was founded in 2019 by experienced engineers who have worked for renown organisations such as the NASA and has developed AI solutions to cope with production challenges within the manufacturing industry. The young company was awarded as one of the best eight companies within the AI industry among 490 European companies applying for the European Data Incubator under Horizon 2020.
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The German provider offers a state-of-the-art smart factory and digital twin software. Based on machine learning the user will get real-time predictions of products´ quality and potential machine failures. Prescriptive dynamic recipes give concrete¿recommendations for optimal process parameters. All this is visualized in user-oriented and customizable dashboards.¿

The solution aims to address the specific challenges of the die casting industry, which is currently facing, as per market research, challenges such as:
1. For every kg of aluminium
a. 1-2% is lost as unrecoverable dross
b. 15-25% is recycled
c. 73-84% makes it to good products

The losses incurred in this process are:
a. Metal loss (dross)
b. Energy lost in furnace and recycling the materials
c. Loss in value of recycled material

2. Defects, porosity -Y- insufficient filling account for approx. 70,000 -Y-euro; financial loss per 5K ton of metal melting

3. Failure to improve the quality of the production at affordable prices

Based on those challenges the innovative software solution for low pressure die casting consisting of AI and ML (Machine Learning) algorithms, provides predictive analysis and Overall Equipment Efficiency (OEE) Key Performance to address those problems regarding the following Key Performance Indicators.

These KPIs are visualized in the German provider´s solution as follows:
1. Predictive Analysis KPIs
a. Average Time to Produce
b. Average Labour Cost
c. Overall Average Defects
d. Average Changeover Time
e. Down Time
f. Average Man Hours
g. Average Production Time by Product
h. Average Defects by Product

2. OEE KPIs
a. Quantity
b. Rework Quantity
c. Labour Cost
d. Service Time
e. Tooling Costs
f. Material Costs
g. Runtime vs Downtime
h. Availability
i. Performance Cost
j. Quality
k. OEE - Availability × Performance × Quality
l. Power Consumption
m. Energy Consumption

The solution runs as part of the German provider´s smart factory offer but it can also be integrated into any existing third-party smart factory solution. It can function on cloud and on premise in customer landscape providing highest level of Data security and flexibility. The solution is ready for demonstration as there already a working system for low pressure die casting at customer premises (TRL 7).

Solution features
1. Real-time¿process¿monitoring
2. Component¿quality¿prediction
3. Scrap root-cause-analysis
4. Global root cause analysis
5. Determination of optimal process -Y- machine settings (dynamic recipes to minimize scrap)
6. What-If analysis for effect assessment of process -Y- machine setting changes
7. Tweaker functionality
8. Secure¿access¿to¿software¿for¿all¿users
9. Customizable dashboards for visualizing the output
10. Notifications¿and¿communication¿function¿via Teams, Outlook,¿Slack¿and SMS
11. Self-learning¿models¿to¿capture¿inconsistencies¿
12. Software¿can¿be¿installed¿on-premise or¿on¿the¿cloud

The German company is looking for manufacturing companies especially in the DACH region which are using aluminium die casting as a process, for a technical cooperation to finalize and scale the solution regarding low pressure die casting solution using AI and ML.

The partnership is envisaged as a mutual collaboration deploying the cutting-edge technology and the manufacturing experience of the partner. The German provider is open for a co-development of a new product or idea using their expertise with AI/ML technologies and the manufacturing domain experience of the partner.
Advantages and Innovations:
The innovative technology developed by the German provider has relevant characteristics and applications such as: connection to standard hardware bus system -Y- IT systems; connection to standard databases; algorithms for data clean-up, anomaly detection, univariate timeseries forecasting, multivariate training; features like lag analysis, tweaker, confidence level of action items; supports with unified APIs, detailed documentation, and interactive examples.

The end-to-end solution has the following components:

1. Edge devices for data extraction
2. AI/ML Engine predictions
3. Visualization/Reporting for 360 view of the complete manufacturing process (predictive -Y- OEE KPIs)

The software monitors processes in real-time, predicts the quality of the casted products, determines the root-causes of failures, and gives specific recommendations for optimal process parameters. This enables to optimize the Overall Equipment Efficiency and reduces operational costs while bringing technological innovation and a smaller environmental footprint.

The German provider is very confident that such smart and technological advanced solution for low pressure die casting does not exist in the market with a Return of Investment (ROI) that the young company has already proven.

Benefits

1. Completely automated digital -Y- smart solution
2. Installation and configuration of the software within hours
3. Highly secure covering all necessary data governance rules
4. Increase¿yield¿and OEE¿of¿casting¿operations
5. Reduce¿scrap¿by¿up¿to¿66% and¿improve¿the¿environmental¿footprint
6. Ensure¿a¿stable¿quality,¿minimize¿Cost of Poor Quality (COPQ) and¿customer¿rejections
7. Reduce¿time and¿needed¿resources¿for¿manual¿analyses
8. Proven benefit of up to 95,000 EUR per production line (based on a past customer project)
Stage of Development:
Available for demonstration
IPs:
Trade Marks,Copyright

Partner sought

Type and Role of Partner Sought:
The German start-up is looking for manufacturing companies, which are using aluminium die casting as a process, for a technical cooperation to finalize and scale the low pressure die casting solution using AI and ML. If the partner has already implemented a smart manufacturing solution it can be enhanced with the AI/ML technology from the German start-up. The young company will integrate their solution with the existing smart manufacturing solution and create a seamless experience for the users.

Through this collaboration the partner can benefit from the AI technology for its digitalization processes as well as being more sustainable while using its resources more efficiently. The German provider will bring the technology and the partner its manufacturing domain expertise.

The partner is expected to have the following tasks:

1. Provide historical data from die casting manufacturing process
2. Provide existing manufacturing challenges and expectations of improvement
3. Feedback about the technology output
4. Use the technology in their production landscape

Client

Type and Size of Client:
Industry SME 11-49
Already Engaged in Trans-National Cooperation:
No
Languages Spoken:
English
German

Dissemination

Restrict dissemination to specific countries:
Austria, Germany, Switzerland

Keywords

Technology Keywords:
01003003 Artificial Intelligence (AI)
01001001 Automation, Robotics Control Systems
02003001 Process automation