Summary
- Profile Type
- Technology offer
- POD Reference
- TONL20241125012
- Term of Validity
- 2 December 2024 - 2 December 2025
- Company's Country
- Netherlands
- Type of partnership
- Commercial agreement with technical assistance
- Targeted Countries
- All countries
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General information
- Short Summary
- A Dutch SME specializing in advanced software development offers an innovative AI-driven quality management solution tailored for the manufacturing industry. This technology utilizes machine learning, real-time analytics, and customizable workflows to optimize quality control, reducing product defects by up to 40% and increasing productivity by 25%. The SME seeks commercial partnerships with technical assistance to implement the solution across European manufacturers.
- Full Description
-
The Dutch SME has developed a highly innovative quality management software that leverages artificial intelligence and machine learning to optimize production processes. Designed specifically for the manufacturing industry, this software uses real-time data analytics and physics-informed neural networks to detect and predict quality issues proactively. By incorporating domain-specific knowledge into AI models, it delivers precise predictions, ensuring better quality control and significant operational savings.
A key innovation of this solution is the use of physics-informed neural networks, which incorporate physical laws and domain knowledge into the AI models. This approach enhances the overall performance and accuracy of the AI models, leading to more reliable predictions and better quality control outcomes. By integrating physics-based constraints, the software can model complex manufacturing processes more effectively than traditional AI methods.
The software integrates seamlessly with any standard data source, such as OPC UA, OPC DA, SQL databases, APIs, and file reading systems, eliminating the need for additional hardware investment. This flexibility ensures that manufacturers can connect the software to their existing data streams without requiring new infrastructure, reducing implementation costs and complexity.
Deployment options are versatile, catering to different organizational preferences. The software can be installed on local systems for companies that prefer on-premise solutions, deployed to the cloud for remote accessibility and scalability, or provided in a packaged PC environment that operates independently, avoiding interference with local IT infrastructure.
The platform continuously monitors production metrics, collecting data from various stages of the manufacturing process to detect deviations promptly. Utilizing physics-informed neural networks and machine learning algorithms, it learns from historical data to predict potential defects, enabling preventive actions that can reduce product defects by up to 40%. This enhancement in product quality significantly reduces waste and rework costs.
Customizable workflows allow manufacturers to tailor quality control processes to their unique environments. The software automates compliance checks against industry standards and regulations, ensuring that products meet all necessary requirements without manual oversight. The user-friendly interface, featuring intuitive dashboards and comprehensive reporting tools, facilitates ease of use for all team members, from floor operators to management.
Implementing this software has been shown to increase overall productivity by up to 25%, as it streamlines quality management processes, saving time and resources. It lowers production costs by minimizing waste and improving process efficiency, contributing to a better bottom line.
The company offers comprehensive technical assistance, including installation support, staff training, and ongoing maintenance services, ensuring a smooth integration of the software into existing systems. The solution's scalability and customization capabilities make it suitable for small enterprises as well as large corporations. - Advantages and Innovations
-
The software's integration capabilities have significant advantages. By connecting seamlessly to any standard data source, it eliminates the need for additional hardware investment, leading to cost savings and easier implementation. This interoperability ensures that the software can fit into diverse manufacturing environments with varying legacy systems.
An innovative aspect of the solution is the use of physics-informed neural networks. By embedding physical laws and domain-specific knowledge into the AI models, the software achieves higher accuracy and reliability in predicting quality issues. This approach allows for better modeling of complex manufacturing processes, leading to more precise detection of anomalies and potential defects. The enhanced performance of the AI models translates into more effective quality control and significant reductions in defect rates.
Deployment flexibility is another advantage. The solution can be deployed on the cloud, on local systems, or provided in a packaged PC environment, depending on the company's preferences and IT policies. This flexibility allows companies to adopt the solution in a manner that best fits their operational needs and constraints.
Predictive analytics utilizing AI and physics-informed neural networks allow the software to forecast quality issues before they occur, enabling companies to take proactive measures. This can lead to up to a 30% reduction in quality-related expenses. The software integrates with existing enterprise systems such as ERP and MES, ensuring minimal disruption during implementation.
By automating compliance checks, the solution reduces the risk of non-compliance penalties by up to 95%. The user-centric design focuses on ease of use, encouraging widespread adoption across the organization and reducing the learning curve. - Stage of Development
- Already on the market
- Sustainable Development Goals
- Goal 12: Responsible Consumption and Production
- Goal 9: Industry, Innovation and Infrastructure
- IPR status
- Secret know-how
Partner Sought
- Expected Role of a Partner
-
The SME seeks manufacturing companies, technology integrators, and industry partners across Europe to engage in a commercial agreement with technical assistance. The ideal partners are those looking to enhance their quality control processes and willing to collaborate closely during the implementation phase.
Partners are expected to adopt the software within their manufacturing operations, working closely with the SME to integrate it into their existing systems without the need for additional hardware. They will collaborate on customizing the software to meet their specific operational needs, including integration with preferred data sources and selecting suitable deployment options. By providing performance data and feedback, partners will contribute to the ongoing development and enhancement of the software, ensuring it remains at the forefront of industry needs. They will work jointly with the SME to establish key performance indicators (KPIs) to measure the success of the software implementation, such as defect rate reduction, productivity improvements, and cost savings. The SME aims to build long-term relationships, offering ongoing support and updates to ensure the software continues to deliver value over time.
Besides manufacturing companies local or International organizations & associations
for specific industries and research institutes could be interesting for them to cooperate with. - Type and Size of Partner
- Big company
- SME 11-49
- SME <=10
- SME 50 - 249
- Type of partnership
- Commercial agreement with technical assistance
Dissemination
- Technology keywords
- 01003003 - Artificial Intelligence (AI)
- 01003010 - Databases, Database Management, Data Mining
- 01003016 - Simulation
- 01003006 - Computer Software
- Market keywords
- 02007016 - Artificial intelligence related software
- 02007024 - Programming services/systems engineering
- 02007014 - Other industry specific software
- 08002006 - Numeric and computerised control of machine tools
- Sector Groups Involved
- Digital
- Targeted countries
- Afghanistan
- Aland Islands
- Albania
- Algeria
- American Samoa
- Andorra
- Angola
- Anguilla
- Antarctica
- Antigua and Barbuda
- Argentina
- Armenia
- Aruba
- Australia
- Austria
- Azerbaijan
- Bahamas
- Bahrain
- Bangladesh
- Barbados
- Belarus
- Belgium
- Belize
- Benin
- Bermuda
- Bhutan
- Bolivia
- Bonaire, Saint Eustatius and Saba
- Bosnia and Herzegovina
- Botswana
- Bouvet Island
- Brazil
- British Indian Ocean Territory
- British Virgin Islands
- Brunei
- Bulgaria
- Burkina Faso
- Burundi
- Cabo Verde
- Cambodia
- Cameroon
- Canada
- Cayman Islands
- Central African Republic
- Chad
- Chile
- China
- Christmas Island
- Cocos Islands
- Colombia
- Comoros
- Cook Islands
- Costa Rica
- Croatia
- Cuba
- Curacao
- Cyprus
- Czechia
- Democratic Republic of the Congo
- Denmark
- Djibouti
- Dominica
- Dominican Republic
- Ecuador
- Egypt
- El Salvador
- Equatorial Guinea
- Eritrea
- Estonia
- Eswatini
- Ethiopia
- Falkland Islands
- Faroe Islands
- Fiji
- Finland
- France
- French Guiana
- French Polynesia
- French Southern Territories
- Gabon
- Gambia
- Georgia
- Germany
- Ghana
- Gibraltar
- Greece
- Greenland
- Grenada
- Guadeloupe
- Guam
- Guatemala
- Guernsey
- Guinea
- Guinea-Bissau
- Guyana
- Haiti
- Heard Island and McDonald Islands
- Honduras
- Hong Kong
- Hungary
- Iceland
- India
- Indonesia
- Iran
- Iraq
- Ireland
- Isle of Man
- Israel
- Italy
- Ivory Coast
- Jamaica
- Japan
- Jersey
- Jordan
- Kazakhstan
- Kenya
- Kiribati
- Kosovo
- Kuwait
- Kyrgyzstan
- Laos
- Latvia
- Lebanon
- Lesotho
- Liberia
- Libya
- Liechtenstein
- Lithuania
- Luxembourg
- Macao
- Madagascar
- Malawi
- Malaysia
- Maldives
- Mali
- Malta
- Marshall Islands
- Martinique
- Mauritania
- Mauritius
- Mayotte
- Mexico
- Micronesia
- Moldova
- Monaco
- Mongolia
- Montenegro
- Montserrat
- Morocco
- Mozambique
- Myanmar
- Namibia
- Nauru
- Nepal
- Netherlands
- Netherlands Antilles
- New Caledonia
- New Zealand
- Nicaragua
- Niger
- Nigeria
- Niue
- Norfolk Island
- North Korea
- North Macedonia
- Northern Mariana Islands
- Norway
- Oman
- Pakistan
- Palau
- Palestinian Territory
- Panama
- Papua New Guinea
- Paraguay
- Peru
- Philippines
- Pitcairn
- Poland
- Portugal
- Puerto Rico
- Qatar
- Republic of the Congo
- Reunion
- Romania
- Russia
- Rwanda
- Saint Barthelemy
- Saint Helena
- Saint Kitts and Nevis
- Saint Lucia
- Saint Martin
- Saint Pierre and Miquelon
- Saint Vincent and the Grenadines
- Samoa
- San Marino
- Sao Tome and Principe
- Saudi Arabia
- Senegal
- Serbia
- Seychelles
- Sierra Leone
- Singapore
- Sint Maarten
- Slovakia
- Slovenia
- Solomon Islands
- Somalia
- South Africa
- South Georgia and the South Sandwich Islands
- South Korea
- South Sudan
- Spain
- Sri Lanka
- Sudan
- Suriname
- Svalbard and Jan Mayen
- Sweden
- Switzerland
- Syria
- Taiwan
- Tajikistan
- Tanzania
- Thailand
- Timor Leste
- Togo
- Tokelau
- Tonga
- Trinidad and Tobago
- Tunisia
- Turkey
- Turkmenistan
- Turks and Caicos Islands
- Tuvalu
- U.S. Virgin Islands
- Uganda
- Ukraine
- United Arab Emirates
- United Kingdom
- United States
- United States Minor Outlying Islands
- Uruguay
- Uzbekistan
- Vanuatu
- Vatican
- Venezuela
- Vietnam
- Wallis and Futuna
- Western Sahara
- Yemen
- Zambia
- Zimbabwe