Summary
Although manufacturing is moving towards digitalization and full automation, some industries, such as the furniture industry, are still heavily reliant on inefficient and outdated technologies. In particular, the furniture sector has been identified to lack any sort of automated solution for wood curing quality control, one of the critical manufacturing processes. Apart from causing a high defect rate, the absence of an inspection system creates a risk of manufacturing hundreds of thousands of pieces of furniture that are not adequately cured and potentially poisonous. This, in turn, leads to increased health risks and possible legal liabilities for the manufacturing company. To address the challenges, Factobotics, a Lithuanian robotics SME, has developed a novel solution– Multicursor. Multicursor is an intelligent non-contact polymerization quality system combining cutting-edge laser technology and machine learning models to provide a real-time response on wood surfaces curing level and quality. On the contrary to the existing solutions on the market, Multicursor is provided with a non-contact sensor, is easy to integrate into the process of manufacturing through, enabling automated quality control and data collection. Thanks to its competitive advantages the system will make measurement faster and allow zero defect manufacturing through real-time system monitoring and collection of valuable data. Multicursor is currently at TRL 6. The next step is moving on to TRL 7 that will require the introduction of the industry-grade prototype with further testing in the furniture production facilities. To ensure successful commercialization, in Phase 1 of SME Instrument, Factobotics intends to develop an elaborated feasibility study for Multicursor that is to include the finalization of Multicursor’s value proposition, the creation of the Technical Specifications for Artificial Intelligence and development of the Multicursor business plan.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/868812 |
| Start date: | 01-06-2019 |
| End date: | 30-09-2019 |
| Total budget - Public funding: | 71 429,00 Euro - 50 000,00 Euro |
Cordis data
Original description
Although manufacturing is moving towards digitalization and full automation, some industries, such as the furniture industry, are still heavily reliant on inefficient and outdated technologies. In particular, the furniture sector has been identified to lack any sort of automated solution for wood curing quality control, one of the critical manufacturing processes. Apart from causing a high defect rate, the absence of an inspection system creates a risk of manufacturing hundreds of thousands of pieces of furniture that are not adequately cured and potentially poisonous. This, in turn, leads to increased health risks and possible legal liabilities for the manufacturing company. To address the challenges, Factobotics, a Lithuanian robotics SME, has developed a novel solution– Multicursor. Multicursor is an intelligent non-contact polymerization quality system combining cutting-edge laser technology and machine learning models to provide a real-time response on wood surfaces curing level and quality. On the contrary to the existing solutions on the market, Multicursor is provided with a non-contact sensor, is easy to integrate into the process of manufacturing through, enabling automated quality control and data collection. Thanks to its competitive advantages the system will make measurement faster and allow zero defect manufacturing through real-time system monitoring and collection of valuable data. Multicursor is currently at TRL 6. The next step is moving on to TRL 7 that will require the introduction of the industry-grade prototype with further testing in the furniture production facilities. To ensure successful commercialization, in Phase 1 of SME Instrument, Factobotics intends to develop an elaborated feasibility study for Multicursor that is to include the finalization of Multicursor’s value proposition, the creation of the Technical Specifications for Artificial Intelligence and development of the Multicursor business plan.Status
CLOSEDCall topic
EIC-SMEInst-2018-2020Update Date
27-10-2022
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