Summary
The seal integrity of packages is crucial to assure product viability and shelf life. The break of the seal can lead to food
contamination, degradation and leaks, causing economic losses and brand reputation damage. There is no method to
quickly detect sealing flaws or understand why they have occurred. 3% of heat-sealed packages are defective. The current
methodology is sampling, which generates waste, products recall, unsafety and unreliability.
We have developed the PAM2 System, Packaging Analytical Monitoring system, a disruptive quality control machine that
analyses all the products in a batch via 3D thermal imaging and advanced real time algorithms to provide complete in-line
monitoring of the sealing process. PAM2 screens 100% of the products in a non-destructive manner without slowing the line
capacity. Our Deep Learning algorithms collect precise data to increase the understanding of the process, improve quality,
allow operators to detect and amend issues in real-time and detect patterns, such as those cases in which the sealed area is
too close to the limit set by the user.
In 2016, we founded Yoran Imaging to start developing the PAM2 System. We have already performed Proof-of-Concept of
our prototypes in major food companies, received the CE mark and have sold machines. Currently, we are pursuing the
implementation of Deep Learning in order to become an Industry 4.0 enabler platform in the primary packaging area.
We are set to serve within the food manufacturing industry, with around 300,000 food and drink manufacturing companies in
Europe contributing towards the sectors total turnover of €1,109 billion with a value-added total of €230 billion. Moreover, the
packaging machinery industry within Europe has over 6,000 enterprises producing packaging, which accounted for €13.5
billion in 2017.
contamination, degradation and leaks, causing economic losses and brand reputation damage. There is no method to
quickly detect sealing flaws or understand why they have occurred. 3% of heat-sealed packages are defective. The current
methodology is sampling, which generates waste, products recall, unsafety and unreliability.
We have developed the PAM2 System, Packaging Analytical Monitoring system, a disruptive quality control machine that
analyses all the products in a batch via 3D thermal imaging and advanced real time algorithms to provide complete in-line
monitoring of the sealing process. PAM2 screens 100% of the products in a non-destructive manner without slowing the line
capacity. Our Deep Learning algorithms collect precise data to increase the understanding of the process, improve quality,
allow operators to detect and amend issues in real-time and detect patterns, such as those cases in which the sealed area is
too close to the limit set by the user.
In 2016, we founded Yoran Imaging to start developing the PAM2 System. We have already performed Proof-of-Concept of
our prototypes in major food companies, received the CE mark and have sold machines. Currently, we are pursuing the
implementation of Deep Learning in order to become an Industry 4.0 enabler platform in the primary packaging area.
We are set to serve within the food manufacturing industry, with around 300,000 food and drink manufacturing companies in
Europe contributing towards the sectors total turnover of €1,109 billion with a value-added total of €230 billion. Moreover, the
packaging machinery industry within Europe has over 6,000 enterprises producing packaging, which accounted for €13.5
billion in 2017.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/967144 |
| Start date: | 01-04-2021 |
| End date: | 30-09-2023 |
| Total budget - Public funding: | 1 162 250,00 Euro - 813 575,00 Euro |
Cordis data
Original description
The seal integrity of packages is crucial to assure product viability and shelf life. The break of the seal can lead to foodcontamination, degradation and leaks, causing economic losses and brand reputation damage. There is no method to
quickly detect sealing flaws or understand why they have occurred. 3% of heat-sealed packages are defective. The current
methodology is sampling, which generates waste, products recall, unsafety and unreliability.
We have developed the PAM2 System, Packaging Analytical Monitoring system, a disruptive quality control machine that
analyses all the products in a batch via 3D thermal imaging and advanced real time algorithms to provide complete in-line
monitoring of the sealing process. PAM2 screens 100% of the products in a non-destructive manner without slowing the line
capacity. Our Deep Learning algorithms collect precise data to increase the understanding of the process, improve quality,
allow operators to detect and amend issues in real-time and detect patterns, such as those cases in which the sealed area is
too close to the limit set by the user.
In 2016, we founded Yoran Imaging to start developing the PAM2 System. We have already performed Proof-of-Concept of
our prototypes in major food companies, received the CE mark and have sold machines. Currently, we are pursuing the
implementation of Deep Learning in order to become an Industry 4.0 enabler platform in the primary packaging area.
We are set to serve within the food manufacturing industry, with around 300,000 food and drink manufacturing companies in
Europe contributing towards the sectors total turnover of €1,109 billion with a value-added total of €230 billion. Moreover, the
packaging machinery industry within Europe has over 6,000 enterprises producing packaging, which accounted for €13.5
billion in 2017.
Status
SIGNEDCall topic
EIC-SMEInst-2018-2020Update Date
27-10-2022
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Geographical location(s)
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