Project description
Better seals to protect brand reputation
A package’s seal integrity is key for product viability, protection and shelf life. Even the slightest break of the seal causes economic and brand reputation damage. The existing method to detect sealing relies on sampling, which is unsafe, unreliable and generates waste. Yoran Imaging has developed the Packaging Analytical Monitoring system, a disruptive quality control machine screening solution. It uses 3D thermal imaging and deep learning algorithms to collect precise data to understand the process and improve quality. This in-line inspection system has been tested in major food companies and received the CE mark. The EU-funded PAM 2 project will implement deep learning to become an industry 4.0 enabler platform in the primary packaging area.
Objective
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.
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-2 - SME instrument phase 2
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-EIC-SMEInst-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
3657 600 Timrat
Israel
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.