Project description
AI for defects detection in the car industry
Manufacturing has changed, requiring flexible and agile production to meet the needs of customers. Therefore, adapted solutions for quality control of products and processes are needed. In particular, current CV-based quality control systems are costly and task-specific, providing an opportunity in the market for a new, cost-effective and task-flexible solution. Computer vision, supported by artificial intelligence, brings the possibility of developing a solution adapted to this situation. The TECHEYE project proposes a CV solution based on IA that comprises accurate hardware for image acquisition, a communication system, a software for image processing and a web front for data visualisation. The solution will require minimal investment, is capable of being relocated to another point of the production line and retrained to perform another control task. It can operate autonomously or integrated into the plant systems. It will also increase quality and reduce total costs in the new Industry 4.0 environment.
Objective
In the automotive industry, quality is the key differentiating factor. Scraps and defects represent a major risk to performance
and competitiveness, leading to very high costs. Besides, there is no specific solution in the market for the automatic quality
control of defects in plastic injection and painting defects, forcing manufacturers to maintain primitive techniques based on
human vision, that can be time-consuming and costly.
By applying Artificial Intelligence (AI) to visual inspections, organisations can identify defects by matching patterns to images
that were previously analysed and classified. They could be detected up to 90% more accurately than humans. In addition,
reduction of personnel costs, rework, and scrap yields a total cost reduction of approximately 9% (~ €26 billion). A new
market report from Market&Market claims that automotive AI will reach €9.37 billion by 2025, at a CAGR of 38.46%.
TECHEYE® is an innovative solution offering a fully automated directional vision system coupled with a self-calibration
lighting unit, based on Neural Networks. It comprises suitable hardware for images acquisition, a communications system
and software for image processing and analysis.
Our algorithms can automate visual inspection activities, even under complex conditions like variable position, orientation of
units or tough lighting conditions. TECHEYE® is able to classify injection faults: gusts, ampoules, pores and scratches.
We offer an affordable web service, user-friendly as plug and play, enabling defect classification. TECHEYE® can be really
suitable for automotive OEMs and plastic injection companies to enhance their production lines, the quality assurance and
cost reduction.
INOVALABS is a technical consulting company founded in 2004 in Vigo (Spain), providing services related to the definition
of innovation and competitiveness strategies, and design of R&D projects. TECHEYE® will boost the company revenues
streams over a new market niche
Fields of science (EuroSciVoc)
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.
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 software
- humanities arts visual arts
- engineering and technology mechanical engineering vehicle engineering automotive engineering
- natural sciences computer and information sciences artificial intelligence computational intelligence
You need to log in or register to use this function
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.
-
H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
See all projects funded under this programme -
H2020-EU.3. - PRIORITY 'Societal challenges
See all projects funded under this programme -
H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
See all projects funded under this programme
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-1 - SME instrument phase 1
See all projects funded under this funding scheme
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
See all projects funded under this callCoordinator
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.
36202 VIGO
Spain
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.