Some of the most common defects in PET preforms with increased rPET concentration are different types of inclusions, haziness, and yellowing. Hence, for an upcoming R&D project funded by Norway Grants Sprana intends to develop a new inspection system that enables the detection of black specks and other contaminations at an early stage of production.
In this project, the company will carry out research and experimental activities in order to improve the quality control of PET preforms in on-line monitoring and analysis and to increase recycled materials concentration in production processes. This is realised by using machine vision and AI technology. Sprana will also develop the system’s prototype, which will be tested and installed on-site. The company states that by optimising and improving quality control of PET preform production, manufacturers will be able to reduce the routine human labour part of the quality assurance process, which is seen as inefficient, time-consuming, and increases the possibility of defective products. Released from routine tasks, staff will instead be able to carry out higher value-added processes and focus on higher quality of the products.
Overall, the project not only aims to promote the usage of secondary PET resin in the industry and to stimulate the market for rPET trading, but the partnership will also take a further step towards the EU goal of creating the circular economy for the PET plastic packaging industry.
During this project, Sprana will be collaborating with local and international partners to carry out the R&D stages and achieve the main goals of the program. In cooperation with Lithuanian PET preform producer Putoksnis Ltd. and Norwegian consulting and projects management company IDN (International Development Norway) Sprana’s objective is to adapt the resulting product/solution in a real industrial environment and to commercialise it in the EU and across world markets.
Sprana Ltd is excited to share an update on our collaboration with International Development Norway AS (IDN) our Norway Grant partner for commercialization activities. Together with Sprana CEO Mindaugas Steponavičius, IDN recently visited (2023.11.28) Doloop, another project partner from Lithuania, to witness the effectiveness of Sprana's inline Black speck and Color Quality control Machine Vision system in real industrial conditions.
IDN's involvement in this project is very important as they are tasked with assessing the market potential for Sprana's innovative machine vision technology within the rPET industry. They will provide a comprehensive market overview, identifying key opportunities and challenges for Sprana's Business Development Team.
This visit to Doloop allowed IDN to gain firsthand insights into the practical applications of Sprana's machine vision system. They observed how the system effectively detects and removes black specks and color inconsistencies from recycled PET (rPET), ensuring the production of high-quality rPET flakes.
We are grateful to IDN representatives for their business visit and their commitment to supporting Sprana's market expansion. Their expertise and collaboration are invaluable as we work together to advance the rPET industry and promote sustainable practices.
We are thrilled to share the exciting outcomes of our recent participation in the "NOR way to green business and ICT" event, which took place on June 7th, 2023. Sprana’s Business Development Manager- Ricardas Razgaitis, had the privilege of presenting the remarkable results achieved through our collaboration with our esteemed partners from Lithuania and Norway: Putoksnis and IDN- International Development Norway.
During the event, we showcased the advancements made in the field of rPET/PET Preform inspection, specifically focusing on color and black speck detection. These quality control challenges have long plagued the plastic manufacturing industry, leading to significant waste and compromising the overall product integrity.
By leveraging cutting-edge technology and the expertise of our cross-border collaboration, we have successfully developed an “Alpha” prototype on-line inspection system that addresses these issues head-on.
We would like to extend our heartfelt gratitude to our partners, Putoksnis and IDN, for their unwavering commitment and invaluable contributions to this project. Together, we are demonstrating the power of international cooperation and the potential for transformative innovation.
We would also like to express our gratitude to the organizers of the "NOR way to green business and ICT" event for providing us with a platform to showcase our achievements. Events like these play a crucial role in fostering collaboration, knowledge sharing, and driving sustainable development.
Looking ahead, we are excited about the future prospects of our rPET/PET Preform inspection system and its potential to revolutionize quality control processes in the plastic industry. As we continue to innovate and push boundaries, we are committed to driving positive change, one inspection at a time.
If you're interested in learning more about our groundbreaking project or exploring potential collaborations, feel free to reach out.
Together, let's pave the way towards a greener, more sustainable future.
On December 21st 2022 SPRANA team have successful adapted “Alfa” prototype to customer UAB “Putoksnis” PET preform manufacturer production line.
Commissioning and startup tasks completed according to the plan.
First stage testing was done, now real time testing on working production line is running and raw data gathered for further analysis.
The „Alfa“ prototype casing has been developed by SPRANA team, the optimal interior of the casing has been selected to minimize the negative geometric effect of light reflection and scatering, and an IR light source has been designed and manufactured - an LED panel that has been integrated into the original prototype design.
Experiments with power supply units for LED panels have been performed, negative effects
of flickering have been observed, which will be eliminated by
improving the design of electronics.
Software analysis of different cameras resolution was performed. The optimal relationship between photo resolution and computational capabilities was sought.
A list of required calculation techniques has been compiled.
Optimal machine vision IR / VIS camera is selected from world leading manufacturers.
Trace simulations with IR machine cameras and IR filters were performed.
Primary defect detection algorithms were developed, and primary initial results were obtained.