_Our research and development projects

Experts from TT PSC are involved in national and international R&D projects

_About us

Transition Technologies PSC is part of the Transition Technologies Group, which was founded in 1991 and has been constantly expanding its structures. Our experts specialize in Cloud, Internet of Things, Augmented Reality, Product Lifecycle Management or nearshoring. We are a strategic partner of such companies as PTC and Rockwell, where we jointly develop and implement the ideas of Industry 4.0.
Transition Technologies PSC team
The experience we have gained through working with the world’s biggest brands helps us to quickly and effectively implement solutions based on modern technologies.
Since 2015, we have been involved in R&D projects, focused on the industrial application of AR and IoT. Our portfolio includes projects funded by both national and international sources. Currently, we are implementing 3 projects in international consortia as part of H2020 with a total value of EUR 33.6 million. Moreover, and we implement our proprietary innovative solutions developed as a result of an individual project financed by the National Center for Research and Development under the European Regional Development Fund.
Transition Technologies Group in figures:

25years of experience

800+specialists at Transition Technologies PSC

2000+specialists in Transition Technologies group

15offices in Poland

7offices: in the USA, France, Denmark, Germany, Great Britain, Taiwan, Malaysia

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_Currently implemented grants

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PIONEER aims the development of an open innovation platform and interoperable digital pipeline for addressing a design-by-simulation optimisation framework.

HORIZON-CL4-2022-RESILENCE-01 – Grant Agreement ID: 101091449
Budget: 5.223.386,25 €
Runs from 01.01.2023 to 31.12.2025
TT PSC S.A. – consortium partner

More about the project


Nowadays, European manufacturing enterprises are facing a number of challenges in a turbulent globalized market facing unprecedented and abrupt changes in market demands, an ever-increasing number of product variants and smaller lot sizes, intensifying the worldwide competition and causing a continuous pressure on production costs, product quality and production efficiency. Therefore, novel product development strategies for ensuring and optimising the manufacturing of new products or variants in low-volume production systems must be implemented.

For that, PIONEER implements inline feedforward control strategies for enhancing the efficiency of the industrial systems in high-mix/low-volume production schemes, based on the connection between materials modelling and materials characterisation, simulation-based digital twins and data-driven models, updated through distributed production data from embedded IoT edge devices and product quality. PIONEER is built over five pillars for development a common methodology deployed in two demonstrators by involving multidisciplinary optimisation for ensuring certified path planning strategies for the manufacturing of topology optimised structural elements through Wire-Arc Additive Manufacturing (WAAM) in construction –i.e., low-volume production schemes–, as well as for ensuring an efficient design and manufacturing strategy for the manufacturing of Carbon Fibre Sheet Moulding Compound (CF-SMC) components in automotive –i.e., high-mix production schemes.

PIONEER is built on the knowledge and results gained in:

  1. previous H2020 EU projects;
  2. associations –i.e. EMMC ASBL, IOF, VMAP Standard Community, IDTA—;
  3. commercial products from project partners.

PIONEER will bring together 14 key industrial and academic stakeholders from 11 countries.
Project website
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Fluently logo


Fluently leverages the latest advancements in AI-driven decision-making process to achieve true social collaboration between humans and machines while matching extremely dynamic manufacturing contexts.

The project results will be: Fluently Smart Interface unit and the Robo-Gym.
HORIZON-CL4-2021-TWIN-TRANSITION – Grant Agreement ID: 101058680
Budget: 11.200.141,55 €
Runs from 01.06.2022 to 31.05.2025
TT PSC S.A. – consortium partner

More about the project


The project results will be: Fluently Smart Interface unit and the Robo-Gym.
The Fluently Smart Interface unit features:

  1. interpretation of speech content, speech tone and gestures, automatically translated into robot instructions, making industrial robots accessible to any skill profile;
  2. assessment of the operator’s state through a dedicated sensors’ infrastructure that complements a persistent context awareness to enrich an AI-based behavioral framework in charge of triggering the generation of specific robot strategies;
  3. modelling products and production changes in a way they could be recognized, interpreted and matched by robots in cooperation with humans.

Robots equipped with Fluently will constantly embrace humans’ physical and cognitive loads, but will also learn and build experience with their human teammates to establish a manufacturing practise relying upon quality and wellbeing. The bond between human and robot is personalized, and it is established during a preliminary training at the Robo-Gym, the first European hub for human-robot interactive training, where human and robot learn from each other a common work practice.

Fluently will be validated by demonstration on three full scale pilots characterized by various level of automation, production dynamism and complexity of the manufacturing decision making process.

Fluently will bring together 21 key industrial and academic stakeholders from 13 countries.

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Connected Worker logo

Connected Worker

A system increasing the efficiency of remote communication and collaboration, thanks to hardware-agnostic AR technology based on a real-time spatial mapping and tracking powered by edge/cloud computing and 3G/4G/5G networks.

POIR Szybka Ścieżka Koronawirusy – Grant Agreement ID: POIR.01.01.-00-2613/20-00
Budget: 5 305 218,59 PLN
Runs from 01.09.2021 to 30.11.2023
TTPSC S.A. – project leader (single-entity project)

More about the project


COVID-19 has drastically changed the existing rules on cooperation in the manufacturing, service and utilities sectors. Hands-on support, frequent delegations and stable workforce must give way to social distancing, flight restrictions and changes in employment. Collaboration, training, supervision and support for “first-line” workers require solutions that enable remote collaboration, immediate upskilling, and independence in accessing the information. These needs are addressed by augmented reality (AR) and communication technologies, democratizing access to knowledge, transferring it at a distance, and collaborative problem solving. However, they are subject to limitations in the context of their professional and industrial applications:

  • Lack of support for industrial wearable devices – current solutions are convenient for casual use on smartphones, but not when working with machines, infrastructure, service provision and tasks requiring having both hands free
  • Dependency on ArCore and ArKit libraries – mobile device like the class of Samsung Galaxy S7, iPhone 7 and better is hard to find on employees’ equipment, which limits the adoption of AR in professional conditions
  • Small scale of the mapped space – AR content is applied to a image markers, floor planes or single objects being detected – it is impossible to map a space larger than several m2, understanding the location of the employee at the scale of the entire factory / building and ones interaction with the real world
  • Short battery life – AR calculations are computationally expensive when it comes to battery consumption – real use of AR is limited to approx. 2-3h

We offer an innovative AR solution for remote cooperation, which will map spaces above 1000 m2, will work on devices that are saturated and incompatible with the libraries ArCore (from Google) and ArKit (from Apple) and thanks to the use of 5G and cloud for AR calculations, it will extend the working time with AR one battery charge.

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Inedit logo


Open Innovation Ecosystems for Do It Together process

H2020-EU. – grant agreement no 869952
Budget: 6.887.475 €
Implemented from 01.10.2019 to 31.03.2023
TT PSC S.A. – consortium partner

More about the project


INEDIT creates an open innovation European DIT ecosystem for sustainable furniture co-creation. It channels the creativity of consumers, shapes it through designers’ professional skills, and makes it viable by leveraging on the expertise of production specialists in order to deliver sustainable, smart and personalized new products in a shorter time to market. INEDIT intends to demonstrate the capacity to turn the well-known ‘Do It Yourself’ (DIY) approach applied by individuals within FabLabs into a professional approach named ‘Do It Together’ (DIT). The DIT approach will be applied by customers and professional producers, especially SMEs, for conveying higher customer satisfaction through customer-driven production. DIT is a novel approach capitalizing on the knowledge, creativity and ideas of design and engineering conceptualized by interdisciplinary stakeholders and sometimes even new actors. It is powered by existing European innovation ecosystems shaping new products across EU countries. INEDIT demonstrates the approach through four cross use cases with high societal impact: sustainable wood panels manufacturing and 3D-printing of wood, 3D printing of recycled plastic and Smartification. Sustainability and consideration of individual preferences, especially of women and men, will be our guiding thread. INEDIT address societal challenges such as contribution to reduce the amount of produced CO2 in focusing on European-wide production, creation and maintenance of EU-wide job opportunities. This will lead to new business opportunities supported by business model innovation.  Moreover, these innovative networked local manufacturing competences and production facilities across the EU will solve ethical concerns within the manufacturing network. INEDIT intends to demonstrate, through its twin – digital and physical – platform, the potential innovation around social manufacturing within the circular economy in designing global while producing local.

Project website
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Penelope logo


Closed-loop digital pipeline for a flexible and modular manufacturing of large components

H2020-EU. – Grant Agreement ID: 958303
Budget: 20.125.750,35 €
Runs from 01.10.2020 to 31.09.2024
TTPSC S.A. – consortium partner

More about the project


New planning for large-part manufacturing.

Machining large parts requires more than just a lot of space. There is also a variety of sub-assemblies and the capability to customise (build to customer demands). This high degree of personalisation hinges on the design and the posterior verification after manufacturing. With this in mind, the EU-funded PENELOPE project will develop a methodology linking product-centric data management and production planning and scheduling in a closed-loop digital pipeline. The aim is to ensure accurate and precise manufacturability from the initial product design. The project is built to develop the methodology and vision in the following sectors: oil and gas, shipbuilding, aeronautics, and bus and coach. It will also provide the training enabling the workforce transition towards Industry 4.0.

Project website
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mari4yard logo


User-centric solutions for a flexible and modular manufacturing in small and medium-sized shipyards

H2020-EU.3.4 – Grant Agreement ID: 101006798
Budget: 5.913.440,00 €
Runs from 01.12.2020 to 30.11.2024
TTPSC S.A. – consortium partner (leader of the AR work package)

More about the project


EU shipbuilding leading edge relies in the complexity, quality, customization, delivery time and lifecycle services (e.g. in situ maintenance, repair and retrofitting) of the vessels manufactured. However, in the last decade, EU small and medium-sized shipyards (SME) have experienced a competitive drawback in their market segments due to an increase of competition from other global regions that benefits from lower labour costs or higher automation degree. Moreover, SME shipyards must also overcome a major impediment related with capital investment that can overwhelm the part cost for shipbuilding. As a result, current automation solutions based on large monolithic equipment, are not still valid for increasing productivity in SME shipyards.

Therefore, shipbuilding, and especially SME shipyards, needs novel cost-effective, reconfigurable, modular and flexible worker-centric methodologies capable of improving worker’s performance and ensuring quality and precision in the execution of the labour-intensive tasks.

Mari4_YARD aims the implementation of a portfolio of worker-centric solutions, by relying on novel collaborative robotics and ubiquitous portable solutions, enabling modular, reconfigurable and usable solutions targeting the execution of labour-intensive tasks by preserving industry-specific workers’ knowledge and skills.

Moreover, replicability and early-adoption of the portfolio of technologies by other SME-shipyards is ensured through several actions on training, technology assessment, benchmarking… by establishing a pan-European network of Didactic Factories, offering general-purpose testbeds and showrooms, as well as providing upskilling and re-skilling of shipyards workforce.

To further maximise the impact, Mari4_YARD plans to use synergies with complementary European and national initiatives, especially those related to MG-3-7-2020. A strategy for collaboration with Mari4_CHAIN and Mari4_PRO proposals, if funded as well, has already been set up.

Project website
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_Completed grants


Innovative Modeling Approaches for Production Systems to raise validatable efficiency

H2020-EU.2.1.1. Grant Agreement ID 678867
Budget: 4.148.554,00 €
Runs from 01.09.2015 to 31.08.2018
TT S.A., TTPSC S.A. – consortium partners


Creating the Factory of the Future with 4.0 Solutions.

Within the manufacturing industry, the complexity of production plants is steadily rising due to increasing product variances, product complexity, and pressures for production efficiency. Production systems must therefore now evolve rapidly and operate optimally, creating challenges for larger Industries and serious problems for SMEs without the needed expertise or sufficient resources to adapt new technical possibilities.

To meet these challenges, the European research and innovation project IMPROVE has developed novel data-based solutions to enhance machine reliability and efficiency. Innovative tools in the ¬fields of simulation & optimization, condition monitoring, alarm management, and quality prediction provide manufacturers with a human machine interface (HMI) and decision support system (DSS) to ensure best possible user support.

Project website
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Real World Engine

Development of interactive methods for spatial mapping and modelling for rapid design of vast digital worlds in mixed reality

POIR GameINN – Grant Agreement ID: POIR.01.02.00-00-0177/17-00
Budget: 2.412.446,40 PLN
Runs from 02.01.2018 to 30.03.2021
TTPSC S.A. – project leader (single-entity project)


The project is focused on performing industrial research leading to the creation of new technologies allowing utilization of sensor-equipped mobile devices for building a 3D mesh of the environment and interpretation of object geometry in near-real-time for the purpose of rapid development of worlds for Augmented (AR), Mixed (MR) and Virtual Reality (VR) games based on real-world environments. Creation of new heuristic methods ensuring a high level of accuracy of object recognition in a 3D space, including utilizing multiple area scanning devices simultaneously, is vital in order to achieve the aforementioned goals. Usage of Artificial Neuron Networks for object recognition based on a 3D mesh will be validated through the course of the research. Existing 2D image recognition algorithms will not be of direct use in these activities, but will be utilized as the starting point. Optimization of performance of the technology will be a significant issue – thus heuristics instead of precise algorithms, which allows for cooperation between multiple users immersed in the same virtual environment. The influence of given elements (algorithms, number of scanning devices, connection throughput) will be evaluated for their influence on accuracy and effectiveness of object recognition, providing insight as to optimal methods combining satisfactory recognition with dynamic collaboration between multiple users in near-realtime.

Synchronization of heuristic algorithms with the ability to dynamically and simultaneously model the environment by multiple devices, including a 3D developmnet environment in AR/MR/VR as well as desktops, will be one of key topics.

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Are you interested in joint implementation of R&D projects? Don't hesitate and contact us!

Paulina Kosmowska TT PSC

Paulina Kosmowska

R&D Process Lead


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