Supply chains and production systems need to be adaptive, robust, flexible, sustainable

Important role of Big Data, of automation, of new robot types (e.g. humanoids), new HMI types

Increasing complexity of cyber-physical systems (CPS), new concepts for production are required to achieve new product features

• Guidance/navigation/manipulation/interaction/perception
• Collaborative robots
• Robots fleet management and control
• zero-defect manufacturing
• Predictive Maintenance

Cognitive, Generative

Bio-inspired

Design modular production systems and reconfigurable
manufacturing equipment that can be quickly adjusted to different product
lines and volumes.

Link materials, design and manufacturing.

Link materials, design and manufacturing.

Challenge: Transition towards smart factories that leverage the Artificial Intelligence Internet of Things (IoT), digital twins, and cyber-physical systems.  Innovation: Create interconnected systems that provide real-time data analytics, enabling proactive and reactive decision-making to optimize production lines and supply chains.

The OPTIMAL approach involves various disciplines, which interact with each other in order to achieve the project objectives. Material research and photochemistry is needed to develop the suitable photoresists (MRT). Laser technology knowledge (JOR, ISE) is required for developing novel laser lithography methods, machines, and processes. The electronics finds its application in the optical based sensors for in-line monitoring, controlling the laser sources and patterning (ILC, DPX). The software engineering expertise (UPR) completes the required skills for the development of self-learning algorithms for generating the virtual photomasks. Mechanical and environmental engineering deal with the equipment and manufacturing processes and their life cycle assessment (JOR). Experts in training and communication science (ILC, UPR) will design workshops and training materials to explain and promote the developed technologies to broad public and stakeholders. 

The OPTIMAL project will integrate for the first-time different laser lithography technologies, quality monitoring systems and processes in one platform for the development of structures with high depth, dimensions in the range from 100 nm to sub-mm, 2D&3D shape on flat surface, combining parallel & serial patterning, no need for external treatments on samples, increased speed and large area. The OPTIMAL consortium consists of three research institutes (JOR, ISE, ILC), one university (UPR), member of the Italian Photonics Association, three Small Medium Enterprises (MRT, DPX, HYP), two big industries, leaders in their corresponding market (SDA and BCD).

The OPTIMAL platform will be validated through the manufacturing of master tools for four different use cases: a) full-polymer micro lenses for industrial optics, b) hierarchical multifunctional drag reduction riblet structures for aviation, c) free-form lens arrays for high-end virtual reality displays and d) microfluidic hierarchical structures for lab on chip medical devices.The OPTIMAL consortium consists of three research institutes (JOR, ISE, ILC), one university (UPR), member of the Italian Photonics Association, three Small Medium Enterprises (MRT, DPX, HYP), two big industries, leaders in their corresponding market (SDA and BCD).

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction. 

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction. 

The OPTIMAL project uses self-learning algorithms to optimize the virtual photomask as well as integrates methods for an inline control of the laser patterning.

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction. 

The OPTIMAL project uses self-learning algorithms to optimize the virtual photomask as well as integrates methods for an inline control of the laser patterning.

The OPTIMAL project uses self-learning algorithms to optimize the virtual photomask as well as integrates methods for an inline control of the laser patterning.