Summary
The need to widen the range of tasks that robots can handle and the emergence of the so-called fenceless robotic systems that can safely work alongside humans have required the development of tactile sensors that can detect changes in the surroundings throughout physical contact and force sensing, allowing improved safety. As a result, we are witnessing a growing demand of force and torque sensors in industries such as automotive, food and beverage, packaging, and pharmaceutical. On the other hand, all the sensing equipment integrated into the manufacturing processes generates enormous volumes of data within industrial control systems that is currently underused. However, there is an increasing need to exploit this data to reduce operating costs, improve reliability, and increase productivity. Likewise, most common industrial robots do not exploit the data they generate to improve their efficiency. They are programmed once and are unable to improve.
OptoForceX aims at providing plant managers with unparalleled F/T sensors that will enhance automation strategies and allow the exploitation of the production data generated on the manufacturing floor using state-of-the-art machine learning techniques. Manufacturers will be able to capture/collect and store vast amounts of data/information from high-quality sensors monitoring the manufacturing process. They will improve the performance of manufacturing robots by 10-20%, improve cycle time up to 15% and reduce quality inspection resources and maintenance efforts by 60%. We therefore offer manufacturers a valuable tool to enhance their manufacturing lines. We forecasted for this project a cumulative revenue of €51.61M for the first 3 years of commercialization, with a cumulative profit of €10.32M. We projected a ROI of 3.52. The payback period is reached during the 2nd commercialization year.
OptoForceX aims at providing plant managers with unparalleled F/T sensors that will enhance automation strategies and allow the exploitation of the production data generated on the manufacturing floor using state-of-the-art machine learning techniques. Manufacturers will be able to capture/collect and store vast amounts of data/information from high-quality sensors monitoring the manufacturing process. They will improve the performance of manufacturing robots by 10-20%, improve cycle time up to 15% and reduce quality inspection resources and maintenance efforts by 60%. We therefore offer manufacturers a valuable tool to enhance their manufacturing lines. We forecasted for this project a cumulative revenue of €51.61M for the first 3 years of commercialization, with a cumulative profit of €10.32M. We projected a ROI of 3.52. The payback period is reached during the 2nd commercialization year.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/791913 |
| Start date: | 01-12-2017 |
| End date: | 31-03-2018 |
| Total budget - Public funding: | 71 429,00 Euro - 50 000,00 Euro |
Cordis data
Original description
The need to widen the range of tasks that robots can handle and the emergence of the so-called fenceless robotic systems that can safely work alongside humans have required the development of tactile sensors that can detect changes in the surroundings throughout physical contact and force sensing, allowing improved safety. As a result, we are witnessing a growing demand of force and torque sensors in industries such as automotive, food and beverage, packaging, and pharmaceutical. On the other hand, all the sensing equipment integrated into the manufacturing processes generates enormous volumes of data within industrial control systems that is currently underused. However, there is an increasing need to exploit this data to reduce operating costs, improve reliability, and increase productivity. Likewise, most common industrial robots do not exploit the data they generate to improve their efficiency. They are programmed once and are unable to improve.OptoForceX aims at providing plant managers with unparalleled F/T sensors that will enhance automation strategies and allow the exploitation of the production data generated on the manufacturing floor using state-of-the-art machine learning techniques. Manufacturers will be able to capture/collect and store vast amounts of data/information from high-quality sensors monitoring the manufacturing process. They will improve the performance of manufacturing robots by 10-20%, improve cycle time up to 15% and reduce quality inspection resources and maintenance efforts by 60%. We therefore offer manufacturers a valuable tool to enhance their manufacturing lines. We forecasted for this project a cumulative revenue of €51.61M for the first 3 years of commercialization, with a cumulative profit of €10.32M. We projected a ROI of 3.52. The payback period is reached during the 2nd commercialization year.
Status
CLOSEDCall topic
SMEInst-02-2016-2017Update Date
27-10-2022
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H2020-EU.2.1.2. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies – Nanotechnologies
H2020-EU.2.1.3. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced materials
H2020-EU.2.1.5. INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Advanced manufacturing and processing
