Trends in manufacturing technologies and initiatives are placing increased importance on the integration of robot technologies in manufacturing facilities (Technology Readiness Levels for Randomized Bin Picking, http://nvlpubs.nist.gov/nistpubs/ir/2012/NIST.IR.7876.pdf ).
InPicker value proposition will be focused on:
• High quality of bin picking performed (as % of parts incorrectly picked).
• Low cost of TCO (low cost of deployment, operation and maintenance, speed of deployment of bin picking, high throughput (high speed bin picking and around the clock production) and reduced labour costs).
• Service support reliability.
• Improved worker's safety as they are replaced from highly repetitive tasks as well as those in hazardous conditions.
The results of the technical and economic feasibility study are highly satisfactory. InPicker includes a software system for recognizing workpieces in a container and deciding the better candidates to be picked. The differentiation of InPicker consists in the use of SLAM technology, as well as a different architecture for placing the vision sensors, that allow the generation of hundreds of different images that provide more information from which discriminate the parts and achieve virtually flawless recognition of parts, a problem with other solutions.
The solution proposed represents an important advance over the state of the art but there are limitations to the range of parts that can be recognized effectively by the system. The present version of InPicker could pick about 50% of the possible parts when all the different types of parts are worked into the system. The characteristics of the other 50% of parts (not rigid, texture and light reflection properties, difficult to identify characteristic features,…) do not allow proper recognition with the present state of art.
Around InPicker other products and services can be provided as the InPicker vision head, maintenance and support services, engineering and technical services regarding specific customer requirements as well as customization of recognition of new parts.
The solution should bring €34,4 million in 2025 revenues, €21,9 million in EBIT (a 63,9% margin, typical of software products), the employment of 140 highly skilled people, mainly engineers, as well as a 46,7% in IRR from capital invested.