D2TECH will address the AIDEAS Machine Passport as a driver to support the machine life cycle. Expected contributions of AIDEAS AI Solutions to the different stages of the product life cycle are described below:

MANUFACTURING phase: To use an AI-driven approach to improve the calibration process of CNC machines. Regarding the manufacturing phase, it is expected that the AIDEAS Fabrication Optimiser solution will support workers in optimising the machine assembly process, but also to find the best tuning for CNC calibration which is a tedious and error prone process. This solution will be used in the calibration process, by setting the optimal configuration of parameters described in the “before AIDEAS” section. For the sourcing of different suppliers of raw material, this phase will rely on the AIDEAS Procurement Optimiser. [KP19 -25%] [KP26 -20%]

USE phase: The main motivation of this phase is twofold: (i) Improve short-time production planning; and (ii) Improve machine efficiency (join several orders for similar types of stone). The production of the finished product can be divided into two different sub-phases (configuration and cutting). The objective would be to learn from operators’ experience and propose a set of configuration parameters according to each type of stone to be processed. Stone cutting process takes into account a final representation of the final product to be produced, which must reflect the requirements specified initially by the final customer. The motivation is to be able to “scan” each stone individually, creating a digital representation of each stone that is unique. An AI-based approach would be able to react in real-time, by a new combination of tiles, and also the best matching stone to replace a damaged stone. For the initial setup and calibration of the machine, which needs to be adapted for the different types of stones, the AIDEAS Machine Calibrator solution will be considered. For assessing the final product quality, in case of readapting to a new combination of tiles to match the initial pattern defined by the end user, three solutions are being considered: AIDEAS Adaptive Controller, the AIDEAS Anomaly Detector and AIDEAS Quality Assurance. [KP12 -15%] [KPI7 +50%] [KP23 -15%] [KP25 -80%]

REPAIR/REUSE/RECYCLE phase: Regarding recycle and repair phases, D2TECH aims to establish a servitisation approach which enables the collection of usage data from their machines, in order to optimise and readapt their maintenance programmes to be better tailored to the different needs of the customers. In that sense, using an AI-driven approach it would enable the detection if a particular component reached the end of its life or if it can be repaired. The adoption of the AIDEAS Prescriptive Maintenance, would greatly extend the condition maintenance among its clients. Within this phase the pilot will mainly rely on the following solutions: AIDEAS Smart Retrofitter, which will enable to detect, in case of malfunction or outdated machines, can be retrofitted; AIDEAS LCC/LCA/S-LCA and the AIDEAS Disassembler will enable to easily identify which components have reached the end-of-life and the ones that can be repaired. [KP8 +20%] [KP17 -15%] [KP18 -10%]

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