PAMA will exploit the potential of the AIDEAS AI technologies to improve sustainability quality and resilience of its products to foster AI-based digital transformation within the manufacturing sectors. PAMA aims to use the AIDEAS Machine Passport to conform large datasets consisting of timestamped signals sensors and CNC/PLC data collected during the use phase (primarily) as well as other phases in the life cycle. Unified standard service modelling techniques will ensure the aforementioned data compatibility, interoperability, consistency and quality. These data sets will be used: i) to improve the performance of the machine learning models that predict machining process anomalies/deviations with respect to nominal conditions, and ii) to improve designs, fabrication and repair/reuse/recycle of the equipment. Expected contributions of AIDEAS AI Solutions to the different stages of the product life cycle are described below:

DESIGN phase: AI-based (data-driven) prediction of products (machine tools) performance within early design stage. Enables smarter and faster optimisation, reduces product development time, and boosts digital transformation. Uses the AIDEAS Machine Design Optimiser solution with a trained model on historical datasets correlating design parameters and performance. [KPI11 -30%] [KPI24 -20%]

MANUFACTURING phase: Retrofit design with manufacturing outcomes to optimise future designs. Exploits AI tools to parse historical production problem data, correlating single part measurements to final assembly accuracy. Uses the AIDEAS Fabrication Optimiser solution trained on labelled datasets. [KPI3 +15%] [KPI26 -10%]

USE phase: Predicts and compensates geometric and thermal errors during machining through adaptive control. Models use process and design variables with AIDEAS Condition Evaluator and Anomaly Detector, predicting energy consumption and optimal working conditions, auto-tuning via AIDEAS Adaptive Controller. [KPI14 -25%] [KPI23 -15%]

REPAIR/REUSE/RECYCLE phase: Assesses machine performance at end-of-life, identifies reusable parts and optimal remanufacturing strategies, estimating costs and maintenance plans. Uses AIDEAS Smart Retrofitter, LCC/LCA/S-LCA and Disassembler solutions. [KPI4 +15%] [KPI8 +20%]

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