BBM | AIDEAS Pilot

Описание: BBM will use AI technologies developed in AIDEAS to enhance the agility, sustainability and resilience of EBMs through their entire life cycle. In addition, the AIDEAS Machine Passport provides an important database for the optimisation of all life stages of an EBM. Expected contributions of AIDEAS AI Solutions to the different stages of the product life cycle are described below:

DESIGN phase : BBM aims to improve its current extrusion head design by using the AIDEAS CAx Addon and the AIDEAS Machine Synthetic Data Generator. Instead of just simulating and verifying designs created by mechanical engineers, the AI technologies shall be used to set-up and improve the first design, thereby increasing the expected regrind share of the final product and reducing the workload for the mechanical engineer. By increasing the regrind share, the sustainability of the whole plastics sector can be improved. By using the AIDEAS Machine Design Optimiser, the cycle of machine control creation and debugging will be improved and the expected software start up time will be reduced substantially. The AIDEAS tool will help to create a more realistic machine simulation that helps the electrical engineers to test and debug the machine control before switching it on for the first time. Due to a high amount of dynamic and fast moving machine parts, AI based technologies will help to improve the design and resilience of EBMs. [KPI6 +15%] [KPI11 -20%]

USE phase : During the use phase of an EBM, several AIDEAS AI tools can lead to a significant improvement for BBM as well as for the customer. At first start up, the machine and process parameters need to be set to achieve the best product quality. This complex task will be performed automatically by the AIDEAS Machine Calibrator and it will also help to decrease the initial start-up time and downtime of the machine in the production phase. After a power shut down, the referencing of drives will be handled automatically by the Machine Calibrator based on the previously collected machine data. A running machine in production needs constant condition evaluation and adjustment of parameters, for example due to thermal changes. The AIDEAS Condition Evaluator will create a machine score to easily evaluate the productivity during the usage. The early detection of abnormal fault conditions of an EBM with the help of the AIDEAS Anomaly Detector will minimise expensive downtimes and time-consuming production halts. [KP12 -10%] [KP23 -15%]