ZDMP | Zero Defect Manufacturing Platform 01-01-2019 - 31-12-2022 Calltopic: DT-ICT-07-2018 : 89 | : 10 Show more information Pathways Hyperconnected Factories Pathway Results: Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations Comment: For the quality assessment and prediction service is crucial to aggregate the data from both the Martinrea Honsel (MRHS) and FORD industrial partners. The quality forecasting or prediction allows optimising and adjusting the production process to achieve better quality of the product – aluminium cylinder blocks, which is not possible or less accurate without digitalized data exchange between industrial partners. Engine block manufacturing: Defects reduction by the optimization of the machining process Comment: In this use-case the main data supplier is the FORD manufacturing facility. The other industrial partner provides the services around the life cycle of the product (machining equipment) deployed within the FORD facility. These services are only possible under the extensive data exchange process between industrial partners (assistance from ZDMP platform), so that the ETXE – equipment manufacturer/supplier, can assist in terms of maintaining the quality of equipment operation. Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning Comment: The main data supplier is the FORM industrial partner. After the data are gathered, they are sent and stored within the ZDMP platform deployed outside of FORM. The data are critical to feed ZDMP platform providing the quality control services. Additionally, data can be shared with FIDIA equipment manufacturer to assist with equipment-related quality problems. Electronic products manufacturing: Component inspection Comment: This use-case targets not only the quality assessment process within the CONT plant, but also can be used by the supply partners delivering material and components for the CONT, as the reports/feedback can be also shared with them. Assembly line: AI-supported optical defects detection Comment: This use-case has the goal to optimize the quality check process within the CONT assembly line. Data that are not utilized by the previous quality check process are used by ZDMP platform services to complement the process. Assembly line: monitoring and control system Comment: In this use-case, besides the services providing performance check and quality control, ZDMP platform also enables communication of the workstations and the database keeping the relevant data. Steel tubes: production monitor Comment: The tools provided by ZDMP are integrated with the steel tube machines automating some critical quality check tasks, while improving the overall quality control process. Stone tiles: equipment wear detection Construction supply chain: quality control at construction site and quality traceability Basic internal connectivity Results: Stone tiles: equipment wear detection ERP and SCM connected Results: Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations Electronic products manufacturing: Component inspection Comment: The usage of ZDMP platform in conjunction with the X-Ray machine allows to automate the quality check process and to improve the inspection scope (as before only few items from each lot of materials/components are checked on compliance with specification due to time constraints). The new approach allows extending the number of inspected parts, only requiring operator involvement, when the deviations from specifications are detected. Assembly line: AI-supported optical defects detection Comment: ZDMP platform assists the internal quality check system. The quality check stations along the assembly line provide the images for optical quality control. These data along with quality test results are accumulated and analysed by ZDMP platform, and the feedback is generated. Assembly line: monitoring and control system Comment: All workstations are connected to the driver layer allowing equipment to communicate with server line layer. The data extracted from the equipment are stored, used by services and made ready for visualization. Stone tiles: equipment wear detection Comment: The stages of production process are tightly interconnected. If ZDMP platform detects the wearing out of the cutting blades, the production process has to be stopped not to possibly waste the material. Or, if some natural defect of material is being detected, it can be still possible to use the material through adjustment of the moulds and avoid the defected part.
