ICP4Life | An Integrated Collaborative Platform for Managing the Product-Service Engineering Lifecycle
01-01-2015
-31-12-2018
01-01-2015
-31-12-2018
11-01-2015
-31-10-2018
09-01-2015
-31-08-2018
01-01-2019
-31-07-2022
As it is described on the Autonomous Smart Factories, in this use case, in addition to the tools that make possible to improve and optimize the manufacturing connected process, it also intends to highly reduce the defective manufacturing increasing the product lifecycle control loop, improving the manufacturing process thanks to the information provided through the product quality control process.
In this use case, GHI and Innovalia will share data in a trust manner through an IDS connector, so that GHI will be able to find correlation between the quality of the parts and the furnace operation parameters.
01-01-2019
-30-06-2023
The suppliers of material to the construction side should be able to timely deliver the data about the quality of materials and, if needed, provide a replacement avoiding significant delays. Even, if the quality of materials is according to specification, accidents leading to material defects can happen during the shipment or on the construction side. Thus, it is important to constantly track the situation to react on the changing circumstances. For the construction company, on the other, hand, is important to align the material shipments to keep up with the schedule.
Sse-cases offer an additional services for quality assessment and prediction based on the aggregated data from the participating industrial partners (Martinrea Honsel (MRHS) and FORD) that will be provided by the ZDMP platform. In this case, the service covers only specific product lifecycle stage, when the product – aluminium cylinder blocks, is produced and arrives at FORD to be used in engine production, as the defected blocks are filtered both at MRHS and FORD. Thus, the goal is to reduce the amount of defected parts through collaboration between two industrial partners.
During the production process, various deviations from the normal functioning of the machining equipment can arise in the given use-case. It is important that ETXE equipment manufacturer could provide a service addressing the whole life cycle of the product (machining equipment) supported by ZDMP platform. The service has the aim of keeping the high efficiency of the machines through detection of abnormalities and quick recovery to the efficient state.
The quality assessment of the products is performed by the FORM industrial partner that utilizes equipment delivered by FIDIA. Degradation in the equipment performance can cause significant quality drop on the FORM side. In order to avoid this, ZDMP platform aggregates the process and equipment data and performs analysis to identify the defects occurring, as well as to detect possible equipment degradation. Analysis of equipment degradation is preformed in cooperation with equipment suppliers.
In order to enable the required automation level for the quality check of the manufacturing process, the necessary equipment will be updated with the ZDMP tools and corresponding services.
This use-case offers additional update to the stone cutting machine through the cutting blades quality control, identifying wearing out. Moreover, the CEI machines allow users to customize the shape and form of products through different moulds and ZDMP provides support for more efficient material usage through more efficient projection of the moulds.
The data generated within the FORD facility are shared with the equipment supplier ETXE with assistance of the ZDMP platform. The local instance of the ZDMP platform is hosted on the FORD side ensuring data protection and confidentiality, while the communication with ETXE is granted. The raw data, as well as aggregated knowledge by ZDMP platform are shared with ETXE for to introduce the recommendations on production process optimization.
The ZDMP platform acquires the process and equipment data from FORM and provides a set of innovative services, namely: (i) parameter adjustment, (ii) operator alerting in case of defect, (iii) correlation among various parameters related to equipment and parameters selected. In the case, when equipment manufacturers need to be involved in the problem solving, data can be securely shared through ZDMP platform.