The CONT industrial partner supplies automotive components for different car producers. To ensure the highest quality of products it uses automatic and manual final tests. The automatic test presumes comparison of images taken by one or more cameras, placed in the check stations along the assembly line, with images of expected product. If the product fails during the automatic test it is sent to the operator that performs manual test, while comparing the product image with reference image. In order, to reduce the number of quality incidents (e.g. related to false positives) during automatic test, ZDMP platform offers a set of services utilizing Artificial Intelligence to learn defects types and acceptance limits, improve testing programs though analysis of false positives resulting in improvements of base models for optical check.

Two industrial partners are involved in this use-case: MASS producing equipment for process automation and CONT producing components for car industry and using MASS equipment within the assembly line. The goal of the use-case is to reduce the quality incidents, equipment breakdown time, time for automatic change (switching the line from producing one product to another) and to increase line productivity based on fast reaction and preventive actions using the ZDMP platform. The ZDMP platform has the driver providing the interface between the equipment and the server side and provides a set of services, namely: (i) product version control and changeover, (ii) automatic call for maintenance, (iii) power management, (iv) cycle time monitoring, (v) automatic material ordering, (vi) data archive control and (vii) visual management and reporting.

This use-case involves 3 industrial partners: FLEX – the steel tubes producer, ALONG – the stone slabs produces and CONS – the construction company. FLEX and ALONG are suppliers hired by the Works Contractor and approved by the Works Supervisor (CONS) to provide, respectively, steel tubes for the formwork and stone slabs for the infrastructure being built. The supply delays sometimes can significantly affect the working schedule causing the productivity loss. In this regard, the goal is to avoid the delays that are considered as defects in this case. Thus, it is important that all the parties have an early access to information about potential delays and about the quality of supplies to act quickly and, if needed, to reschedule activities.

The use case includes two industrial partners, ALFA the company which focus is on X-Ray material inspection and CONT plant located in Timisoara that produces instrument clusters and displays for car manufacturers. The use-case presumes the introduction if the X-Ray machine for material and components quality check in order to identify deviations from specifications. One of the production lines of the CONT plant will be utilized for the use case. Moreover, additional functionality will be provided through ZDMP platform to store the inspection samples, as well as statistical analysis of current measurements with historical data/samples.

The use cases address the engine block manufacturing process, in terms of detecting and predicting defects in aluminium injection and machining operations. Two industrial partners are involved in this use-case – the Martinrea Honsel (MRHS), located in Madrid, specialized in manufacturing of aluminium cylinder blocks and FORD Valencia Engine Plant finishing the rough Cylinder Blocks received from MRHS to produce engines. The main types of defects occurring are categorized into two groups: porosity and leakage. The goal is to improve the quality through the scrap output reduction, but also to provide the quality predictions.

The machines of ETXE industrial partner are installed on the FORD plant as a part of cylinder block production line. The raw process data are collected about the equipment state, as well as about the production process itself (e.g. type of cylinder blocks being produced at the moment). These data are utilized in order to detect anomalies/abnormalities and to develop a mitigation plan to return to the efficient production state. In mitigation plan development the ETXE equipment supplier has one of the leading roles. The ZDMP platform, in this case, has the goal to assist in the fulfilment of this task, through knowledge generation and automation of abnormalities detection.

This use case includes two industrial partners, FORM – producer of moulds for plastic injections and FIDIA machine producer. To protect the machines it is important to avoid collisions, for instance, between the machine and the workpiece. FIDIA industrial partner also supplies the anti-collision software based on 3D models in .stl format. The 3D models are generated from the data acquired by scanning of the working surface, including machines, tools, target workpieces and other objects within the working area. ZDMP platform has the aim to simplify the whole process of 3D models generation from communication to data cleaning and processing.

These use-cases come from the machine tools domain encompassing three industrial partners: (i) HSD – the electro spindle manufacturer, (ii) FIDIA – the manufacturer of high-speed milling systems and flexible manufacturing systems using the HSD spindles in their products, and (iii) FORM – enterprise for maintenance and modification of the of the large plastic injection moulds utilizing machines from FIDIA. The goal is to collect the equipment and machining process data to detect the abnormalities in the production process and inform the operator on the FORM side. In the case, if the quality control detects a scrap part the machine tools user (FORM) can ask FIDIA for to identify the cause of the defect, while FIDIA, in its turn, can acquire help from the HSD, if the problem is with the electro spindle. Another goal is to be able to adjust the parameters of the production process to achieve the optimal quality results.

Two industrial partners are involved in this use-case: PTM – the steel tube machine tool manufacturer and FLEX – steel tubes producer that is using PTM machines. The current method that is applied for quality control relies on the operator evaluating tubes for defects. If defect is detected, the operator has to stop the production process and adjust production parameters, as defects are tending to propagate to the next tube being produced. This use-case has the goal of reducing the load on the operator through automation of quality checking tasks and producing the warning, if defect is detected. In this way, the risk of human errors is reduced through the introduction of the defects detection tools.

Another use-case addresses a very specific area of stone slabs ant tiles production. The industrial partners involved are: CEI – the manufacturer of the stone cutting machines and ALONG – producer of stone slabs and tiles. The process of stone slabs and tiles production includes several steps: (i) raw stone is cut and divided in multiply stone slabs, (ii) polishing of the stone slabs, and (iii) then the tiles moulds are used to cut the stone slabs. After every stage a quality check is performed to identify possible material defects, such as voids, natural cracks, etc, as well as production defects. The use-case has multiply goals, including: amount reduction of defected parts due to equipment failures, automation of the quality check procedure reducing the manual checks and correspondingly the load on operator considering both natural defects and production defects detection.

Industry Scenarios and Use Cases