The X-Ray machine will be deployed at the CONT factory for quality analysis improvement and in-time defects detection. The analysis will be applied to materials and components used within the production process. Before the process start, machine requests the inspection program from ZDMP platform, if one is available, the process starts automatically.

After the inspection process finished, a report is produced and if the product or material corresponds to the specifications the production process continues, but if some deviations are detected, report is sent to the operator for detailed check.

The quality control is important stage of every production process, as a defected part can significantly affect the product functionality. To be able to find possible defects at the earliest possible stage and minimizing the effect on the whole production process at the factory scale the X-Ray inspection machine in conjunction with ZDMP platform are utilized.

The ZDMP platform assists the process of quality inspection, while providing a library inspection programs for specific materials/components. Moreover, to understand the tendency over time current measurements can be compared with historical ones.

Usually the assembling of electronic components within the CONT is performed using 6-11 working stations. AS the workstations can be from different manufacturers and have no direct connection, the goal of ZDMP platform is to provide a needed middleware and services for centralized assembly line control by acquiring data from different workstations.

The assembly process is mostly automated. However, some manufacturing stages, as well as some quality operations are performed manually. In this regard, the production process can be improved when quality and performance details can be delivered in time and to the right person.

The ZDMP platform targets more the assembly line layer, than separate workstations. The idea is to aggregate the information coming from the workstations along the assembly line and provide the quality control and performance services.

In this use-case ZDMP platform provides a middleware between the workstations and the database keeping the production process details. Moreover, it provides a set of services for the production process improvement.

The test check stations along the assembly line equipped with the cameras serving the goal of optical quality control. Data in the form of images taken within these check stations is a valuable resource that is used not only to check the quality of product, but also to improve the efficiency of quality testing programs. The images taken allow detecting, for instance, defects related to the shape of the product.

In the case of the negative automatic test, operator performs the manual check of the product comparing it with the reference images. The operator decisions with corresponding images are collected and stored to learn or extract the defects types and acceptance limits.

In the case of the negative automatic test, operator performs the manual check of the product comparing it with the reference images. The operator decisions with corresponding images are collected and stored to learn or extract the defects types and acceptance limits.

The ZDMP platform provides an optimisation services for the quality check performed within the CONT assembly line, resulting in the reduction of false-positives during the automatic test, as well as creating the models based on operator decisions used for generation of acceptance patterns.

The machine centres operating within the plant are equipped with sensors (e.g. controlling vibrations, power consumption, etc.) supplying the process data. On the other hand, industrial computers controlling the machine also provide additional information about production process, such as process times, machine status and cylinder block type in production. All these data are captured and stored within the database to be further analysed on abnormalities and to provide recommendations on changing of certain parameters to recover production process.

In some cases, FORD production engineer has to contact machine builder to get the recommendations on improving the machining process, while sending the process data to the equipment manufacturer. On the EXTE side the data undergo further analysis to provide recommendation on production process improvement. The recommended actions are manually introduced into the ZDMP platform. Afterward, the platform can assess the effectiveness of provided recommendations and improve its knowledge base.

The operation of machining equipment installed in production line can be optimised and improved through analysis of the process data acquired from the equipment. In some cases the optimisation process can be done by the platform. However, some cases might require involvement of engineers from equipment manufacturer to analyse data and provide recommendations on optimisation. The effectiveness of recommendations can be further assessed by the platform.

The ZDMP platform offers for both industrial partners an opportunity to improve the communication, through knowledge generation from the raw data. The platform also offers a service for the equipment optimisation to improve the production process.

To be able to make prediction and automated quality assessment, process data need to be gathered and presented in the form suitable for processing. Process data are gathered from various sensors and smart meters, as well as from PLCs at MRHS and automatically uploaded to the database. As the production cycle takes around 2 minutes, subsequently data are uploaded every 2 minutes. The ultimate goal is to receive the anomaly warnings close to real-time.

The process data required for anomaly detection and production process optimization are gathered from multiply sources both in MRHS and in FORD and aggregated to predict the quality of the product and a rejection probability. Based on the data gathered, the model for parameters’ optimization is generated to achieve a certain, user-defined, objective.

ZDMP platform has the goal to improve and automate the quality check on every stage of the stone slabs and tiles production. Reduce, where possible, the human involvement in the quality check to minimum, e.g. control of the wearing out of the cutting blades. Both the data about equipment performance, as well as material scanning data are utilized. Moreover, CEI machines also provide the data from cameras and projectors used to optimize the cutting process and save material.

One of the goals of the use-case is to minimize the human involvement in the quality assessment process. However, it is not always feasible, as for instance to detect natural defects of material (stone), but still operator can get significant assistance from ZDMP platform and corresponding services to automatically detect some defects.

Reduction of the scrap output of the production process, as well as automation of control check operations has significant impact on the quality of the products and leads to a more efficient use of resources.

In order to indetify the wearing out of the cutting blades, the machine is equipped with additional sensor that can detect any deviations from the normal functioning.

Utilization of ZDMP platform with corresponding services allows optimization of production process in terms of automation of production and natural defects and better use material through spatial mould optimization.

The material manufacturer stores in the platform the information concerning the production of a specific lot, including production quality control information. The work contractor is informed about the type and amount of material that are shipped to the construction side with estimated time of arrival. If some delays occur, the corresponding application running on ZDMP platform provides an assessment of the delay’s impact on the schedule and suggestions/recommendation for rescheduling.

Each user will have different levels of interaction with the ZDMP platform. Both contractor and supervisor should have access to the construction schedule, but their own task schedules should only be accessible to each of them. Similarly, the Supplier will not have access to the Supervisor or Works Contractor’s areas and vice-versa.

Coordination of the activities within the construction plays a crucial role. Delays in materials shipping and materials quality issues may significantly affect the construction process. However, not all delays have the same impact. ZDMP platform provides the necessary assistance for delays’ impact assessment and enables agile information exchange among involved partners.

ZDMP platform allows automated exchange of the critical information that can affect the schedule. Ability to adjust the activities regarding potential delays has significant impact on the construction consortia performance.

The quality assurance process will be supported by the ZDMP services for steel width detection, tube shape and horizontal and vertical weld of the steel sheet quality control.

Through utilization of ZDMP platform, the operator will get a notification, if a defect is detected. This releases the quality operator from their cursory monitoring task, and it is moved into a reactive role. Before, the operator was in charge for manual detection of possible defects. In its turn, ZDMP platform has the goal to reduce the load on operator and make the production process and quality control more self-reliant.

The assistance in quality control that is offered by ZDMP platform through the timely warning allows reduction of the amount of waste and increase in the number of quality products per meter of steel sheet.

Machinery provided by PTM will be updated with ZDMP tools for assistance of the manufacturing process.

In this use-case significant impact is made by the tools provided by ZDMP platform addressing the automation of the quality control process reducing the load on operators.

Based on the state of the cells and the robot's current pose an algorithm calculates  the next task.  The task is decomposed into a set of robot actions, navigation, manipulation or material transfer to a production cell. 

There are four production cells:

• Wash cell -  Wash  printed parts
• Sort cell - Sorts parts into trays
• Cure cell - Human loads curing oven
• 3D Print cell - prints parts on plates

The assembly line's current state can be viewed in and altered in real time using an on-line user interface