Projects overview

Sort by


Toggle all information

Z-Fact0r | Zero-defect manufacturing strategies towards on-line production management for European factories

01-10-2016

-

31-03-2020

Show more information
Pathways
Autonomous Smart Factories Pathway
Comment:

Z-Fact0r is expected to support the transition to the so-called smart factories of the future. Smart factory is one equipped with technology that enables machine-to-machine and machine-to-human communication in tandem with analytical and cognitive technologies so that decisions are made correctly and on time. Factory automation, inparticular, implies a set of technologies and automatic control devices to enhance the productivity and quality of products and simultaneously decrease the production cost. It also entails the minimization of human intervention in the industry and ensures a superior performance as compared to humans. It comprises the use of computers, robots, control systems, and information technologies to handle industrial processes. Given the above definition, it is clear that the Z-Fact0r solution can be viewed as a factory automation tool, as it can significantly contribute to the integration and convergence of technologies for measurement and quality control, for data collection, storage and analysis at the factory level, aiming to guarantee high-quality of products without interfering, actually improving the production efficiency of the entire system. Since the concept of smart factories is under development and in practice a lot of changes are anticipated in this field in the near future, new markets may emerge or existing ones may shift to accommodate integrated and state of the art solutions, such as Z-Fact0r. 

Fortissimo 2 | Factories of the Future Resources, Technology, Infrastructure and Services for Simulation and Modelling 2

11-01-2015

-

31-12-2018

Show more information
Pathways
Autonomous Smart Factories Pathway
Realtime optimisation
Autonomous /online/realtime Manufacturing Process Optimisation on factory level
Result items:
Advanced, cloud-based HPC simulation in the foundry business
Advanced, cloud-based HPC simulation in the foundry business
Autonomous /online/realtime Manufacturing Process Optimisation on machine level
Result items:
Cloud-based HPC processing for knowledge generation in camshaft manufacture
Cloud-based HPC processing for knowledge generation in camshaft manufacture
Cloud-based-HPC optimisation of manufacturing processes
Cloud-based-HPC optimisation of manufacturing processes
HPC based high-resolution modelling of magnets
HPC based high-resolution modelling of magnets
Near Real-time Analysis of Airframe Certification Test Data
Near Real-time Analysis of Airframe Certification Test Data

ZAero | Zero-defect manufacturing of composite parts in the aerospace industry

01-10-2016

-

30-09-2019

Show more information
Pathways
Autonomous Smart Factories Pathway
Comment:

Through oinline monitoring an immediate reaction to quality problems is possible and the autonomy of the production line is increased.

Realtime optimisation
Comment:

Part flow simulation provides real-time feedback about the state of the production line and enables the evaluation of different strategies to optimize performance.

Z-BRE4K | Strategies and Predictive Maintenance models wrapped around physical systems for Zero-unexpected-Breakdowns and increased operating life of Factories

01-10-2017

-

31-03-2021

Show more information
Pathways
Autonomous Smart Factories Pathway
Comment:

Z-Bre4k will provide a complete monitoring solution at component, machine and system level by combining the high capabilities and effectiveness in sensors and actuation, networking and computational power, utilisation of better and smarter technologies (e.g. material and tools). The latest technologies and algorithms will be utilized for adaptive systems while surpassing the fact that they are disjointed, overwhelmed by complexity, vulnerable to external influence and poor Predictive Capabilities.

Realtime optimisation
Comment:

A real-time adaptive simulator with high fidelity will be a demonstrator (remote or local) of the machine’s state, in which a fast-forward simulation mechanism (prognostic models) predicts the potential events of breakdown of components and machines. What-if capabilities will allow the maintenance planners to find the most effective and cost-efficient schedules for component replacement and maintenance plans.

Autonomous /online/realtime Manufacturing Process Optimisation on factory level
Comment:

Strategies to improve maintainability and increase operating life of production will be applied to update the existing and to develop a set of new strategies based on real data in order to improve maintainability and operating life of production systems. This approach will use a method to translate optimization objectives defined at production and factory levels, into optimized maintenance policies at asset/production process levels.

Autonomous /online/realtime Manufacturing Process Optimisation on machine level
Comment:

At the asset and machine level, the Z-BR3AK solution will perform a condition monitoring and generate health status reports. Attention will be given to the faults detection through FMEA analysis (FMECA) to allow remedial actions and synchronise the manufacturing process. The proposed engine will perform monitoring, inspection and control at component, machine, system and product level to issue warnings, alerts (e.g. about deviations from production and quality requirements), reports on (potential) failures or failure prone situations and pass related information to a higher-level Z-Bre4k DSS (for decision support at manufacturing and enterprise level).

ROSSINI | RObot enhanced SenSing, INtelligence and actuation to Improve job quality in manufacturing

01-10-2018

-

31-03-2022

Show more information
Pathways
Autonomous Smart Factories Pathway
Comment:

ROSSINI provides several advances beyond the state of the art, developing a Safety Aware Control Architecture for robot cognitive perception and optimal task planning and execution. 

In order to enable actual perception, ROSSINI leverages on a data processing technique for real-time image recognition, to obtain a semantic scene map that adapts to dynamic working conditions. 

ROSSINI adopts also algorithms for motion prediction of humans and moving entities, and embeds their stochastic information in the dynamic semantic scene map. This allows the robot to further refine its planning in order to maximize performance while preserving safety. 

In this way, ROSSINI introduces a novel perception and control architecture blending safety and performance oriented planning/control that wants to reach the goal of optimising the trade-off between human operator safety and manufacturing productivity.

Realtime optimisation
Comment:

The ROSSINI platform implementation of a Safety Aware Control Architecture makes it possible for robots to optimally schedule the tasks reacting to a changing environment. in fact, each action to be execute is sent to a dynamic planner that dynamically optimizes its execution in terms of trajectory to follow and/or interactive behaviour to reproduce while considering the variable safety conditions in the working area. 

FA3D | Future Automated Aerospace Assembly Demonstrator Project

Show more information
Pathways
Autonomous Smart Factories Pathway
Connected IT and OT
Result items:
Manufacturing Service Buses for Data Interoperability
Manufacturing Service Buses for Data Interoperability

ATS Bus   - Enabled a single, common service bus for data exchange between the PLCs and other high level components of the system, including a SCADA system. Used a broker-based publish-subscribe approach to decouple the physical sources and destinations of the data to facilitate reconfigurability.

 

VIEWS | Validation and Integration of Manufacturing Enablers for Future Wing Structures

Show more information
Pathways
Autonomous Smart Factories Pathway
Connected IT and OT
Result items:
Manufacturing Service Buses for Data Interoperability
Manufacturing Service Buses for Data Interoperability

ATS Bus   - Enabled a single, common service bus for data exchange between the PLCs and other high level components of the system, including a SCADA system. Used a broker-based publish-subscribe approach to decouple the physical sources and destinations of the data to facilitate reconfigurability.

 

X-ACT | Expert cooperative robots for highly skilled operations for the factory of the future

01-10-2012

-

30-09-2015

Show more information
Pathways
Autonomous Smart Factories Pathway
Off-line optimisation
Off-line Digital Manufacturing Process Optimisation on factory level
Comment:

Simulation of Robot and human processes at station level.

Off-line Digital Manufacturing Process Optimisation on machine level
Comment:

Dual arm robot simulation developed.

Realtime optimisation
Autonomous /online/realtime Manufacturing Process Optimisation on factory level
Comment:

Integration of Robot and human processes at station level.

Autonomous /online/realtime Manufacturing Process Optimisation on machine level
Comment:

Dual arm robot planning and contorl developed.

ReconCell | A Reconfigurable robot workCell for fast set-up of automated assembly processes in SMEs

11-01-2015

-

28-02-2019

Show more information
Pathways
Autonomous Smart Factories Pathway
Off-line optimisation
Off-line Digital Manufacturing Process Optimisation on factory level
Off-line Digital Manufacturing Process Optimisation on machine level
Realtime optimisation
Autonomous /online/realtime Manufacturing Process Optimisation on factory level
Autonomous /online/realtime Manufacturing Process Optimisation on machine level

DISRUPT | Decentralised architectures for optimised operations via virtualised processes and manufacturing ecosystem collaboration

01-09-2016

-

31-08-2019

Show more information
Pathways
Autonomous Smart Factories Pathway
Connected IT and OT
Result items:
D2.3: The DISRUPT Platform Integration Plan
D2.3: The DISRUPT Platform Integration Plan
MOM-SCADA systems connected
Result items:
D2.3: The DISRUPT Platform Integration Plan
D2.3: The DISRUPT Platform Integration Plan
IoT enabled SCADA, MOM-MES, ERP (…) connectivity
Humans actively connected
Comment:

CloudBoard: offers multiple views and access rights to different human actors Decision Support Toolkit: supports decisions authorised by humans, especially in the shop floor Enterprise and Factory models: accessible and re-configurable through user interaction

Off-line optimisation
Off-line Digital Manufacturing Process Optimisation on factory level
Platform enabled optimisation
Result items:
D2.3: The DISRUPT Platform Integration Plan
D2.3: The DISRUPT Platform Integration Plan

SAFIRE | Cloud-based Situational Analysis for Factories providing Real-time Reconfiguration Services

01-10-2016

-

30-09-2019

Show more information
Pathways
Autonomous Smart Factories Pathway
Connected IT and OT
IoT enabled SCADA, MOM-MES, ERP (…) connectivity
Result items:
Methodology for Dynamic and Predictable Reconfiguration and Optimisation Engine
Methodology for Dynamic and Predictable Reconfiguration and Optimisation Engine
Realtime optimisation
Autonomous /online/realtime Manufacturing Process Optimisation on factory level
Result items:
Methodology for Dynamic and Predictable Reconfiguration and Optimisation Engine
Methodology for Dynamic and Predictable Reconfiguration and Optimisation Engine

ZDMP | Zero Defect Manufacturing Platform

01-01-2019

-

30-06-2023

Show more information
Pathways
Autonomous Smart Factories Pathway
Result items:
Assembly line: AI-supported optical defects detection
Assembly line: AI-supported optical defects detection
Assembly line: monitoring and control system
Assembly line: monitoring and control system
Construction supply chain: quality control at construction site and quality traceability
Construction supply chain: quality control at construction site and quality traceability
Electronic products manufacturing: Component inspection
Electronic products manufacturing: Component inspection
Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations
Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations
Engine block manufacturing: Defects reduction by the optimization of the machining process
Engine block manufacturing: Defects reduction by the optimization of the machining process
Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning
Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning
Steel tubes: production monitor
Steel tubes: production monitor
Stone tiles: equipment wear detection
Stone tiles: equipment wear detection
Connected IT and OT
Result items:
Construction supply chain: quality control at construction site and quality traceability
Construction supply chain: quality control at construction site and quality traceability
Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations
Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations
Steel tubes: production monitor
Steel tubes: production monitor
Stone tiles: equipment wear detection
Stone tiles: equipment wear detection
ERP-MOM systems connected
Result items:
Construction supply chain: quality control at construction site and quality traceability
Construction supply chain: quality control at construction site and quality traceability

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.

IoT enabled SCADA, MOM-MES, ERP (…) connectivity
Result items:
Assembly line: AI-supported optical defects detection
Assembly line: AI-supported optical defects detection

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.

Assembly line: monitoring and control system
Assembly line: monitoring and control system

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.

Electronic products manufacturing: Component inspection
Electronic products manufacturing: Component inspection

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.

Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations
Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations

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.

Engine block manufacturing: Defects reduction by the optimization of the machining process
Engine block manufacturing: Defects reduction by the optimization of the machining process

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.

Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning
Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning

The sensors deployed on the FORM side are used to aquire the process and the equipment data. These data are sent and stored on the ZDMP platform that is used to detect the abnormalities and failures right after they occur and immediately inform the operator, but also to be able to predict and avoid further malfunctions. The components of the ZDMP platform are used to detect any deviations from the normal production process.

The parameters of each manufacturing operation are reported to the ZDMP platform. Within ZDMP platform the parameters are analysed to identify, if selected parameters will result in the good quality and if not, how the parameters can be changed.

Moulds manufacturing: in-line 3D modelling
Moulds manufacturing: in-line 3D modelling

he collision avoidance software relies on the 3D models acquired by scanning of the working area. However, before the 3D model can be built the scanning results, also called “cloud of points”, are cleaned and processed.

Steel tubes: production monitor
Steel tubes: production monitor

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.

Stone tiles: equipment wear detection
Stone tiles: equipment wear detection

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.

Humans actively connected
Result items:
Assembly line: AI-supported optical defects detection
Assembly line: AI-supported optical defects detection

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.

Assembly line: monitoring and control system
Assembly line: monitoring and control system

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.

Construction supply chain: quality control at construction site and quality traceability
Construction supply chain: quality control at construction site and quality traceability

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.

Electronic products manufacturing: Component inspection
Electronic products manufacturing: Component inspection

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.

Engine block manufacturing: Defects reduction by the optimization of the machining process
Engine block manufacturing: Defects reduction by the optimization of the machining 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.

Moulds manufacturing: in-line 3D modelling
Moulds manufacturing: in-line 3D modelling

The operator is involved in the working area scanning process. Afterwards the scanning results can be automatically sent to the ZDMP platform to be further processed and converted into the .stl format.

Steel tubes: production monitor
Steel tubes: production monitor

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.

Stone tiles: equipment wear detection
Stone tiles: equipment wear detection

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.

Off-line optimisation
Result items:
Construction supply chain: quality control at construction site and quality traceability
Construction supply chain: quality control at construction site and quality traceability
Steel tubes: production monitor
Steel tubes: production monitor
Stone tiles: equipment wear detection
Stone tiles: equipment wear detection
Off-line Digital Manufacturing Process Optimisation on factory level
Result items:
Assembly line: AI-supported optical defects detection
Assembly line: AI-supported optical defects detection

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.

Assembly line: monitoring and control system
Assembly line: monitoring and control system

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.

Construction supply chain: quality control at construction site and quality traceability
Construction supply chain: quality control at construction site and quality traceability

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.

Electronic products manufacturing: Component inspection
Electronic products manufacturing: Component inspection

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.

Steel tubes: production monitor
Steel tubes: production monitor

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.

Stone tiles: equipment wear detection
Stone tiles: equipment wear detection

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.

Off-line Digital Manufacturing Process Optimisation on machine level
Result items:
Engine block manufacturing: Defects reduction by the optimization of the machining process
Engine block manufacturing: Defects reduction by the optimization of the machining process

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.

Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning
Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning

If the machine suffers major or unexpected failure, the machine is likely to be stopped. However, some other problems, such as components wearing, can lead to significant degradation in performance. In this regard, an early diagnosis of the defects and early detection of degradation signs reduces production process time. Moreover, introduction of preventive measures, in terms, for instance, of parameter adjustment, allows quality improvement and reduction of defected parts.

Moulds manufacturing: in-line 3D modelling
Moulds manufacturing: in-line 3D modelling

Besides the anomalies caused, for instance, by equipment degradation, this use-case targets the human error called collision. Some common collisions identified by the industrial partners are: movement of the milling head crashing into workpiece or machine itself or the CAD/CAM model defines paths involving movements that cause a crash. Collision avoidance is critical for machine damage prevention, as well as product quality maintenance.

Steel tubes: production monitor
Steel tubes: production monitor

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

Stone tiles: equipment wear detection
Stone tiles: equipment wear detection

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.

Platform enabled optimisation
Result items:
Assembly line: AI-supported optical defects detection
Assembly line: AI-supported optical defects detection

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.

Assembly line: monitoring and control system
Assembly line: monitoring and control system

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.

Construction supply chain: quality control at construction site and quality traceability
Construction supply chain: quality control at construction site and quality traceability

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.

Electronic products manufacturing: Component inspection
Electronic products manufacturing: Component inspection

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.

Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations
Engine block manufacturing: Defects detection and prediction in aluminium injection and machining operations

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.

Engine block manufacturing: Defects reduction by the optimization of the machining process
Engine block manufacturing: Defects reduction by the optimization of the machining process

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.

Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning
Moulds manufacturing: Process alert system for machine tool failure prevention and Smart process parameter tuning

The ZDMP platform which is deployed outside of the FORM facility, allows for FORM to reduce the maintenance and investment costs for an internal platform that is important for SME. Moreover, ZDMP platform, as data and knowledge aggregator can be utilized by all industrial partners in order to optimise the production process.

Moulds manufacturing: in-line 3D modelling
Moulds manufacturing: in-line 3D modelling

The ZDMP platform which is deployed outside of FORM, allows for FORM to simplify the process for data acquisition and processing enabling quick and effortless way of anti-collision system utilization.

Steel tubes: production monitor
Steel tubes: production monitor

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.

Stone tiles: equipment wear detection
Stone tiles: equipment wear detection

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.

Powered by Chris Decubber BV