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Machine Vision for Warehouse Optimization

Project: AI REGIO

Updated at: 25-01-2024

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

The experiment has achieved the following objectives:

Provide a tool able to help operators to find the exact sheet they need for production line.

The tool can significatively decrease time usually needed to find out, handle and pick up the sheet that is needed from the production line.

The tool is expected to self-learn over time.

Significance of the results for SMEs
Comment:

Optimize the Handling

Reduce Technical Checks by Humans

Improve data quality

Numerical modelling and simulation of heat treating processes

Project: CloudiFacturing

Updated at: 12-01-2024

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Tools developed and deployed on CloudiFacturing platform during this experiment allow end-users who operate water quenches to derive operational conditions of the water quench and thus, increase precision and repeatability of the process and decrease its dependence on the experience of the operator. The outcomes of the experiment also bring new knowledge to the whole process. Additionally, the developed technologies allow using numerical modeling and simulation in the design of a new generation of water quenches and their components.

Significance of the results for SMEs
Comment:

"In our field, it is no simple task to find a partner who is not only a top expert in a given field but also able to take initiative in finding innovative solutions. It is only in more challenging situations
when cooperation with real professionals is genuinely appreciated. CloudiFacturing project has certainly been the right choice", Ondřej Tůma, Managing Director, FERRAM STROJÍRNA s.r.o.

MARKET4.0 Metal domain DATA SPACE based on IDS RA

Project: MARKET4.0

Updated at: 12-01-2024

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Simplified and Efficient Selection of Suitable Manufacturing Equipment:  For the equipment manufacturer, IDSRAM permits the trusted connection of the equipment repository with external apps (ESS), permitting (in a time-saving process) the best selection of a manufacturing equipment, thanks to accessible data that where not accessible before.

The MARKET4.0 Metal Domain Data Space propose two solutions:

  • The first solution permits the connection of equipment manufacter repositories with a single connector (LMS/TNO). The benefit of this solution is that equipment manufacturers do not require knowledge of IDS RA and it is the connector owner who has it.
  • The second solution has the benefit to connect one service with several data providers through several IDS connectors. The benefit of this second solution is that the data provider controls the data flow and is independent of the connector provider.
Significance of the results for SMEs
Comment:

As a customer, easy access to equipment manufacturers repositories or to manufacturing services. As an equipment or service provider, easy access to the market.

Lessons learned
Comment:

IDS RA configuration and implementation not only on a peer to peer basis, but creating a data space.

Landing gear retraction actuator assembly: Manual deburring operation | Assembly process (CESA)

Project: A4BLUE

Updated at: 22-12-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

A collaborative robotic cell has been implemented for the deburring operation where the robot executes the most exhausting phases, while the worker focuses on final quality inspection. Regarding the assembly process, an AR solution, using ultra-real animations has been implemented to guide operators through tasks. Additional AR functionalities include the visualization of textual information (tips, best practices…), access to technical documents and voice recording

Lessons learned
Comment:

The introduction of the is perceived by workers as helpful, especially when productive tasks are exhausting and may provoke health issues. They are not received with reluctance but as supportive in workers’ tasks at the workplace. Regarding AR, it is generally considered as very useful, although the HMD (HoloLens) are too heavy for long time tasks.

Idss For Predictive Quality Assurance

Project: AI REGIO

Updated at: 17-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Automation and integration of the manual Quality Control  (QC)

Objectiveness and precision of the QC

Productive increase of QC supervisors 

Significance of the results for SMEs
Comment:

Early estimating the potential faultiness could help local manufacturing companies on planning, controlling and executing productive activities in an optimized and predictive manner.

Production planning optimization

Reduced costs 

Optimized efficiency and effectiveness of the manufacturing systems

 

Water leakage detection

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Monitoring and prediction of water consumption

Automatic detection of water leakages

Optimization of the water pipes network maintenance and installation planning

Significance of the results for SMEs
Comment:

Optimize water consumption.

Generate Reports and Field Maps

Identify malfunction in the water consumption.

Prevent unintendedly water leakages. 

Identify and Predict water consumption

Measure water quality

A Smart Predictive Maintenance Toolbox for drawing lines of car body elements - SPMTcar

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Improved fault detection

Increased facility availability

Reduced maintenance service costs (for the customer)

Reduced analysis & diagnosis times (of the Maintenance Service provider)

Significance of the results for SMEs
Comment:

Higher reliability and availability of stamping facilities by reducing downtime due to unforeseen breakdowns.

Reduced the analysis times of specialized personnel.

Reduce the costs of the Predictive Maintenance service for stamping companies, facilitating the access of SMEs to the advantages of failure prevention technologies

Improved ability to failure anticipation by being possible a much faster analysis,

Improve competitiveness of the stamping sector by reducing production costs due to unforeseen failures, as well as the Predictive Maintenance service provider

AI-enhanced control strategy for production environment

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Enhance production and control strategy with AI,

Improve  Worker’s safety using AI to identify unsafe working conditions

Improve predictive maintenance accuracy

Enable remote and highly interactive control strategy for working environment

Significance of the results for SMEs
Comment:

Reduction of maintenance costs and number of faults

Optimization of production quality (reduction of discards), costs (times, maintenance)

Optimization of safety and wellness of operators

AI-based Process Control c/o ARMAC bv

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Provide methods for the continual learning of AI model

Provide a specific user solution designed to help decision making of operators

Significance of the results for SMEs
Comment:

Estimate the weather conditions at the city of Purmerend to help operators on the decision making

Increase AI based projects at ARMAC BV

Increase the heat delivery on set point 

Reduce heat loss

Automatic Capability Matchmaking For Re-Configurable Robotics Platform

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Provide automatically feasible resource suggestions to the system designer

Reduce time used for system design and reconfiguration planning

Allow more alternative resources to be considered during design and planning, leading to potentially innovative solutions  

Reduce humane errors in search and filtering

Automating the search and filtering of feasible resources and resource combinations for specific product requirements from large search spaces.

Automating the identification of required reconfiguration actions on current layout.

Significance of the results for SMEs
Comment:

Letting the designers and reconfiguration planners to use their time for the actual design and planning tasks, instead of cumbersome search and filtering of feasible resources and resource combinations from various catalogues with somewhat incomparable information. 

Reducing human errors in resource search and filtering (e.g. potential alternative resources overlooked by human, selecting resources with incompatible interfaces) 

Increasing the amount of alternative resource solutions considered, leading potentially to more efficient production system configurations. This may mean, e.g. faster throughput time, better product quality, reduced investment cost or some other improvement, depending on the target KPIs. 

Reducing the time used for system design and reconfiguration planning activity, and thus lowering the design costs.

The Royal Eijkelkamp BV Exp.09

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Score the quality of measurement

Detect failures and their root causes

Significance of the results for SMEs
Comment:

Having insights on the accuracy of measurement in real-time is important not only for the end-user, as it can add a layer of subjectivity to the observations conclusions, but it also impacts the network management maintenance strategy.

The AI model reduces the time spent by the maintenance staff and optimize the routine of maintenance.

AI-enabled Operators Assistance through AR

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

An adaptive support system for training and guidance in assembly making use of an AI based adaptive algorithm  based on both productivity and quality as well as operator capacity and needs 

Significance of the results for SMEs
Comment:

Increase of productivity and quality of work (increase competiveness)

Increase  in workers employability

Increase in job satisfaction and reduction of work-related stress

Natural Language Processing for Troubleshooting

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

The troubleshooting system implemented in the Experiment is an AI-driven advanced solution that improved an already existing system, totally deterministic. The new solutions instead is based on a probabilistic approach. Compared to the previous one, it is:

  • more robust: each answer modifies the probability associated with each component without deleting or discarding any of them
  • more flexible: the system also includes the ability to skip a specific question
  • more efficient: the tool can determine the best question based on the probability associated with each component. 
Significance of the results for SMEs

AI for better lifecycle and project management for palstronic products

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Shorten the engineering cycle => automatic feedback and decision making

Save time and reduce cost => reduce manual operations, automation process

Automatic recommendation for printing configuration and additive manufacturing feasibility => Covering all the lifecycle (ideation, request, design, simulation …)

Significance of the results for SMEs
Comment:

SWARM platform aims to enable building blocks to digitalize the life cycle, project management, collaborative conception and additive manufacturing prototyping. 

It creates a unique and consistent source of data across the entire product lifecycle form the idea to production, including customer feedback, training and after-sale service.

Better life cycle and project management for plastronic product and automatic generation of the control process on the basis of specifications and other project documents.

AI-based Predictive Dynamic Production Planner

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Increased Overall Equipment Effectiveness

Reduced Carrying Cost of Inventory

Increased On Time Orders

Significance of the results for SMEs
Comment:

The experiment provide a useful tool to help the enterprise to optimize the inventory and the use of resources, support components purchasing, support day to day production management on shop floor, support on-time delivery, improve quality.

Predictive Analysis

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Improved Reliability of Maintenance and Service

Reduced Working Capital

Improved Customers Acceptance

Decreased Number of training data to adapt the model to new applications

Decreased Training time

Significance of the results for SMEs
Comment:

Optimization of maintenance intervals 

Reduction of regular service intervals such as (scanner cleaning, ..) by replacing a service call according to schedule with a service call according to actual need

Early detection of sensor faults (Lidar, IMU, Camera, ...) to ensure a proactive fault clearance of the system

Intelligent Computer Vision for Digital Twin and Reinforcement Learning for Assembly Line Balancing

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Deployment of an IIoT platform serving IILAB demonstrators

Increased real time visibility on a production system

Increased flexibility and efficiency of a production system

Increased robustness of operations of robotic mobile manipulators

Real-time Production Data Monitoring

Industrial Autonomous Systems Reliability

Significance of the results for SMEs
Comment:

Increased visibility on the execution of a production schedule

Increased flexibility and efficiency of a production system

Increased robustness of operations of robotic mobile manipulators

Industrial processes AI-based Optimization

Project: AI REGIO

Updated at: 04-07-2023

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Significant innovations and lessons learned, training aspects
Significant innovations and achievements
Comment:

Online prediction of the maximum number of pieces to be produced by a specific machine according to the current status of the tooling and the readings of its control parameters.

Optimization of machine control parameters configuration to maximize the tooling life while the quality of the production is maintained.

Maximization of the tooling usage time of every machine, while maintaining the machining quality.

Optimization of machine control parameters configuration to maximize the tooling life while the quality of the production is maintained

Coordination of the tooling change in all the machines. This objective would  face the tooling change considering the impact of machines among themselves, instead of just one by one.

Significance of the results for SMEs
Comment:

Tooling savings.

Operators savings. Less operators needed for machines management. 

Increase of the production due to increase of the machine availability.

Increase of quality of pieces and tools life time.

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