Relevant:
Associated Results
Optimize the Handling
Reduce Technical Checks by Humans
Improve data quality
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.
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.
Higher product quality, higher production flexibility, optimized costs
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
Increase of productivity and quality of work (increase competiveness)
Increase in workers employability
Increase in job satisfaction and reduction of work-related stress
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.
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
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.
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
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
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
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
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
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.