Aerospace Industry
Aerospace Industry 4.0 is part of that fourth industrial revolution known as Industry 4.0, which has made use of the most advanced IT to optimize its entire value chain.
Control of the production line
Quality control of manufacturing and maintenance processes
Automation and robotization
Empowerment of line workers
Optimization of maintenance plans
Use of digital twins for prototyping and testing
Improving confidence in the supply chain
Reduction of aircraft and component downtime
Optimization of production and maintenance schedules
Automated quality inspection
Detection of production line anomalies
Generation of reliable and secure parts authenticity verification records
Improved remote work capabilities of maintenance mechanics
Reduced training time for production and maintenance mechanics
Simulation of running and operating conditions
Leverage organizational knowledge
Real-time remote monitoring and control of on-board equipment
Business Intelligence
& Data Analytics
Artificial
Intelligence
Extended
Realities
Robotic
Process Automation
IoT
Digital
Twins
Data-driven strategies for companies in the aerospace industry.|
.| Discover the knowledge hidden in the data, from any source.
.| Do it in a collaborative way among all participants.
.| Enable all levels of the organization to make decisions efficiently.
.| Emplear capacidades de IA para acceder a centeneras de visualizaciones de datos de forma intuitiva.
.| Employ AI capabilities to access hundreds of data visualizations intuitively.
Discover the knowledge hidden in the data, from any source.
Do it in a collaborative way among all participants.
Enable all levels of the organization to make decisions efficiently.
Employ AI capabilities to access hundreds of data visualizations intuitively.
Reduce reporting times and complex solutions.
Power BI
Aerospace sector: analysis of the supply process
.| Directly applicable to the industry due to the relevance of the analysis of costs and maintenance times of auxiliary and main manufacturing equipment, assembly, etc.
.| Provides comparisons by period, including the acquisition of spare parts and labor.
.| Compares with initially planned budgets.
Mixed Reality and its tools .|
Microsoft Dynamics 365 Remote Assist
Microsoft Dynamics 365 Remote Assist enables technicians to collaborate and troubleshoot with remote collaborators using Dynamics 365 Remote Assist for mobile devices or Microsoft Teams. It reduces costs and travel time. Remote technicians can add mixed reality annotations to provide instructions in context.
Microsoft Dynamics 365 Guides
Microsoft Dynamics 365 Guides is a mixed reality tool that enables employees to learn through interactive instructions. Help your employees gain new knowledge faster without writing code with Dynamics 365 Guides on HoloLens devices.
Increase employee productivity by up to 25% through the use of available tools.
Improved training and preparation for complex tasks that require several steps for execution.
Quality assurance by providing a better service with a much more skilled staff
Optimization of direct costs thanks to remote assistance that avoids the displacement of personnel and through employee training
Digitization and automation of processes by standardizing a large part of the processes.
Optimize your production chain by obtaining statistics through tools that allow you to analyze processes and make decisions.
Remote monitoring allows companies to continuously monitor the health and performance of individual assets and entire factories to predict potential problems and manage changing customer demand.
Monitor overall machine operation.
Monitor production parameters.
Identify the presence of personnel in the factory in real-time.
Control environmental variables that may influence production or worker health and safety.
Digital Twins.|
.| Virtual models of physical objects or business processes.
.| Based on IoT platforms.
.| Possibility of remote control of operating parameters.
.| Simulation of different situations or process states.
.| Allows analysis of results and anticipation of events or risks.
.| A complete logistic chain can be simulated including manufacturing, distribution, and points of sale.
Criticality assessment
Definition of the progressive digitalization plan
Analysis of digitizable processes and objects
Detailed process definition
Evaluation of the expected return
Cost assessment
Simulation of on-board equipment operation
.| Simulation of special operating conditions.
.| Recreation of repetitive failures or failure chains.
.| Initial testing of low-cost prototypes.
.| Confirmation of component compatibility.
.| Analysis of cross-influences of parameters on subcomponents.
Digital twins – Production .|
– Environmental conditions incidence analysis.
– Simulation of production impact of equipment failures.
– Production balancing between lines.
– Production balancing between lines.
– Optimization of stock levels in the face of demand variations.
– Identification of bottlenecks in production lines.
– Definition of production buffers.
Vision Solution for the aerospace industry.|
Machine vision, also known as computer vision or technical vision, is a scientific discipline that includes methods for acquiring, processing, analyzing, and understanding real-world images in order to produce numerical or symbolic information that a computer can process.
Definition and deployment of anomaly detection solutions.|
.I Analysis of detectable anomalies in production equipment.
.I Assessment of criticality degree.
.I Definition of the appropriate detection models.
.I Deployment of AI architecture and models.
.I Deployment of detection systems, if applicable.
.I Connection with pre-existing detection systems.
.I Evaluation of the expected return.
Continuous real-time data collection/after-flight downloading
Building predictive models/learning algorithms
Real-time data analysis to detect failures
Sending alerts/notifications to perform actions
Improve equipment maintenance plan
Optimize inventories and spare parts costs
Artificial vision applied to security .|
Detection of dangerous objects
.| Aisles
.| Objects on shelves or workbenches
.| Spillage of substances
Accident detection
Automatic control of PPE use
Increases employee productivity
Immediate presentation of validation results
Cost optimization
Improved quality thanks to algorithms
guaranteed security
Speed and machine learning
KPIs and real improvements .|
– Initial reduction of 8% in processing times.
– Initial reduction of 8% in processing times.
– Complete elimination of manual process confirmations.
– Ease of scalability of the solution.
– Overall improvement of traceability throughout the process.
– 98% reduction in model training times.
– 30% reduction in image labeling time.
– Reduced hardware requirements for Poka-Yoke systems.
The Automatic Calendar Scheduler .|
Data Logging
Storage of historical data of the tasks performed.
Obtaining the different metrics of the employees.
Preparation of a scalable Data Warehouse with the relevant information.
Artificial Intelligence
Advanced analytics of the different parameters and metrics were recorded.
Application of AI models to predict which employee is the right one.
Decision-making to prioritize tasks through AI.
Calendar management
With the prioritization done, a manager updates the daily tasks of the workforce.
The workforce will be able to visualize which task is the right one to perform.
Automatically, the calendar is updated through AI.
The Automatic Calendar Scheduler.|
.| The appearance of urgent tasks on an already configured schedule with specific skill requirements.
.| Need to include priority tasks on full schedules of workers.
.| Need to apply more resources to tasks with a shorter deadline than the time needed to complete them with the resources initially assigned.
.| Assignment of tasks according to geographical location and mobility of each resource.
.| Assignment of subtasks according to skills and workload of each one.
Deploying Automatic Calendar Scheduler.|
.| Analyze the specific parameters involved in the scheduling of your jobs.
.| Adapt ACS to those parameters.
.| Connect ACS data to your own repositories, so that you use your data transparently for your company.
.| Train your team of planners to use it.
.| Support your operation and manage the application’s lifecycle.
.| Generate the reports that allow you to demonstrate the benefits obtained.
