SUCCESS STORIES

PROBLEMS

In the manufacturing process of parts for the automotive sector, the assembly by welding of certain mechanical components can be affected by deformations that could be detrimental to quality.

Until then, the result could only be determined by manual inspection, resulting in a significant loss of raw material and time.

RESULTS

• Deformation prediction through the Digital Twin
• Reduction of time and raw material in the testing process of the parts.
• Higher quality of the assembly result by obtaining more robust parts thanks to the predictive model.

SOLUTION

Predictive model of part deformation:

• Investigation of previous parts (pre- and post-assembly) to determine the influence of the parameters involved on the final finish.
• Development and training of a predictive model to estimate the deformations of the given part under input conditions.
• Establish acceptance thresholds to translate these deformations into quality metrics.

TOOLS

PROBLEMS

• Data from different equipment involved in the drug manufacturing steps are manually sorted in Excel tables.
• In the absence of an integrated data collection study, data needs to be exploited and processed manually, and human errors can occur.

SOLUTION

Creation of a platform that receives data from the manufacture of medicines, displaying them in real time and providing different types of graphs and statistical data. of medicines, displaying them in real time and providing different types of graphs and statistical data in order to check the evolution of processes and quality controls.

RESULTS

• Reliable and quality data collection
• Statistical reports and graphs to improve the work of pharmaceutical production sites
• Better results at the end of quality processes, considerably reducing waste.

TOOLS

PROBLEMS

Hospitals do not have an optimal method to transform all the data already recorded into relevant information, so the ability to identify patients at risk of non-adherence to their treatment increases considerably.

RESULTS

• Increasing the quality of information for prescribing treatment.
• Increased capacity and agility in decision-making.
• Reduction in the number of unscheduled consultations and visits or emergencies.
• Reduction in the number of hospital admissions.

SOLUTION

It is proposed to create a predictive model to predict the risk of non-adherence to oral antineoplastic therapy. The aim is to identify, from the outset, those patients on whom it will be necessary to focus interventions and resources individually, without having to wait for possible clinical and/or economic consequences.

TOOLS

OBJECTIVE

The client requires a solution that allows him to automate the reading of license plates and the identification of vehicles (make/model) in order to be able to invoice the corresponding tariff.

RESULTS

Development of a tool that by means of Artificial Vision-Deep Learning (convolutional neural networks), allows the reading of license plates.

Development of a vehicle category classification system.

Some of the advantages gained are:

• Task automation
• Improving the quality of information
• Optimisation of invoicing conditions

SOLUTION

• Computer vision
• Neural networks (CNN)
• Machine Learning: object classification and detection algorithms.

TOOLS

OBJECTIVE

The customer has several hydraulic presses for the manufacture of parts in the automotive sector, each of which has a sensor to monitor its correct operation.

Another of our customers, with a similar case, has a combined cycle electric generator that monitors the air fuel flow parameters as well as the electrical parameters of the power generated and has a series of alarms that warn if anything is outside the operating limits considered as normal.

The need for these customers lies in anticipating any problems that might occur with the machines, with the intention of preventing unscheduled downtime.

SOLUTION

It is proposed to develop a data acquisition system for the more than 700 sensors, centralised in a platform that allows us not only to measure their operation in real time, but also to develop a predictive model.

RESULTS

• Reduce the number of breakdowns by 55%.
• Downtime reduction (MTTR = 60%)
• Reduction of spare parts stock
• Increased life of parts
• Increase in production (30%)

TOOLS

OBJECTIVE

The customer requires a solution to optimise the costs and maintenance time of the Spanish railway infrastructure.

RESULTS

• Enormous reduction in the working time of the maintenance team required for track maintenance.
• Reduction of the cost associated with it

SOLUTION

Artificial vision model using neural networks that allows:

• Detect and analyse each frame automatically
• Detect elements that are in a state of deterioration.
• Identify anomalous or non-infrastructure items
• Establish a register of those points on the road where the deteriorated elements are located.

TOOLS

OBJECTIVE

The customer requires a tool that allows it to exploit the data from the Data Link of the air traffic control system to facilitate the analysis and monitoring of the data.

Therefore, it is proposed to automate the processing and exploitation of log data from the air traffic control system to monitor the occurrence and frequency of different types of messages.

SOLUTION

The main objective of the project is the analysis, design, development and implementation of a data processing and exploitation tool that facilitates the reading and analysis of air traffic control system messages, ensuring their quality control.

RESULTS

• Time and cost savings in data collection (centralised, accurate, quality and traceable).
• Optimise decision making, through an intuitive and robust exploitation layer.
• Focus the effort on the business and not on technology or on manual or semi-manual procedures.
• Provide users with the self-service capability to perform their own analysis.

TOOLS

OBJECTIVE

The main objective of the project is the construction of an information extraction process, mainly from the ERP, for the monitoring of commercial information from the second-hand vehicle department and its subsequent consultation, ensuring the quality control of the information.

SOLUTION

To cover the main needs of information analysis and automatic generation of information, guaranteeing scalability and future maintenance.

RESULTS

• Optimisation of the selling price of used vehicles.
• Estimation of the depreciation of a given asset in order to know when to sell it.
• Establish a sales scenario simulation model.

TOOLS

PROBLEMS

The project aims to develop a comprehensive solution to customise a "Virtual Subscriber Office", adapting pre-existing components and microservices. The aim is to create a highly configurable system that allows the user interface, logos, icons and functionalities to be adjusted from an entity configurator. In addition, a new FrontEnd microservice will be developed using the shared infrastructure, facilitating the efficient adaptation of the platform. Modifications will also be made to the microservices to integrate forms, manage styles and functionalities dynamically, adapting to the specific needs of the client.

RESULTS

• Flexible configuration of the "Virtual Office" according to customer requirements
• Use of microservices and pre-existing components to reduce time and costs.
• Creation of a FrontEnd microservice that facilitates the adaptation of the platform.
• Modification of forms, styles and functionalities in a flexible and dynamic way.

SOLUTION

• A customised Virtual Subscriber Office (VSO) will be created for the customer, including logos, images and specific mobile applications.
• An entity manager will be set up to allow independent customisation of aspects such as look & feel, URLs and logos, and a separate database will be established for each entity.
• The OVA will be adaptable to external systems and will allow integration with document managers, payment gateways and other systems, guaranteeing an independent configuration for each entity.

TOOLS

PROBLEMS

Development of an application of monitoring of the operation, management and monitoring of a solar, storage, hydrogen generation or hybrid plant, which makes it possible to visualise in an efficient way and in real time the condition and performance of the equipment, as well as manage alarms and generate reports customised.

SOLUTION

• Modular architecture, using technologies such as Angular for the front-end and Java for the back-end.
• Azure PaaS services, such as Azure Database PostgreSQL, for database management and real-time data ingestion.
• Azure Active Directory (Azure AD) for user authentication.
• Visualisation of geolocated plants on an interactive map using the Leaflet library.
• Display of weather forecast for each floor according to time zone.

TOOLS

PROBLEMS

Rocket engine propellants are used to generate the thrust needed to move a rocket, and are generally developed by the companies' r&d department, forming part of the most important developments within all types of munitions.

PURPOSE

EXCELTIC's work covers the following tasks:

• -Indoor, outdoor and effect ballistic simulation.
• -Thermochemical simulations.
• -Preparation and review of documentation.
• -Development of test plans and analysis of results.

CHARACTERISTICS

• Small, medium and large calibre
• Cross-cutting rocket engines for all products.
• Support for SILAM and SPIKE projects.
• Initiating Devices.

TOOLS

PROBLEMS

The F-100 frigates, also known as the Álvaro de Bazán class, are a class of multi-mission frigates built for the Spanish Navy. They are the first European warships to use the AEGIS combat system and are considered among the most advanced frigates in the world.

PURPOSE

EXCELTIC takes part in the following tasks for the WECDIS, Cartographic Server and IFF systems:

• Development of Graphical Interfaces with QT.
• Design of tests for verification and validation of the software of the different projects.
• Performance of FAT and Regression tests.
• Development of new SW functionalities. Documentation and creation of guides for developers.

CHARACTERISTICS

• Functionality and performance testing
• Sensor simulation
• Manual and automatic regression tests
• Standards STANAG and UNE-EN IEC 62288

TOOLS

PROBLEMS

Exceltic collaborates with the industry's leading rolling stock companies in the system. TCMSin electromechanical systems (doors, traction, braking, air conditioning, lighting), auxiliary power systems (inverters, converters, batteries, power generation, heating) and in the communication and diagnostic systems, collaborating in the areas of design, architecture and systems engineering, ensuring that the train control and monitoring systems are efficient, safe and fully integrated into the railway operation. Some of the most important projects include Metro Barcelona, Australia and Switzerland.

SOLUTION

• Definition of interface-specific tests.
• Definition of test protocols and procedures.
• Definition and manufacture of specific tools.
• Urgent resolution of incidents.
• Test performance and reporting.
• Preparation of maintenance documentation.

PURPOSE

EXCELTIC takes part in the entire product life cycle:

• Design, defining and developing a system that meets the functional and operational needs of the train,
• -Architecture, creating the technical structure that allows the different subsystems of the train to be properly integrated, both at software and hardware level, making the system work as a single ecosystem, optimising performance and safety
• .-Systems engineering, developing technical solutions to ensure that the TCMS is designed to meet safety, reliability and availability standards.

TOOLS

PROBLEMS

Exceltic collaborates with the main technology companies in the railway sector by carrying out design tests with interlocking equipment and, subsequently, validation and verification tests of ENCE/CBTC/ERTMS railway systems.in both national and international projects, participating in projects as important as Chamartín, PCB, Monforte de Lemos, Parets - La Garriga or Pravia - Gijón at national level or Metro Medellín, EKB, Ankara - Konya, Metro Finland or Metro Oporto at international level.

CHARACTERISTICS

• Specific knowledge of centralised traffic and control systems.
• Knowledge of virtual environments, both Windows and Linux.
• Knowledge of railway regulations.
• Document and requirements management.
• Development of protocols and creation of test cases.
• Critical analysis for the resolution of non-conformities.

PURPOSE

EXCELTIC takes part in the entire validation cycle:

• Traceability of requirementsusing tools such as Doors to correctly track the requirements of the test version.
• Development of test protocolsThe test scenarios necessary to validate the requirements of the released version will be created.
• Test execution and debugging using simulation environments such as vmware, simulating the conditions that will later be encountered in a real environment.
• Generation of results reports, developing test tracking KPIs for subsequent traceability.
• Non-conformity management, producing a detailed graphical and detailed report on the problems encountered.

TOOLS

PROBLEMS

We implemented an integrated automation and QA system, specifically designed for the air traffic management (ATM), focusing on two key areas: Communications and Robot Framework Solutions. This project addresses the challenges of validating critical communication protocols and automating functional cases, ensuring high levels of safety, reliability and performance in aviation-critical systems.

RESULTS

• Efficient automated solutions, automating more than 80% of manual test cases
• Significant increase in the safety, reliability and efficiency of ATM systems.
• Successful simulation and validation of critical scenarios
• Market-ready solutions, guaranteed compliance with international standards

SOLUTION

Innovation Platform for ATM

• Development and execution of automated tests to validate the behaviour of standard protocols.
• Automation of specific test cases to ensure the correct operation of communication systems.
• Automation of functional tests in areas such as monitoring, traffic management and interface validation.
• Automatic reporting and real-time analysis to detect anomalies in early stages of development.

TOOLS

PROBLEMS

The problem in this case was a manual reading process of codes on box labels by means of a scanner gun to take inventory of the material entering the warehouse. The process blocked a worker completely and could last up to 45 minutes.. The development of the solution frees the worker from interacting with the cash registers and turns his work into a supervisory rather than an active job.

RESULTS

• The client was able to automate a time-consuming and human resource-intensive process, increasing productivity of each worker, in a way that easily scalableThe duration of the process has been reduced from 45 minutes to 2 minutes.
• A substantial reduction in human errorthanks to the self-correcting reading systems and the completeness of the model and its visual feedback.

SOLUTION

Design and training of two machine learning models for visual identification of labels, and recognition and reading of codes within each label.

All the necessary hardware for image acquisition was purchased, and a graphical user interface application was created for the user to interact with the model.

TOOLS