X Intl. Summer School on Diagnosis of complex systems: Early bird registration fee is one month away

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Belarmino Pulido

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May 2, 2024, 8:27:17 AMMay 2
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Dear colleagues,

this is just a reminder that the early bird registration for the Summer
School in Diagnosis is one month away. We have extended the deadline to
May, 31st.

Additionally, we have centralized all the information about the school
in our web page: https://dxsummerschool24.infor.uva.es

With best regards,

Belarmino Pulido and Aníbal Bregón

////////////////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////// 10th INTL. SUMMER SCHOOL ON FAULT DIAGNOSIS OF
COMPLEX SYSTEMS ////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////// Valladolid, July, 1st-5th, 2024
/////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////
https://dxsummerschool24.infor.uva.es/ /////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////////////////

The Spanish Thematic Network on Supervision and Diagnosis of Complex
systems will
organize in July 2024 the 10th Intl. Summer School on Fault Diagnosis of
Complex systems.

Currently, automated diagnosis of devices is an interesting research and
development field.
It can be approached with different techniques (knowledge-based systems,
case-based reasoning,
machine-learning or model-based reasoning) coming from different fields:
Control Engineering,
Artificial Intelligence or Statistics. It is not easy to include several
of these techniques
in a single course.

This School is an intensive seminar that will take place along 5 days
(30 hours) in Valladolid,
Spain. Its main goal is introducing students to different diagnosis
approaches coming
from different research communities: Control Engineering, Artificial
Intelligence, Statistics, ...
This year we will introduce also Machine Learning methods for
prognostics and condition-based maintenance.

The School is open to PhD/master students and also to industrial
practitioners interested in
these approaches to diagnosis. Successful applications to fields like
electronic circuits,
chemical processes, continuous industrial processes, automotive,
satellites, software, etc. have been made.

The Summer School oficial language will be English.

For further information visit: https://dxsummerschool24.infor.uva.es/ or
send an email to be...@infor.uva.es or ani...@infor.uva.es

PROGRAMME:

T1. INTRODUCTION. FUNDAMENTAL CONCEPTS
T1.1 Basic definitions: fault, failure, detection, diagnosis, reliability...
T1.2 Foundations for fault detection and diagnosis in FDI and DX:
detectability, observability,  diagnosability...

T2. THE FDI APPROACH
T2.1. Structural analysis and analytical redundancy.
T2.2. Model-based detection methods: parameter estimation, parity
equations, state observers for linear and non-linear models.
T2.3. Fault detection: residual evaluation by consistency tests, and
envelope generators.
T2.4. Fault isolation: structured and directional residuals.

T3. THE DX APPROACH
T3.1 Model-based diagnosis from AI Community. Consistency-based
diagnosis, CBD: Theoretical (Reiter's ) approach.
T3.2 GDE: the computational approach to CBD.
T3.3 Computational alternatives to GDE. Diagnosing multiple faults.
T3.4 Constraint-driven fault diagnosis.

T4. DIAGNOSING BUSINESS PROCESSES
T4.1 Introduction to Business Processes
T4.2 Diagnosis in the Business Process lifecycle
T4.3 Self-adaptative Business Processes
T4.4 Challenges and applications

T5. SOFTWARE DIAGNOSIS
T5.1 Introduction
T5.2 Software Testing
T5.3 Software Debugging
T5.4 Software Configuration Diagnosis

T6. STATISTICAL APPROACHES TO FAULT DIAGNOSIS
T6.1. Fault diagnosis using statistical methods.

T7. BRIDGE: INTEGRATION OF FDI AND DX APPROACHES
T7.1 Theoretical links and comparison.
T7.2 Practical comparison and potential synergies.

T8. MACHINE LEARNING MODELS FOR PROGNOSTICS AND CONDITION BASED MAINTENANCE
T8.1 Introduction to prognostics
T8.2 Statistical background: survival analysis and reliability
T8.3 Machine learning models for prognostics
T8.4 Application

T9. INTRODUCTION TO DEEP REINFORCEMENT LEARNING

Location: This next edition will take place on July, 1st to 5th, 2024 in
the city of Valladolid, Spain.
Valladolid is the capital of the Castille and the Lion region, and it is
located 200 km north-east to Madrid.
It is easy to arrive by high speed train from Madrid (55 minutes trip),
and also by plain from Barcelone.

The teaching will take place at the Escuela de Ingenieria Informática de
Valladolid (Valladolid Informatics Engineering School),
in the Valladolid Campus Miguel Delibes.

Special Guests: Erik Frisk (Linköping University, Sweden), Gautam Biswas
(Vanderbilt University, USA) and Louise Trave-Massuyes (LAAS-CNRS, France)

Academic Staff:  C. Alonso-González (U. Valladolid), J. Armengol (U.
Girona), A. Bregon (U. Valladolid),
M.J. de la Fuente (U. Valladolid), R. M. Gasca (U. Sevilla), M. Teresa
Gomez (U. Sevilla), J. Melendez (U. Girona),
V. Puig (UPC), B. Pulido (U. Valladolid).

Registration: Early bird registration 500 euro (before May, 31st, 2024),
late registration 750 euro (after June, 1st, 2024):
Registration site:
https://funge.uva.es/area-formacion/fault-diagnosis-of-complex-systems/

Accommodation: We will not manage accommodation for the Summer School
but there are several Residence Halls in the Universidad de Valladolid
where you
can find accommodation within the city historial center:
https://reyescatolicos.uva.es/ (please contact be...@infor.uva.es or
ani...@infor.uva.es for further information)

Summer school web page: https://dxsummerschool24.infor.uva.es/

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