Master's Degree in Industrial Engineering

Academic year 2018-19 | 78 credits | 30 places

Degree data and benchmarks



Data and description

2016-17 2017-18
New 18 20
SIIU New 18 18
Registered 18 36
Graduates 0 2

New students: these students are starting their studies from the beginning for the first time. They may have recognised credits or not.

New SIIU students: these students are starting their studies from the beginning, registering on a programme for the first time and, in accordance with SIIU criteria, may have fewer than 10 credits (for a Master's) or 30 credits (for an undergraduate programme) recognised. This set of students may also be referred to as the optimum new entry group. 

Registered students: these students have an active registration on a programme for an academic year. This set of students may also be referred to as the total student population.

  • Registration reservations are not included (due to the students awaiting a place at another university or credit recognition)
  • Registration cancellations are not included
  • Students with unpaid debts are not included

Graduates: these students have passed (passed or accredited) all credits required for the degree programme and have, therefore, finished their course regardless of whether they have requested their degree certificate be issued or not.

Graduating Class


Data and description

2016-17 2017-18
Graduate Efficiency Rate - 100%

The efficiency rate is defined as the percentage ratio between the total number of credits passed by students throughout the registered programme from which they have graduated, and the total number of credits they effectively registered for. The reference population is the optimum group.

Credits Taken and Passed


Data and description

2016-17 2017-18
Degree Success Rate 97% 92%
Performance Rate 88% 79%

Success rate: the percetage ratio between the number of passed credits and the number of credits taken for assessment.

Performance rate: the percentage ratio between the number of credits passed and the number of credits registered for.

Who directly oversees the quality of the degree programme?

Quality Assurance Commission

Quality manager
Eugenio Miguel Isern Riutort
 Vicente Jose Canals Guinand
Teaching and Research Staff
  • Miguel Jesús Roca Adrover
  • Victor Martínez Moll
Admin and Services Staff
M. Consolación Hernández Guerra
 Francisco Estévez Fernández

The Quality Assurance Committee (CGQ) gathers all of the information regarding the degree programme (survey reports, data, statistics, complaints, suggestions, etc.) and analyses them. Here, you can see the regulations and duties of the Quality Assurance Committee (CGQ).

Commitment to quality

Declaration in which the person in charge of ensuring the quality of the Master's programme wishes to express his/her commitment to quality and the constant improvement of his/her actions.

Planning improvement measures

Improvement plan

Accountability and transparency

Link to the Register of Universities, Centres, and Degrees (RUCT)

Procedure Document Date/Year
Accreditation Final accreditation report 28/02/2019
Monitoring External follow-up report (2016-17) 24/09/2018
Monitoring Annual follow-up and internal assessment report (2016-17) 23/03/2018
Verification Final verification report 24/11/2015
Verification Official university degree statement 19/02/2013

End of master projects

  • Dimensionamiento de la instalación geotérmica para la climatización de un hotel de 4 estrellas
  • Disseny, implementació i avaluació d'un sistema d'enrutament de vehicles
  • Estudi d’optimització de subministres energètics en un bloc d’habitatges. Electricitat versus Gas Natural
  • Estudio de la idoneidad del Stream Reservation Protocol para dar soporte a Sistemas Empotrados Distribuidos Críticos Adaptativos
  • Estudio de viabilidad de la instalación de solar térmica en un hotel con trigeneración
  • Evaluación y comparación de algoritmos de posicionamiento basados en tecnología Ultra-Wide-Band
  • Instalación climática mediante geotermia en un hotel de 4 estrellas
  • Mando multimodal para el estudio de neuropatologías
  • Mejora TFG-Desarrollo de una unidad “Pan-Tilt” para el seguimiento visual de objetivos.
  • Reconocimiento Visual de Escenas en Entornos Multi-Robot
  • Design and control of an Autonomous Surface Vehicle to improve Link Communications
  • Deslastrador BT: diseño e implementación de un sistema “Smart” para la optimización de la potencia contratada en Baja Tensión
  • Diseño de un sistema de almacenamiento de datos a largo plazo.