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Fandango: Advanced automotive component manufacturing through reliable and secure digital twins

National Project

The CIEN FANDANGO project is aimed at improving operational efficiency in the automotive components sector by acting on three key challenges of the sector: visibility of information throughout the supply chain, maximisation of product quality and optimisation of processes that do not provide direct value (maintenance).

To achieve this objective, the FANDANGO project will use the concept of Digital Twin, understood as the hybridization of virtual models or simulations with real data captured from assets, processes or products. This concept allows the early detection of problems and prediction of process results with greater accuracy than pure simulation models.

In the case of GRUPO ANTOLÍN, the general objective is to approach the development of the digital twin concept from the point of view of maintenance optimization with the purpose of:

  • Evolving your maintenance strategy from one based exclusively on prevention to one based on condition-based maintenance.
  • Acquire more knowledge about your production processes and then optimize them.

 

Within GRUPO ANTOLÍN the developments will have an indirect economic impact:

  • Increase the profitability of the lines by reducing the number of both scheduled and unscheduled stops.
  • To increase the profitability of the plant by optimizing resources destined to machine maintenance.
  • To be a pioneer in the implementation of digital twins in its processes and to position itself as a leading company in its sector.

 Technical Objectives

Among the specific technical objectives we can find the following:

  1. Definition of a reference architecture for the connectivity to the productive elements: Within the strategy of monitoring the plant, one of the key elements is to guarantee the connectivity to the different manufacturing elements to obtain real time information. Although given the diversity of elements to which access is not the objective of the project the design of a single solution for all of them, it is intended to define a solution model that serves as a standard reference for the collection of heterogeneous data through the connection to assets of various kinds within a production line. This will simplify the development of connectors to assets of different nature, origin or supplier, such as: Manufacturing equipment: specifically presses, plastic injection moulding machines, grinding machines, water cutting machines.
  2. Research into sensorization solutions for tools: One of the main technological challenges in the processes of stamping, casting or injection is the sensorization of the moulds or dies for measuring process parameters in them. The demanding operating conditions in terms of temperature, pressure and vibrations, as well as the difficulty of connecting and feeding them, means that there are no mature technological solutions to solve this problem today. The project will address this line with two use cases: Sensorization of plastic injection molds
  3. Development of models for maintenance optimisation: The second of the major improvement challenges in the area of the proposal is maintenance optimisation with the final objective of progressively replacing strategies based on preventive maintenance with more advanced ones based on condition based maintenance. Making use of the technologies addressed in the previous objectives will address:
  • Quantitative analysis of failure modes and causes and related machine variables (RAMS analysis) to model the physical characteristics of the systems and identify the failure modes for which it makes sense to perform diagnostic or prognostic modules.
  • Working on the development of services based on advanced data analysis techniques for the diagnosis or even prognosis of different failure modes in: plastic injection machines and water cutting machines.
  1. Validation of the developed technologies: A transversal objective to the previous ones is the validation of the developed technology in pilots applied to real use cases. In this sense, as mentioned above, three different use cases will be built in which the different technological developments will be totally (or partially) integrated.

Project partners

Project collaborators

  • ITCL
  • Tecnalia

Duration: 2018-2022

The project has been funded through the CDTI‘s CIEN Call for 2018