Open AccessMaintenance management and Optimization of the thermoforming process for the agri-food industry using the S2 model
Author(s) -
Francisco Javier Álvarez Rodríguez,
David Rodríguez Salgado,
Aizpurua Gonzalez,
Olga Gloria Barbón Pérez,
Fernando Romero
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1193/1/012112
Subject(s) - thermoforming , computer science , process (computing) , production (economics) , automation , actuator , control (management) , reliability engineering , manufacturing engineering , industrial engineering , risk analysis (engineering) , engineering , artificial intelligence , business , mechanical engineering , economics , macroeconomics , operating system
The agri-food industry has been greatly enhanced in recent years with the introduction of process control and the automation [1] of certain links in the production chain. The seasons of the year in which these machines must be operational and show robust and reliable operation, have short durations (2 to 4 months) and are therefore greatly affected by unexpected failures that cause stops on the production lines. This paper attempts to expose a comparative advantages that can be obtained in terms of availability and efficiency in the thermoforming process. With the introduction of Industry 4.0 [2, 4] and the S 2 model [5] and actuator control and early action, it is possible to optimize availability and efficiency ratios on thermoformer machines. Results show that it’s possible to reduce unexpected failures by means of this optimization tools. Two improvement strategies are outlined. Maintenance Management improvement model improves response to failures but does not optimize the useful life of the components. Algorithm life optimization based on S 2 model optimizes service life and improves response to failure.