￼58<< Slot Module 1 Kistler 5171A 2 NI 9234 3 NI 9239 4 NI 9244 Features 1-4 charge inputs 24 bit analog-to-digital conversion Data rate up to 50.8 kS/s per channel Measuring ranges: 1,000 ... 1,000,000 pC Frequency ≈ 0 ... 20,000 Hz 51.2 kS/s per channel maximum sampling rate; ±5 V input 24-bit resolution; 102 dB dynamic range; anti-aliasing lters 4 differential channels, 50 kS/s per channel sample rate ±10 V measurement range, 24-bit resolution Antialias lter 250 Vrms ch-ch, CAT II (screw terminal), or 60 VDC ch-ch, CAT I (BNC) isolation Single-ended channels, 50 kS/s per channel simultaneous sample rate 400 Vrms L-N, 800 Vrms L-L measurement range; 24-bit resolution 400 Vrms CAT III working voltage Magnitude Forces [N] Acceleration [m/s2] Sound pressure [Pa] Intensity [A] Voltage [rms] INDUSTRY 4.0 Table 1. Modules for the Project in LabVIEW developed by UPV/EHU. Conclusions As it has been mentioned, in order to face the new demands of the industry in terms of new design and production reliability, it is necessary to collect, store and process large amount of data during production. One of the key aspects is to have the capacity of storage and analysis of all data, as well as the possibility of making decisions with the results of these analyses. Thus, it is necessary to start from a deep knowledge of the processes and the relationship among the relevant parameters. In this way, the process data will help to observe unforeseen trends and events and will be possible to adapt the wor- king conditions to a new scenario, not only once the product has been manufactured but before and during the process. References Many of the latest developments drive the manufacturing industry in this direction. The combination of virtual and augmented reality, simulation tools, process monitoring and hybrid machines increase the rapid adaptability of production lines and the ability to handle with more complex and dif cult parts. In the same way, some production software are introducing new modules with predictive maintenance tasks, storage of large amounts of process data, integration of process simulation with real recorded data... All these initiatives shape a mix of sensors, information and production facilities that can be analysed and used for a better management of production and a better quality of the product, an important step that introduces what is known as industry 4.0. •  http://www3.weforum.org/docs/WEF_FOJ_Executive_Summary_Jobs.pdf. [Accessed 16 Jan. 2017]  http://www.esade.edu/web/eng/about-esade/today/esade-opinion/viewelement/319393/1/industria-4.0:-que-impacto-tiene- en-la-produccion-y-el-empleo- [Accessed 18 Feb. 2017]  www.hobbyconsolas.com [Accessed 20 Feb. 2017]  www.ideaingenieria.es [Accessed 20 Feb. 2017]  http://blog.cartif.com/en/realidad-aumentada-espacial-en-la-industria/ [Accessed 14 Feb. 2017]  CGTech. (2017). HAAS - CGTech. [online] Available at: http://www.vericut.com.br/solutions/machine-tool-showrooms/haas/ [Accessed 15 Jan. 2017].  S. Martínez, A. Lamikiz, E. Ukar, I. Tabernero, I. Arrizubieta, Control loop tuning by thermal simulation applied to the laser trans- formation hardening with scanning optics process, Applied Thermal Engineering, Volume 98, 5 April 2016, Pages 49-60, ISSN 1359-4311.  S. Martínez, A. Lamikiz, E. Ukar, A. Calleja, J.A. Arrizubieta, L.N. Lopez de Lacalle, Analysis of the regimes in the scanner-based laser hardening process, Optics and Lasers in Engineering, Volume 90, March 2017, Pages 72-80, ISSN 0143-8166.  E. Artetxe, G. Urbikain, A. Lamikiz, L. N. López-De-Lacalle, R. González, and P. Rodal, “A Mechanistic Cutting Force Model for New Barrel End Mills,” Procedia Eng., vol. 132, pp. 553–560, 2015.  A. Calleja, A. Fernández, F. J. Campa, A. Lamikiz, and L. N. López De Lacalle, “Reliable manufacturing process in turbine blisks and compressors,” Procedia Eng., vol. 63, pp. 60–66, 2013.