Cyber-physical manufacturing systems: An architecture for sensor integration, production line simulation and cloud services

none9noThe pillars of Industry 4.0 require the integration of a modern smart factory, data storage in the Cloud, access to the Cloud for data analytics, and information sharing at the software level for simulation and hardware-in-the-loop (HIL) capabilities. The resulting cyber-physical system (CPS) is often termed the cyber-physical manufacturing system, and it has become crucial to cope with this increased system complexity and to attain the desired performances. However, since a great number of old production systems are based on monolithic architectures with limited external communication ports and reduced local computational capabilities, it is difficult to ensure such production lines are compliant with the Industry 4.0 pillars. A wireless sensor network is one solution for the smart connection of a production line to a CPS elaborating data through cloud computing. The scope of this research work lies in developing a modular software architecture based on the open service gateway initiative framework, which is able to seamlessly integrate both hardware and software wireless sensors, send data into the Cloud for further data analysis and enable both HIL and cloud computing capabilities. The CPS architecture was initially tested using HIL tools before it was deployed within a real manufacturing line for data collection and analysis over a period of two months.openPrist Mariorosario; Monteriu' Andrea; Pallotta Emanuele; Cicconi Paolo; Freddi Alessandro; Giuggioloni Federico; Caizer Eduard; Verdini Carlo; Longhi SauroPrist, Mariorosario; Monteriu', Andrea; Pallotta, Emanuele; Cicconi, Paolo; Freddi, Alessandro; Giuggioloni, Federico; Caizer, Eduard; Verdini, Carlo; Longhi, Saur

Influence of calcination temperature on structural and magnetic properties of nanocomposites formed by Co-ferrite dispersed in sol-gel silica matrix using tetrakis(2-hydroxyethyl) orthosilicate as precursor

Effects of calcination temperatures varying from 400 to 1000°C on structural and magnetic properties of nanocomposites formed by Co-ferrite dispersed in the sol-gel silica matrix using tetrakis(2-hydroxyethyl) orthosilicate (THEOS) as water-soluble silica precursor have been investigated. Studies carried out using XRD, FT-IR, TEM, STA (TG-DTG-DTA) and VSM techniques. Results indicated that magnetic properties of samples such as superparamagnetism and ferromagnetism showed great dependence on the variation of the crystallinity and particle size caused by the calcination temperature. The crystallization, saturation magnetization Ms and remenant magnetization Mr increased as the calcination temperature increased. But the variation of coercivity Hc was not in accordance with that of Ms and Mr, indicating that Hc is not determined only by the crystallinity and size of CoFe2O4 nanoparticles. TEM images showed spherical nanoparticles dispersed in the silica network with sizes of 10-30 nm. Results showed that the well-established silica network provided nucleation locations for CoFe2O4 nanoparticles to confinement the coarsening and aggregation of nanoparticles. THEOS as silica matrix network provides an ideal nucleation environment to disperse CoFe2O4 nanoparticles and thus to confine them to aggregate and coarsen. By using THEOS as water-soluble silica precursor over the currently used TEOS and TMOS, the organic solvents are not needed owing to the complete solubility of THEOS in water. Synthesized nanocomposites with adjustable particle sizes and controllable magnetic properties make the applicability of Co-ferrite even more versatile

Dynamic magnetization of

We have studied the magnetization of a system of γ-Fe2O3 (0.68 vol.%) nanoparticles isolated in an SiO2 amorphous matrix placed in an alternating magnetic field with a frequency of 640 Hz and in the temperature range of (77–300) K. Compared to temperatures closer to 300 K (where the system has a superparamagnetic behaviour), at lower temperatures, the magnetization has a dynamic hysteresis loop due to the magnetization's phase shift between the field and the magnetization. The delay of the magnetization (attributed to the Néel relaxation processes) increases with the decrease of temperature. It has been shown that the relaxation time resulting from the Néel theory is determined by an effective anisotropy constant $(K_{\it eff})$ that takes into account the magnetocrystalline anisotropy, as well as the shape, surface and strain anisotropies. In the following we will show that the surface and strain anisotropy components have the most significant influence. When the temperature decreases from 300 to 77 K, the relative increase of the saturation magnetization of the nanoparticles is much higher than that of the (spontaneous) saturation magnetization of bulk γ-Fe2O3. This increase is due to the increase of the mean magnetic diameter of the particles attached to the core of aligned spins, from 10.16 nm to 11.70 nm, as a result of the modification of the superexchange interaction in the surface layer

Online Fault Detection: A Smart Approach for Industry 4.0

none8noThe fourth industrial age takes the manufacturing factory to a new level by introducing smart, extendible, flexible, modular and customized mass production technologies. Production lines or machines need to be integrated at the management level to be industry 4.0 compliant: in this way they can create and optimize a customer-oriented production, while constantly maintaining good performance conditions. In this context, one of the main challenges is the possibility to detect faults as fast as possible, to accurately diagnose those faults which can negatively affect the overall production cycle, and finally address them before it is too late. Due to the great importance that electric motors play in this context, an online smart algorithm for fault detection in electric motors is proposed in this paper. The effectiveness of the proposed method has been validated by applying it on an experimental benchmark, where the results show that the method is accurate and fast in detection of faults.nonePrist Mariorosario; Monteriù Andrea; Freddi Alessandro; Cicconi Paolo; Giuggioloni Federico; Caizer Eduard; Verdini Carlo; Longhi SauroPrist, Mariorosario; Monteriù, Andrea; Freddi, Alessandro; Cicconi, Paolo; Giuggioloni, Federico; Caizer, Eduard; Verdini, Carlo; Longhi, Saur

Cyber-Physical Manufacturing Systems for Industry 4.0: Architectural Approach and Pilot Case

The pillars of Industry 4.0 require a modern smart factory to be integrated, store data into the Cloud, access the Cloud for data analytics and share information at software level for simulation and Hardware-In-the-Loop capabilities. The resulting Cyber-Physical System is often called Cyber-Physical Manufacturing System, and it becomes fundamental to cope with the increased system complexity and the desired performances. However, since a lot of old production systems are based on monolitic architectures, with limited external communication ports and reduced local computational capabilities, it is very difficult to make such production lines compliant to Industry 4.0 pillars. Wireless Sensor Network is a solution for the smart connection of a production line to a Cyber-Physical System architecture, data processing through Cloud Computing. The scope of this research work is to propose an intermediate layer within the architecture that allows each device, production line and machine to be independently connected despite the adopted protocol. The solution is based on OSGi Framework, which is able to seamlessly integrate both hardware and software wireless sensors, send data into the Cloud for further data analysis, and grant both Hardware-In-the-Loop and Cloud Computing capabilities. A general description of the architecture is here proposed, together with preliminary results on a real manufacturing line for data collection and analysis over a period of two months