https://mikelayuso.com/tags/manufacturing/ManufacturingHugoBlox Kit (https://hugoblox.com)en-usMon, 23 Aug 2021 00:00:00 +0000https://mikelayuso.com/media/icon_hu_b0970716f810afd6.pnghttps://mikelayuso.com/tags/manufacturing/https://mikelayuso.com/papers/cpps-industry-4-0/Mon, 23 Aug 2021 00:00:00 +0000https://mikelayuso.com/papers/cpps-industry-4-0/<h2 id="abstract">Abstract</h2> <p>The Hyperconnected Architecture for High Cognitive Production Plants (HyperCOG) project aims at the process industry’s complete digital transformation through an advanced Industrial Cyber-Physical Infrastructure. It is based on advanced technologies that allow a hyperconnected network of digital nodes to be created improving the classic automation hierarchy of communication layers. The nodes will collect data streams in real-time, offering cognitive sensing and information along with high performance computing capabilities making the process industry businesses solid in different scenarios. The system is validated in three fields of the process industry: steel, cement and chemical where optimization in the use of energy and raw materials is obtained, among other benefits.</p> <h2 id="key-contributions">Key Contributions</h2> <ul> <li>Framework for CPPS implementation in smart factories</li> <li>Integration patterns for legacy and modern manufacturing equipment</li> <li>Case studies demonstrating improved production efficiency</li> </ul>https://mikelayuso.com/papers/electrode-degradation/Thu, 30 Jun 2016 00:00:00 +0000https://mikelayuso.com/papers/electrode-degradation/<h2 id="abstract">Abstract</h2> <p>This work presents the preliminary analysis done to determine the electrode degradation during a resistance spot welding manufacturing process of aluminium-based unions. This process represents a critical step in a high production rate manufacturing line, where currently identical welding parameters are used for the tens of thousands of dayly produced parts. During the welding process, the aluminium can melt locally, producing droplets that adhere to the electrode speeding its degradation that affects the quality of the joint. Degradation is hard to predict since it depends on part surface quality, electrode preparation and system set-up. In this work, an analysis of the degradation of the electrode associated with the observed and measured quality of the parts is carried out. With the final aim to advance toward a zero defect manufacturing scenario and increase the quality of the produced parts, a process data analysis based on fuzzy logic algorithms will be performed. An assessment of (i) produced part quality, (ii) the electrode degradation state, (iii) detection of different performance modes of the parameters and (iv) detection of events or process changes, will be done using image and production line data. This will allow to determine (i) when the electrode must be changed and (ii) the optimal combination of welding parameters to extend electrodes&rsquo; life assuring welding quality.</p> <h2 id="key-contributions">Key Contributions</h2> <ul> <li>Detailed characterization of electrode degradation patterns</li> <li>Analysis of process parameters affecting electrode lifespan</li> <li>Recommendations for electrode maintenance and replacement</li> </ul>