AI for Improving the Overall Equipment Efficiency in Manufacturing Industry

Industry 4.0 has emerged as the perfect scenario for boosting the application of novel artificial intelligence (AI) and machine learning (ML) solutions to industrial process monitoring and optimization. One of the key elements on this new industrial revolution is the hatching of massive process monitoring data, enabled by the cyber-physical systems (CPS) distributed along the manufacturing processes, the proliferation of hybrid Internet of Things (IoT) architectures supported by polyglot data repositories, and big (small) data analytics capabilities. Industry 4.0 paradigm is data-driven, where the smart exploitation of data is providing a large set of competitive advantages impacting productivity, quality, and efficiency key performance indicators (KPIs). Overall equipment efficiency (OEE) has emerged as the target KPI for most manufacturing industries due to the fact that considers three key indicators: availability, quality, and performance. This chapter describes how different AI and ML solutions can enable a big step forward in industrial process control, focusing on OEE impact illustrated by means of real use cases and research project results

Fortistis: Split extension in dense passive optical networks by inline amplification with remote ASE-shaped pump delivery via colorless optical network units

A method for extending the customer density via ASE-pumped splitters in the tree in a WDM/TDM-PON is presented. The influence of Rayleigh backscattering in the feeder is faced, originally prohibiting any upstream transmission.Peer ReviewedPostprint (published version

Design of Industrial Cold-Formed Steel Rack Upright Frames for Loads in Cross-Aisle Direction

This paper summarizes research on the cross-aisle stiffness and strength of industrial cold-formed steel rack upright frames for loads in cross-aisle direction. Tests were carried out at the Universitat Politècnica de Catalunya, Barcelona, Spain on joints as well as entire upright frames. A possible rather simple analysis procedure is developed and described

Machine Learning Based Surrogate Model for Press Hardening Process of 22MnB5 Sheet Steel Simulation in Industry 4.0

The digitalization of manufacturing processes offers great potential in quality control, traceability, and the planning and setup of production. In this regard, process simulation is a well-known technology and a key step in the design of manufacturing processes. However, process simulations are computationally and time-expensive, typically beyond the manufacturing-cycle time, severely limiting their usefulness in real-time process control. Machine Learning-based surrogate models can overcome these drawbacks, and offer the possibility to achieve a soft real-time response, which can be potentially developed into full close-loop manufacturing systems, at a computational cost that can be realistically implemented in an industrial setting. This paper explores the novel concept of using a surrogate model to analyze the case of the press hardening of a steel sheet of 22MnB5. This hot sheet metal forming process involves a crucial heat treatment step, directly related to the final part quality. Given its common use in high-responsibility automobile parts, this process is an interesting candidate for digitalization in order to ensure production quality and traceability. A comparison of different data and model training strategies is presented. Finite element simulations for a transient heat transfer analysis are performed with ABAQUS software and they are used for the training data generation to effectively implement a ML-based surrogate model capable of predicting key process outputs for entire batch productions. The resulting final surrogate predicts the behavior and evolution of the most important temperature variables of the process in a wide range of scenarios, with a mean absolute error around 3 °C, but reducing the time four orders of magnitude with respect to the simulations. Moreover, the methodology presented is not only relevant for manufacturing purposes, but can be a technology enabler for advanced systems, such as digital twins and autonomous process control

A Reinforcement Learning Control in Hot Stamping for Cycle Time Optimization

Hot stamping is a hot metal forming technology increasingly in demand that produces ultra-high strength parts with complex shapes. A major concern in these systems is how to shorten production times to improve production Key Performance Indicators. In this work, we present a Reinforcement Learning approach that can obtain an optimal behavior strategy for dynamically managing the cycle time in hot stamping to optimize manufacturing production while maintaining the quality of the final product. Results are compared with the business-as-usual cycle time control approach and the optimal solution obtained by the execution of a dynamic programming algorithm. Reinforcement Learning control outperforms the business-as-usual behavior by reducing the cycle time and the total batch time in non-stable temperature phases

Industrial Cold-Formed Steel Rack Column Base Fixity and Strength

This paper summarizes the testing done at the Universitat Politècnica de Catalunya, Barcelona, Spain and the possible use of the results in design for column base stiffness and strength. The test setup and procedure are adopted in the European rack design standards

Virtual Sensors for Smart Data Generation and Processing in AI-Driven Industrial Applications

The current digitalisation revolution demonstrates the high importance and possibilities of quality data in industrial applications. Data represent the foundation of any analytical process, establishing the fundamentals of the modern Industry 4.0 era. Data-driven processes boosted by novel Artificial Intelligence (AI) provide powerful solutions for industrial applications in anomaly detection, predictive maintenance, optimal process control and digital twins, among many others. Virtual Sensors offer a digital definition of a real Internet of Things (IoT) sensor device, providing a smart tool capable to face key issues on the critical data generation side: i) Scalability of expensive measurement devices, ii) Robustness and resilience through real-time data validation and real-time sensor replacement for continuous service, or iii) Provision of key parameters’ estimation on difficult to measure situations. This chapter presents a profound introduction to Virtual Sensors, including the explanation of the methodology used in industrial data-driven projects, novel AI techniques for their implementation and real use cases in the Industry 4.0 context

Conservation and management of isolated pools in temporary rivers

Temporary rivers are characterized by shifting habitats between flowing, isolated pools, and dry phases. Despite the fact that temporary rivers are currently receiving increasing attention by researchers and managers, the isolated pools phase has been largely disregarded. However, isolated pools in temporary rivers are transitional habitats of major ecological relevance as they support aquatic ecosystems during no-flow periods, and can act as refugees for maintaining local and regional freshwater biodiversity. Pool characteristics such as surface water permanence and size, presence of predators, local physicochemical conditions, time since disconnection from the river flow, or distance to other freshwater habitats challenge a comprehensive understanding of the ecology of these habitats, and challenge ecological quality assessments and conservation practices in temporary rivers. In this paper, we aim at providing a characterization of isolated pools from a hydrological, geomorphological, physicochemical, biogeochemical, and biological point of view as a framework to better conceptualize, conserve, and manage these habitats

Adapting participatory processes in temporary rivers management.

The European Water Framework Directive (WFD) mandates to incorporate the participation of stakeholders and the general public in the development and updating of the river basin management plans. So far, the WFD implementation has been mainly focused on perennial rivers without considering temporary rivers properly, neither in biomonitoring programs nor participatory processes. This paper aims at adapting participatory processes in river basin management to enhance the inclusion of ecosystems with poor or no social recognition such as temporary rivers. To do so, we examined previous experiences of participatory processes conducted in the WFD and adapted them to propose and implement an approach for promoting stakeholders' engagement in temporary rivers. The approach is based on a collaborative leadership, includes multiple participatory engagement mechanisms, uses future global change scenarios and the concept of ecosystem services at different stages of the process, and aims at involving stakeholders not only in the proposal of measures stage but in the diagnosis of the ecological status. It also includes an evaluation of participants' satisfaction on the process. We tested our approach in temporary rivers from the Mediterranean region. We found that the combination of environmental education and citizen science activities, together with the inclusion of the ecosystem services concept, was the most useful way to raise awareness on the biodiversity and ecological value of temporary rivers and to promote stakeholders' engagement. Workshops conducted during the diagnosis stage played an important role in both including stakeholders' suggestions and increasing their knowledge on temporary rivers. Further, envisaging climate-related future scenarios allowed participants to incorporate measures that could tackle new and emerging pressures on these ecosystems. As future environmental changes will increase the proportion of rivers with temporary flow regimes, our approach can contribute to adapt current participatory processes to future needs

Impacts of Use and Abuse of Nature in Catalonia with Proposals for Sustainable Management

This paper provides an overview of the last 40 years of use, and in many cases abuse, of the natural resources in Catalonia, a country that is representative of European countries in general, and especially those in the Mediterranean region. It analyses the use of natural resources made by mining, agriculture, livestock, logging, fishing, nature tourism, and energy production and consumption. This use results in an ecological footprint, i.e., the productive land and sea surface required to generate the consumed resources and absorb the resulting waste, which is about seven times the amount available, a very high number but very similar to other European countries. This overexploitation of natural resources has a huge impact on land and its different forms of cover, air, and water. For the last 25 years, forests and urban areas have each gained almost 3% more of the territory at the expense of agricultural land; those municipalities bordering the sea have increased their number of inhabitants and activity, and although they only occupy 6.7% of the total surface area, they account for 43.3% of the population; air quality has stabilized since the turn of the century, and there has been some improvement in the state of aquatic ecosystems, but still only 36% are in good condition, while the remainder have suffered morphological changes and different forms of nonpoint source pollution; meanwhile the biodiversity of flora and fauna remains still under threat. Environmental policies do not go far enough so there is a need for revision of the legislation related to environmental impact and the protection of natural areas, flora, and fauna. The promotion of environmental research must be accompanied by environmental education to foster a society which is more knowledgeable, has more control and influence over the decisions that deeply affect it. Indeed, nature conservation goes hand in hand with other social and economic challenges that require a more sustainable vision. Today's problems with nature derive from the current economic model, which is environmentally unsustainable in that it does not take into account environmental impacts. Lastly, we propose a series of reasonable and feasible priority measures and actions related to each use made of the country's natural resources, to the impacts they have had, and to their management, in the hope that these can contribute to improving the conservation and management of the environment and biodiversity and move towards sustainability