Automated experience-based learning for plug and produce assembly systems

This paper presents a self-learning technique for adapting modular automated assembly systems. The technique consists of automatically analysing sensor data and acquiring experience on the changes made on an assembly system to cope with new production requirements or to recover from disruptions. Experience is generalised into operational knowledge that is used to aid engineers in future adaptations by guiding them throughout the process. At each step, applicable changes are presented and ranked based on: (1) similarity between the current context and those in the experience base; (2) estimate of the impact on system performance. The experience model and the self-learning technique reflect the modular structure of the assembly machine and are particularly suitable for plug and produce systems, which are designed to offer high levels of self-organisation and adaptability. Adaptations can be performed and evaluated at different levels: from the smallest pluggable unit to the whole assembly system. Knowledge on individual modules can be reused when modules are plugged into other systems. An experimental evaluation has been conducted on an industrial case study and the results show that, with experience-based learning, adaptations of plug and produce systems can be performed in a shorter time.     

Selective High‐Frequency Mechanical Actuation Driven by the VO2 Electronic Instability

Relaxation oscillators consist of periodic variations of a physical quantity triggered by a static excitation. They are a typical consequence of nonlinear dynamics and can be observed in a variety of systems. VO₂ is a correlated oxide with a solid‐state phase transition above room temperature, where both electrical resistance and lattice parameters undergo a drastic change in a narrow temperature range. This strong nonlinear response allows to realize spontaneous electrical oscillations in the megahertz range under a DC voltage bias. These electrical oscillations are employed to set into mechanical resonance a microstructure without the need of any active electronics, with small power consumption and with the possibility to selectively excite specific flexural modes by tuning the value of the DC electrical bias in a range of few hundreds of millivolts. This actuation method is robust and flexible and can be implemented in a variety of autonomous DC‐powered devices.     

Topology optimization and geometric nonlinear modeling using positional finite elements

Optimization and Engineering - Topology optimization is an effective approach for the efficient layout design of structures and their components. This approach is well-established in the solid...     

Chitin derived biochar as an alternative adsorbent to treat colored effluents containing methyl violet dye

Chitin was used to prepare an alternative, eco–friendly and low–cost adsorbent by a simple pyrolysis process. The adsorbent, named chitin derived biochar, was characterized and applied to treat colored effluents containing methyl violet dye (MV). Pyrolysis using N₂ flow rate of 0.25 L min^?1, heating rate of 10 °C min^?1 until 800 °C was suitable to prepare a chitin derived biochar with good characteristics. Chitin derived biochar presented surface area of 275.0 m² g^?1. The MV adsorption on the chitin derived biochar was favored in alkaline conditions and ambient temperature. The adsorption process presented fast kinetics and, the maximum adsorption capacity was higher than 1000 mg g^?1. Chitin derived biochar can be used for 7 consecutive adsorption/desorption cycles maintaining the same adsorption capacity. Also, the material was suitable to treat colored effluents, reaching color removal percentage of 95%. In brief, it was demonstrated that chitin derived biochar is a low–cost and efficient material to treat colored effluents.     

A biased‐randomized iterated local search for the distributed assembly permutation flow‐shop problem

Modern production systems require multiple manufacturing centers—usually distributed among different locations—where the outcomes of each center need to be assembled to generate the final product. This paper discusses the distributed assembly permutation flow‐shop scheduling problem, which consists of two stages: the first stage is composed of several production factories, each of them with a flow‐shop configuration; in the second stage, the outcomes of each flow‐shop are assembled into a final product. The goal here is to minimize the makespan of the entire manufacturing process. With this objective in mind, we present an efficient and parameter‐less algorithm that makes use of a biased‐randomized iterated local search metaheuristic. The efficiency of the proposed method is evaluated through the analysis of an extensive set of computational experiments. The results show that our algorithm offers excellent performance when compared with other state‐of‐the‐art approaches, obtaining several new best solutions.     

Design of a Bio-Inspired Autonomous Underwater Robot

The following paper presents the design and fabrication of an ostraciiform swimming robot and its navigation control and guidance system. Compared to other biomimetic vehicles, the chosen architecture has a lower propulsive efficiency but is easier to waterproof and capable to withstand greater pressures. To generate the alternating motion of the robot bio-inspired thruster, namely a plane fin, a transmission system was designed to replace the direct drive widely adopted in underwater biomimetic vehicles. The mechanical efficiency of two alternative mechanisms capable to actuate the fin were computed according to a preliminary sizing of the robot and its targeted swimming performances. Therefore, the more suitable solution was manufactured and installed aboard. At the same time, a proper navigation, guidance and control architecture (NGC) was designed and then integrated in the robot main controller. The proposed solution allows the vehicle to perform different missions autonomously once their profiles are received from the base station. Preliminary tests results and future works are discussed in the final conclusions.     

On "Over-Sized" High-Gain Practical Observers for Nonlinear Systems

In this paper, it is shown that the performances of a class of high-gain practical observers can be improved by estimating the time derivatives of the output up to an order that is greater than the dimension of the system, which is assumed to be in observability form and, possibly, time-varying. Such an improvement is achieved without increasing the gain of the observers, thus allowing their use in a wide variety of control and identification applications.