Abstract
The technological market is increasingly evolving as evidenced by the innovative and streamlined manufacturing processes. Printed Circuit Boards (PCB) are widely employed in the electronics fabrication industry, resorting to the Gerber open standard format to transfer the manufacturing data. The Gerber format describes not only metadata related to the manufacturing process but also the PCB image. To be able to map the electronic circuit pattern to be printed, a parser to convert Gerber files into a bitmap image is required. The current literature as well as available Gerber viewers and libraries showed limitations mainly in the Gerber format support, focusing only on a subset of commands. In this work, the development of a recursive descent approach for parsing Gerber files is described, outlining its interpretation and the renderization of 2D bitmap images. All the defined commands in the specification based on Gerber X2 generation were successfully rendered, unlike the tested commercial parsers used in the experiments. Moreover, the obtained results were comparable to those parsers regarding the commands they can execute as well as the ground-truth, emphasizing the accuracy of the proposed approach. Its top-down and recursive architecture allows easy integration with other software regardless of the platform, highlighting its potential inclusion and integration in the production of electronic circuits.

Abstract
In the manufacturing domain, the digital twin has become an emerging concept for decision-making through the integration of what-if simulation capabilities. In such systems, the processing of the entire space of alternative solutions is very time-consuming; recommendation systems are used to solve this; however, these suffer from several problems, namely data sparsity and cold-start. The application of trust-based models can mitigate these problems, particularly the cold-start problems, by providing valuable background for the recommendation system. This paper presents the implementation and experimental validation of a trust-based model for improving the digital twin based what-if simulation recommendation system, addressing the cold-start problems. The proposed trust model was applied in an assembly line case study to recommend the best configurations for the optimal number of AGVs (Autonomous Guided Vehicles). The results show that applying the trust-based model with similarity metrics improved the mitigation of the cold-start problem.

Abstract
Purpose The purpose of this paper is to present a programming by demonstration (PbD) system based on 3D stereoscopic vision and inertial sensing that provides a cost-effective pose tracking system, even during error-prone situations, such as camera occlusions. Design/methodology/approach The proposed PbD system is based on the 6D Mimic innovative solution, whose six degrees of freedom marker hardware had to be revised and restructured to accommodate an IMU sensor. Additionally, a new software pipeline was designed to include this new sensing device, seeking the improvement of the overall system's robustness in stereoscopic vision occlusion situations. Findings The IMU component and the new software pipeline allow the 6D Mimic system to successfully maintain the pose tracking when the main tracking tool, i.e. the stereoscopic vision, fails. Therefore, the system improves in terms of reliability, robustness, and accuracy which were verified by real experiments. Practical implications Based on this proposal, the 6D Mimic system reaches a reliable and low-cost PbD methodology. Therefore, the robot can accurately replicate, on an industrial scale, the artisan level performance of highly skilled shop-floor operators. Originality/value To the best of the authors' knowledge, the sensor fusion between stereoscopic images and IMU applied to robot PbD is a novel approach. The system is entirely designed aiming to reduce costs and taking advantage of an offline processing step for data analysis, filtering and fusion, enhancing the reliability of the PbD system.

Abstract
The optimisation of forest fuels supply chain involves several entities actors, and particularities. To successfully manage these supply chains, efficient tools must be devised with the ability to deal with stakeholders dynamic interactions and to optimize the supply chain performance as a whole while being stable and robust, even in the presence of uncertainties. This work proposes a framework to coordinate different planning levels and event-based models to manage the forest-based supply chain. In particular, with the new methodology, the resilience and flexibility of the biomass supply chain is increased through a closed-loop system based on the system forecasts provided by a discrete-event model. The developed event-based predictive model will be described in detail, explaining its link with the remaining elements. The implemented models and their links within the proposed framework are presented in a case study in Finland and results are shown to illustrate the advantage of the proposed architecture.

Abstract

Abstract
This article presents the development of a tethered fixed-wing tail-sitter VTOL (Vertical Take-Off and Landing) Unmanned Aerial Vehicle system. The design focuses on improving energy efficiency by utilizing the wings to harness wind power, similar to a kite, while maintaining VTOL functionality. A distinguishing feature is the purpose-built autopilot system, with custom hardware and software components specifically engineered for this application. The study presents the system identification process for obtaining five MIMO (Multiple-Input Multiple-Output) transfer functions that characterize the dynamics between roll-yaw commands and responses, including the tether angle feedback. To address the inherent coupling effects and uncertainties in the system, robust mixed sensitivity (H-infinity) MIMO controllers are developed. The controllers were validated through both simulations and experimental flights, demonstrating effective performance in handling cross-coupling effects and maintaining stability under various operating conditions. According to flight test findings, the system can precisely manage the tether angle while adjusting for ground effect disturbances. This allows for accurate tethered navigation, a stable attitude, and the maintenance of an adequate yaw heading.