Energy Driven Process Planning and Machine Tool Dynamic Behavior Assessment

AbstractThe current work outlines an approach to close the loop between process planning and machine tool dynamic modeling by addressing the problem of energy efficiency across the process design and realization chains, from the process settings and pallet configuration to the machine tool design and usage phases. The proposed closed loop approach consists of an off-line and on-line component enabling the process and equipment dynamic and energy assessment over time. The benefits of the approach have been evaluated against an industrial case study related to the automotive industry

Multi-robot spot-welding cell design: Problem formalization and proposed architecture

The multi-robot cell design for car-body spot welding is faced by industry as a sequence of tasks, where researches are focused on issues of the problem as a whole. In authors’ knowledge, none work in literature have suggested any formalization for the complete process. This paper tries to bridges the gap proposing coherent process formalization, and presenting a corresponding innovative architecture for the automatic optimal cell design. Specifically, the formalization involves the identification and allocation of the resources in terms of a set of decisional variables (e.g. robot model/positioning/number, welding gun models/allocation/number, welding point allocation etc.); then, the design optimization process minimizes the investment costs granting the cycle time. The multi-loop optimization architecture integrates both new algorithms and existent procedures from different fields. Test-bed showing its feasibility is reported

Multi-robot spot-welding cells: An integrated approach to cell design and motion planning

The necessity to manage several vehicle models on the same robotized assembly cell has made the cell design and the robot off-line motion planning two fundamental activities. Industrial practice and state-of-the-art methods focus on the technical issues of each activity, but no integrated approach has been yet proposed, resulting in a lack of optimality for the final cell configuration. The paper introduces a formalization of the whole process and proposes a heuristic multi-stage method for the identification of the optimal combination of cell design choices and motion planning. The proposed architecture is depicted through a real case for welding application

Zero-point fixture systems as a reconfiguration enabler in flexible manufacturing systems

ABSTRACT: Today's manufacturing systems need to be able to quickly adapt to customer demands, ranging from high volumes of mass production to high volumes of mass customization. Flexible Manufacturing Systems provide a high degree of flexibility to cope with these challenges. They consist of machine tools capable of executing a wide range of machining operations while the use of pallets to reference and block the parts allows the decoupling of the setup operations from the machining centers activity. This paper presents an ontology-based framework to support the design and management of flexible manufacturing systems, aimed at integrating the various involved activities including the pallet configuration and process planning, the management policies for short-term production planning and the pallet checking to verify the correct configuration of the physical pallet

Validation of an extended approach to multi-robot cell design and motion planning

According to both industrial practice and literature, multi-robot cell design and robot motion planning for vehicle spot welding are two sequential activities, managed by different functional units through different software tools. Due to this sequential computation, the whole process suffers from inherent inefficiency. In this work, a new methodology is proposed, that overcomes the above inefficiency through the simultaneous resolution of design and motion planning problems. Specifically, three mathematical models were introduced that (i) select and positions the resources, (ii) allocate the tasks to the resources and (iii) identify a coordinated robot motion plan. Based on the proposed methodology, we built three ad-hoc cases with the goal to highlight the relations between design, motion planning and environment complexity. These cases could be taken as reference cases so on. Moreover, results on an industrial case are presented

Design and motion planning of body-in-white assembly cells

This paper proposes a method for the automatic and simultaneous identification of the body-in-white assembly cell design and motion plan. The method solution is based on an iterative algorithm that looks for a global optimum by iteratively identifying the optimum of three sub-problems. These sub-problems concern system layout design and motion planning for single and multi-robot systems, while collision detection is addressed. The sub-problems are handled through ad-hoc developed Mixed Integer Programming (MIP) models. The proposed solution overcomes the limitations of the current design and motion plan approaches. In fact, the design of body-in-white assembly cell and the robot motion planning are two time-expensive and interconnected activities, up to now generally managed from different human operators. The resolution of these two activities as non-interrelated could lead to an increase of the engineer-to-order time and a reduction of the solution quality. Thus, a test bed is described in order to prove the applicability of the approach

Planning and execution with robot trajectory generation in industrial human-robot collaboration

The co-presence of a robot and a human sharing some activities in an industrial setting constitutes a challenging scenario for control solutions, requiring highly flexible controllers to preserve productivity and enforce human safety. Standard methods are not suitable given the lack of methodologies able to evaluate robot execution time variability, caused by the necessity to continuously modify/adapt robot motions to grant human safety. This paper presents a novel dynamic planning system for Human-Robot Collaboration (HRC) which leverages an offline motion planning technique and deploys planning and execution features dealing with temporal uncertainty and kinematics both at planning and execution time. The proposed system is deployed in a manufacturing case study for controlling a working cell in which a robot and a human collaborate to achieve a shared production goal. The approach has been shown to be feasible and effective in a real case study

On the lookout for influenza viruses in Italy during the 2021-2022 season: along came A(H3N2) viruses with a new phylogenetic makeup of their hemagglutinin

Aims: To assess influenza viruses (IVs) circulation and to evaluate A(H3N2) molecular evolution during the 2021-2022 season in Italy. Materials and methods: 12,393 respiratory specimens (nasopharyngeal swabs or broncho-alveolar lavages) collected from in/outpatients with influenza illness in the period spanning from January 1, 2022 (week 2022-01) to May 31, 2022 (week 2022-22) were analysed to identify IV genome and molecularly characterized by 12 laboratories throughout Italy. A(H3N2) evolution was studied by conducting an in-depth phylogenetic analysis of the hemagglutinin (HA) gene sequences. The predicted vaccine efficacy (pVE) of vaccine strain against circulating A(H3N2) viruses was estimated using the sequence-based Pepitope model. Results: The overall IV-positive rate was 7.2% (894/12,393), all were IV type A. Almost all IV-A (846/894; 94.6%) were H3N2 that circulated in Italy with a clear epidemic trend, with 10% positivity rate threshold crossed for six consecutive weeks from week 2022-11 to week 2022-16. According to the phylogenetic analysis of a subset of A(H3N2) strains (n=161), the study HA sequences were distributed into five different genetic clusters, all of them belonging to the clade 3C.2a, sub-clade 3C.2a1 and the genetic subgroup 3C.2a1b.2a.2. The selective pressure analysis of A(H3N2) sequences showed evidence of diversifying selection particularly in the amino acid position 156. The comparison between the predicted amino acid sequence of the 2021-2022 vaccine strain (A/Cambodia/e0826360/2020) and the study strains revealed 65 mutations in 59 HA amino acid positions, including the substitution H156S and Y159N in antigenic site B, within major antigenic sites adjacent to the receptor-binding site, suggesting the presence of drifted strains. According to the sequence-based Pepitope model, antigenic site B was the dominant antigenic site and the p(VE) against circulating A(H3N2) viruses was estimated to be -28.9%. Discussion and conclusion: After a long period of very low IV activity since public health control measures have been introduced to face COVID-19 pandemic, along came A(H3N2) with a new phylogenetic makeup. Although the delayed 2021-2022 influenza season in Italy was characterized by a significant reduction of the width of the epidemic curve and in the intensity of the influenza activity compared to historical data, a marked genetic diversity of circulating A(H3N2) strains was observed. The identification of the H156S and Y159N substitutions within the main antigenic sites of the most of sequences also suggested the circulation of drifted variants with respect to the 2021-2022 vaccine strain. Molecular surveillance plays a critical role in the influenza surveillance architecture and it has to be strengthened also at local level to timely assess vaccine effectiveness and detect novel strains with potential impact on public health

Multi-agent Collaboration in Shared Workspace

Presented on March 16, 2016 at 12:00 p.m. in the TSRB Banquet Hall.Stefania Pellegrinelli is a researcher at the Intelligent and Autonomous Robot Systems Division, Institute of Industrial Technologies and Automation, National Research Council of Italy - CNR-ITIA, where she arrived in 2009. She is currently a visiting researcher at the Carnegie Mellon University, Robotics Institute, Personal Robotics Lab. Her research interests initially centered on the development of automated methodologies for chip-removal process planning with CNC machine tools. She developed new holistic nonlinear process planning methodologies for the automatic configuration of multi-fixturing pallets in compliance to the STEP-NC standard. Currently, she is focusing on motion planning techniques for the automatic generation of industrial robot trajectories in static and dynamic environmentsRuntime: 52:41 minutesIn the last decades, the use of robots has become a reality in different industrial sectors, such as the automotive and logistic sectors, in terms of automated or semi-automated cells. On the basis of this trend, it is credible that robots will be part of our daily life in the next future, entering our houses and workplaces. One of key factors in the use of robots in our everyday activities is the ability to plan the robot, so that an effective and efficient collaboration among the involved agents (robots and/or humans) is enabled. In this talk, I will discuss my research efforts in robot motion planning when more agents are collaborating in a shared workspace. Specifically, I will present three main research directions: (1) multi-robot motion planning and coordination under design uncertainties in the context of multi-robot cells for car-body spot welding; (2) human-robot coordination through off-line planning of the robot motion on the basis of pre-analyzed human movements; (3) human-robot coordination through real-time planning of the robot motion on the basis of human intention prediction