Α Behavior Trees-based architecture towards operation planning in hybrid manufacturing

In modern manufacturing, the capability of process scheduling and task allocation is a major feature for the proper organization of complex production schedules. More particularly, the case of human-robot collaboration within assembly lines is considered as a quite challenging field, where an efficient process scheduling can reduce products’ delivery times, increasing in parallel its quality. The purpose of this paper is to propose an approach focusing on operation planning for Human-Robot Collaborative processes that consist of many tasks and multiple resources, such as the assembly of large-scale parts. The implementation of the Human-Robot Operation Planning (HROP) module is presented, which aim at the allocation of multiple operations between multiple and different types of resources. This development’s main pillar is a dynamic decision-making logic that combines both constraints, that exclude resources from the evaluation, as well as mathematical criteria, that provide finally a specific solution. The HROP particularity is that it is developed under the Behavior Trees (BT) architecture. For the validation of the proposed approach, a case study under a real industrial environment of the automotive industry is presented, based on the assembly of large-scale parts, such as buses, in a hybrid cell of both human operators and multi-type robots

Capital Tax Competition in the European Union: Theory and Evidence from Two Natural Experiments

We investigate the effects of European integration on corporate tax competition. Both economic and monetary integration result in lower transaction costs in �financial markets - by reducing capital controls, red tape and exchange rate uncertainty - and thereby in higher capital mobility. Nevertheless, monetary integration leads to a common pool problem vis-a-vis the shared revenues from issues of the common currency and to higher tax revenue needs due to lower inflation and the defficit constraints embedded in the stability pact. Economic integration may lead to access to better technologies, for the less developed members. It will also lead to more tax-responsive capital and higher user-cost of capital due to the abolition of tariffs. We show that monetary integration leads to lower taxes, while economic integration leads to higher taxes. Furthermore, we �find robust evidence of a race-to-bottom effect. Throughout, we investigate the impact of EU enlargement

Capital Tax Competition in the European Union: Theory and Evidence from Two Natural Experiments

We investigate the effects of European integration on corporate tax competition. Both economic and monetary integration result in lower transaction costs in �financial markets - by reducing capital controls, red tape and exchange rate uncertainty - and thereby in higher capital mobility. Nevertheless, monetary integration leads to a common pool problem vis-a-vis the shared revenues from issues of the common currency and to higher tax revenue needs due to lower inflation and the defficit constraints embedded in the stability pact. Economic integration may lead to access to better technologies, for the less developed members. It will also lead to more tax-responsive capital and higher user-cost of capital due to the abolition of tariffs. We show that monetary integration leads to lower taxes, while economic integration leads to higher taxes. Furthermore, we �find robust evidence of a race-to-bottom effect. Throughout, we investigate the impact of EU enlargement

A Cloud-to-Edge Approach to Support Predictive Analytics in Robotics Industry

Data management and processing to enable predictive analytics in cyber physical systems holds the promise of creating insight over underlying processes, discovering anomalous behaviours and predicting imminent failures threatening a normal and smooth production process. In this context, proactive strategies can be adopted, as enabled by predictive analytics. Predictive analytics in turn can make a shift in traditional maintenance approaches to more effective optimising their cost and transforming maintenance from a necessary evil to a strategic business factor. Empowered by the aforementioned points, this paper discusses a novel methodology for remaining useful life (RUL) estimation enabling predictive maintenance of industrial equipment using partial knowledge over its degradation function and the parameters that are affecting it. Moreover, the design and prototype implementation of a plug-n-play end-to-end cloud architecture, supporting predictive maintenance of industrial equipment is presented integrating the aforementioned concept as a service. This is achieved by integrating edge gateways, data stores at both the edge and the cloud, and various applications, such as predictive analytics, visualization and scheduling, integrated as services in the cloud system. The proposed approach has been implemented into a prototype and tested in an industrial use case related to the maintenance of a robotic arm. Obtained results show the effectiveness and the efficiency of the proposed methodology in supporting predictive analytics in the era of Industry 4.0

A Reconfigurable Gripper for Dexterous Manipulation in Flexible Assembly

In this paper, a high-speed multi-fingered reconfigurable gripper is presented. The aim is to create a robotic end effector that is capable of handling parts of different geometries and weight. It consists of three fingers, accounting for a total of eight Degrees of Freedom (DoFs). The paper discusses the design, control, and reconfiguration aspects of the gripper, and demonstrates its applicability to different manipulation tasks. The gripper has the ability of high-force movement and its high number of DoFs enables it to grasp a large variety of geometries, while retaining the design simplicity. The preliminary grasping experiments highlight its potential in robotic handling applications in both research and production environments

An Agent-Based System for Automated Configuration and Coordination of Robotic Operations in Real Time—A Case Study on a Car Floor Welding Process

This paper investigates the feasibility of using an agent-based framework to configure, control and coordinate dynamic, real-time robotic operations with the use of ontology manufacturing principles. Production automation agents use ontology models that represent the knowledge in a manufacturing environment for control and configuration purposes. The ontological representation of the production environment is discussed. Using this framework, the manufacturing resources are capable of autonomously embedding themselves into the existing manufacturing enterprise with minimal human intervention, while, at the same time, the coordination of manufacturing operations is achieved without extensive human involvement. The specific framework was implemented, tested and validated in a feasibility study upon a laboratory robotic assembly cell with typical industrial components, using real data derived from a car-floor welding process