This paper presents the selection of a set of Key Performance Indicators (KPI) to improve the awareness of different manufacturing assets, including those related to energy efficiency. The implementation relies on Service Oriented Architecture deployed by Web Services and the further processing of the generated events by the application of an Event Processing Language based on rules. The proposed approach is illustrated with the implementation on a multi robot production line.
This paper presents a method to identify at an early stage incipient faults in pieces of equipment typically used for transportation of parts in discrete manufacturing settings. The method relies on knowledge of the typical energy consumption of the described devices using different workloads (the energy signature of the machines). At runtime, Support Vector Machines (SVM) are used to classify the input energy data into two pattern descriptions, typical of regular workloads expected on the devices. Consecutive mismatches between the output of the SVM and the workloads observed in real time indicate possibility of incipient failure at device level. The method is implemented using Web Services deploying Service Oriented Architecture in a real multirobot factory automation industrial testbed, originally used for assembly of mobile phones.
Energy management systems (EMS) play an important role to achieve improvements in energy efficiency at manufacturing enterprises. Development and implementation of EMS is rather challenging due to the distributed nature of enterprises and heterogeneity of enterprise medium. Modern ICT solutions and improved architecture paradigms can help to overcome these obstacles. In this paper we propose an energy management system architecture based on SOA 2.0 technologies to ensure intra-and cross-layer interoperability of system components.
After installation, safety systems are usually not upgraded anymore, because producers have no financial incentive to impose modifications on the production line . The traditional approach to installing safety systems is to connect all safety components within a workcell in series. The crucial associated problem is the subsequent identification of the source of a fail state. This paper proposes a safety monitoring system as a way to overcome this problem using the 6LoWPAN wireless technology. The used technology supports the implementation of a sensor network, fully accessible by IPv6, on top of existing solutions without any additional rewiring. Sensor data is processed by the monitoring system and displayed on the operator panel, to provide information concerning the location and type of the safety issue.
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