Calibration of Low-Frequency, Wide-Field Radio Interferometers Using Delay/Delay-Rate Filtering

We present a filtering technique that can be applied to individual baselines of wide-bandwidth, wide-field interferometric data to geometrically select regions on the celestial sphere that contain primary calibration sources. The technique relies on the Fourier transformation of wide-band frequency spectra from a given baseline to obtain one-dimensional "delay images", and then the transformation of a time-series of delay images to obtain two-dimensional "delay/delay-rate images." Source selection is possible in these images given appropriate combinations of baseline, bandwidth, integration time and source location. Strong and persistent radio frequency interference (RFI) limits the effectiveness of this source selection owing to the removal of data by RFI excision algorithms. A one-dimensional, complex CLEAN algorithm has been developed to compensate for RFI-excision effects. This approach allows CLEANed, source-isolated data to be used to isolate bandpass and primary beam gain functions. These techniques are applied to data from the Precision Array for Probing the Epoch of Reionization (PAPER) as a demonstration of their value in calibrating a new generation of low-frequency radio interferometers with wide relative bandwidths and large fields-of-view.Comment: 17 pages, 6 figures, 2009AJ....138..219

Component detection with on-board UHF RFID reader for Industrie 4.0 capable Returnable Transit Items

Industrie 4.0, Cyber-Physical Systems and Smart Manufacturing are all terms used to describe a vision of how intelligent products, processes and services can provide connectivity and real time information based technologies to improve manufacturing. This can be realised by embedding intelligence at the product and operational level to provide predictive, risk preventative and high performing manufacturing systems. The work outlined in this paper details how a Returnable Transit Item (RTI) can become an integral part of the Industrie 4.0 vision as an intelligent container that can interact with components, machines and other manufacturing services

Cyber-physical systems in the re-use, refurbishment and recycling of used electrical and electronic equipment

The aim of the research outlined in this paper is to demonstrate the implementation of a Cyber-Physical System (CPS) within the End of Life (EoL) processing of Electrical and Electronic Equipment (EEE). The described system was created by reviewing related areas of research, capturing stakeholder’s requirements, designing system components and then implementing within an actual EoL EEE processer. The research presented in this paper details user requirements, relevant to any EoL EEE processer, and provides information of the challenges and benefits of utilising CPSs systems within this domain. The system implemented allowed an EoL processer to attach passive Ultra High Frequency (UHF) Radio Frequency Identification (RFID) tags to cores (i.e. mobile phones and other IT assets) upon entry to the facility allowing monitoring and control of the core’s refurbishment. The CPS deployed supported the processing and monitoring requirements of PAS 141:2011, a standard for the correct refurbishment of both used and waste EEE for reuse. The implemented system controls how an operator can process a core, informing them which process or processes should be followed based upon the quality of the core, the recorded results of previous testing and any repair efforts. The system provides Human-Computer Interfaces (HCIs) to aid the user in recording core and process information which is then used to make decisions on the additional processes required. This research has contributed to the knowledge of the advantages and challenges of CPS development, specifically within the EoL domain, and documents future research goals to aid EoL processing through more advanced decision support on a core’s processes

A data management system for identifying the traceability of returnable transit items using radio frequency identification portals

The advancement of paradigms such as Industry 4.0 and cyber physical systems herald increased productivity and efficiency for manufacturing businesses through increased capture and communication of data, information and knowledge. However, interpreting the raw data captured by sensing devices into useful information for decision making can be challenging as it often contains errors and uncertainty. This paper specifically investigates the challenges of analysing and interpreting data recorded using Radio Frequency IDentification (RFID) portals to monitor the movements of Returnable Transit Items (RTI), such as racks and stillage, within an automotive manufacturing environment. Data was collected over a yearlong pilot study using an RFID portal system installed across two automotive facilities to trace the movement of RTIs between the sites. Based upon the results key sources of errors and uncertainty have been identified and a data management framework is proposed to alleviate these errors

Industrie 4.0 implementations in the automotive industry

To address the challenges imposed by the adoption of new technology to realise the Industrial Internet also known as Industrie 4.0, manufacturing companies are recognising the need to set up and manage “intelligent test factories”. The result is networks of cyber-physical systems (CPS) where software interfaces and services are developed to support interoperability between physical and control structures. A test factory using Radio Frequency Identification (RFID) as a first generation enabler of CPS in industrial production systems is presented in this paper. The research outlined in this paper describes the first generation of CPS that uses identification technologies such as RFID tags embedded into engine components and their carries, which allow unique identification. Data storage, processing and analytics are also provided to support real-time algorithmic intelligent services that may be used in manufacturing operations including supply chain logistics, quality audits and manufacturing strategies