Hands-On Learning Environment and Educational Curriculum on Collaborative Robotics

The objective of this paper is to describe teaching modules developed at Wayne State University integrate collaborative robots into existing industrial automation curricula. This is in alignment with Oakland Community College and WSU’s desire to create the first industry-relevant learning program for the use of emerging collaborative robotics technology in advanced manufacturing systems. The various learning program components will prepare a career-ready workforce, train industry professionals, and educate academicians on new technologies. Preparing future engineers to work in highly automated production, requires proper education and training in CoBot theory and applications. Engineering and Engineering Technology at Wayne State University offer different robotics and mechatronics courses, but currently there is not any course on CoBot theory and applications. To follow the industry needs, a CoBot learning environment program is developed, which involves theory and hands-on laboratory exercises in order to solve many important automaton problems. This material has been divided into 5-modules: (1) Introduce the concepts of collaborative robotics, (2) Collaborative robot mechanisms and controls, (3) Safety considerations for collaborative robotics, (4) Collaborative robot operations and programming, (5) Collaborative robot kinematics and validation. These modules cover fundamental knowledge of CoBots in advanced manufacturing systems technology. Module content has been developed based on input and materials provided by CoBot manufacturers. After completing all modules students must submit a comprehensive engineering report to document all requirements

Monitoring and diagnosis of assembly fixture faults using modified multivariate control charts and surface scanning content

Recent advances in process monitoring technology have introduced an influx of exceptionally large data sets containing information on manufacturing process health. Recorded data sets are comprised of numerous parameters for which multivariate statistical process control (MSPC) methodologies are required. Current multivariate control charts are ideal for monitoring data sets with a minimal amount of parameters, however, new monitoring devices such as surface scanning cameras increase the number of parameters by two orders of magnitude in some cases. This paper proposes a modified form of the original multivariate Hotelling T2 chart possessing the capability to monitor manufacturing processes containing a large number of parameters and a fault diagnosis procedure incorporating least squares analysis in conjunction with univariate control charts. A case study considering surface scanning of compliant sheet metal components and comparisons to processes utilizing Optical CMM\u27s is presented as verification of the proposed assembly fixture fault diagnosis methodology and modified Hotelling T2 multivariate control chart. Copyright © 2007 by ASME

Fault detection and prognosis of assembly locating systems using piezoelectric transducers

Fixture faults have been identified as a principal root cause of defective products in assembly lines; however, there exists a lack of fast and accurate monitoring tools to detect fixture fault damage. Locating fixture damage causes a decrease in product quality and production throughput due to the extensive work required to detect and diagnosis a faulty fixture. In this paper, a unique algorithm is proposed for fixture fault monitoring based on the use of autoregressive models and previously developed piezoelectric impedance fixture sensors. The monitoring method allows for the detection of changes within a system without the need for healthy references. The new method also has the capability to quantify deterioration with respect to a calibrated value. Deterioration prognosis can then be facilitated for structural integrity predictions and maintenance purposes based on the quantified deterioration and forecasting algorithms. The proposed robust methodology is proven to be effective on an experimental setup for monitoring damage in locating fixtures. Fixture wear and failure are successfully detected by the methodology, and fixture structural integrity prognosis is initiated. © Springer Science+Business Media, LLC 2009

Starlikeness of Libera transformation (II) (Applications of Complex Function Theory to Differential Equations)

The GEOTRACES Intermediate Data Product 2017 (IDP2017) is the second publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2016. The IDP2017 includes data from the Atlantic, Pacific, Arctic, Southern and Indian oceans, with about twice the data volume of the previous IDP2014. For the first time, the IDP2017 contains data for a large suite of biogeochemical parameters as well as aerosol and rain data characterising atmospheric trace element and isotope (TEI) sources. The TEI data in the IDP2017 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at crossover stations. The IDP2017 consists of two parts: (1) a compilation of digital data for more than 450 TEIs as well as standard hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing an on-line atlas that includes more than 590 section plots and 130 animated 3D scenes. The digital data are provided in several formats, including ASCII, Excel spreadsheet, netCDF, and Ocean Data View collection. Users can download the full data packages or make their own custom selections with a new on-line data extraction service. In addition to the actual data values, the IDP2017 also contains data quality flags and 1-σ data error values where available. Quality flags and error values are useful for data filtering and for statistical analysis. Metadata about data originators, analytical methods and original publications related to the data are linked in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2017 as section plots and rotating 3D scenes. The basin-wide 3D scenes combine data from many cruises and provide quick overviews of large-scale tracer distributions. These 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of tracer plumes near ocean margins or along ridges. The IDP2017 is the result of a truly international effort involving 326 researchers from 25 countries. This publication provides the critical reference for unpublished data, as well as for studies that make use of a large cross-section of data from the IDP2017. This article is part of a special issue entitled: Conway GEOTRACES - edited by Tim M. Conway, Tristan Horner, Yves Plancherel, and Aridane G. González