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Data Standardization and Analysis Model for Enhanced Global Productivity
Technical Paper
2015-26-0069
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Every organization needs to effectively manage its data collection and analysis process in order to efficiently collaborate on a global scale. This paper describes a model for standardizing the data collection and analysis process and specifically deals with two challenges in this regard: 1) A method for standardization of the nomenclature of different physical parameters measured during a typical engine test. This is essential for processing data from facilities spread across the globe to run them through a standard set of calculations. The process of storing and performing a given set of complex processes on the data while allowing analysts to view the steps of the processing in a transparent intuitive manner is also described in the paper. 2) Building on the first point, the paper also describes a process for performing a standard set of data quality checks on data as it is being collected. This allows for detection of issues in the data on a real-time basis. The paper further describes how this process can be applied to analyzing data and reporting issues while running a transient test in which the engine is rapidly changing its state every second.
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Citation
Chatterjee, S., Kyasa, R., Gopidi, N., and Prashanth Ravi, P., "Data Standardization and Analysis Model for Enhanced Global Productivity," SAE Technical Paper 2015-26-0069, 2015, https://doi.org/10.4271/2015-26-0069.Also In
References
- Janitor , W. and Van Gorder , K. The Advantages of Using Standard Vehicle Dynamics Procedures and Analysis Programs SAE Technical Paper 981077 1998 10.4271/981077
- Breuer , H. , Tiba , M. , Shastri , R. , Itkin , S. et al. Global Standardization of the Acquisition and Presentation of Comparable Data on Plastics SAE Technical Paper 940438 1994 10.4271/940438
- Williams , G. and Muir , E. A Study of Closed Loop Control and Data Acquisition for Engine Test Cells SAE Technical Paper 680134 1968 10.4271/680134
- Rachow , K. and Hieronimus , K. Improved Noise and Vibration Development by Employing Computer Aided Testing (CAT) SAE Technical Paper 911049 1991 10.4271/911049
- Thipse , Y. Utilization of Knowledge Based Utilities for Streamlining the Characterization Procedure of Acoustic Material Properties SAE Technical Paper 2014-28-0034 2014 10.4271/2014-28-0034
- Carlson , A. , Geenens , L. , Pobocik , E. , LaBo , J. et al. Transition from Quality Control to Quality Assurance at a Stamping Facility SAE Technical Paper 840101 1984 10.4271/840101
- Crawford , H. , Colshan , L. , and Cardenas , J. Statistical Process Control: Real-Time Data Acquisition and Response SAE Technical Paper 941840 1994 10.4271/941840
- Krisp , H. , Lamberg , K. , and Leinfellner , R. Automated Real-Time Testing of Electronic Control Units SAE Technical Paper 2007-01-0504 2007 10.4271/2007-01-0504
- McLaughlin , J. , Owsley , L. , Atlas , L. , and Bernard , G. Advances in Real-Time Monitoring of Acoustic Emissions SAE Technical Paper 972254 1997 10.4271/972254
- Weir , W. Automated Data Acquisition and Analysis from Production Testing SAE Technical Paper 810395 1981 10.4271/810395
- Microsoft Microsoft Excel Redmond Washington 2010
- Foehner , O. , Melder , W. , and Mueller , R. ASAM: Standards in Measurement and Automation Technology SAE Technical Paper 2000-01-0391 2000 10.4271/2000-01-0391
- AVL AVL CAMEO Graz, Austria 2012
- Van Rossum G. and Drake F. L. Python Reference Manual Python Software Foundation http://www.python.org 2006
- National Instruments NI DIAdem Singapore 2012
- Ying H. , Silex C. , Schnitzer A. and Leonhardt S. Automatic Step Detection in the Accelerometer Signal 4th International Workshop on Wearable and Implantable Body Sensor Networks (BSN 2007) IFMBE Proceedings 13 80 85 2007 10.1007/978-3-540-70994-7_14
- Ryu U. , Ahn K. , Kim E. and Kim M. Adaptive Step Detection Algorithm for Wireless Smart Step Counter Information Science and Applications (ICISA), 2013 International Conference 2013 10.1109/ICISA.2013.657933214
- Jones E. , Oliphant T. and Peterson P. SciPy: Open source scientific tools for Python http://www.scipy.org/ 2001