An Integrated Approach for Design Improvement Based on Analysis of Time-Dependent Product Usage DataSource: Journal of Mechanical Design:;2017:;volume( 139 ):;issue: 011::page 111401DOI: 10.1115/1.4037246Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: With the recent advances in information gathering techniques, product performances and environment/operation conditions can be monitored, and product usage data, including time-dependent product performance feature data and field data (i.e., environmental/operational data), can be continuously collected during the product usage stage. These technologies provide opportunities to improve product design considering product functional performance degradation. The challenge lies in how to assess data of product functional performance degradation for identifying relevant field factors and changing design parameters. An integrated approach for design improvement is developed in this research to transform time-dependent usage data to design information. Many data modeling and analysis techniques such as hierarchal function model, performance feature dimension reduction method, Gaussian mixed model (GMM), and data clustering method are employed in this approach. These methods are used to extract principal features from collected performance features, assess product functional performance degradation, and group field data into meaningful data clusters. The abnormal field data causing severe and rapid product function degradation are obtained based on the field data clusters. A redesign necessity index (RNI) is defined for each design parameter related to severely degraded functions based on the relationships between this design parameter and abnormal field data. An associate relationship matrix (ARM) is constructed to calculate the RNI of each design parameter for identifying the to-be-modified design parameters with high priorities for product improvement. The effectiveness of this new approach is demonstrated through a case study for the redesign of a large tonnage crawler crane.
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contributor author | Ma | |
contributor author | Hongzhan;Chu | |
contributor author | Xuening;Lyu | |
contributor author | Guolin;Xue | |
contributor author | Deyi | |
date accessioned | 2017-12-30T11:43:16Z | |
date available | 2017-12-30T11:43:16Z | |
date copyright | 10/2/2017 12:00:00 AM | |
date issued | 2017 | |
identifier issn | 1050-0472 | |
identifier other | md_139_11_111401.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4242759 | |
description abstract | With the recent advances in information gathering techniques, product performances and environment/operation conditions can be monitored, and product usage data, including time-dependent product performance feature data and field data (i.e., environmental/operational data), can be continuously collected during the product usage stage. These technologies provide opportunities to improve product design considering product functional performance degradation. The challenge lies in how to assess data of product functional performance degradation for identifying relevant field factors and changing design parameters. An integrated approach for design improvement is developed in this research to transform time-dependent usage data to design information. Many data modeling and analysis techniques such as hierarchal function model, performance feature dimension reduction method, Gaussian mixed model (GMM), and data clustering method are employed in this approach. These methods are used to extract principal features from collected performance features, assess product functional performance degradation, and group field data into meaningful data clusters. The abnormal field data causing severe and rapid product function degradation are obtained based on the field data clusters. A redesign necessity index (RNI) is defined for each design parameter related to severely degraded functions based on the relationships between this design parameter and abnormal field data. An associate relationship matrix (ARM) is constructed to calculate the RNI of each design parameter for identifying the to-be-modified design parameters with high priorities for product improvement. The effectiveness of this new approach is demonstrated through a case study for the redesign of a large tonnage crawler crane. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | An Integrated Approach for Design Improvement Based on Analysis of Time-Dependent Product Usage Data | |
type | Journal Paper | |
journal volume | 139 | |
journal issue | 11 | |
journal title | Journal of Mechanical Design | |
identifier doi | 10.1115/1.4037246 | |
journal fristpage | 111401 | |
journal lastpage | 111401-13 | |
tree | Journal of Mechanical Design:;2017:;volume( 139 ):;issue: 011 | |
contenttype | Fulltext |