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Maintenance method of logistics vehicle based on data science and quality
Yu Ping Peng
, Shih Chieh Cheng
, Yu Tsung Huang
,
Jun Der Leu
企業管理學系
研究成果
:
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›
會議論文篇章
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同行評審
4
引文 斯高帕斯（Scopus）
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深入研究「Maintenance method of logistics vehicle based on data science and quality」主題。共同形成了獨特的指紋。
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Keyphrases
Maintenance Method
100%
Data Quality
100%
Vehicle-based
100%
Data Science
100%
Logistics Vehicle
100%
Decision Support System
50%
Service Parts
50%
Wrong Decision
25%
Service Life
25%
Divergence
25%
Algorithm Analysis
25%
Competitive Advantage
25%
Data for Good
25%
Chi-square Test
25%
Classification Rules
25%
Classification Model
25%
Vehicle Service
25%
Decision Support
25%
Good Quality
25%
Vehicle Maintenance
25%
Logistics Management
25%
Research Department
25%
Big Data Era
25%
Business Opportunities
25%
Replacement Cycle
25%
Cost Increase
25%
Work Order
25%
Global Logistics
25%
Vehicle Components
25%
Predictive Maintenance
25%
Optimal Replacement
25%
Changes in Consumption
25%
Manual Analysis
25%
Quality Considerations
25%
Replacement Rules
25%
Freight Car
25%
Freight Logistics
25%
Vehicle Repairs
25%
Chi-square Algorithm
25%
Maintenance History
25%
Computer Science
Business Opportunity
100%
Big Data
100%
Classification Rule
100%
Classification Models
100%
Wrong Decision
100%
Maintenance History
100%
Engineering
Quality Data
100%
Service Part
66%
Logistics Management
33%
Classification Rule
33%
Case Company
33%
Service Period
33%
Freight Vehicle
33%
Predictive Maintenance
33%
Big Data
33%