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Mapping Quality in Extended Value Streams using Data Recorders
Author(s) -
Olsen Eric,
Fung Christopher,
Singh Jay,
Singh Paul
Publication year - 2017
Publication title -
packaging technology and science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 50
eISSN - 1099-1522
pISSN - 0894-3214
DOI - 10.1002/pts.2205
Subject(s) - energy (signal processing) , value stream mapping , measure (data warehouse) , chain (unit) , value (mathematics) , quality (philosophy) , energy consumption , computer science , data mining , statistics , engineering , mathematics , operations management , philosophy , physics , electrical engineering , epistemology , astronomy , lean manufacturing
This research compares three new methods and measures for mapping and evaluating the transportation segment of a value chain. The three methods are total energy, energy‐time and energy‐distance. The methods combine practices used in traditional physical distribution system analysis and extended value stream mapping (VSM) analysis. This research concludes that the energy‐distance method and measure is the most effective for analysing, comparing,and identifying opportunities for value chain improvement. It also identifies a ‘U‐shape’ that is characteristic of the energy transfer pattern during a transportation segment that suggests that damage from transportation may need to be screened for quality at a subsequent value chain node.