Easters, DJ ORCID: https://orcid.org/0000-0002-7614-9181, 2014. The PACTUM model: product analysis of cost and time using mathematics. International Journal of Modeling, Simulation, and Scientific Computing, 5 (1). ISSN 1793-9623
Preview |
Text
218101_1232.pdf Download (825kB) | Preview |
Abstract
Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies. This paper discusses the prevailing relationships found within apparel supply-chain environments, and contemplates the complex issues indicated for constituting a mathematical model. Principal results identified within the data suggest, that the multifarious nature of global supply-chain activities require a degree of simplification in order to fully dilate the necessary factors which affect, each sub-section of the chain. Subsequently, the research findings allowed the division of supply-chain components into sub-sections, which amassed a coherent method of product development activity. Concurrently, the supply-chain model was found to allow systematic mathematical formulae analysis, of cost and time, within the multiple contexts of each sub-section encountered. The paper indicates the supply-chain model structure, the mathematics, and considers how product analysis of cost and time can improve the comprehension of product lifecycle management.
Item Type: | Journal article |
---|---|
Publication Title: | International Journal of Modeling, Simulation, and Scientific Computing |
Creators: | Easters, D.J. |
Publisher: | World Scientific |
Date: | 2014 |
Volume: | 5 |
Number: | 1 |
ISSN: | 1793-9623 |
Identifiers: | Number Type 10.1142/S1793962314410049 DOI |
Divisions: | Schools > School of Art and Design |
Record created by: | EPrints Services |
Date Added: | 09 Oct 2015 10:23 |
Last Modified: | 09 Jun 2017 13:28 |
URI: | https://irep.ntu.ac.uk/id/eprint/12276 |
Actions (login required)
Edit View |
Statistics
Views
Views per month over past year
Downloads
Downloads per month over past year