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Forecasting return of used products for remanufacturing using graphical evaluation and review technique (GERT)

Forecasting return of used products for remanufacturing using graphical evaluation and review technique (GERT)

Zhou, Li ORCID: 0000-0001-7132-5935, Xie, Jiaping, Gu, Xiaoyu, Lin, Yong ORCID: 0000-0001-7118-2946, Ieromonachou, Petros ORCID: 0000-0002-5842-9585 and Zhang, Xiaole (2016) Forecasting return of used products for remanufacturing using graphical evaluation and review technique (GERT). International Journal of Production Economics, 181 (B). pp. 315-324. ISSN 0925-5273 (doi:https://doi.org/10.1016/j.ijpe.2016.04.016)

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Abstract

This research develops a forecasting model that can predict the quantity, time and probability of product return, recyclable parts/components/materials and disposal. It adopts the Graphical Evaluation and Review Technique (GERT) by translating the remanufacturing operational process into a stochastic network. This stochastic network possesses two characteristics: activities having a probability of occurrence associated with them; and time to perform an activity. Together with the GERT method, Mason’s rule is applied to calculate the equivalence transfer function of the system, therefore predicting the desired outcomes. A generic eight-step process on how to implement this method in any structure of return products and remanufacturing network is provided. A numerical example is presented to demonstrate the result of using GERT on forecasting printer remanufacturing outcomes. The main contribution of this research is: Instead of giving one result such as either return quantity, or time, or probability, our research can forecast three of these outcomes simultaneously, and the algorithm is generalised to be applicable to any product structure and remanufacturing network.

Item Type: Article
Additional Information: SJR 4* Journal (Quartile 1 Journal)
Uncontrolled Keywords: Return forecasting; GERT; Product return; Remanufacturing; Moment-Generating Function; Transfer function
Subjects: H Social Sciences > H Social Sciences (General)
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group
Faculty of Business > Department of Systems Management & Strategy
Last Modified: 17 May 2019 21:37
Selected for GREAT 2016: None
Selected for GREAT 2017: GREAT b
Selected for GREAT 2018: None
Selected for GREAT 2019: GREAT 3
URI: http://gala.gre.ac.uk/id/eprint/17085

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