Quality-driven recovery decisions for used components in reverse logistics

Abstract

Reverse logistics has emerged as a promising strategy for enhancing environmental sustainability through remanufacturing, reusing, or recycling used components. It is crucial to pursue quality-driven decision-making for component recovery because quality is a dominant factor for component salvage value and its recoverability. To maximise the profit from component recovery, a quality-driven decision model was proposed in this study. Remaining useful life (RUL) was utilised as a measure of quality in the proposed model, where conditional RUL distribution was predicted by utilising both the failure data and condition monitoring data based on a proportional hazard model. Under RUL uncertainty, an interval decision-making approach was developed to suggest recovery strategies for the decision-makers to identify a satisfactory solution according to their risk preferences. Compared to the existing approaches for quality-driven recovery decision-making based on RUL prediction, this work provides a more accurate and powerful approach to managing and mitigating decision risk. Numerical experiments demonstrated the effectiveness and superiority of the proposed model.

Keywords:

• component recovery
• recovery decision-making
• remaining useful life
• quality uncertainty
• reverse logistics
• decision analysis

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This work was supported by Jiangsu Key Laboratory of Precision and Micro-Manufacturing Technology, and the Key Technology R&D Programme of Jiangsu Province of China [grant number BE2014137], [grant number BE2016004-3].