Stochastic analysis of quality uncertainty and optimal acquisition strategies for engine remanufacturing

Abstract

Returned used products vary widely in terms of their condition. For large used machinery, restoration processes are divided into reuse, remanufacture, recycle (3R) based on their condition. To quantify the environmental impacts of the 3R processing arising from the quality uncertainty of returns, this study presents a model that analyzes the carbon footprint at different processing nodes, and then establishes a quantitative relationship between environmental indexes and processing quantities at these nodes. Also, the overall condition of the returned cores can be directly reflected by processing quantities. As opposed to passive assessment, we then derive two optimal strategies to maximize the environmental benefit under different acquisition scenarios using stochastic analysis of the quantity distribution. The results, which were grounded with the data of engine remanufacturing, illustrate that prioritizing higher quality returns is not necessarily the best strategy. Rather, there exists an optimal overall quality coefficient that can maximize the comprehensive benefit of remanufacturing. Which provides the theoretical basis for managers to devise optimal acquisition strategy for maximal production efficiency with lower energy and resource input.