Abstract
Remanufacturing is widely recognized as an effective strategy to address the negative environmental impacts of product disposal and minimize costs across the entire value chain. Short life cycle product like smartphone manufacturers and their e-commerce partners are offering tempting incentives to exchange obsolete handsets to gain market share. This increase in exchange programs has created issues about returns management, notably remanufacturing and disposal regulations. While we realize new product demand, we cannot guarantee returning item quality or quantity. Due to rapid technology changes that make components obsolete in 2-3 years, anticipating spare part needs is harder. An effective remanufacturing policy should replenish a percentage of spare parts inventory through returns recovery to solve these problems and optimize inventory levels. We propose two steps. First, we use Bayesian Estimation to predict returns and spare parts. This reduces production risk. The return quality function determines the spare part manufacturing curve. This two-step technique reduces production uncertainty and optimizes inventory. This study concludes with a comprehensive approach to smartphone returns management, remanufacturing, and spare parts inventories. Numerical examples show how our approach works.
