A Deterministic Inventory Model with Automation-Enabled Processes for Defective Item Management

Abstract

The increasing demand for sustainable practices has highlighted the role of automation in enhancing production and inventory management systems. Although inventory models with imperfect items, rework process, and unmet demand have been extensively studied, they frequently ignore the capability of small-scale automation to improve performance and cut expenses. This study proposes a sustainable production inventory model by incorporating machine enabled techniques while capturing their effect on storage, rework, and backordering costs. The model is structured based on two conditions: (i) an inventory model with defective items, rework and shortages backordered and (ii) an inventory model with automated systems for defective item management. The optimum production lot size, backorder quantity, and the overall system costs are derived analytically and a numerical example is used to validate the suggested models. By comparing both the models, results demonstrate that the incorporation of automation significantly decreases the overall costs from $8922.65 to $8874.81. This research offers a decision-making framework for academics as well as real-world application by incorporating automation into production systems to improve efficiency and promote sustainability.