“Smart” Lead Time Prediction in SMEs environments: a theoretical framework proposal

Abstract

One of the most challenging tasks in Production Planning and Control (PPC) is Lead Time (LT) prediction. This problem is particularly acute in Small and Medium Enterprises (SMEs), which are typically labor-intensive environments where operators "dominate" the production process rather than being subjected to pure automation. In these environments, characterized by high product variability, such as Engineer-to-Order (ETO) or Make-to-Order (MTO) production systems, lead times are usually treated as static data or often outdated, and it is difficult to predict them when a new order arrives in the system. The scientific literature reveals the absence of tools to support SMEs in this planning task and the lack of integration of workforce characteristics and related data in LT prediction methods. To fill these gaps, the main objective of the study is the development of a preliminary theoretical framework for forecasting LT, according to a double planning horizon, which represents the starting point for the development of a decision support system adapted to SME characteristics.