Lead time estimation by using regression and fuzzy regression methods

Lead time estimation plays a critical role in supply chain management by enabling timely order fulfillment and optimizing the operations of organizations. Accurate lead time estimation is crucial not only for ensuring customer satisfaction but also for important considerations in stock, time, and cost planning. Various statistical methods are used for forecasting, and one of them is regression analysis. The statistical method used to analyze the relationship between two or more variables is called regression analysis. On the other hand, fuzzy regression analysis is an alternative method used in cases where the application of classical regression is not recommended due to the fact that some or all of the data is fuzzy in system structures with uncertainty or because the system structure does not allow to define precise relationships between variables. In this study, classical linear regression and fuzzy linear regression which is one of the applications based on fuzzy logic was examined theoretically and then, an application was made on lead time estimation of productions in an R&D company serving in the defense industry and the results were examined.