Product-mix analysis with discrete event simulation

Abstract

Discrete event simulation (DES) has been used as a design and validation tool in various production and business applications. DES can also be utilized for analyzing the product-mix for production planning and scheduling. Product-mix decisions using analytical methods such as linear programming (LP) are usually made so that the market demand is met and the firm profit is maximized. However, the complexity and stochastic and dynamic nature of real-world production and business systems may lead to production levels that are different from those determined by analytical methods. Also, coping with the dynamic changes in the product-mix usually requires enhancing system parameters and/or process configuration. Therefore, it is in some cases essential to conduct the product-mix analysis using a DES model that accounts for the complexity and stochastic and dynamic behavior of real-world systems. Utilizing DES to measure the system response to potential changes in product-mix is necessary to arrive at a flexible system configuration that is adaptable to dynamic changes in the product-mix. Therefore, the primary goals of this paper are to highlight the importance of analyzing the product-mix with DES, present a methodology for performing the analysis, and provide a case study to clarify the methodology.