Capacity planning using Monte Carlo simulation: an illustrative application of commonly available PC software

Abstract

Reviews the literature on capacity planning at strategic, tactical and operational levels but points out that, in practice, many enterprise resource planning systems make unrealistic assumptions for production planning; and the advanced production software packages which can deal with uncertainty are both complex and expensive. Uses a theoretical company to demonstrate how a normal Excel spreadsheet can be used in conjunction with a common add‐on package (@RISK) to improve analysis and run Monte Carlo simulations as a basis for decision making. Compares the results produced with standard spreadsheet analysis and discusses the additional financial and operational insights they provide into the implications of different capacity levels under conditions of uncertainty. Warns that the validity of the simulation depends on the quality of the data and model; and that human judgement is still required to actually make a decision.

Customer Concentration Versus Fragmentation and Its Implications in Corporate Risk

“…Stochastic models using Monte Carlo simulations are also implemented (Shi et al 2013). Interesting models testing capacity planning have been successfully made by Yang et al (2001). Risk analysis applications to the aero engine multiple failures have been also conducted (Li et al 2016).…”