Using Design Of Experiments To Define Factory Simulations For Manufacturing Investment Decisions

For many manufacturing investment decisions production metrics only form part of the significant data, financial data such as cash-flow, Return on Investment, profitability are also critically important. However generating financial metrics from predicted or real production data is a non-trivial task.Moreover the nature of financial and production metrics are typically dissimilar in fidelity and interval and careful attention is required to standardise data for robust decision making. The paper demonstrates how a Design of Experiments approach can be used to systematically create simulation output combinations which can be used to understand and quantify the critical interactions between engineering and financial metrics. The results illustrate the need to carefully consider financial metrics, and the risk of reducing a systems performance within a period to a single financial value.