Industrial cost modelling and multi-objective optimisation for decision support in production systems development

• Economically sound decisions are crucial to optimal production systems development.
• An incremental cost modelling method suitable for industrial use is proposed.
• Post-optimality analysis can extract knowledge to support decision-making.
• The methodology is verified in an industrial study with an automotive manufacturer.

Recent developments in cost modelling, simulation-based multi-objective optimisation, and post-optimality analysis have enabled the integration of costing data and cost estimation into a new methodology for supporting economically sound decision-making in manufacturing enterprises. Within this methodology, the combination of production engineering and financial data with multi-objective optimisation and post-optimality analysis has been proven to provide the essential information to facilitate knowledge-driven decision-making in real-world production systems development. The focus of this paper is to present the incremental cost modelling technique specifically designed for the integration with discrete-event simulation models and multi-objective optimisation within this methodology. A complete example, using the simulation model and data modified from a previous real-world case study, is provided in this paper to illustrate how the methodology and cost modelling are applied for the optimal investment decision support.