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

A review of cost estimation models for determining assembly automation level

“…The literature also underlines that the possible use of multiple alternative machines and integration of manufacturability analyses with process evaluation and optimization have not yet been fully addressed in the literature Gayretli and Abdalla (1999). This was confirmed in Pehrsson et al (2013) where the need to analyze various production line design options and possible improvements from a financial perspective is highlighted to allow an efficient support to decision-making. In the same work, the authors underlined the fact that a strong basis for analysis and decision-making should be created by combining operational and financial data.…”

“…A lot of information about this process and about the production is still lacking or missing. Pehrsson et al (2013) mentioned that a cost analysis or a simple parametric cost calculation alone is not enough to support decision-making in the development of production systems: expertise from other disciplines, such as industrial engineering and operation management, is required to support such complex decision-making based on both costing and operational information. These multidisciplinary competences should enable predicting, based on a conceptual system design, performances and indicators that can be crucial in cost estimating.…”

“…The cost represents one of the most important decision criteria and an essential ingredient in the process of creating support for business decisions within manufacturing operations for every manufacturer (Gayretli & Abdalla, 1999;Pehrsson, Ng, & Stockton, 2013). It is also admitted that it represents a focal point for design and operational strategies and a key agenda for managerial policies and business decisions (Niazi, Dai, Balabani, & Seneviratne, 2006).…”

An interactive decision support system using simulation-based optimization and data mining

“…Simulation studies can help a company to answer what-if questions, but in order to know which parameters are best suited for the manufacturing system, an optimization technique has to be applied. When combined with optimization technologies, simulation has a potential to generate data as a basis for decisions made by decision makers (Pehrsson, Ng, and Stockton 2013).…”

Production simulation education using rapid modeling and optimization: Successful studies

“…The key features that FACTS Analyzer 2.0 added were more complex product variant and setups handling as well as additional modeling objects, like Selections, for rapidly comparing different scenarios by switching the connections to different submodels. Started already in the first version, simulation-based optimization (SBO), particularly multiobjective optimization (MOO), has been an integral component of FACTS Analyzer to facilitate managers/engineers to run their own optimization runs in order to seek the optimal combinations of model variables so that more confident decisions can be made by analyzing the Pareto-optimal solutions, as demonstrated in Ng et al (2011), Pehrsson and Ng (2011) and Pehrsson et al (2013) with real-world applications.…”