Scalability is a key feature of reconfigurable manufacturing systems (RMS). It enables
fast and cost-effective adaptation of their structure to sudden changes in product demand. In principle, it allows to adjust a system's production capacity to match the existing orders. However, scalability can also act as a "safety buffer" to ensure a required minimum level of productivity, even when there is a decline in the reliability of the machines that are part of the machine tool subsystem of a manufacturing system. In this article, we analysed selected functional structures of an RMS under design to see whether they could be expanded should the reliability of machine tools decrease making it impossible to achieve a defined level of productivity. We also investigated the impact of the expansion of the system on its reliability. To identify bottlenecks in the manufacturing process, we ran computer simulations in which the course of the manufacturing process
was modelled and simulated for 2-, 3-, 4- and 5-stage RMS structures using Tecnomatix
Plant Simulation software.
Currently-used decision support solutions allow decision makers to estimate the cost of developing a new product, its production, and promotion, and compare the estimated cost to the target cost. However, these solutions are inadequate for supporting simulations of identifying conditions, by which the specific cost is reached. The proposed approach provides a framework for searching for possible variants towards reaching the target production cost. This paper is concerned with a prototyping problem of product development described in terms of a constraint satisfaction problem. The proposed method uses parametric estimation to identify relationships between variables, and constraint programming to search for project completion variants within the company’s resources and project requirements. The results of an experiment indicate that constraint programming provides effective search strategies for finding admissible solutions. Consequently, the proposed approach allows decision makers to obtain alternative scenarios within the limits imposed by the production process. In this, it outperforms current methods dedicated to the support of evaluating the total cost of a new product. The declarative approach presented in this paper is used to model the production cost; however, it can be effortlessly extended to other aspects of product development (e.g., product reliability).
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