Integrated system configuration and layout planning for flexible manufacturing systems
Péter Dobrovoczki, András Kovács, Hiroyuki Sakata, Daisuke Tsutsumi
Abstract
During the (re-)design of manufacturing systems, geometrical limitations on the available floor space may seriously impact the applicable resource configurations, including the selection of machines, robots, as well as auxiliary equipment. In current practice, such cases are managed by arduous manual iterations over the selection of resources and their geometrical arrangement. To overcome this inefficiency of existing approaches, the paper introduces a generic, integrated configuration-and-layout problem where the configuration sub-problem can encode arbitrary application-specific constraints on the selection of items (e.g., CNC machines and robots), while the layout sub-problem ensures geometrical feasibility, via a 2D rectangle packing representation. The generic model is demonstrated on an industrial application that involves the design of a flexible manufacturing system: items corresponding to CNC machines and robots must be selected, assigned to multiple manufacturing cells, and placed in the workshop blueprint to ensure that a given mix of products can be manufactured in the desired volume. For solving the generic configuration-and-layout problem, a logic-based Benders decomposition method is proposed. The efficiency of the approach is ensured by adding lifted cuts, symmetry breaking, and redundant constraints inspired by 2D bin packing lower bounds to the core Benders framework. Thorough computational evaluation is performed on a large set of problem instances, whereas practical applicability is verified in a real industrial case study. • Formal model and Benders solution approach are defined for generic configuration-and-layout problems. • The generic approach is applied to solving a flexible manufacturing system design problem. • Various computational techniques are proposed for making the Benders approach efficient. • The methods are evaluated on a large set of randomly generated FMS design problem instances. • Results of a real industrial FMS design case study are reported.