ProdSim: An Open-source Python Package for Generating High-resolution Synthetic Manufacturing Data on Product, Machine and Shop-Floor Levels

Abstract

Due to steadily increasing product and manufacturing complexity, the mutual dependencies between production system states and product properties increase as well. The flow of information in a multi-stage production setup also represents a material flow, as the metadata about the product and the production process grows. Changes of the production system state or product properties can influence downstream process steps and thus create hidden dependencies across a production system. However, if the individual process steps are examined in isolation, which is common for currently available simulation software, the generated data do not reflect these dependencies. Therefore, this work introduces the open-source simulation environment ProdSim, which brings together process simulations on product, machine, and shop-floor levels. The shop-floor simulation layer models the material flow between individual process steps, ensuring that the generated data also map interactions across multiple production steps. In contrast, the machine level maps specific production processes using user-definable Python functions. ProdSim is specifically designed to synthesize high-resolution data with complex interaction patterns that can be used to develop and apply data-driven quality prediction techniques. Furthermore, the shop-floor level offers flexible modeling options, such as assembly hierarchies, buffer storage, different production types, multi-stage, and multi-product production. ProdSim is distributed as an open-source Python package, using the discrete-event simulation framework SimPy as a simulation core.