Digital framework for metallic subtractive process planning: Liger optimisation case study

Metallic subtractive process planning is challenging. It requires a blend of expert knowledge, experience, and established manufacturing methods. Decision-making in this domain is multifaceted and complex, and this includes the need to satisfy multiple conflicting demands faced by the manufacturing sector today. However, with the evolving landscape of manufacturing, combined with increased adoptions of digital technologies, the traditional rules of thumb are becoming obsolete. In response, this research investigated these decision-making processes within a subset of the digital framework for subtractive process planning. In particular, it has demonstrated that an advanced open-source optimisation tool (Liger) could be integrated with commercial industrial software and applied to a machining case study. The integrated software intelligently executed and automated simulations using advanced optimisation techniques. The outputs are a range of optimised solutions that support manufacturing engineers’ decision-making. One of the major benefits of the open-source software is that it provides an intuitive to use interface suitable for the non-expert in optimisation, offers a varied range of state-of-the-art multi-objective optimisation algorithms, and is capable of incorporating many different third-party types of software, models and simulations. In this paper, the Liger software has been applied to a simple case study to find the best feedrate and depths of cut that simultaneously minimise the cutting force and the time it takes to complete the machining process. The case study demonstrates proof-of-principle results that the optimisation software can be implemented in a wider process planning context with additional digital manufacturing simulation models.