Machine Tool Design Via Lightweighting For Reduced Energy Consumption
thesisposted on 2021-12-03, 20:11 authored by Matthew J TriebeMatthew J Triebe
Machine tools are an important piece of manufacturing equipment that are widely used throughout many industries. Machine tools shape and form raw materials into desired products through processes such as grinding, cutting, bending, and forming, and when they perform these operations, they consume large amounts of energy. Due to the significant energy consumption, machine tools have a large environmental footprint. Addressing the environmental footprint of machine tools through energy reduction is important to addressing manufacturing and industry’s footprint. One strategy with great potential to reduce machine tool energy consumption is lightweighting. Lightweighting is a design strategy that reduces the mass of moving components with a goal of reducing energy consumption. This strategy is effective since a greater mass requires more energy to move. Lightweighting has had great success in the transportation sector where lightweight materials and lightweight design strategies have been implemented. There has been some work to explore the potential benefits of lightweighting machine tools, however an in-depth study relating mass to energy consumption in machine tools along with exploring other potential concerns, i.e., impact on dynamics and cost, is required.
To explore the lightweighting of machine tools, a lightweighting application along with models are proposed to investigate the connection between mass and energy in machine tools and potential concerns associated with lightweighting, i.e., decreased dynamic performance and increased machine tool cost. First, a method to reduce the mass of a vertical milling machine tool table is proposed. This method will include the implementation of a sandwich panel for the table while optimizing the structure of the table to maximize its strength and minimize its mass. Following, to link mass to energy consumption, an energy model is proposed to quantify the energy required to drive the table throughout the use of the machine, including cutting and non-cutting moves. In addition to modeling energy, this model will explore the role of motor sizing in the energy consumption of the drive system. To address dynamic concerns resulting from lightweighting, a dynamic model is proposed. This model will provide insight into the dynamic performance of the table and explore the impact of lightweighting on machine tool performance. Finally, a cost model of machine tools is proposed to study the impact of lightweighting on cost. Machine tool cost drivers will be explored along with the role that design complexity has on purchase price.
This dissertation provided a proof of concept for a lightweighting application through the sandwich panel design of the slide table. The energy model built considering the lightweight table provided a link between the mass and energy consumption in the machine tool. It was shown that more than 30% of the drive system energy could be saved by lightweighting the table. A 30% savings is substantial, especially if applied to multiple systems throughout the machine tool. The static and dynamic models showed that designing lightweight components can be accomplished without sacrificing performance. Various design tools, e.g., finite element analysis, can be used to address static and dynamic concerns. The cost model showed how lightweighting will not increase the cost of the machine tool and therefore will not discourage machine builders from implementing lightweighting to reduce energy consumption.
The contributions of this research are summarized as follows:
1. A shape optimization method to design the sandwich panel table, accomplished through a genetic algorithm. This provides a lower-cost lightweighting application.
2. A mechanistic model linking mass to energy consumption. This provides insight into design considerations required to implement lightweighting
3. Static and dynamic models of the milling machine slide table. These provide understanding of how lightweighting affects the performance machine tools
4. A cost model of milling machines. This provides insight into how lightweighting affects the machine tool cost