Energy Requirements of Steel and Cutting Tool - Paper Example

Determine the energy requirements for each set of steel and cutting tool

Compare electrical energy utilized vs Mechanical energy required for each of the optimal combinations.

Develop a model that compares energy efficiency vs hardness of cutting tool vs quality of the finish (smoothness).

Literature review

Over the last few years, energy conservation has become an agenda for all industries, owing to the adverse effects of global warming and climate change. The manufacturing industry, one of the economies primary consumer of energy, has been under pressure to reduce its carbon footprint. Different research has been done on energy consumption and conservation in the milling process. Analysis by Danganescu et al., (2003) for example wanted to determine energy consumption in finish hard milling of tool sets. Their research classified energy consumption at different levels. Another study identified the energy consumption associated with mass removed. Over the years mathematical models that theoretically calculate the mechanical energy required during milling. Research shows that models that predict surface roughness have been developed that gives you the minimum level of surface quality.

Most of the current models, however, only determine the energy consumption at either submachine or machine level (Li et al., 2011). That information should be used to assess production methodology that will be the most energy efficient. To most people, energy conservation goes hand in hand with compromise, but this must not be the case in the manufacturing industry. As much as it is environmentally conscious to conserve energy, compromised quality of work is just as dangerous. There is detailed research that links metal milling to environmental pollution. By-products of milling such as milling fluids, oil and general waste from workshops have been linked ecological degradation.

During the testing of most of the developed energy models, values did not match the electrical power consumption. Furthermore, those models could not account for the difference in the profits. Of the models developed, one that estimates, mathematically, the mechanical energy required for cutting is:

Pc=apaevfKc60106hWhere Pc = cutting power

Ap= depth of cut in mm

Ae = width of cut in mm

Vf= table feed per min (mm/min)

h = machine coefficient

With the aim of keeping quality constant, this research proposes to determine the best cutting tool for any of the selected steel pieces. Research on the best configuration of machine parameter (feed speed, cutting speed, etc.) is available and will be used as the default configuration to test the hypothesis on. From the literature, the most focus of the research is energy consumption during metal milling and cutting parameters. However, there is no research that directly compares the quality of the finish to energy consumption.

Methodology

An experimental approach is proposed for this experiment as it allows the researcher to compare different mechanisms. Four various alloys of steel will be used as the work-pieces with a pair of coated and uncoated cutting tools of varying composition and hardness. The first stage of the experiment will be to determine the best configuration of the various elements that will give you the same quality of finish. Models can be used to predetermine the optimal shape of machine parameters, but actual testing will be done. The next step will be to determine both mechanical and electrical energy consumed during the operation. Electrical strength will be measured while mechanical power will be determined from previously developed models. Scientific analysis will then be done to determine the most energy efficient combination(s) for obtaining the same quality of finish.

References

Borgia s, Leonesio M, Bianchi S, Cacace A. A machine tool energy analysis in general milling operations. Proceedings of ANIPLA Motion Control Conference, 2013.

Borgia S, Leonesio M, Pellegrinelli S, Valente A. Energy driven process planning and machine tool dynamic behavior assessment. Procedia CIRP, 2013;9:91-96.

Daganescu F, Gheeorghe M, Doicin CV. Models of machine tool efficiency and specific consumed energy. J. Mater, Process Tech,. 2003;141(1)1:9-5.

Li W, Kara S. An empirical modle for predicting energy consumption of manufacturing processes: a case of turning process. J. Eng. Manuf., 2011;255(B9):1636-1646.

Schlosser R, Klocke F, Lung D. sustainability in manufacturing-energy consumption of cutting processes. Advances in sustainable manufacturing: proceedings of the 8th global conference on Sustainable Manufacturing, Springer-Verlag, 2011;85-89.

Siemens. Sync. Motors 1FT6 series, Configuraton Manual, 2005.

US Energy Information Administration. Manufacturing Energy Consumption Survey (MECS): Total consumption of electricity by manufacturing industry and region. Technical report. 2013