| It is important to find a way to manufacture products using sustainable methods and processes that minimize the use of MWF (metalworking fluids) in machining operations. To reach this ecological and coolant less goal, it is essential to determine the optimal cutting conditions and parameters, while maintaining long tool-life, acceptable surface finish and good part accuracy. A method that has demonstrated success in the minimization of MWF is NDM (Near Dry Machining). NDM is a sustainable manufacturing process that uses very small amounts of MWF in a flow of compressed air that can be on the order of 10,000 times less than overhead conventional flood cooling. The use and quantity of MWF is a direct indicator of sustainability that links the benefits of the economy, while protecting the public health, welfare, and environment from the extraction of raw materials to final disposition. Overall, it can be agreed that the delivery of NDM exhibits a smaller and much leaner process window than overhead conventional flood cooling. The primary objective of this work was to extend a dry machining tool-life equation that includes the delivery of NDM that maximizes tool-life performance by answering three basic questions: What should I apply? Where and how should I apply it? and How much should I apply?; The results of this study demonstrated that improvements can be made in tool-life (∼3 to 28%) varying the amount of MWF, the location of the nozzle with respect to the cutting tool and the type of MWF. However, enormous gains up to 300% in tool-life performance may be achieved by selecting the optimal NDM condition that provides a balance of lubrication and cooling.; The new tool-life equation for Near Dry Machining (NDM) contains much greater accuracy and less error (3 to 65%) than the original dry machining model (58 to 463%) when the effect of NDM is statistically different than dry machining. Likewise, when the effect of NDM is small or negligible, predictive modeling using the new tool-life equation is less accurate, yielding approximately 35% more error than the original DM model. |
