TOOL CHANGING POLICIES FOR A MULTI-TOOL MACHINING CENTER.

摘要

During the past decade, the prospect of Computer-Aided Manufacturing has presented engineers with unsurpassed challenges in system theory and promises of precise control, better productivity, and improved tooling system. Numerical control is the forerunner of modern Computer-Aided Manufacturing. The versatility acquired by combining numerical control with metal-cutting machine tools is best represented by machining centers. The machining center incorporates several features into one machine tool which then performs a multiplicity of operations such as tapping, drilling, milling, reaming, and boring. The life of cutting tools used in machining centers, or any other machine tool, has been modeled using probabilistic methods because of the stochastic nature of tool wear. Both linear and nonlinear models have been developed for tool wear.; An approximate expression for the renewal function has been developed and used to establish an optimum scheduled tool replacement interval for minimum production cost using optimum set of cutting conditions. Confidence bounds on the coefficient of variation have been developed under certain assumptions and a general optimization model for multi-tool machining systems has been formulated when the replacement interval and the operating conditions are all decision variables. Constraints that impose restrictions on the cutting parameters (such as the required surface finish, the force developed and the power consumption) are considered in the optimization process. A user-friendly interactive-nonlinear constrained-optimization package has been developed to carry out the above analyses. Two examples are given to show the practical application of this study to a conventional machine tool and a computer-aided manufacturing system such as the machining center. Sensitivity analysis on the results of the optimization process for these two examples has been conducted using the lower and the upper bounds of the renewal function versus the developed expression, a change in the cost ratio by increasing the scheduled replacement cost or decreasing the premature failure cost, and the lower and upper bound on the coefficient of variation. Their combined effect on the optimization process has been examined.