Paul H. Cohen

Virtual manufacturing cells : exploiting layout design and intercell flows for the machine sharing problem

Existing approaches to cell formation concentrate on machine grouping and part family formation. Since their input data usually do not consider flow directions and volumes, they neglect layout and handling strategies that can simplify the machine sharing problem. Hence, these approaches fail to relate the intracell and intercell layout decisions to the machine grouping and sharing decisions. This paper introduces a new approach for cell formation which integrates machine grouping and layout design, neglecting part family formation. The concepts of a hybrid cellular layout and virtual manufacturing cells are related. It is shown that a combination of overlapping GT cells, functional layout and handling reduces the need for machine duplication among cells. This approach questions the traditional emphasis on machine duplication to create independent cells that is suggested by the standard machine-part matrix clustering methods. The steps in the method are demonstrated by using two illustrative examples obtai...

Dynamic modeling of the fixture-workpiece system

Abstract This paper presents a methodology for dynamic modeling and simulation of a fixture-workpiece system. A simulation approach is required since standards typically do not exist for dynamic situations like machining operations. In addition, an accurate model is developed for the contact interface at each locating and clamping region on the workpieces surface. An end milling operation is simulated to analyze the effects of various factors on workpiece accuracy and demonstrate the advantage of the simulation approach. The clamping forces required to keep the workpiece in contact with its locators are obtained, and the influences of locator placement, clamp placement, clamping forces, and clamping sequence on linear and angular errors are reported. Elastic effects of the locator-workpiece and clamp-workpiece contacts, yielding nonlinear dynamic equations of motion, are included in the model. Since system dynamics are considered, results are obtained as a function of time. The study compares well with previous experimental work by other investigators, and the method shows promise as a fixture design tool.

Process plan generation for sheet metal parts using an integrated feature-based expert system approach

This paper describes a relational database system for semi-generative process planning for sheet metal parts that emulates expert system capabilities. The system integrates a feature-based relational database for the parts, a forward chaining rule-based strategy for machine selection, both global and feature-specific execution of the rules and a graph theoretic cost optimization model for optimal process plan selection. This system, which is currently being developed for a sheet metal fabrication company, suggests that, using the experience of shopfloor personnel, an efficient integration of feature-based process planning and expert system strategies can be accomplished.

The effect of grinding on the flexural strength of a sialon ceramic

The effect of selected grinding parameters on the flexural strength of a sialon ceramic was studied. Support compliance was found to have no significant effect, while depth of incursion and grinding direction did. Weibull statistics and analysis of variance techniques were used to detect these effects which are explained through flaw magnitude and direction.

Neural network driven fuzzy inference system

Based on theoretical results, fuzzy systems are universal approximators. In this paper, the authors propose a novel learning approach, self-organizing and self-adjusting fuzzy modeling (SOSAFM), for inference rules. Basically, the proposed system consists of two stages, the self-organizing stage (SOS) and the self-adjusting stage (SAS). In the first stage, the input data is divided into several groups by applying Kohonens feature maps. Gaussian distribution functions are employed as the standard form of the membership functions. Methods of statistics are used to determine the center and width of the membership function for each group. Regarding the consequences, the linear regression method is used. After the above procedures, one can decide the initial parameters of fuzzy systems. Then, the error backpropagation-type learning method is used to fine-tune the parameters. The simulation results show that the proposed approach is better than conventional neural networks in both accuracy and speed.<<ETX>>

Dry sliding wear behavior of an Si-Al-O-N ceramic

Abstract Dry sliding wear tests were conducted on (Si-Al-O-N)-cast iron sliding pairs using a wear tester specifically designed to simulate closely the high pressures, velocities and resultant temperatures encountered in heavily loaded machinery and other engineering applications. A wear tester was designed so that both the contact load level and the sliding velocity could be varied. Wear testing indicated that, following a short wear-in period, mass loss varied linearly with sliding distance for all contact loads and sliding velocities investigated. The steady state wear rates, expressed in terms of mass loss per unit sliding distance, were found to increase as the applied contact load was increased for all the sliding velocities investigated. Further, the wear rate was found to vary inversely with sliding velocity for the highest contact load level investigated. For the intermediate and lowest contact load levels, this inverse relationship between velocity and wear rate (i.e. reduced wear for higher velocities) was less pronounced and restricted to the lower range of velocities investigated. Several different grinding procedures were used to prepare the specimens prior to wear testing but were found to have no significant influence on the measured wear rates. The experimental results are qualitatively explained by considering combined wear mechanisms involving brittle fracture and plastic deformation, which depend on the relative magnitudes of contact load and sliding velocity. Brittle fracture is assumed to be the primary wear mechanism especially at high contact loads and low sliding velocities. Plastic deformation mechanisms are also active and intensify with increasing frictional heating and concomitant thermal softening.

A new forward temperature estimator for remote thermocouple sensing in machining

Abstract The application of the method of differential quadrature for forward temperature estimation in remote thermocouple sensing during machining is demonstrated and the results are verified by analytical and experimental data.

THE DEVELOPMENT OF A MATHEMATICAL MODEL FOR PREDICTING THE DEPTH OF PLASTIC DEFORMATION IN A MACHINED SURFACE

ABSTRACT The development and verification of a mathematical model for the prediction of plastic deformation in a machined surface are presented. The main assumption for developing this model is that there is a linear relation between plastic strain and the depth to which it extends. The model relates the work required to shear the workpiece material to the work needed to compress the workpiece material ahead of the cutting tool. The resulting depth of plastic deformation in the machined surface is a function of the true stress-strain characteristics of the workpiece material, the shear stress and shear strain on the shear plane, and the distribution of plastic strain. Results of the model agree well with data found in the literature. An improvement of the model is suggested through application of actual distribution data of plastic strain and calculation of frictional behavior on the rake face of the tool.

Remote sensing for on-line temperature estimation in machining: A basic framework

Abstract Remote thermocouple sensing (RTS) is a technique that utilizes analytical and experimental evidence to create models for temperature sensing, thus integrating the advantages of both approaches. The remote solution is an inverse problem of predicting the source based on some remote location temperatures. An accurate forward solution should be available that determines the relation between the source and sink, for estimation of the inverse relationship. Extensive simulation has to be performed on the forward solution, thus establishing a need for fast and accurate computation. A mathematical formulation for RTS is done using an elliptic partial differential equation. Boundary conditions are formulated to simulate the actual machining situation. Some of these are derived by placing an insulator between the tool and tool holder. For inverse solution, three thermocouples are used for enhancing the accuracy of source prediction. Issues such as steady-state machining, and location of thermocouples are discussed. Overall, a basic framework for RTS in machining is presented.

Electro-Machining (EM) Using Metal Coated Atomic Force Microscope Tip and Single-Walled Carbon Nanotube Buckypaper Films

Using metal-coated atomic force microscope (AFM) tips and single-walled carbon nanotube (SWNT) BuckyPaper films, the authors have successfully explored the feasibility of electro-machining (EM) at the nanometer scale. Highly ordered pyrolytic graphite (HOPG) and thin metal films were used as a substrate (workpiece) and metal-coated (Cr/Au) Si AFM tips and BuckyPaper films were used as electrodes. A negative voltage pulse was applied to the AFM tip to fabricate holes as small as 30 nm in diameter on the HOPG surface. Using SWNT BuckyPaper films, the submicron holes were fabricated on a metal surface, demonstrating that SWNTs can work as electrodes.Copyright