Prakash Krishnaswami

Automated process planning method to machine A B-Spline free-form feature on a mill-turn center

In this paper, we present a methodology for automating the process planning and NC code generation for a widely encountered class of free-form features that can be machined on a 3-axis mill-turn center. The free-form feature family that is considered is that of extruded protrusions whose cross-section is a closed, periodic B-Spline curve. In this methodology, for machining a part with B-Spline protrusion located at the free end, the part is first rough turned to the maximum profile diameter of the B-Spline, followed by rough profile cutting and finish profiling with axially mounted end mill tools. The identification and sequencing of machining volumes is completely automated, as is the generation of actual NC code. The approach supports both convex and non-convex profiles. In the case of non-convex profiles, the process planning algorithm ensures that there is no gouging of the work piece by the tool. The algorithm also identifies when sections of the tool path lie outside the work piece and utilizes rapid traverses in these regions to reduce cutting time. This methodology presents an integrated turn-mill process planning where by making the process fully automated from design with no user intervention making the overall process planning efficient. The algorithm was tested on several examples and test parts using the unmodified NC code obtained from the implementation were run on a Moriseiki mill-turn center. The parts that were produced met the dimensional specifications of the desired part.

Modeling of hybrid electromechanical systems using a component-based approach

Current approaches for modeling electromechanical systems (EMS) are either based on deriving the system equations by applying a single formulation to all problem domains, or they are based on trying to integrate different software packages/modules to solve the interdisciplinary problem. In this paper, we present a component-based approach that is suitable for hybrid electromechanical systems. This approach allows the governing equations of each component to be defined in terms of its natural variables. The different component equations are then brought together to form a single system of differential-algebraic equations (DAEs), which can be numerically solved to obtain the system response. The formulation includes monitor functions which can be used to detect when a qualitative system change has occurred, and to switch to a new set of governing equations to reflect this change. To handle discrete devices, the approach takes advantage of the fact that even such devices generally display piecewise smooth behavior, i.e., in the interval between successive sampling/switching times, they usually act as continuous devices. A single step integrator is used to integrate the system response interval by interval, without stepping over a sampling/switching time during an integration time step. The integration is restarted at each sampling/switching time. There is considerable flexibility in how the components can be defined. Examples of mechanical and electrical components are presented, and two numerical examples are solved to illustrate the efficacy of the proposed method. One example is a link that is driven by a DC motor through a gearbox. The results of this example were verified against Simulink, and good agreement was observed. The second example is a hybrid system that uses encoder feedback to control velocity of a dc motor driven link.

A comparative analysis of genetic algorithms and directed grid search for parametric optimization

In this paper, a comparative analysis of the performance of the Genetic Algorithm (GA) and Directed Grid Search (DGS) methods for optimal parametric design is presented. A genetic algorithm is a guided random search mechanism based on the principle of natural selection and population genetics. The Directed Grid Search method uses a selective directed search of grid points in the direction of descent to find the minimum of a real function, when the initial estimate of the location of the minimum and the bounds of the design variables are specified. An experimental comparison and a discussion on the performance of these two methods in solving a set of eight test functions is presented.

Automation of Process Planning for Boring of Turned Components With Arbitrary Internal Geometry From a Semi-Finished Stock

This paper describes a novel method for automated process planning for rough boring of turned components with arbitrary internal geometry from a semi-finished stock. Earlier work has been reported on process planning for boring of components with monotonic internal geometry made from bar stock. This paper addresses the more general problem of process planning of parts with non-monotonic internal feature list from arbitrary given initial geometry, i.e., from a casting or from a semi-finished stock. With the algorithms developed, we are able to achieve full automation of all aspects of the process plan, including operations sequencing, parameter selection, NC code generation, etc. Thus, it becomes possible to go from design to NC code in a fully automated fashion. In the present work we focus on a tightly defined part family, which results in very simple but robust automation algorithms. This is in contrast to much of the reported work on automated process planning, which generally targets broad part families, leading to complex algorithms that fall short of complete design-to-NC automation.Copyright

Integrated Design and Minimum Sensitivity Design of Controlled Multibody Systems

The design methods that have been traditionally used for controlled mechanical systems suffer from three major drawbacks. First, the design process is generally sequential, with the mechanical design being done first and frozen before the control system design is done. Secondly, the design is usually tuned to improve performance only without worrying about the sensitivity of the system’s performance to small variations in the system parameters. Third, there is a lack of systematic guidance for traversing the design space and arriving at a high quality design. In this work, we propose a design approach that addresses all three of these concerns. This approach first extends the constrained multi-element formulation for multibody systems to include a generic controller model. This gives the basic capability to simulate controlled multibody systems in a general way by numerically solving a set of differential-algebraic equations (DAE’s). A direct differentiation technique is then applied to the unified mathematical model to obtain a set of DAE’s in the sensitivities of the system variables. This is then used to compute the sensitivity of any performance function of interest. The system analysis and sensitivity analysis are then treated as inputs to a suitable nonlinear programming problem (NLP). The NLP serves as a vehicle to unify mechanical system and control criteria in the design process, and to incorporate sensitivity considerations along with performance considerations. The NLP also provides the means for automating the solution process through the use of optimization algorithms. Two representative example, including an industrial problem, are solved using this method. The results clearly show that the methodology is feasible and leads to a vast improvement in the quality of the final design, whatever the design considerations may be.Copyright

A truly meshless pre- and post-processor for meshless analysis methods

Abstract In recent years, meshless methods have been developed to eliminate the known drawbacks in finite element methods. Generating the input file for a meshless method and interpreting the output obtained can be difficult without graphical pre-processing and post-processing support. Unfortunately, most existing pre- and post-processing techniques are based on using an underlying finite element mesh or finite difference grid. Since meshless methods have neither, new approaches are required for providing this support for meshless methods. In this paper, a pre-processor and a post-processor are presented for the meshless method using node-based and pixel-based approaches as opposed to an element-based approach. Pre-processing supports for automated generation of nodes, support domains, and sub-domains along with local refining are also included. An extensive example is presented to demonstrate the effectiveness of the given pre-processor and post-processor.

An Innovative Web Application for Design and Automated NC Code Generation

With the ever-increasing importance of e-commerce/e-business in the manufacturing, traditional standalone CAD/CAPP applications are evolving into web-based applications deployed via the Internet. This paper presents a unique web-based application for automated process planning and NC code generation for mill-turn parts. The application is targeted at a wide range of users. It requires no special software or CAD package at the user’s end, and can be used even by people with virutally no manufacturing knowledge. At the same time, it is also a valuable service for manufacturing experts. This application uses client/server architecture and is developed using Java technologies. This web-based application can be accessed via Internet using any standard web browser with JRE (Java run-time environment), and Java Web Start is used to deploy this application. For wide usability, the application supports easy part specification and automated process planning. Once the part is designed, the user may request NC code generation. The process planning kernel on the server automatically executes all process planning tasks like machinable volume identification, operations sequencing, parameter selection, etc. and generates an intermediate Cutter Location (CL) code. The Cutter Location code is quite generic and can be adapted for any machine using the respective post processors. The interface is also capable of displaying the tool path for verification. The NC code is generated based on the post processor selected by the user and can be downloaded to the client machine if the user is satisfied. It is hoped that this application will develop into a pay-per-use instant NC code generation web service for novices and experts; such a service is currently not offered anywhere on the Internet.Copyright

Fuel-Efficient Operation of Compressor Stations Using Simulation-Based Optimization

One of the primary concerns in the operation of a compressor station is minimization of fuel consumption while maintaining the desired throughput of natural gas. In practice, the station operator tries to achieve this by shutting down units or controlling individual unit speeds based on experience. This is generally a trial-and-error process without any guarantee of optimality. In this paper we present a robust structured solution process for tackling this problem using simulation-based optimization. The first step to develop this solution process is to devise an analysis scheme that provides the simulation support required by the optimization. This was achieved by developing a fully implicit finite difference formulation of the continuity, momentum and energy equations for flow under non-isothermal conditions. The performance of each compressor unit was modeled by fitting polynomials to the compressor map. These polynomial equations were appended to the flow equations to obtain a complete set of system governing equations. The nonlinear algebraic equations resulting from this formulation were then solved using a Newton-Raphson iteration to obtain system performance. The problem of optimizing the operation of a compressor station was then formulated as a nonlinear programming problem (NLP) in which the design variables are the compressor unit speeds and the objective function to be minimized is the fuel consumption. A constraint was also placed on the minimum mass flow rate through the station to ensure that adequate flow is maintained while minimizing fuel consumption. This NLP was then solved using a sequential unconstrained minimization technique (SUMT) with a derivative-free grid search for handling the unconstrained minimizations. The simulation algorithm mentioned earlier is invoked whenever the optimization needs to evaluate the system response at a candidate operating point. The results obtained show that the simulation works very well in terms of predicting system response, and the proposed simulation-based optimization approach is highly effective in minimizing fuel consumption in a systematic way. The approach is successfully applied to single stations as well as to a sequence of stations along a pipeline, thereby establishing its applicability to station-level and network-level optimization.© 2004 ASME

Application of virtual convex polytope in transforming protrusions for automated process planning

In this paper, a two-tier methodology for the transformation of protrusion design features to manufacturing features is presented. In the first stage of the proposed algorithm, a method is proposed to encapsulate the protrusions with virtual convex polytope and transform them into a set of negative machining volumes. The design feature model is transformed into the intermediate feature model that consists of machining volumes using the concept of generic virtual pocket. In the second stage, called the feature refinement stage, relevant manufacturing information is appended to the negative machining volumes to transform the intermediate feature model into the manufacturing feature model. The proposed methodology can be used in the feature-based design and manufacturing systems to support automated process planning and machining functions. Practical examples and computer implementation in an object-oriented environment are also presented in this paper.

Metamodeling of Mechatronic Systems in the MIXEDMODELS Platform

The parametric design of mechatronic systems requires several detailed analyses of the system, thereby slowing down the design process significantly. In the recent past, there has been a lot of interest in using lower fidelity, but higher efficiency metamodels (also called surrogate models) instead of the actual detailed models to guide parametric design, particularly in the early stages of parametric design. One common approach to forming metamodels is to run the detailed model to obtain the system response at selected points in design space and fit a response surface to the results which becomes the metamodel. Since this method uses only zero order information at each design point, a large number of points are required to form a reasonably accurate metamodel. For example, in a single design variable problem, a two-point response surface can only be linear, whereas we can generate a cubic response surface if we also had derivative information at the two points. In this paper, we present a metamodeling approach for mechatronic systems that computes and utilizes first order derivative information at each point in the design space at which a detailed analysis is performed. The first order derivative information that is computed is the set of design sensitivity coefficients of the system state variables and performance functions. A unified modeling approach for the mechanical, electrical, and electronic aspects of the system is first developed. This approach generates a single set of governing equations for the entire system in the form of a system of differential-algebraic equations (DAE’s). Based on these DAE’s, a set of equations in the state design sensitivity coefficients is analytically derived using a direct differentiation approach. This set of equations also turns out to be a set of DAE’s which can be solved simultaneously in parallel with the system governing equations. We have successfully implemented this methodology for design sensitivity analysis of multidisciplinary systems in a computational platform called MIXEDMODELS (Multidisciplinary Integrated eXtensible Engine for Driving Metamodeling, Optimization, and DEsign of Large-scale Systems). Once we know the state design sensitivity coefficients, we can compute the design sensitivity coefficients of any system performance function. After we have obtained the necessary design sensitivity information, we can devise several schemes for generating a metamodel for the system based on the sensitivity information. Some examples of metamodels obtained using this approach are presented for selected mechatronic systems, along with the relevant accuracy measures.Copyright