Institute for Systems Research
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Item Interpreting Product Designs for Manufacturability Evaluation(1993) Gupta, Satyandra K.; Nau, D.S.; Zhang, G.M.; ISRThe ability to quickly introduce new quality products is a decisive factor in capturing market share. Because of pressing demands to reduce lead time, analyzing the manufacturability of the proposed design has become an important step in the design stage. In this paper we present an approach for evaluating the manufacturability of machined parts.Evaluating manufacturability involves finding a way to manufacture the proposed design, and estimating the associated production cost and quality. However, there often can be several different ways to manufacture a proposed design - so to evaluate the manufacturability of the proposed design, we need to consider different ways to manufacture it, and determine which one best meets the manufacturing objectives.
In this paper we describe a methodology for systematically generating and evaluating alternative operation plans. As a first step, we identify all machining operations which can potentially be used to create the given design. Using these operations, we generate different operation plans for machining the part. Each time we generate a new operation plan, we assign it a manufacturability rating. The manufacturability rating for the design is the rating of the best operation plan.
We anticipate that by providing feedback about possible problems with the design, this work will be useful in providing a way to speed up the evaluation of new product designs in order to decide how or whether to manufacture them.
Item Estimation of Achievable Tolerances(1993) Gupta, Satyandra K.; Nau, D.S.; Zhang, G.M.; ISRThis report presents a new and systematic approach to assist decision-making in selecting machining operation plans. We present a methodology to estimate achievable tolerances of operations plan. Given an operation plan, we use variety of empirical and mathematical models to evaluate process capabilities of various machining operations and compute achievable tolerances using tolerance charting techniques.Item Implementation of an Integrated CAD and CAM System(1992) Chen, A.T.; Zhang, G.M.; ISRThis is a progress report on a joint research project between the University and the M.S. Willett, Inc. The research focus is on the integration of a CAD system and a CAM system currently being used at the Willett.The development of CAD systems has revolutionized the process of preparing engineering designs and drawings. Likewise, CAM systems have significantly impacted the stop floor production process. Numerically controlled machines have improved accuracy and productivity in many applications. Integration of these two systems would tie the design phase of a project to the production process, and if done efficiently, could result in significant cost reduction and quality improvement.
In this project, two computer programs have been developed to automate NC code generation directly from a CAD file, either in DXF format or in IGES format. These two programs have been successful in identifying the important elements of an integrated CAD and CAM system. The initial results also indicated how the Willett could shorten the time of product development cycle, low the production cost, and improve the quality of end products.
This project has been supported by the Center for Manufacturing on the College Park campus.
Item Neural Network Applications in On-line Monitoring of Turning Processes(1992) Zhang, G.M.; Khanchustambham, Raju G.; ISRThe need to improve quality and decrease scrap rate while increasing the production rate is motivating industry to consider untended machining as viable alternative. On-line monitoring of a machining process is the key component to success for an untended machining operation. In this chapter, a framework for sensorbased intelligent decision-making systems to perform on- line monitoring is proposed. Such a monitoring system interprets the detected signals from the sensors, extracts the relevant information, and decides on the appropriate control action. Emphasis is laid on applying neural networks to perform information processing, and to recognize the process abnormalities in a machining operation. A prototype monitoring system is implemented to demonstrate the working mechanism. For successful implementation of the developed intelligent monitor, an instrumented force transducer is designed for signal detection and is used in a real time turning operation. A neural network monitor based on feedforward back-propagation algorithm is developed and tested under the machining of advanced ceramic materials and steel. The monitor is trained by the detected cutting force signal, the measured surface finish, and the observed tool wear. The superior learning and noise suppression abilities of the developed monitor enable high success rates for monitoring in machining process.Item Generation of Machining Alternatives for Machinability Evaluation(1992) Gupta, Satyandra K.; Nau, D.; Zhang, G.M.; ISRThis paper presents a new methodology for evaluating the machinability of a machined part during the design stage of the product development cycle, so that problems related to machining can be recognized and corrected while the product is being designed. Our basic approach is to perform a systematic evaluation of machining alternatives throughout each step in the design stage. This involves three basic steps: (1) generate alternative interpretations of the design as different collections of machinable features, (2) generate the various possible sequences of machining operations capable of producing each interpretation, and (3) evaluate each operation sequence, to determine the relevant information on achievable quality and associated costs. The information provided by this analysis can be used not only to give feedback to the designer about problems that might arise with the machining, but also to provide information to the manufacturing engineer about alternative ways in which the part might be machined.Item A Neural Network Approach to On-line Monitoring of a Turning Process(1992) Khanchustambham, Raju G.; Zhang, G.M.; ISRProduction automation has been the focus of the research to improve product quality and to increase productivity. Implementation of computer-based untended machining has attracted great attention in the manufacturing community. In this paper, a framework for sensor-based intelligent decision-making systems to perform on-line monitoring is proposed. Such a monitoring system interprets the detected signals from the sensors, extracts the relevant information, and decide on the appropriate control action. Emphasis is given to applying neural networks to perform information processing, and to recognize the process abnormalities in a machining operation. A prototype monitoring system is implemented. For signal detection, an instrumented force transducer is designed and used in a real time turning operation. A neural network monitor based on a feedforward back- propagation algorithm is developed. The monitor is trained by the detected cutting force signal and measured surface finish. The superior learning and noise suppression abilities of the developed monitor enable high success rates for monitoring the cutting force and the quality of surface finish under the machining of advanced ceramic materials.Item Generation and Evaluation of Alternative Operation(1992) Nau, D.S.; Zhang, G.M.; Gupta, Satyandra K.; ISRThis paper presents a new and systematic approach to assist decision-making in selecting machining operation sequences. The approach is to produce alternative interpretations of design as different collections of machinable features, use these interpretations to generate alternative machining operation sequences, and evaluate the cost and achievable machining accuracy of each operations sequence. Given the operation sequences and their evaluations, it is then possible to calculate the performance measures of interest, and use these performance measures to select, from among the various alternatives, one or more of them that can best balance the need for a quality product against the need for efficient machining.Item Dynamic Visualization of the Surface Texture Formed During Machining(1991) Zhang, G.M.; Hwang, Tsu-Wei; Song, J.F.; ISRThis paper presents a new methodology to study the properties of machined surfaces. A conceptual framework designed for dynamically visualizing the surface texture formed during machining is proposed. By integrating material science, machining science, and metrology science, the framework provides a systematic approach to investigate the mechanism of surface irregularity formation during machining. Studying the variability of basic material properties in micro-scale and relating this information to the surface texture formation during machining, this research provides a computer-based and comprehensive metrological system for industrial control and diagnostics of the surface quality during machining.