Intelligent feature based resource selection and process planning

Lien vers la version éditeur: https://www.inderscience.com/books/index.php?action=record&rec_id=755&chapNum=3&journalID=1022&year=2010This paper presents an intelligent knowledge-based integrated manufacturing system using the STEP feature-based modeling and rule based intelligent techniques to generate suitable process plans for prismatic parts. The system carries out several stages of process planning, such as identification of the pairs of feature/tool that satisfy the required conditions, generation of the possible process plans from identified tools/machine pairs, and selection of the most interesting process plans considering the economical or timing indicators. The suitable processes plans are selected according to the acceptable range of quality, time and cost factors. Each process plan is represented in the tree format by the information items corresponding to their CNC Machine, required tools characteristics, times (machining, setup, preparatory) and the required machining sequences. The process simulation module is provided to demonstrate the different sequences of machining. After selection of suitable process plan, the G-code language used by CNC machines is generated automatically. This approach is validated through a case

Manufacturing Process Modeling and Simulation

This paper presents a methodology to be employed in the whole process design phase including first and second processing. This methodology consists of a set of steps which are characterised by an independent model. This paper’s objective is to analyse the coherence between the different models and the coherence between the model and the objectives of each step. The final stage is to develop the production plans. The casting process was the first one to be analyzed. Casting models were created using CAD software (Catia V5R17) and imported into the casting simulation environment (Magmasoft). Filling and solidifying processes have been simulated using different casting models in order to optimize the final configuration. The machining process was modeled using the machining features concept and it was simulated using Catia’s Advanced Machining environment. Two machining strategies have been analyzed according to positioning strategies. Process engineering software was used to create the process plans and to analyze the resource allocation

Variation propagation of bench vises in multi-stage machining processes

Comunicación presentada a MESIC 2019 8th Manufacturing Engineering Society International Conference (Madrid, 19-21 de Junio de 2019)Variation propagation has been successfully modeled by the Stream of Variation (SoV) approach in multistage machining processes. However, the SoV model basically supports 3-2-1 fixtures based on punctual locators and other workholding systems such as conventional vises are not considered yet. In this paper, the SoV model is expanded to include the fixture- and datum-induced variations on workholding devices such as bench vises. The model derivation is validated through assembly and machining simulations on Computer Aided Design software. The case study analyzed shows an average error of part quality prediction between the SoV model and the CAD simulations of 0.26%

Part Form Errors Predicted from Machine Tool Performance Measurements

Machine tool performance testing, as defined by IS0 230 and ANSI B5.54 has been successfully used to maintain and improve the accuracy and repeatability of production-level machine tools. In this study, a controlled series of experiments have been used to test the efficacy of these performance tests in the prediction of part form errors. Results are shown for flatness, squareness, position, and profile tolerances. The experimental results suggest that standard machine tool performance tests can also be used to predict the “best-case” tolerances that can be achieved for particular part features

Design methodology for smart actuator services for machine tool and machining control and monitoring

This paper presents a methodology to design the services of smart actuators for machine tools. The smart actuators aim at replacing the traditional drives (spindles and feed-drives) and enable to add data processing abilities to implement monitoring and control tasks. Their data processing abilities are also exploited in order to create a new decision level at the machine level. The aim of this decision level is to react to disturbances that the monitoring tasks detect. The cooperation between the computational objects (the smart spindle, the smart feed-drives and the CNC unit) enables to carry out functions for accommodating or adapting to the disturbances. This leads to the extension of the notion of smart actuator with the notion of agent. In order to implement the services of the smart drives, a general design is presented describing the services as well as the behavior of the smart drive according to the object oriented approach. Requirements about the CNC unit are detailed. Eventually, an implementation of the smart drive services that involves a virtual lathe and a virtual turning operation is described. This description is part of the design methodology. Experimental results obtained thanks to the virtual machine are then presented

Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin