Development of an Integrated Approach to the Design of Reconfigurable Micro/Mesoscale CNC Machine Tools

Pérez, Roberto; Molina, Arturo; Ramírez-Cadena, Miguel

doi:10.1115/1.4025405

Cited by 25 publications

(8 citation statements)

References 14 publications

(15 reference statements)

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“…In this research the technologies for sensing resources used are RFID, WSN and Real-time networked systems [18]. For smart resources: Machines, AGVs, Robots, PLCs, CNCs with Intelligent Control systems based on Fuzzy logic and Artificial Organic Networks [19,20].…”

Section: Fig 2 S 2 -Reference Model: Models Methodologies and Toolsmentioning

confidence: 99%

Designing a S2-Enterprise (Smart x Sensing) Reference Model

Molina

Ponce

Ramírez

et al. 2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Part 11: Reference and Conceptual ModelsInternational audienceThe definition of the concept of S2-Enterprise (Smart x Sensing) reference model is presented. The S2 Reference Model (S2-RM) is targeted to assist in the system specification and development of future computer based systems, which support the creation of this concept. It is a hybrid reference model that includes Enterprise Integration Engineering Concepts and Interoperability models. The Reference Model for Open Distributed Processing or RM-ODP is used as the basis to define S2-RM because it allows the definition of the structure and characteristic of the Smart and Sensing systems in terms of five different views (enterprise, information, computational, engineering and technology). The importance of using reference models for the definition, design and implementation of S2-Enterprise systems is outlined. A pilot system has been developed using a micro-factory concept and a collaborative networked organization

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Section: Fig 2 S 2 -Reference Model: Models Methodologies and Toolsmentioning

confidence: 99%

Designing a S2-Enterprise (Smart x Sensing) Reference Model

Molina

Ponce

Ramírez

et al. 2014

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Self Cite

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“…Namely, for the tool to move with a speed of 3 m/min, the actuator speed would need to be ~30 m/min. Although design methodologies for RmMTs have been pre sented [31], design methodologies for Redundant Reconfigurable meso-Milling Machine Tools (RRmMTs) have not been reported in the literature. Therefore, the viability of the proposed design methodology is demonstrated herein via the design test case of a new PKM-based RRmMT that can attain the high feed-rates required in meso-milling.…”

Section: Meso-millingmentioning

confidence: 99%

A Multi-Tier Design Methodology for Reconfigurable Milling Machines

Azulay

Mills

Benhabib

2014

Journal of Manufacturing Science and Engineering

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Reconfigurable Machine Tools (RMTs) have been developed in response to agile flexible manufacturing demands. Current design methodologies fo r RMTs support modular reconfigurability in which a machine configuration is assembled fo r a given part. In this paper, on the other hand, reconfigurability relies on redundancy, namely, a desired RMT configuration is obtained through topological reconfiguration by locking!unlocking degrees-of-freedom (dof). Thus, in order to design a Redundant Reconfigurable Machine Tool (RRMT) with all o f its d of already included, a new multi-tier optimization based design methodology was developed. The design is formulated fo r the efficient selection o f the best architecture from a set o f serial!parallel!hybrid solutions, while considering the redundant reconfigurability effect on performance. The viability o f the methodology is demonstrated herein via a design test case o f a Parallel Kinematic Mechanism (PKM)-based Redundant Reconfigurable meso-Milling Machine Tool (RRmMT) that can attain high stiffness at the high feed-rate required in meso-milling.

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“…NC machine tool is the significant production basis or fundamental unit of other equipment in manufacturing industry; thus the reliability of NC machine tool will seriously influence or restrict the development of manufacturing industry [1][2][3]. Ball screw, the key component of NC machine tool, is directly related to the reliability of NC machine tool.…”

Section: Introductionmentioning

confidence: 99%

Screw Remaining Life Prediction Based on Quantum Genetic Algorithm and Support Vector Machine

Zhang

Jiang

2017

Shock and Vibration

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To predict the remaining life of ball screw, a screw remaining life prediction method based on quantum genetic algorithm (QGA) and support vector machine (SVM) is proposed. A screw accelerated test bench is introduced. Accelerometers are installed to monitor the performance degradation of ball screw. Combined with wavelet packet decomposition and isometric mapping (Isomap), the sensitive feature vectors are obtained and stored in database. Meanwhile, the sensitive feature vectors are randomly chosen from the database and constitute training samples and testing samples. Then the optimal kernel function parameter and penalty factor of SVM are searched with the method of QGA. Finally, the training samples are used to train optimized SVM while testing samples are adopted to test the prediction accuracy of the trained SVM so the screw remaining life prediction model can be got. The experiment results show that the screw remaining life prediction model could effectively predict screw remaining life.

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Development of an Integrated Approach to the Design of Reconfigurable Micro/Mesoscale CNC Machine Tools

Cited by 25 publications

References 14 publications

Designing a S2-Enterprise (Smart x Sensing) Reference Model

Designing a S2-Enterprise (Smart x Sensing) Reference Model

A Multi-Tier Design Methodology for Reconfigurable Milling Machines

Screw Remaining Life Prediction Based on Quantum Genetic Algorithm and Support Vector Machine

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