New PDF release: Collaborative design and planning for digital manufacturing
By Jay Lee, Linxia Liao, Edzel Lapira, Jun Ni (auth.), Lihui Wang, Andrew Y.C. Nee (eds.)
ISBN-10: 1848822863
ISBN-13: 9781848822863
ISBN-10: 1848822871
ISBN-13: 9781848822870
Collaborative layout has attracted a lot consciousness between researchers in recent times. With more and more decentralized production platforms and methods, extra collaborative techniques are had to aid dispensed production operations.
Collaborative layout and making plans for electronic Manufacturing provides a targeted choice of caliber chapters at the state of the art learn efforts within the region of collaborative layout and making plans, in addition to their sensible functions in the direction of electronic manufacturing.
A diversity of cutting edge equipment and collaborative platforms is analysed, analyzing the rising applied sciences and their useful functions that give a contribution on to electronic production. every one bankruptcy of the publication addresses a selected new method and provides functional strategies for actual situations of collaborative layout and making plans in electronic production. The authors speak about suggestions in a few components, including:
• cross-discipline info sharing;
• workflow management;
• integration of providers right into a procedure chain; and
• functionality measures of allotted production systems.
Collaborative layout and making plans for electronic Manufacturing presents either a broad-based assessment of the most important parts of analysis in electronic production, and an in-depth remedy of specific methodologies and platforms, from collaborative layout to allotted making plans, tracking and keep an eye on. fresh improvement and techniques during this sector offer a pool of concentrated study efforts, correct to a large readership from educational researchers to practicing engineers.
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Additional resources for Collaborative design and planning for digital manufacturing
Example text
Traditionally, tool selection for a specific application is purely heuristic, which is usually not applicable if expert knowledge is lacking, and could be time-consuming for complex problems. In order to automatically benchmark and be able to recommend different tools for various applications, a quality function deployment (QFD) based algorithm selection method is utilised for automatic algorithm selection. 28]. The purpose is to construct the affinity between the user’s requirements or application conditions and the most appropriate tools.
A PC/104 wireless board and PC/104 GPRS (General Packet Radio Service) module can also be selected to equip the integrated hardware platform with wireless and GPRS communication capabilities, if necessary. These communication boards are also connected to the main board with compatible PC/104 extension slots. 12. 13. There are three main agents in this reconfigurable architecture: the system agent (SA), knowledge-database agent (KA) and executive agent (EA), which play important roles in the software reconfiguration process.
For the hardware platform, it is necessary to harvest the developed technologies and standards to enhance interoperability and information security, and to accelerate the deployment of emanufacturing systems in real-world applications. Regarding autonomous prognosis design, a signal characterisation mechanism, which can automatically evaluate some mathematical properties of the input signal, is of great interest to facilitate ‘plug-n-prognose’ with minimum human intervention. The purpose of the signal characterisation mechanism is to cluster identical machine operating conditions that require different prognostics models.
Collaborative design and planning for digital manufacturing by Jay Lee, Linxia Liao, Edzel Lapira, Jun Ni (auth.), Lihui Wang, Andrew Y.C. Nee (eds.)
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