934 resultados para advanced control technology
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Issued Jan. 1977.
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Issued April 1978.
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Issued Dec. 1978.
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"Prepared in response to requirements of Section 144(a)--to Public Law 95-604 U.S. Dept. of Energy."
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"DOE/EV-0078."
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"DOE/EV-0083."
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"DOE/EV-0092."
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"DOE/EV/01621-T1."
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"UC-11."
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Contract no. DE-AM-03-76SF0015.
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"Document no. ARA-1026 [etc.]."
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This paper challenges current practices in the use of digital media to communicate Australian Aboriginal knowledge practices in a learning context. It proposes that any digital representation of Aboriginal knowledge practices needs to examine the epistemology and ontology of these practices in order to design digital environments that effectively support and enable existing Aboriginal knowledge practices in the real world. Central to this is the essential task of any new digital representation of Aboriginal knowledge to resolve the conflict between database and narrative views of knowledge (L. Manovich, 2001). This is in order to provide a tool that complements rather than supplants direct experience of traditional knowledge practices (V. Hart, 2001). This paper concludes by reporting on the recent development of an advanced learning technology that addresses this.
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This paper reports on the results of research into the connections between transaction attributes and buyer-supplier relationships (BSRs) in advanced manufacturing technology (AMT) acquisition and implementation. The investigation began by examining the impact of the different patterns of BSR on the performance of the AMT acquisition. In understanding the phenomena, the study drew upon and integrated the literature of transaction cost economics theory, BSRs, and AMT, and used this as the basis for a theoretical framework and hypotheses development. This framework was then empirically tested using data that were gathered through a questionnaire survey with 147 companies and analyzed using a structural equation modeling technique. The results of the analysis indicated that the higher the level of technological specificity and uncertainty, the more firms are likely to engage in a stronger relationship with technology suppliers. However, the complexity of the technology being implemented was associated with BSR only indirectly through its association with the level of uncertainty (which has a direct impact upon BSR). The analysis also provided strong support for the premise that developing strong BSR could lead to an improved performance in acquiring and implementing AMT. The implications of the study are offered for both the academic and practitioner audience.
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This paper presents two hybrid genetic algorithms (HGAs) to optimize the component placement operation for the collect-and-place machines in printed circuit board (PCB) assembly. The component placement problem is to optimize (i) the assignment of components to a movable revolver head or assembly tour, (ii) the sequence of component placements on a stationary PCB in each tour, and (iii) the arrangement of component types to stationary feeders simultaneously. The objective of the problem is to minimize the total traveling time spent by the revolver head for assembling all components on the PCB. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method, the nearest neighbor heuristic, and the neighborhood frequency heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different population sizes. It is proved that the performance of HGA2 is superior to HGA1 in terms of the total assembly time.
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A chip shooter machine in printed circuit board (PCB) assembly has three movable mechanisms: an X-Y table carrying a PCB, a feeder carrier with several feeders holding components and a rotary turret with multiple assembly heads to pick up and place components. In order to get the minimal placement or assembly time for a PCB on the machine, all the components on the board should be placed in a perfect sequence, and the components should be set up on a right feeder, or feeders since two feeders can hold the same type of components, and additionally, the assembly head should retrieve or pick up a component from a right feeder. The entire problem is very complicated, and this paper presents a genetic algorithm approach to tackle it.