Coal handling machinery, designed and manufactured by C.W. Hunt company, New York ...

At head of title: No. 9306.

An effective heuristic for stockyard planning and machinery scheduling at a coal handling facility

Coal handling is a complex process involving different correlated and highly dependent operations such as selecting appropriate product types, planning stockpiles, scheduling stacking and reclaiming activities and managing train loads. Planning these operations manually is time consuming and can result in non-optimized schedules as future impact of decisions may not be appropriately considered. This paper addresses the operational scheduling of the continuous coal handling problem with multiple conflicting objectives. As the problem is NP-hard in nature, an effective heuristic is presented for planning stockpiles and scheduling resources to minimize delays in production and the coal age in the stockyard. A model of stockyard operations within a coal mine is described and the problem is formulated as a Bi- Objective Optimization Problem (BOOP). The algorithm efficacy is demonstrated on different real-life data scenarios. Computational results show that the solution algorithm is effective and the coal throughput is substantially impacted by the conflicting objectives. Together, the model and the proposed heuristic, can act as a decision support system for the stockyard planner to explore the effects of alternative decisions, such as balancing age and volume of stockpiles, and minimizing conflicts due to stacker and reclaimer movements.

Longwall coal cutting machinery;

Mode of access: Internet.

Coal handling and stowage.

Chapter 54 of the Bureau of ships manual.

Operating characteristics of pneumatic grain conveyors /

Cover title.

Performance of auger conveyors for farm feed materials at restricted delivery rates /

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A vibrator-powered meter for small grain and ground feed /

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Volumetric feed meters : their performance for automatic feeding systems /

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The Elements of mining engineering [microform] /

Includes indexes.

Neural bruise prediction models for fruit handling and machinery evaluation.

Some neural bruise prediction models have been implemented in the laboratory, for the most traded fruit species and varieties, allowing the prediction of the acceptability or rejectability for damages, with respect to the EC Standards. Different models have been built for both quasi-static (compression) and dynamic (impact) loads covering the whole commercial ripening period of fruits. A simulation process has been developed gathering the information on laboratory bruise models and load sensor calibrations for different electronic devices (IS-100 and DEA-1, for impact and compression loads respectively). Some evaluation methodology has been designed gathering the information on the mechanical properties of fruits and the loading records of electronic devices. The evaluation system allows to determine the current stage of fruit handling process and machinery.