摘要:

A steady state control algorithm has been developed. The algorithm is based on steady-state process models, established and used to provide algebraic control models. The control model can be applied for on-line computation of new levels of aluminium turning process control variables required to compensate for detected errors in the controlled variables. Workability of the developed control algorithm and its performance are evaluated by computer simulation. Although the control methodology is developed for an aluminium turning process, it is general and can be applied to any machining process.

ISSN:0020-7543    

DOI:10.1080/00207549208942901

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

One of the important elements of strategic management is to establish resource levels over the long run—capacity planning. More specifically, managers are faced with the need to determine resource levels that are sufficient to meet corporate objectives and remain competitive; and, yet, not excessive. This research has explored the relationship between ten different availability levels of resources in a constrained, multiple resource environment and their impact on project completion times and promise date performance measures. It also evaluated four finite scheduling heuristics which use a finite scheduling system and are used to estimate and, then, meet a project's completion date in the dynamic, multi-project environment. As a part of the discussion we examine the tradeoff between project completion times and resource availability levels. This research has found that (1) three of the four tested finite scheduling heuristics can produce/meet very good promise dates; (2)-resources do not need to be provided in quantities that exceed 160% of system requirements; (3) when resources are provided at the 130% or greater level, all four heuristics perform equally well with regard to completion times, and complete projects at less than one and a half times a project's critical path time; and (4) when resources are greatly constrained (110% to 130%) the effects are significant and the choice of heuristic is very important.

ISSN:0020-7543    

DOI:10.1080/00207549208942902

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor

摘要:

Dynamic selection of scheduling rules during real operations has been recognized as a promising approach to the scheduling of the production line. For this strategy to work effectively, sufficient knowledge is required to enable prediction of which rule is the best to use under the current line status. In this paper, a new learning algorithm for acquiring such knowledge is proposed. In this algorithm, a binary decision tree is automatically generated using empirical data obtained by iterative production line simulations, and it decides in real time which rule to be used at decision points during the actual production operations. The configuration of the developed dynamic scheduling system and the learning algorithm are described in detail. Simulation results on its application to the dispatching problem are discussed with regard to its scheduling performance and learning capability.

ISSN:0020-7543    

DOI:10.1080/00207549208942903

出版商:Taylor & Francis Group    

年代:1992

数据来源: Taylor