2 resultados para Random lead times and bulk demands

em Aston University Research Archive


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From a manufacturing perspective, the efficiency of manufacturing operations (such as process planning and production scheduling) are the key element for enhancing manufacturing competence. Process planning and production scheduling functions have been traditionally treated as two separate activities, and have resulted in a range of inefficiencies. These include infeasible process plans, non-available/overloaded resources, high production costs, long production lead times, and so on. Above all, it is unlikely that the dynamic changes can be efficiently dealt with. Despite much research has been conducted to integrate process planning and production scheduling to generate optimised solutions to improve manufacturing efficiency, there is still a gap to achieve the competence required for the current global competitive market. In this research, the concept of multi-agent system (MAS) is adopted as a means to address the aforementioned gap. A MAS consists of a collection of intelligent autonomous agents able to solve complex problems. These agents possess their individual objectives and interact with each other to fulfil the global goal. This paper describes a novel use of an autonomous agent system to facilitate the integration of process planning and production scheduling functions to cope with unpredictable demands, in terms of uncertainties in product mix and demand pattern. The novelty lies with the currency-based iterative agent bidding mechanism to allow process planning and production scheduling options to be evaluated simultaneously, so as to search for an optimised, cost-effective solution. This agent based system aims to achieve manufacturing competence by means of enhancing the flexibility and agility of manufacturing enterprises.

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Predicting future need for water resources has traditionally been, at best, a crude mixture of art and science. This has prevented the evaluation of water need from being carried out in either a consistent or comprehensive manner. This inconsistent and somewhat arbitrary approach to water resources planning led to well publicised premature developments in the 1970's and 1980's but privatisation of the Water Industry, including creation of the Office of Water Services and the National Rivers Authority in 1989, turned the tide of resource planning to the point where funding of schemes and their justification by the Regulators could no longer be assumed. Furthermore, considerable areas of uncertainty were beginning to enter the debate and complicate the assessment It was also no longer appropriate to consider that contingencies would continue to lie solely on the demand side of the equation. An inability to calculate the balance between supply and demand may mean an inability to meet standards of service or, arguably worse, an excessive provision of water resources and excessive costs to customers. United Kingdom Water Industry Research limited (UKWlR) Headroom project in 1998 provided a simple methodology for the calculation of planning margins. This methodology, although well received, was not, however, accepted by the Regulators as a tool sufficient to promote resource development. This thesis begins by considering the history of water resource planning in the UK, moving on to discuss events following privatisation of the water industry post·1985. The mid section of the research forms the bulk of original work and provides a scoping exercise which reveals a catalogue of uncertainties prevalent within the supply-demand balance. Each of these uncertainties is considered in terms of materiality, scope, and whether it can be quantified within a risk analysis package. Many of the areas of uncertainty identified would merit further research. A workable, yet robust, methodology for evaluating the balance between water resources and water demands by using a spreadsheet based risk analysis package is presented. The technique involves statistical sampling and simulation such that samples are taken from input distributions on both the supply and demand side of the equation and the imbalance between supply and demand is calculated in the form of an output distribution. The percentiles of the output distribution represent different standards of service to the customer. The model allows dependencies between distributions to be considered, for improved uncertainties to be assessed and for the impact of uncertain solutions to any imbalance to be calculated directly. The method is considered a Significant leap forward in the field of water resource planning.