Manufacturing planning and control in small companies A contribution to the application of 'scientific' methods in small business with the help of microcomputers

2 volsAvailable from British Library Document Supply Centre- DSC:DX83447 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

An Empirical Investigation of Lead Time Distributions

Part 2: Knowledge Discovery and SharingInternational audienceThis paper proposes a methodology for analyzing lead time behavior. The method focuses on identifying whether lead times are in fact identically independently distributed (i.i.d.). The method uses a combination of time series analysis, Kolmogorov-Smirnov’s test for similar distributions and data sampling to arrive at its result. The method is applied to data obtained from a manufacturing company. The conclusions are that while the lead time to customers can for some products be assumed to be i.i.d. this is not uniformly true. Some products’ lead times are in fact neither independently nor identically distributed

Collaborative Tactical Planning in Multi-level Supply Chains Supported by Multiagent Systems

International audienceIn the supply chain modeling context, the agent-based model aims to represent not only each node, but also the information sharing process among these nodes. Despite the complexity of the configuration, the agent-based model can be applied straightforwardly to support the collaborative planning process. This allows the parties to achieve common goals effectively. Thus by sharing accurate, action-based information, collaboration among the nodes will emerge to improve the decision-making process in supply chain planning processes. Therefore, this paper presents a novel collaborative planning model in multi-level supply chains that considers a multiagent system modeling approach to carry out the iterative negotiation processes which will support the decision-making process from a decentralized perspective

A multi-criteria decision-making analysis for the selection of fibres aimed at reinforcing asphalt concrete mixtures

In the last few years, fibers have been proposed as one of the most important additives for the development of reinforced asphalt mixtures. The optimal fiber selection is a very complex task, as an extensive range of criteria and alternatives have to be taken into account. Decision support systems have been applied in the construction sector, but not for selecting fibers for bituminous mixtures. To fill this gap, two Multi-Criteria Decision-Making Analysis methodologies for the selection of the best fiber to be used in Asphalt Concretes are presented in this paper. The Weighted Aggregate Sum Product Assessment (WASPAS) methodology and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) integrated with Fuzzy Analytic Hierarchy Process (FAHP) are used to evaluate the effect of various types of fibers on the mechanical performance of bituminous mixtures. Given the uncertainty involved, a stochastic simulation is proposed using the Monte Carlo method. A statistical analysis is carried out to verify the results obtained. Both methods of multi-criteria analysis were effective, with TOPSIS being slightly more conservative in the assignment of performance scores. Synthetic fibers proved to be a suitable option as did fibers with high tensile strength and elastic modulus