A disputa pelo financiamento de veículos no Brasil: como prevalecer em um mercado competitivo do ponto de vista de um banco de montadora

Trata de analisar o mercado de financiamento de veículos no Brasil, que vem se mostrando cada vez mais competitivo devido à entrada de novos bancos, especialmente os estrangeiros. Aborda o mercado sob a perspectiva do Banco Ford, avaliando seu potencial de crescimento e as possibilidades de manutenção do market share frente a uma competição cada vez mais sofisticada.

Auto safety: effectiveness of Ford Transmission settlement still at issue.

Mode of access: Internet.

Requests by General Motors and Ford to reduce fuel economy standards for MY 1981-85 passenger automobiles. Report.

Mode of access: Internet.

Safety systems optimization model (SSOM). Final report. Volume 1 - introduction and executive summary.

National Highway Traffic Safety Administration, Washington, D.C.

Implementation cost to consumers of Part 581 - Bumper Standard, Phase II; weight and cost study of three "X" body bumper systems; and consumer replacement cost for complete bumper systems studied. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Ford news.

Description based on: Vol. 15, no. 8 (Aug. 1935); title from cover.

Ford times.

"The Ford owner's magazine."

Ford documents and photographs, and exhibit.

Mode of access: Internet.

Innovative chemical supply contracts : a source of competitive advantage /

"September 1997."

Survey of university industrial relations centers, Fall, 1954.

Mode of access: Internet.

Knowledge based improvement:simulation and artificial intelligence for identifying and improving human decision-making in an operations systems

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

Simulation based knowledge elicitation:effect of visual representation and model parameters

Since much knowledge is tacit, eliciting knowledge is a common bottleneck during the development of knowledge-based systems. Visual interactive simulation (VIS) has been proposed as a means for eliciting experts’ decision-making by getting them to interact with a visual simulation of the real system in which they work. In order to explore the effectiveness and efficiency of VIS based knowledge elicitation, an experiment has been carried out with decision-makers in a Ford Motor Company engine assembly plant. The model properties under investigation were the level of visual representation (2-dimensional, 2½-dimensional and 3-dimensional) and the model parameter settings (unadjusted and adjusted to represent more uncommon and extreme situations). The conclusion from the experiment is that using a 2-dimensional representation with adjusted parameter settings provides the better simulation-based means for eliciting knowledge, at least for the case modelled.

Humans:the missing link in manufacturing simulation?

Computer based discrete event simulation (DES) is one of the most commonly used aids for the design of automotive manufacturing systems. However, DES tools represent machines in extensive detail, while only representing workers as simple resources. This presents a problem when modelling systems with a highly manual work content, such as an assembly line. This paper describes research at Cranfield University, in collaboration with the Ford Motor Company, founded on the assumption that human variation is the cause of a large percentage of the disparity between simulation predictions and real world performance. The research aims to improve the accuracy and reliability of simulation prediction by including models of human factors.