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In recent years car manufacturers have been gradually moving from the procurement of discrete parts to the procurement of modular systems. However, research into this development has not yet sought to identify how such a shift is likely to influence the operations of key suppliers within a modular supply chain and more specifically, how such suppliers are likely to interpret their respective ap...

Three issues have deeply influenced the Canadian automobile industry in the last decades. Proliferation of models and vehicle-types has reduced the average sales per vehicle with important consequences on the manufacturing side. Manufacturers have responded by adopting flexible production technology in their assembly plants. One of the most important features of the flexible technology is the a...

We formulate a structural econometric model to analyze the impact of service attributes (warranty length, after-sales service quality) on consumer demand in the U.S.automobile industry. Our results indicate that service attributes play a compensatory role with respect to product quality, i.e., the impact of warranty length and service quality on demand increases when product quality decreases. ...

the critical success factors (csfs) of knowledge management (km) systems are considered as areas that must be given the required attention for the successful implementation of knowledge management. in this respect and to reduce the failure risk of knowledge management projects, the current paper aims to arrive at a conceptual model by identifying and prioritizing factors for guiding research in...

Present time the main issue of automobile industry are weight reduction. The automobile industry has looking for any implementation or modification to reduce the weight of the vehicle. The suspension leaf spring is one of the potential items for weight reduction in automobile as it accounts for 10% to 20% of the unsprung weight. The introduction of composite leaf spring made of glass fiber rein...

Increasing pressure on companies in the modern automobile industry creates a need for constant development and cost effectiveness. One major part of this process is the management of human factors. In this paper we discuss the effects of human factors on production performance with artificial neural networks.

We present a unified multi-agent technology for decision making support in production planning and scheduling, manufacturing simulation in and supply chain management. The technology has been tested on several industrial cases and is used in a daily production planning processes of one important automobile industry supplier in the Czech Republic.