AMPROS is a project which aims to study and develop a middleware-based platform for mobile environments. AMPROS provides a distributed, just-in-time, and contextaware deployment of component-based applications. The deployment adaptation is carried out by a set of adaptive components able to vary the architecture of the application as well as the attributes of its components. In this paper we de...

Low inventory, a crucial part of just-in-time (JIT) manufacturing systems, enjoys increasing application worldwide, yet the behavioral effects of such systems remain largely unexplored. Operations research (OR) models of low-inventory systems typically use a simplifying assumption that processing times of individual workers are independent random variables. This leads to predictions that low-in...

In this paper, the authors discuss the evolution of automobile market creation employing a “Total Marketing System” (TMS)as a core technology of New JIT, which contributes to constructing a Scientific Mixed Media Model (SMMM)for boosting automobile dealer visits. More concretely, the authors develop and validate the effectiveness of putting together four core elements (Video that Unites Custome...

In today’s competitive global markets, Just-in-Time (JIT) is one of the main lean manufacturing approaches. It is used in organizations to improve performance and reduce costs and as a strategic core capability to ensure their market position. However, using JIT tightly couples various functions of the Supply Chain and increases the risk of propagating disruptions through the entire system. Thi...

Indian industries are in the process of implementing best production practices of Supply Chain Management (SCM), Just in Time (JIT) and Total Quality Management (TQM). These practices are being applied in isolation and collectively in different combinations. The integration of these practices is a major issue which this paper will try to address. Models of these practices as applicable to indus...

MIRROR PLANT uses physical plant modeling based on physical and chemical laws. However, the physical model cannot express some phenomena in plants, especially those which are not physically determined yet. We propose a hybrid model of a physical model and a statistical model based on historical plant operation data. Combining the physical model and statistical model improves the estimation accu...