Self-organization for scheduling in agile manufacturing

Agility refers to the manufacturing system ability to rapidly adapt to market and environmental changes in efficient and cost-effective ways. This paper addresses the development of self-organization methods to enhance the operations of a scheduling system, by integrating scheduling system, configuration and optimization into a single autonomic process requiring minimal manual intervention to increase productivity and effectiveness while minimizing complexity for users. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to build future Decision Support Systems (DSS) for Scheduling in agile manufacturing environments.

On-line self-healing of circuits implemented on reconfigurable FPGAs

To boost logic density and reduce per unit power consumption SRAM-based FPGAs manufacturers adopted nanometric technologies. However, this technology is highly vulnerable to radiation-induced faults, which affect values stored in memory cells, and to manufacturing imperfections. Fault tolerant implementations, based on Triple Modular Redundancy (TMR) infrastructures, help to keep the correct operation of the circuit. However, TMR is not sufficient to guarantee the safe operation of a circuit. Other issues like module placement, the effects of multi- bit upsets (MBU) or fault accumulation, have also to be addressed. In case of a fault occurrence the correct operation of the affected module must be restored and/or the current state of the circuit coherently re-established. A solution that enables the autonomous restoration of the functional definition of the affected module, avoiding fault accumulation, re-establishing the correct circuit state in real-time, while keeping the normal operation of the circuit, is presented in this paper.

A marcha: a influência do Gerador de Padrão Central

A marcha é influenciada por um conjunto de factores que resultam da interacção e organização própria de sistemas neurais e mecânicos, entre os quais, da dinâmica músculo-esquelética, da modulação pelos centros nervosos superiores, pela modulação aferente e é, também, assumida como sendo controlada pelo Gerador de Padrão Central (GPC), que se define como um programa central baseado num circuito espinal geneticamente determinado, capaz de produzir um ritmo associado a cada marcha. Apresenta-se como objectivo deste trabalho abordar quais os modelos explicativos para o funcionamento do GPC e qual a evidência científica, que continua a ter muitas divergências.

A marcha: a influência do Gerador de Padrão Central

A marcha é influenciada por um conjunto de factores que resultam da interacção e organização própria de sistemas neurais e mecânicos, entre os quais, da dinâmica músculo-esquelética, da modulação pelos centros nervosos superiores, pela modulação aferente e é, também, assumida como sendo controlada pelo Gerador de Padrão Central (GPC), que se define como um programa central baseado num circuito espinal geneticamente determinado, capaz de produzir um ritmo associado a cada marcha. Apresenta-se como objectivo deste trabalho abordar quais os modelos explicativos para o funcionamento do GPC e qual a evidência científica, que continua a ter muitas divergências.

Self-similarity principle: the reduced description of randomness

A new general fitting method based on the Self-Similar (SS) organization of random sequences is presented. The proposed analytical function helps to fit the response of many complex systems when their recorded data form a self-similar curve. The verified SS principle opens new possibilities for the fitting of economical, meteorological and other complex data when the mathematical model is absent but the reduced description in terms of some universal set of the fitting parameters is necessary. This fitting function is verified on economical (price of a commodity versus time) and weather (the Earth’s mean temperature surface data versus time) and for these nontrivial cases it becomes possible to receive a very good fit of initial data set. The general conditions of application of this fitting method describing the response of many complex systems and the forecast possibilities are discussed.