Simulation of production scheduling in manufacturing systems

Research into production scheduling environments has been primarily concerned with developing local priority rules for selecting jobs from a queue to be processed on a set of individual machines. Most of the research deals with the scheduling problems in terms of the evaluation of priority rules with respect to given criteria. These criteria have a direct effect on the production cost, such as mean make-span, flow-time, job lateness, m-process inventory and machine idle time. The project under study consists of the following two phases. The first is to deal with the development of computer models for the flow-shop problem, which obtain the optimum make-span and near-optimum solutions for the well-used criteria in the production scheduling priority rules. The second is to develop experimental analysis using a simulation technique, for the two main manufacturing systems, 1. Job-shop 2. Flexible Manufacturing System The two manufacturing types were investigated under the following conditions i. Dynamic problem conditions ii. Different operation time distributions iii. Different shop loads iv. Seven replications per experiment with different streams of random number v. The approximately steady state point for each replication was obtained. In the FMS, the material handling system used was the automated guided Vehicles (AGVs), buffer station and load/ unload area were also used. The aim of these analyses is to deal with the effectiveness of the priority rules on the selected criteria performance. The SIMAN software simulation was used for these studies

Sistema de información para el control, seguimiento y mantenimiento del equipamiento hospitalario

The main purpose of this research is to present a solution that enable to manage efficient and reliable way, all of the information in relation to control, tracking and the hospital equipment maintenance. So, was taken as an object of study of Engineering Department of the Central Hospital of the Air Force of Peru, which presents a lot of administrative deficiencies character in its internal processes of reception, record and closing of Work Orders as well as the preventive and corrective maintenance of the hospital equipment of the HCFAP.The contemplated solution comprises from analysis and design to the development of some use cases more significant of the application.El presente trabajo de investigación tiene como propósito fundamental presentar una solución que permita administrar de forma eficiente y confiable toda la información respecto al control, seguimiento y mantenimiento del equipamiento hospitalario. Para ello se tomó como objeto de estudio al Departamento de Ingeniería del Hospital Central de la Fuerza Aérea del Perú, el cual presenta muchas deficiencias de carácter administrativo en sus procesos internos de recepción, registro y cierre de Órdenes de Trabajo así como el mantenimiento preventivo y correctivo de los equipos hospitalarios del HCFAP. La solución contemplada abarca desde el análisis y diseño hasta el desarrollo de algunos casos de uso más significativos de la aplicación.Tesi

Investigation of a Neural Network Methodology to Predict Transient Performance in Fms

Most rapid analytical evaluative models for Flexible Manufacturing Systems (FMSs) are based on the steady-state performance. There is a practical need to develop robust, easy to construct, and transportable transient-state evaluative models for FMSs. This study proposes an ANN based metamodeling framework that can capture various post disruption system behaviors of FMS. The proposed ANN based meta-modeling scheme consists of a hierarchical taxonomy of mutilple ANNs. Each set of ANNs collectively represents a different part of the underlying system modeling domain. The taxonomical arrangement of multiple ANNs overcomes shortcomings often found in single ANN based meta-modeling schemes. These shortcomings are generally related to the limited knowledge acquisition capability of these schemes. The study uses an Extend based discrete simulation model that is built after an experimental FMS with a limited disruption trigger and handling capabilities. The simulation model is used to study various post-disruption behaviors by a given FMS and to study the feasibility of the proposed modeling scheme as a viable means to provide "lookahead" capability for a low level controller.Findings and Conclusions: The proposed ANN based metamodeling approach using multiple ANNs, in a taxonomically organized modeling structure, is an efficient way to capture multiple target performance index observation processes with a similar overall post-disruption behavior pattern. Despite its accuracy issues, this methodology was proven especially effective when it has to deal with noisy time series such as TIS at observation under a data rich environment. The study is to prove that the proposed methodology could be a viable means to model transient system behaviors. As long as individual observation processes of the selected performance index can keep their variances smaller among themselves, the accuracy of the overall model would be acceptable. This non-parametric performance modeling technique using hierarchically organized multiple ANNs, is worth further investigation.Industrial Engineering & Managemen