An improved approach for automatic process plan generation of complex borings

The authors are grateful for funding provided to this project by the French Ministry of Industry, Dassault Aviation, Dassault Systemes, and F. Vernadat for his review and recommendations.The research concerns automated generation of process plans using knowledge formalization and capitalization. Tools allowing designers to deal with issues and specifications of the machining domain are taken into account. The main objective of the current work is to prevent designers from designing solutions that would be expensive and difficult to machine. Among all available solutions to achieve this goal, two are distinguished: the generative approach and the analogy approach. The generative approach is more adapted to generate the machining plans of parts composed of numerous boring operations in interaction. However, generative systems have two major problems: proposed solutions are often too numerous and are only geometrically but not technologically relevant. In order to overcome these drawbacks, two new concepts of feature and three control algorithms are developed. The paper presents the two new features: the Machining Enabled Geometrical Feature (MEGF) and the Machinable Features (MbF). This development is the result of the separation of the geometrical and the technological data contained in one machining feature. The second objective of the paper is to improve the current Process Ascending Generation (PAG) system with control algorithms in order to limit the combinatorial explosion and disable the generation of unusable or not machinable solutions

An approach to model and manage cost-risk trade-off in Networked Manufacturing

Le présent article introduit une évaluation du risque dans la planification des systèmes manufacturiers, impliquant différents acteurs travaillant séquentiellement pour réaliser un produit. Nous considérons ici un environnement dynamique virtuel, où différentes firmes soumissionnent pour des taches précises. L’approche traditionnelle est d’assigner des firmes à des taches pour minimiser les coûts d’utilisation de la chaîne. Cette approche néglige ainsi la notion de fiabilité et de risque. L’objectif de cet article est de proposer une façon d’incorporer la notion de risque au processus de planification de la chaîne. Nous avons identifié le risque comme une combinaison de trois principaux intrants, et nous l’évaluons grâce à une approche dérivée de la logique floue. Nous décrivons comment fonctionne notre programme, et comment le risque évalué est utilisé pour établir quelles firmes choisir afin d’optimiser le compromis coût-risque.This paper introduces elements of risk into supply-chain manufacturing systems that involve various actors acting sequentially to achieve an end-result. We consider a virtual dynamic environment, where different firms bid on sequential tasks. The traditional approach has been to assign tasks to firms, in order to realize production as cost-effective chains of activities. This approach neglects elements of risk, which we show how to incorporate. We have identified risk as a combination of three inputs, using a fuzzy logic approach. We show how a fuzzy controller can measure the risk involved in a supply-chain, which is constructed on an order-contract basis. We use this measure of risk to build a decision support environment that helps isolate alternative supply-chains that are potentially interesting from a cost perspective and compares them from a risk minimization stand point.

An improved approach for automatic process plan generation of complex borings

The authors are grateful for funding provided to this project by the French Ministry of Industry, Dassault Aviation, Dassault Systemes, and F. Vernadat for his review and recommendations.The research concerns automated generation of process plans using knowledge formalization and capitalization. Tools allowing designers to deal with issues and specifications of the machining domain are taken into account. The main objective of the current work is to prevent designers from designing solutions that would be expensive and difficult to machine. Among all available solutions to achieve this goal, two are distinguished: the generative approach and the analogy approach. The generative approach is more adapted to generate the machining plans of parts composed of numerous boring operations in interaction. However, generative systems have two major problems: proposed solutions are often too numerous and are only geometrically but not technologically relevant. In order to overcome these drawbacks, two new concepts of feature and three control algorithms are developed. The paper presents the two new features: the Machining Enabled Geometrical Feature (MEGF) and the Machinable Features (MbF). This development is the result of the separation of the geometrical and the technological data contained in one machining feature. The second objective of the paper is to improve the current Process Ascending Generation (PAG) system with control algorithms in order to limit the combinatorial explosion and disable the generation of unusable or not machinable solutions

Supply chain operational transport planning by using an interactive fuzzy multi-objective linear programming approach

[EN] In this paper, we propose a new fuzzy multi-objective linear programming model (FMOLP) for the supply chain operational transport planning problem that considers simultaneously the fuzziness in the aspiration levels and uncertainty in some critical parameters such as transport capacity levels. We also present an interactive solution methodology to convert this FMOLP model into an auxiliary crisp single-objective linear model and to find a preferred compromise solution in an interactive fashion. We validated the proposed model and the solution methodology with a real-world automobile supply chain. The experimental results indicate that the proposed approach outperforms the heuristic decision-making procedure applied in the automobile supply chain under study.[ES] En este trabajo se propone un modelo de programación lineal fuzzy multiobjetivo (PLFMO) para la planificación operativa del transporte que considera simultáneamente la borrosidad en los niveles de aspiración del planificador y en ciertos parámetros críticos como son los niveles de capacidad del transporte. Asimismo, se presenta una metodología de resolución para convertir el modelo de PLFMO en un modelo monoobjetivo lineal auxiliar equivalente y encontrar una solución de compromiso de forma interactiva. Se validan el modelo y la metodología de resolución en una cadena de suministro CS real del sector del automóvil. Por último, los resultados obtenidos muestran la mejora aportada por el modelo propuesto respecto al procedimiento heurístico para la toma de decisiones empleado actualmente en la CS.Este trabajo está financiado por el Proyecto Nacional del Ministerio de Ciencia e Innovación (MiCiNN) del Gobierno Español titulado: Tecnología de producción basada en la realimentación de decisiones de planificación de producción, transporte y descargas y el rediseño de almacenes en cadena de suministro (REVOLUTION) (Ref. DPI2010-19977).Díaz-Madroñero Boluda, FM.; Peidro Payá, D.; Mula, J. (2012). Planificación operativa del transporte en una cadena de suministro mediante un enfoque interactivo de programación lineal fuzzy multiobjetivo. Dirección y Organización. (46):31-44. http://hdl.handle.net/10251/35961S31444

Modeling the Crude Oil Scheduling Problem with Integration with Lower Level Production Optimization and Uncertainty

This research is focused on the modeling and optimization of the crude oil scheduling problem in order to generate the most appropriate schedule for the unloading, charging, blending, and movement of crude oil in a refinery, which means obtaining the schedule that generates the lowest costs. Uncertainty, which is often present in these types of optimization problems, is also analyzed and taken into account for the resolution of crude oil scheduling problem. A comprehensive novel model is proposed to describe the upper level crude oil scheduling problem, generate an optimal solution for the mentioned problem, and allow integration with the lower level production optimization problem of a refinery. This integration is possible due to the consideration of total flows of the different types of crude oil instead of flows of a particular key component in the crude oil to linearize the upper level problem and generate a less complex model. The proposed approach incorporates all the logistical costs including the sea waiting, unloading and inventory costs together with the costs associated with the transfer of crude oil from one to another entity. Moreover, this model also offers the possibility of considering multiple tank types including storage and blending tanks throughout the supply chain and the incorporation of the capability of storing more than one crude oil type in the storage tanks during the schedule horizon. A comparative analysis is performed against other models proposed and preliminary results of integration with a lower operational level are provided. In order to take into account the possibility of uncertainty or fuzziness in the scheduling problem, for the first time an approach is proposed to face the resolution of this problem in order to obtain a more realistic scheduling of the allocations of crude oil. Fuzzy linear programming theory is used here to represent this uncertainty in order to find an optimal solution that takes into account the lack of precise information on the part of the decision maker without losing the linearity of the original system. Uncertainty in the minimum demand to be satisfied in the distillation unit according to the necessities of the market and the lack of precise information about certain costs involved in the operations throughout the supply chain are separately considered. Among the different approaches utilized in fuzzy linear programming, the flexible programming or Zimmermann method and its extension to fuzziness in objective functions are implemented. A comparison between the two cases studied and the crisp model is performed with the aim of determining the effect of these uncertainties in the schedule of the crude oils movements between the different entities in the supply chain and the total cost generated

Strategic development in the petrochemical industry

Imperial Users onl

A model-based methodology for managing technological risk

Imperial Users onl