Product Lifecycle Management (PLM) has been identified as a key concept within manufacturing industries for improving product quality, time-to-market and costs. Previous works on this field are focused on processes, functions and information models, and those aimed at putting more intelligence on products are related to specific parts of the product lifecycle (e.g. supply chain management, shop floor control). Therefore, there is a lack of a holistic approach to PLM, putting more intelligence on products through the complete lifecycle. In this paper, a PLM framework supported by a proactive-product approach based on intelligent agents is proposed. The developed model aims at being a first step toward a reference framework for PLM, and complements past works on both product information and business process models (BPM), by putting proactivity on product's behavior. An example of an instantiation of the reference framework is presented as a case study.
Most of the available plan recognition techniques are based on the use of a plan library in order to infer user's intentions and/or strategies. Until some years ago, plan libraries were completely hand coded by human experts, which is an expensive, error prone and slow process. Besides, plan recognition systems with hand-coded plan libraries are not easily portable to new domains, and the creation of plan libraries require not only a domain expert, but also a knowledge representation expert. These are the main reasons why the problem of automatic generation of plan libraries for plan recognition, has gained much importance in recent years. Even when there is considerable work related to the plan recognition process itself, less work has been done on the generation of such plan libraries. In this paper, we present an algorithm for learning hierarchical plan libraries from action sequences, based on a few simple assumptions and with little given domain knowledge, and we provide a novel mechanism for supporting interleaved plans in the input example cases.
Deux dimensions occupent une place importante dans la littérature sur les produits alimentaires depuis plus de vingt ans : la performance de la chaîne logistique et la standardisation de la traçabilité des produits. Dans la chaîne logistique du vin (CLV), ces défis revêtent une importance toute particulière en raison du caractère particulier des processus industriels et logistiques visant une clientèle de gourmets. Pourtant, aucune réponse globale n’est apportée pour l’heure à la mesure de la performance. L’objectif de l’article est de proposer une méthodologie détaillée et des mesures concrètes de performance en lien avec la standardisation de la traçabilité de la CLV, en s’appuyant pour cela sur l’analyse des réseaux sociaux. Ceci doit permettre à chaque membre de la chaîne logistique d’avoir une vision holistique qui accroît la visibilité totale des flux de produits et d’information.
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