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This paper deals with the conceptual design and development of an enterprise modeling and integration framework using knowledge discovery and data mining. First, the paper briefly presents the background and current state-of-the-art of knowledge discovery in databases and data mining systems and projects. Next, enterprise knowledge engineering is dealt with. The paper suggests a novel approach of utilizing existing enterprise reference architectures, integration and modeling frameworks by the introduction of new enterprise views such as mining and knowledge views. An extension and a generic exploration of the information view that already exists within some enterprise models are also proposed. The Zachman Framework for Enterprise Architecture is also outlined versus the existing architectures and the proposed enterprise framework. The main contribution of this paper is the identification and definition of a common knowledge enterprise model which represents an original combination between the previous pro...

Batch sizes have a considerable impact on the performance of a manufacturing process. Determining optimal values for batch sizes helps to reduce inventories/costs and lead times. The deterministic nature of the available batch size optimisation models reduces the practical value of the obtained solutions. Other models focus only on critical parts of the system (e.g., the bottleneck). In this paper, we present an approach that overcomes important limitations of such simplified solutions. We describe a combination of queueing network analysis and a genetic algorithm that allows us to take into account the real characteristics of the system when benefiting from an efficient optimisation mechanism. We are able to demonstrate that the application of our approach on a real-sized problem with 49 products allows us to obtain a solution (values for batch sizes) with less than 4% relative deviation of the cycle time from the exact minimal value.

Managing coalition networks of organisations is gradually becoming more complex and challenging as the current trends of the market conditions are becoming more dynamic. The dynamism nature is experienced in many aspects including: advances in technologies, rising demand of resources for each opportunity, growing volatility of opportunities, and so forth. Owing to advances in digital technology, emerging breakthrough solutions responding to market needs are becoming increasingly innovative and complex. A large amount of resources, competencies, skills, etc. are required to accomplish such solutions, usually beyond capabilities and capacities of a single organisation. The emergence of coalition networks of organisations as breeding environments for creation of temporary consortiums has enhanced the possibility of success for organisations by facilitating their collaborations. One obstacle to configuration of such consortiums as well as collaboration has been the difficulty in assessing the trust level of potential partners. So far, the assessment of trust level has been performed manually by organisations and in an ad hoc manner, which is both time consuming and hardly produces accurate results. Consequently, the formation of collaborative initiatives in the form of temporary consortiums has become more challenging and organisations are reluctant to work with each other. This paper addresses the supervised automation of the assessment of trust level of organisations in coalition networks to smoothen the formation of temporary consortiums. It first presents the concepts of a system developed to support the management of long-term coalition networks of organisations. It then addresses the design and development of Trust Management system by focusing its analysed specifications, designed architectures and applied implementation aspects.

Consider a production situation where it is desirable that the production orders of different product types have different flow rates, independent of their production characteristics such as processing times. Flow rates are mainly determined by the work centre waiting times, thus the product types should have different production order waiting times at the work centres. In this paper we derive a method which makes this possible in a controlled way: given certain values for some parameters the different waiting times (and thus the flow rates) are predictable, By means of simulation this method has been tested for a production situation where only two different flow rates are required per work centre. This simulation study shows that, using a simple balance equation and operation due-date sequencing, it is possible to create different predictable flow rates. It turns out that until a required waiting time reduction for one of the (categories of) products of about 60% has been achieved a one-to-one relation ...