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CORDIS - Resultados de investigaciones de la UE
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Contenido archivado el 2024-04-30

CONCURRENT ENGINEERING WORKFLOW

Objetivo

The project has two major objectives:

- The development of a fundamental approach to dynamic linking workflow design and execution to product structures to achieve product-object driven workflow management functionality for concurrent engineering;
- The application of autonomous knowledge acquisition techniques to obtain intelligent workflow management functionality for recurrent engineering tasks.

In the engineering domain the product structure fixes the tasks which have to be performed to achieve a certain goal. The product components (objects), their characteristics (attributes) and their relationships within assemblies (interference) determine the planning and operational processes needed to manufacture an optimal product in terms of price, time to market and quality. Therefore, reference processes have to be defined at the component level that describe which workflows (activities and work items) within the product and process definition have to be conducted according to the component attributes. At the assembly level, the relationship between the components has to be represented in order to assess the interdependence between the reference processes at the component level. The process definition module of the workflow management system has to be enabled to connect the reference processes with the product structure. Modifications in the product structure must automatically result in adapted process definitions. According to the resulting design, the workflow management system executes the workflow, manages the engineering work units involved, provides them with the required data and, in this way, establishes efficient concurrent engineering.

In order to achieve a dynamic link between the product structure and the workflow design, rules are required which adapt the workflows to particular component attributes and interference. The manual definition of these rules is a very tedious work and requires an enormous effort. In addition, conventionally established rule bases are very difficult to manage. Therefore, artificial intelligence techniques that allow the automatic set up and administration of rule bases via autonomous knowledge acquisition will be applied. Inductive learning algorithms are able to learn from facts represented in the form of cases and automatically extract rules from the cases representation. From "Workflow Cases" consisting of product structure characteristics on the one hand, and workflow definitions on the other, the algorithms are able to extract rules which establish the mentioned dynamic link and help to manage recurrent engineering tasks.

Ámbito científico (EuroSciVoc)

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Coordinador

TECHNISCHE UNIVERSITAET CLAUSTHAL
Aportación de la UE
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Dirección
2A,ADOLPH-RÖMER-STRASSE
38678 CLAUSTHAL-ZELLERFELD
Alemania

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Participantes (6)

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