Manufacturing Process Management: iterative synchronisation of engineering data with manufacturing realities

Fortin, Clément; Huet, Greg

doi:10.1504/ijpd.2007.012496

Cited by 24 publications

(18 citation statements)

References 22 publications

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“…product simulation behaviour, like [26][27][28]. Only the approach described in [29] has been proposed within the DF, but they do not tackle the problem of multiple actors in DF.…”

Section: Actual Proposedmentioning

confidence: 99%

Conceptual Model for Management of Digital Factory Simulation Information

Ayadi

Affonso

Cheutet

et al. 2013

Int. j. simul. model.

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Digital Factory (DF) aims at proposing simulation tools to design a product and its production system in parallel. Nevertheless, DF is marked by the multiplicity and heterogeneity of simulation models that are used, that slows down its usage in industry. We propose in this paper a conceptual model to manage the different simulation information created and manipulated through a DF project. This model is based on an analysis of the current design strategies and the used simulation tools. Finally, an industrial application has been developed to validate the completeness of this model.

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“…product simulation behaviour, like [26][27][28]. Only the approach described in [29] has been proposed within the DF, but they do not tackle the problem of multiple actors in DF.…”

Section: Actual Proposedmentioning

confidence: 99%

Conceptual Model for Management of Digital Factory Simulation Information

Ayadi

Affonso

Cheutet

et al. 2013

Int. j. simul. model.

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show abstract

“…The PPO information kernel stores persistent data on the interoperable files that might be reached by several external applications on the collaborative PLM system among the whole product life cycle [22]. Danesi [36] have proposed the P4LM methodology, which allows the management of Projects, Products, Processes, and Proceeds in collaborative design. It aims at allowing the integration of information coming from different partners which are involved in a PLM application.…”

Section: 2mentioning

confidence: 99%

A Meta-Model for Knowledge Representation Integrating Maturity for Decision Making in Engineering Design

Dremont

Troussier

Whitfield

et al. 2013

Product Lifecycle Management for Society

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Abstract. Computer Aided Design (CAD) and Computer Aided Engineering (CAE) models are often used during product design. Various interactions between the different models must be managed in a PLM approach for the designed system to be robust and in accordance with defined specifications. To effectively manage engineering changes on the system definition, the dependencies between the different models must be known and managed in a PLM system. A lot of data are exchanged in collaborative design and different problems must be managed in terms of data consistency. We propose a metamodel for knowledge representation integrating maturity concept to support decision making in preliminary collaborative design. A literature survey about existing knowledge models is done before presenting the proposed meta-model of knowledge.

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“…As-designed structure or engineering BOM (eBOM) and as-planned structure or manufacturing BOM (mBOM) are two frequently encountered BOMs. Some modern PLM frameworks already operate the interconnection between the two structures to support product definition and process planning concurrent activities (Fortin et al, 2007). This is typically done through robustly linked PDM and MPM modules.…”

Section: Typical Context Of Dmu Technologiesmentioning

confidence: 99%

“…This is typically done through robustly linked PDM and MPM modules. Fortin and Huet (2007) approach product development from a systematic perspective and address concerns on how to carry out the process in the current information-scattered environment that characterises the modern enterprise. The authors argue that the use of complementary information structures and an optimal parallelization of the processes can significantly improve the product development performance through the digital collaborative environment.…”

Section: Typical Context Of Dmu Technologiesmentioning

confidence: 99%

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Set-Based Prototyping with Digital Mock-Up Technologies

Toche

Pellerin

Fortin

et al. 2012

Product Lifecycle Management. Towards Knowledge-Rich Enterprises

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Abstract. A prototype results from the need to verify various qualities of the product at different stages of its development. In set-based design, multiplying prototypes is particularly critical to enable a broad exploration of the design space before committing to a solution. The exploration targets the choice of the best of all viable concepts on one hand but on the other hand also focuses on documenting them to better orient the search during the next attempts. This ultimately contributes to gradually improving the company's engineering knowledge. According to current aerospace industry practices and considering the set based development paradigm in Lean thinking, an approach to handle multiple prototypes information with Digital Mock-Up (DMU) technologies is forwarded in this paper. This approach postulates that prototyping and testing activities may be supported by a Manufacturing Process Management (MPM) solution with a special use of three key functionalities, namely: Product Data Management (PDM) and MPM instantiation, MPM links, and Configuration Management (CM). These aspects are essential when handling multiple prototyping sets along with their test results.

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Manufacturing Process Management: iterative synchronisation of engineering data with manufacturing realities

Cited by 24 publications

References 22 publications

Conceptual Model for Management of Digital Factory Simulation Information

Conceptual Model for Management of Digital Factory Simulation Information

A Meta-Model for Knowledge Representation Integrating Maturity for Decision Making in Engineering Design

Set-Based Prototyping with Digital Mock-Up Technologies

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