On the use of Process Mining and Machine Learning to support decision making in systems design

Research on process mining and machine learning techniques has recently received a significant amount of attention by product development and management communities. Indeed, these techniques allow both an automatic process and activity discovery and thus are high added value services that help reusing knowledge to support decision-making. This paper proposes a double layer framework aiming to identify the most significant process patterns to be executed depending on the design context. Simultaneously, it proposes the most significant parameters for each activity of the considered process pattern. The framework is applied on a specific design example and is partially implemented.FUI GONTRAN

Bacterial Colonization of Low‐Wettable Surfaces is Driven by Culture Conditions and Topography

Effect of surface low‐wettability on bacterial colonization has become a prominent subject for the development of antibacterial coatings. However, bacteria's fate on such surfaces immersed in liquid as well as causal factors is poorly understood. This question is addressed by using a range of coatings with increasing hydrophobicity, to superhydrophobic, obtained by an atmospheric plasma polymer method allowing series production. Chemistry, wettability, and topography are thoroughly described, as well as bacterial colonization by in situ live imaging up to 24 h culture time in different liquid media. In the extreme case of superhydrophobic coating, substrates are significantly less colonized in biomolecule‐poor liquids and for short‐term culture only. Complex statistical analysis demonstrates that bacterial colonization on these low‐wettable substrates is predominantly controlled by the culture conditions and only secondary by topographic coating's properties (variation in surface structuration with almost constant mean height). Wettability is less responsible for bacterial colonization reduction in these conditions, but allows the coatings to preserve colonization‐prevention properties in nutritive media when topography is masked by fouling. Even after long‐term culture in rich medium, many large places of the superhydrophobic coating are completely free of bacteria in relation to their capacity to preserve air trapping

Effect of Austenite Deformation on the Microstructure Evolution and Grain Refinement Under Accelerated Cooling Conditions

Although there has been much research regarding the effect of austenite deformation on accelerated cooled microstructures in microalloyed steels, there is still a lack of accurate data on boundary densities and effective grain sizes. Previous results observed from optical micrographs are not accurate enough, because, for displacive transformation products, a substantial part of the boundaries have disorientation angles below 15 deg. Therefore, in this research, a niobium microalloyed steel was used and electron backscattering diffraction mappings were performed on all of the transformed microstructures to obtain accurate results on boundary densities and grain refinement. It was found that with strain rising from 0 to 0.5, a transition from bainitic ferrite to acicular ferrite occurs and the effective grain size reduces from 5.7 to 3.1 μm. When further increasing strain from 0.5 to 0.7, dynamic recrystallization was triggered and postdynamic softening occurred during the accelerated cooling, leading to an inhomogeneous and coarse transformed microstructure. In the entire strain range, the density changes of boundaries with different disorientation angles are distinct, due to different boundary formation mechanisms. Finally, the controversial influence of austenite deformation on effective grain size of low-temperature transformation products was argued to be related to the differences in transformation conditions and final microstructures

Product–process interface for manufacturing data management as a support for DFM and virtual manufacturing

This research work was supported by SNECMA as part of the MAIA ( http://www.le-webmag.com/article.php3?id_ article=2&lang=) project, the Region Champagne-Ardennes and Sisson Lehmann of the Wheelabrator group.In order to tackle a continuous improvement of virtual engineering, product modelling has to integrate more knowledge that refers to every decision taken during the product development process. Those decisions have to be related to the assessment of the whole product life cycle. This paper particularly addresses the domain of product’s industrialisation that aims at selecting the manufacturing processes. This selection must currently be done as soon as possible and has to be strongly linked with product definition and computer aided design (CAD) modelling. Thiswork first presents some new results concerning a product–process interface to integrate manufacturing information in the product model and how it leads to the definition of the CAD model. Then this interface that also manages specific information coming from the manufacturing process (tolerances, stresses gradient…) is used to improve the wholemanufacturing process plan simulation. This process plan has, indeed, to track every material transformation issued from each manufacturing operation

Design and manufacturing interface modelling for manufacturing processes selection and knowledge synthesis in design

This research is part of the regional French project IFP2R : “ Manufacturing constraints integration in rapid prototyped part design ” with IFTS (Higher Technical Formation Institute of Charleville Mézières- France).The research results presented in this paper are related to the specification of a method and models that tackle the problem of manufacturing processes selection and the integration, as soon as possible, of their constraints in the product modelling (i.e. information synthesis). This method is based on a skin and skeleton design/manufacturing interface model that ensures connection between design and manufacturing information. The use of these features is justified by their capacity to make a product representation which allows integration of both design and manufacture data and therefore assists the product breakdown definition (including the 3D forms) by least commitment. This method first analyses the product data issued from functional analysis and component selection (form, roughness, tolerance interval, etc.). Then, it deals with manufacturing information (manufacturing processes constraints). The approach is formalised with IDEF and UML models and has been consolidated with software developments based on C++ and open CASCADE technologies

Analysis of work hardening and recrystallization during the hot working of steel using a statistically based internal variable model

A mathematical model has been developed which describes the hot deformation and recrystallization behavior of austenite using a single internal variable: dislocation density. The dislocation density is incorporated into equations describing the rate of recovery and recrystallization. In each case no distinction is made between static and dynamic events, and the model is able to simulate multideformation processes. The model is statistically based and tracks individual populations of the dislocation density during the work-hardening and softening phases. After tuning using available data the model gave an accurate prediction of the stress&ndash;strain behavior and the static recrystallization kinetics for C&ndash;Mn steels. The model correctly predicted the sensitivity of the post deformation recrystallization behavior to process variables such as strain, strain rate and temperature, even though data for this were not explicitly incorporated in the tuning data set. In particular, the post dynamic recrystallization (generally termed metadynamic recrystallization) was shown to be largely independent of strain and temperature, but a strong function of strain rate, as observed in published experimental work.<br /

LED Failure Localization Method due to Thermal Shock and Residual Stress Impact

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