Search results for " Modeling"
showing 10 items of 2411 documents
Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics
2016
To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformation rules based on the domain knowledge of manufacturing engineers and data scientists. Our approach uses a model of a manufacturing process and its associated data as inputs, and generates a trained neural network model as an output to predict a quantity of interest. This pape…
Experimental Research on the Cutting of Metal Materials by Electrical Discharge Machining with Contact Breaking with Metal Band as Transfer Object
2020
The scientific paper presents practical research carried out by a mixed team of Romanian researchers from universities and the business environment. The research consists in applying the process of cutting metallic materials through electrical discharge machining with contact breaking using a metal band as a transfer object. The research was implemented with the help of a specially designed installation in the laboratory and subsequently all the necessary steps were taken to obtain the patent for it. Various metallic materials were cut using this process, but first of all, high alloy steels. In the global research conducted by the authors, active experimental programs and classic experiment…
Assembly Process Modeling Through Long Short-Term Memory
2021
This paper studies Long Short-Term Memory as a component of an adaptive assembly assistance system suggesting the next manufacturing step. The final goal is an assistive system able to help the inexperienced workers in their training stage or even experienced workers who prefer such support in their manufacturing activity. In contrast with the earlier analyzed context-based techniques, Long Short-Term Memory can be applied in unknown scenarios. The evaluation was performed on the data collected previously in an experiment with 68 participants assembling as target product a customizable modular tablet. We are interested in identifying the most accurate method of next assembly step prediction…
Diode laser welding of ABS: Experiments and process modeling
2009
International audience; The laser beam weldability of acrylonitrile/butadiene/styrene (ABS) plates is determined by combining both experimental and theoretical aspects. In modeling the process, an optical model is used to determine how the laser beam is attenuated by the first material and to obtain the laser beam profile at the interface. Using this information as the input data to a thermal model, the evolution of the temperature field within the two components can be estimated. The thermal model is based on the first principles of heat transfer and utilizes the temperature variation laws of material properties. Corroborating the numerical results with the experimental results, some impor…
Additively manufactured textiles and parametric modelling by generative algorithms in orthopaedic applications
2020
Purpose The purpose of this paper is to implement a new process aimed at the design and production of orthopaedic devices fully manufacturable by additive manufacturing (AM). In this context, the use of generative algorithms for parametric modelling of additively manufactured textiles (AMTs) also has been investigated, and new modelling solutions have been proposed. Design/methodology/approach A new method for the design of customised elbow orthoses has been implemented. In particular, to better customise the elbow orthosis, a generative algorithm for parametric modelling and creation of a flexible structure, typical of an AMT, has been developed. Findings To test the developed modelling a…
A proposed mapping method for aligning machine execution data to numerical control code
2019
The visions of the digital thread and smart manufacturing have boosted the potential of relating downstream data to upstream decisions in design. However, to date, the tools and methods to robustly map across the related data representations is significantly lacking. In response, we propose a mapping technique for standard manufacturing data representations. Specifically, we focus on relating controller data from machining tools in the form of MTConnect, an emerging standard that defines the vocabulary and semantics as well as communications protocols for execution data, and G-Code, the most widely used standard for numerical control (NC) instructions. We evaluate the efficacy of our mappin…
Friction Model for Tool/Work Material Contact Applied to Surface Integrity Prediction in Orthogonal Cutting Simulation
2017
Abstract Tribological behavior at both tool/chip and tool/work material interfaces should be highly considered while simulating the machining process. In fact, it is no longer accurate to suppose one independent constant friction coefficient at the tool/chip interface, since in reality it depends on the applied contact conditions, including the sliding velocity and pressure. The contact conditions at both above mentioned interfaces may affect the thermal and mechanical phenomena and consequently the surface integrity predictions. In this article, the influence of contact conditions (sliding velocity) on the tribological behavior of uncoated tungsten carbide tool against OFHC copper work mat…
VARIABLE SELECTION FOR NOISY DATA APPLIED IN PROTEOMICS
2014
International audience; The paper proposes a variable selection method for pro-teomics. It aims at selecting, among a set of proteins, those (named biomarkers) which enable to discriminate between two groups of individuals (healthy and pathological). To this end, data is available for a cohort of individuals: the biological state and a measurement of concentrations for a list of proteins. The proposed approach is based on a Bayesian hierarchical model for the dependencies between biological and instrumental variables. The optimal selection function minimizes the Bayesian risk, that is to say the selected set of variables maximizes the posterior probability. The two main contributions are: (…
Modeling Energy Demand Aggregators for Residential Consumers
2013
International audience; Energy demand aggregators are new actors in the energy scenario: they gather a group of energy consumers and implement a demand- response paradigm. When the energy provider needs to reduce the current energy demand on the grid, it can pay the energy demand aggregator to reduce the load by turning off some of its consumers loads or postponing their activation. Currently this operation involves only greedy energy consumers like industrial plants. In this paper we want to study the potential of aggregating a large number of small energy consumers like home users as it may happen in smart grids. In particular we want to address the feasibility of such approach by conside…
DESDEO: The Modular and Open Source Framework for Interactive Multiobjective Optimization
2021
Interactive multiobjective optimization methods incorporate preferences from a human decision maker in the optimization process iteratively. This allows the decision maker to focus on a subset of solutions, learn about the underlying trade-offs among the conflicting objective functions in the problem and adjust preferences during the solution process. Incorporating preference information allows computing only solutions that are interesting to the decision maker, decreasing computation time significantly. Thus, interactive methods have many strengths making them viable for various applications. However, there is a lack of existing software frameworks to apply and experiment with interactive …