Search results for "MAC"
showing 10 items of 24950 documents
Integrated WAAM-Subtractive Versus Pure Subtractive Manufacturing Approaches: An Energy Efficiency Comparison
2019
Over the last years, additive manufacturing (AM) has been gathering momentum both in the academic and in the industrial world. Besides the obvious benefits in terms of flexibility and process capabilities, the environmental performance of such processes has still to be properly analyzed. Actually, the advantages of additive manufacturing over conventional processes are not obvious. Indeed, different manufacturing approaches result in different amounts of involved material and in different processing energy demands. Environmental comparative analyses are hence crucial to properly characterize AM processes. In this paper, an energetic comparison between the emerging wire arc additive manufact…
Selecting between CNC milling, robot milling and DMLS processes using a combined AHP and fuzzy approach
2017
Abstract Recent advancements in manufacturing technology allow now a much wider selection of machining processes. Milling with industrial robots or additive manufacturing could now replace traditional milling performed on CNC machine-tools, for certain applications. This work presents a decision-making process for selecting between CNC milling, robot milling and a process of additive manufacturing (DMLS) for a certain class of parts. The AHP method was used for selecting between the three variants of manufacturing processes. The criteria used for AHP were divided into crisp ones and criteria described by linguistic variables. For the last ones, fuzzy inference systems were built to extract …
Intelligent agents for feature modelling in computer aided design
2017
Abstract CAD modelling can be referred to as the process of generating an integrated multiple view model as a representation of multiple views of engineering design. In many situations, a change in the model of one view may conflict with the models of other views. In such situations, the model of some views needs to be adapted in order to make all models consistent. Thus, CAD models should be capable of adapting themselves to new situations. Recently, agent based technologies have been considered in order to increase both knowledge level and intelligence of real and virtual objects. The contribution of this paper consists in introducing the intelligent agents in intelligent CAD modelling. T…
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…
Extreme Learning Machines for Data Classification Tuning by Improved Bat Algorithm
2018
Single hidden layer feed forward neural networks are widely used for various practical problems. However, the training process for determining synaptic weights of such neural networks can be computationally very expensive. In this paper we propose a new learning algorithm for learning the synaptic weights of the single hidden layer feedforward neural networks in order to reduce the learning time. We propose combining the upgraded bat algorithm with the extreme learning machine. The proposed approach reduces the number of evaluations needed to train a neural network and efficiently finds optimal input weights and the hidden biases. The proposed algorithm was tested on standard benchmark clas…
Linearized Piecewise Affine in Control and States Hydraulic System: Modeling and Identification
2018
In this paper, the modeling and identification of a nonlinear actuated hydraulic system is addressed. The full-order model is first reduced in relation to the load pressure and flow dynamics and, based thereupon, linearized over the entire operational state-space. The dynamics of the proportional control valve is identified, analyzed, and intentionally excluded from the reduced model, due to a unity gain behavior in the frequency range of interest. The input saturation and dead-zone nonlinearities are considered while the latter is identified to be close to 10% of the valve opening. The mechanical part includes the Stribeck friction detected and estimated from the experiments. The lineariza…
Crowd-Averse Robust Mean-Field Games: Approximation via State Space Extension
2016
We consider a population of dynamic agents, also referred to as players. The state of each player evolves according to a linear stochastic differential equation driven by a Brownian motion and under the influence of a control and an adversarial disturbance. Every player minimizes a cost functional which involves quadratic terms on state and control plus a cross-coupling mean-field term measuring the congestion resulting from the collective behavior, which motivates the term “crowd-averse.” Motivations for this model are analyzed and discussed in three main contexts: a stock market application, a production engineering example, and a dynamic demand management problem in power systems. For th…
Sensorless Speed Control for Double-Sided Linear Induction Motor Applications
2019
In this work, a flux and speed observer for double-sided linear induction motor applications is presented and experimentally validated. More in detail, from a Double-Sided Linear Induction Motor (DLIM) prototype, the complete modelling and the determination of the related parameters are here reported. Furthermore, the equations for a d-flux and q-flux observer are conceived and several simulation tests are performed. From the good agreements between the trends over time of the speed estimated by the observer and the simulated one, it can be stated that the observer is well designed. Moreover, in order to experimentally validate the proposed observer, a test bench is set-up for the DLIM/obse…
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…