Yield prediction models for optimization of high-speed micro-processor manufacturing processes

2002 ◽  
Author(s):  
Tae Seon Kim ◽  
Se Hwan Ahn ◽  
Young Gyun Jang ◽  
Jeong In Lee ◽  
Kil Jae Lee ◽  
...  
Keyword(s):  
High Speed ◽  
Prediction Models ◽  
Manufacturing Processes ◽  
Yield Prediction

scholarly journals Inspection planning by defect prediction models and inspection strategy maps

2021 ◽  
Author(s):  
Elisa Verna ◽  
Gianfranco Genta ◽  
Maurizio Galetto ◽  
Fiorenzo Franceschini
Keyword(s):  
Probabilistic Models ◽  
Prediction Models ◽  
Design Tool ◽  
General Interest ◽  
Manufacturing Processes ◽  
Analysis Tool ◽  
Manufacturing Companies ◽  
Inspection Planning ◽  
Inspection Strategy ◽  
Defect Prediction Models

AbstractDesigning appropriate quality-inspections in manufacturing processes has always been a challenge to maintain competitiveness in the market. Recent studies have been focused on the design of appropriate in-process inspection strategies for assembly processes based on probabilistic models. Despite this general interest, a practical tool allowing for the assessment of the adequacy of alternative inspection strategies is still lacking. This paper proposes a general framework to assess the effectiveness and cost of inspection strategies. In detail, defect probabilities obtained by prediction models and inspection variables are combined to define a pair of indicators for developing an inspection strategy map. Such a map acts as an analysis tool, enabling positioning assessment and benchmarking of the strategies adopted by manufacturing companies, but also as a design tool to achieve the desired targets. The approach can assist designers of manufacturing processes, and particularly low-volume productions, in the early stages of inspection planning.

scholarly journals Cutting Force Prediction Models by FEA and RSM When Machining X56 Steel with Single Diamond Grit

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 326
Author(s):  
Lan Zhang ◽  
Xianbin Sha ◽  
Ming Liu ◽  
Liquan Wang ◽  
Yongyin Pang
Keyword(s):  
Cutting Force ◽  
Coefficient Of Friction ◽  
High Speed ◽  
Prediction Models ◽  
Pipeline Steel ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Force Prediction ◽  
Force Prediction ◽  
Diamond Wire Saw

In the field of underwater emergency maintenance, submarine pipeline cutting is generally performed by a diamond wire saw. The process, in essence, involves diamond grits distributed on the surface of the beads cutting X56 pipeline steel bit by bit at high speed. To find the effect of the different parameters (cutting speed, coefficient of friction and depth of cut) on cutting force, the finite element (FEA) method and response surface method (RSM) were adopted to obtain cutting force prediction models. The former was based on 64 simulations; the latter was designed according to DoE (Design of Experiments). Confirmation experiments were executed to validate the regression models. The results indicate that most of the prediction errors were within 10%, which were acceptable in engineering. Based on variance analyses of the RSM models, it could be concluded that the depth of the cut played the most important role in determining the cutting force and coefficient the of friction was less influential. Despite making little direct contribution to the cutting force, the cutting speed is not supposed to be high for reducing the coefficient of friction. The cutting force models are instructive in manufacturing the diamond beads by determining the protrusion height of the diamond grits and the future planning of the cutting parameters.

Free Vibration Analysis for Thin Wire of Modern Wiresaw Between Sliced Wafers in Wafer Manufacturing Processes

2000 ◽  
Author(s):  
Songbin Wei ◽  
Imin Kao
Keyword(s):  
High Speed ◽  
Free Vibration Analysis ◽  
Equation Of Motion ◽  
Manufacturing Processes ◽  
Thin Wire ◽  
Wire Vibration ◽  
The Wire ◽  
The Impact ◽  
Wafer Manufacturing ◽  
Impact Problem

Abstract In wiresaw manufacturing process where thin wire moving at high speed is pushed onto ingot to produce slices of wafer, the wire is constrained by two wafer walls as it slices into the ingot. In this paper, we investigate the vibration of such wire under the constraints of wafer walls. To address this problem, the model for wire vibration with impact to wafer walls is developed. The equation of motion is discretized using the Galerkin’s method. The principle of impulse and momentum is utilized to solve the impact problem. The results of analysis and simulation indicate that the response under a pointwise sinusoidal excitation is neither periodical nor symmetric with respect to the horizontal axis, due to the excitation from the impact. The wire vibration behavior is affected dramatically by the wafer wall constraints.

scholarly journals Predicting tomato field-yield using continuous monitoring of young tomato water status

2021 ◽  
Author(s):  
Sanbon Gosa ◽  
Amit Koch ◽  
Itamar Shenhar ◽  
Joseph Hirschberg ◽  
Dani Zamir ◽  
...  
Keyword(s):  
Prediction Models ◽  
Water Status ◽  
Total Yield ◽  
Field Measurements ◽  
Carotenoid Biosynthesis ◽  
Yield Prediction ◽  
Drought Treatment ◽  
Recessive Mutations ◽  
Tomato Yield ◽  
Tomato Field

To address the challenge of predicting tomato yields in the field, we used whole-plant functional phenotyping to evaluate water relations under well-irrigated and drought conditions. The genotypes tested are known to exhibit variability in their yields in wet and dry fields. The examined lines included two lines with recessive mutations that affect carotenoid biosynthesis, zeta z2083 and tangerine t3406, both isogenic to the processing tomato variety M82. The two mutant lines were reciprocally grafted onto M82 and multiple physiological characteristics were measured continuously, as well as before, during and after drought treatment in the greenhouse. A comparative analysis of greenhouse and field yields showed that the whole-canopy stomatal conductance (gsc) in the morning and cumulative transpiration (CT) were strongly correlated with field measurements of total yield (TY: r2 = 0.9 and 0.77, respectively) and plant vegetative weight (PW: r2 = 0.6 and 0.94, respectively). Furthermore, the minimum CT during drought and the rate of recovery when irrigation was resumed were both found to predict resilience. Keywords: drought tolerance, functional genomic mapping, functional phenotyping, physiological trait, time-series measurements, tomato, yield prediction, yield-prediction models

scholarly journals Conduction-Based Thermally Assisted Micromilling Process for Cutting Difficult-to-Machine Materials

2020 ◽  
Vol 4 (2) ◽  
pp. 34 ◽  
Author(s):  
Timo Platt ◽  
Alexander Meijer ◽  
Dirk Biermann
Keyword(s):  
Tool Wear ◽  
High Speed ◽  
End Milling ◽  
High Speed Steel ◽  
High Strength ◽  
Process Conditions ◽  
Manufacturing Processes ◽  
Central Process ◽  
Workpiece Temperature ◽  
Micro End Milling

The increasing demand for complex and wear-resistant forming tools made of difficult-to-machine materials requires efficient manufacturing processes. In terms of high-strength materials; highly suitable processes such as micromilling are limited in their potential due to the increased tool loads and the resulting tool wear. This promotes hybrid manufacturing processes that offer approaches to increase the performance. In this paper; conduction-based thermally assisted micromilling using a prototype device to homogeneously heat the entire workpiece is investigated. By varying the workpiece temperature by 20 °C < TW < 500 °C; a highly durable high-speed steel (HSS) AISI M3:2 (63 HRC) and a hot-work steel (HWS) AISI H11 (53 HRC) were machined using PVD-TiAlN coated micro-end milling tools (d = 1 mm). The influence of the workpiece temperature on central process conditions; such as tool wear and achievable surface quality; are determined. As expected; the temporary thermal softening of the materials leads to a reduction in the cutting forces and; thus; in the resulting tool wear for specific configurations of the thermal assistance. While only minor effects are detected regarding the surface topography; a significant reduction in the burr height is achieved.

A New Approach for Training-load Quantification in Elite-level Soccer: Contextual Factors

2020 ◽  
Author(s):  
Berni Guerrero-Calderón ◽  
Maximilian Klemp ◽  
Alfonso Castillo-Rodriguez ◽  
José Alfonso Morcillo ◽  
Daniel Memmert
Keyword(s):  
High Speed ◽  
Prediction Models ◽  
Contextual Factors ◽  
Soccer Players ◽  
Total Distance ◽  
Professional Soccer ◽  
Equivalent Distance ◽  
Physical Responses ◽  
Match Location

AbstractThe aims of this study were to analyse the physical responses of professional soccer players during training considering the contextual factors of match location, season period, and quality of the opposition; and to establish prediction models of physical responses during training sessions. Training data was obtained from 30 professional soccer players from Spanish La Liga using global positioning technology (N=1365 performances). A decreased workload was showed during training weeks prior to home matches, showing large effects in power events, equivalent distance, total distance, walk distance and low-speed running distance. Also, the quality of the opposition also affected the training workload (p<0.05). All regression-models showed moderate effects, with an adjusted R2 of 0.37 for metabolic-work, 0.34 for total distance covered, 0.25 for high-speed running distance (18–21 km·h−1), 0.29 for very high-speed running distance (21–24 km·h−1), 0.22 for sprint running distance (>24 km·h−1) and 0.34 for equivalent distance. The main finding of this study was the great association of match location, season period and quality of opposition on the workload performed by players in the training week before the match; and the development of workload prediction-models considering these contextual factors, thus proposing a new and innovative approach to quantify the workload in soccer.

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