Variation Analyses Using SugarCube

2012 ◽  
Author(s):  
Xing Jin ◽  
Jason V. Clark
Keyword(s):  
Design Space ◽  
Process Variations ◽  
Ease Of Use ◽  
Test Cases ◽  
Device Performance ◽  
Variation Analysis ◽  
Excitation Parameter ◽  
Process Yield ◽  
Cad Tool ◽  
Expansion Coefficients

In this paper, we present new variation analysis features added to SugarCube. SugarCube is a novice-friendly online CAD tool for exploring the design space of compact MEMS models. Such variation analysis can help to evaluate the bounded effects of unavoidable process variations during the fabrication (such as Young’s modulus, overcut, gap asymmetry, etc.), packaging (such as variations in temperature, expansion coefficients, etc.), and operation (such as variations in voltage sources, etc.). Compared to other software tools for MEMS, the benefits of variation analysis in SugarCube include its comprehensiveness, ease of use, speed, and accessibility. In SugarCube, any geometric, material, or excitation parameter may be easily explored for its effect on device performance. Such analysis is expected to benefit feasibility analyses on process survivability, process yield, and operational robustness. For a couple of test cases, we perform our variation analysis on a micro-scale accelerometer and gyroscope.

Process Yield Improvement Through Optimum Design of Fixture Layouts in 3D Multistation Assembly Systems

2008 ◽  
Vol 130 (6) ◽  
Author(s):  
T. Phoomboplab ◽  
D. Ceglarek
Keyword(s):  
Genetic Algorithm ◽  
Design Space ◽  
Assembly System ◽  
Industrial Case Study ◽  
Process Yield ◽  
Space Reduction ◽  
Complex Design ◽  
Hammersley Sequence ◽  
Multistation Assembly ◽  
Fixture System

Fixtures control the positions and orientations of parts in an assembly process. Inaccuracies of fixture locators or nonoptimal fixture layouts can result in the deviation of a workpiece from its design nominal and lead to overall product dimensional variability and low process yield. Major challenges involving the design of a set of fixture layouts for multistation assembly system can be enumerated into three categories: (1) high-dimensional design space since a large number of locators are involved in the multistation system, (2) large and complex design space for each locator since the design space represents the area of a particular part or subassembly surfaces on which a locator is placed, (here, the design space varies with a particular part design and is further expanded when parts are assembled into subassemblies), and (3) the nonlinear relations between locator nominal positions and key product characteristics. This paper presents a new approach to improve process yield by determining an optimum set of fixture layouts for a given multistation assembly system, which can satisfy (1) the part and subassembly locating stability in each fixture layout and (2) the fixture system robustness against environmental noises in order to minimize product dimensional variability. The proposed methodology is based on a two-step optimization which involves the integration of genetic algorithm and Hammersley sequence sampling. First, genetic algorithm is used for design space reduction by estimating the areas of optimal fixture locations in initial design spaces. Then, Hammersley sequence sampling uniformly samples the candidate sets of fixture layouts from those predetermined areas for the optimum. The process yield and part instability index are design objectives in evaluating candidate sets of fixture layouts. An industrial case study illustrates and validates the proposed methodology.

scholarly journals Use of Response Surface Metamodels for Identification of Stiffness and Damping Coefficients in a Simple Dynamic System

2005 ◽  
Vol 12 (5) ◽  
pp. 317-331 ◽  
Author(s):  
A.C. Rutherford ◽  
D.J. Inman ◽  
G. Park ◽  
F.M. Hemez
Keyword(s):  
Parameter Identification ◽  
Response Surface ◽  
Structural Dynamics ◽  
Design Space ◽  
Ease Of Use ◽  
Surface Model ◽  
Training Requirements ◽  
System Parameters ◽  
Polynomial Response Surface ◽  
Stiffness And Damping

Metamodels have been used with success in many areas of engineering for decades but only recently in the field of structural dynamics. A metamodel is a fast running surrogate that is typically used to aid an analyst or test engineer in the fast and efficient exploration of the design space. Response surface metamodels are used in this work to perform parameter identification of a simple five degree of freedom system, motivated by their low training requirements and ease of use. In structural dynamics applications, response surface metamodels have been utilized in a forward sense, for activities such as sensitivity analysis or uncertainty quantification. In this study a polynomial response surface model is developed, relating system parameters to measurable output features. Once this relationship is established, the response surface is used in an inverse sense to identify system parameters from measured output features.A design of experiments is utilized to choose points, representing a fraction of the full design space of interest, for fitting the response surface metamodel. Two parameters commonly used to characterize damage in a structural system, stiffness and damping, are identified. First changes are identified and located with success in a linear 5DOF system. Then parameter identification is attempted with a nonlinear 5DOF system and limited success is achieved. This work will demonstrate that use of response surface metamodels in an inverse sense shows promise for use in system parameter identification for both linear and weakly nonlinear systems and that the method has potential for use in damage identification applications.

A Complexity-Based Approach to Robust Design and Structural Assessment of Aero Engine Components

2007 ◽  
Author(s):  
D. Lomario ◽  
G. P. De Poli ◽  
L. Fattore ◽  
J. Marczyk
Keyword(s):  
Design Space ◽  
Response Surfaces ◽  
Probability Density Functions ◽  
Test Cases ◽  
System A ◽  
Aero Engine ◽  
Novel Method ◽  
Design Requirements ◽  
Definition Of ◽  
Engine Components

This paper presents a complexity-based methodology for the design of aero engine components. Upon a rigorous definition of complex system, a metric for the complexity is introduced as a function of system’s topology and entropy. As a consequence, complexity becomes a measurable and manageable property of systems. Furthermore, a novel definition of robustness is provided, based on the shape of the probability density functions (PDF) of the performances. Complexity and robustness are related together by a simple, qualitative law. Based on these premises, two algorithms are introduced, namely the Stochastic Design Improvement (SDI) and the Complex Systems Analyzer (CSA). The former searches the design space seeking for solutions which meet the design requirements. The latter extracts the fundamental features of the design, previously perturbed by means of Monte Carlo Simulation (MCS). The SDI is proposed as a competitor of the practice of optimization. Though both can be used separately, the combination of SDI and CSA provides a powerful novel method for design. The capabilities of the algorithms are illustrated on three test-cases, namely an LPT Casing, a Turbo-prop bearing retainer and an LPT disk. It is important to point out that response surfaces or other surrogates have never been used.

Process Yield Improvement Through Optimum Design of Fixture Layouts in 3D Multi-Station Assembly Systems

2007 ◽  
Author(s):  
T. Phoomboplab ◽  
D. Ceglarek
Keyword(s):  
Genetic Algorithm ◽  
Design Space ◽  
Industrial Case Study ◽  
Process Yield ◽  
Space Reduction ◽  
Multi Stage ◽  
Complex Design ◽  
Hammersley Sequence ◽  
System Robustness ◽  
Fixture System

This paper presents a new approach to improve process yield by determining an optimum set of fixture layouts for a given multi-station assembly system which can satisfy: (i) parts and subassemblies locating stability in each fixture layout; and (ii) fixture system robustness against environmental noises in order to minimize product dimensional variability. Three major challenges of the multi-stage assembly processes are addressed: (i) high-dimensional design space; (ii) large and complex design space of each locator; and (iii) the nonlinear relations between locator positions, also called Key Control Characteristics, and Key Product Characteristics. The proposed methodology conducts two-step optimization based on the integration of Genetic Algorithm and Hammersley Sequence Sampling. First, Genetic Algorithm is used for design space reduction by determining the areas of optimal fixture locations in initial design spaces. Then, Hammersley Sequence Sampling uniformly samples the candidate sets of fixture layouts from the areas predetermined by GA for the optimum. The process yield and part instability index are design objectives in evaluating candidate sets of fixture layouts. An industrial case study illustrates and validates the proposed methodology.

scholarly journals A guide to improving the e-commerce user interface design

2005 ◽  
Author(s):  
◽  
Alveen Singh
Keyword(s):  
User Interface ◽  
South African ◽  
Interface Design ◽  
Ease Of Use ◽  
Test Cases ◽  
Independent Research ◽  
Research Institution ◽  
Internet Users ◽  
Study Selection ◽  
Selection Of

This study examines the efficiency, ease of use and ease of understanding of user interface designs implemented in current e-commerce websites. Four South African based e-commerce websites formed the test cases of this study. Selection of the test cases was based on the results and conclusions of previous surveys conducted by an independent research institution. The outcome of that survey identified the most popular e-commerce websites among South African internet users.

scholarly journals CHIP: Clustering Hotspots in Layout Using Integer Programming

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Rohit Reddy Takkala ◽  
Chris Chu
Keyword(s):  
Circuit Design ◽  
Integrated Circuit ◽  
Design Space Exploration ◽  
Design Space ◽  
Triangle Inequality ◽  
Clustering Algorithms ◽  
Test Cases ◽  
Integrated Circuit Design ◽  
Yield Optimization ◽  
Clustering Problems

Clustering algorithms have been explored in recent years to solve hotspot clustering problems in integrated circuit design. With various applications in design for manufacturability flow such as hotspot library generation, systematic yield optimization, and design space exploration, generating good quality clusters along with their representative clips is of utmost importance. With several generic clustering algorithms at our disposal, hotspots can be clustered based on the distance metric defined while satisfying some tolerance conditions. However, the clusters generated from generic clustering algorithms need not achieve optimal results. In this paper, we introduce two optimal integer linear programming formulations based on triangle inequality to solve the problem of minimizing cluster count while satisfying given constraints. Apart from minimizing cluster count, we generate representative clips that best represent the clusters formed. We achieve a better cluster count for both formulations in most test cases as compared to the results published in the literature in the ICCAD 2016 contest benchmarks as well as the reference results reported in the ICCAD 2016 contest website.

scholarly journals Leakage Mitigation in NW FET using Negative Schottky Junction Drain and its Process Variation Analysis

2021 ◽  
Author(s):  
Mohd Rizwan Uddin Shaikh ◽  
Sajad A Loan ◽  
Abdullah G Alharbi
Keyword(s):  
Field Effect ◽  
Field Effect Transistor ◽  
Schottky Barrier Height ◽  
Process Variation ◽  
Process Variations ◽  
Schottky Junction ◽  
Variation Analysis ◽  
Drain Side ◽  
Band To Band Tunneling ◽  
Effect Transistor

Abstract In this work, a Schottky junction on the drain side employing low workfunction (WF) metal is proposed as a method to suppress the OFF-state leakage in nanowire (NW) field-effect transistor (FET). Instead of a highly n+ doped drain, low WF metal with negative electron Schottky-barrier height (SBH) as a drain minimizes the lateral band-to-band tunneling (L-BTBT) considerably. L-BTBT is the movement of carriers (holes) from the drain conduction band (CB) into the channel valence band (VB) during the OFF-state. Impact of varying WF at channel-drain junction on the device characteristics is studied. It is observed that SBH60 eV is required to mitigate L-BTBT compared to the conventionally-doped and junctionless (JL) NW counterpart. Furthermore, unlike L-BTBT, leakage in NW Schottky-drain (SD) comprises of holes tunneling through the SB from the metal drain into the channel and termed as the lateral SB tunneling (L-SBT). In contrast to JL NW FET, the process variation immunity (varying channel doping, NCh and NW diameter, dNW ) and the ON-state current of the proposed device is not compromised at the expense of lower OFF-state LSBT. Instead, the device is less susceptible to process variations and retains the ON-state performance of the NW MOSFET. For a ±20% change in NCh, ∆IOF F /IOF F of 7% compared to 97% in NW JL FET is observed.

Variation Analysis Toolbox for Non-Nominal Path Planning for Industrial Robots

2007 ◽  
Author(s):  
Lars Lindkvist ◽  
Rikard So¨derberg ◽  
Johan S. Carlson
Keyword(s):  
Path Planning ◽  
Process Design ◽  
Manufacturing Process ◽  
Industrial Robots ◽  
Test Cases ◽  
Variation Analysis ◽  
On Line ◽  
Geometrical Variation ◽  
Assembly Analysis ◽  
Robot Path

Industrial robots are frequently used in the manufacturing process. One important aspect in the manufacturing process design is to assure that there exists a collision-free assembly path for each part and subassembly including the assembly equipment, e.g. a robot. In order to reduce the need of physical verification the automotive industry uses digital mock-up tools with collision checking for this kind of geometrical assembly analysis. However, in real production, all equipment, parts and subassemblies are affected by geometrical variation, often resulting in conflicts and on-line adjustments of off-line generated assembly paths. This paper presents a variation analysis toolbox for path planning for industrial robots. This toolbox can help to avoid problems with on-line adjustments. The variation analysis includes the variation in joints and actuators in the robot and can also be used by robot manufacturers when designing new robots. A new tool for variation analysis of a robot path is presented. Also, variation analysis of the product at the assembly line is used to enhance the off-line generated assembly paths. With better knowledge of the variation in the robot and product we can allow the assembly path to reach closer to areas of low variation, while avoiding areas of high variation. The proposed approach is illustrated with test cases.

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