Automating Injection Molding Simulation using Autonomous Optimization
|
|
- Austen Day
- 5 years ago
- Views:
Transcription
1 Automating Injection Molding Simulation using Autonomous Optimization Matt Proske, Rodrigo Gutierrez, & Gabriel Geyne SIGMASOFT Virtual Molding Autonomous optimization is coupled to injection molding simulation to help molders make more informed decisions with less manual labor. The concept is to automatically create and calculate hundreds or thousands of simulations within a predetermined design space of millions of possibilities to learn about the relationship between final part quality and the material, mold, process, and molding machine. Instead of running ten simulations with an operator, the software is running hundreds or thousands of simulations on its own. Better decisions are then possible because there is significantly more information to base the decisions on. Obviously, making a decision based on five thousand simulated variations (variants) provides much less room for speculation than basing the same decision on only three or four simulations. With a larger sample size, there is a much clearer understanding of the relationship between the part/mold design and the process. This approach provides even more value to the molder because the software is completing a much larger portion of the work. It s also completed well in advance of building a mold. In a traditional simulation approach, an operator sets up a single simulation, clicks start, and then evaluates the results either while the simulation is running or after it s complete. The evaluation requires time; look at individual results, think about them, decide if improvement is required, decide what inputs to change (probably as a group), make changes, click start, and repeat. The manually iterative procedure continues possibly several times a day for several days until the group is satisfied the result is as good as it will get with the time available. Each set up might take 15 minutes and each review might take another 15 to 30 minutes. Calculation times can vary from as little at 60 seconds or as long as an entire day. Manually operating the software for ten simulation designs can require a full workday of labor, maybe more. The new, automatic approach is quite different. The software operator sets up the initial design which includes objectives, variables, and constraints. (This procedure can also be further simplified using preexisting templates.) The software automatically produces each future variant (simulated design) by changing the process and/or geometry in milliseconds, generates the mesh, queues it up for calculation, runs the simulation, and plots the results of the objectives. The results of all variants are plotted in a single chart so the operator can easily determine which of the variants produce the results which most closely meet their objectives (Figure 1). AUTONOMOUS OPTIMIZATION 1
2 Figure 1 - Autonomous Optimization Operating Space The operator time is reduced from 7.5 hours to 0.75 hours (an improvement of 10x). The decisions of the operator are based on thousands of simulations instead of only a few. This is something like a DoE (design of experiments), which is also possible. However, the main difference is that instead of simulating all of the variants, the software focusses on changes that produce results which more closely meet the objectives. The software knows what can and cannot be changed, how much it can be changed and what the objectives are to avoid creating unfeasible situations. It creates and runs multiple variants over several generations learning about which changes are most desirable. Several variants are calculated in parallel to speed the process. The faster the results are available, the faster the software learns what changes support our objectives. This is a completely different approach for solving problems or achieving new goals when compared to traditional simulation. All molders don t necessarily have the same goals, or constraints however. Some may want to find the lowest melt pressure to fit the largest part into the smallest machine while others may want to achieve the fastest cycle time. Some may have significant latitude on gate location or material selection while others may have none. Autonomous optimization may not be able to find the solution, but it can explore the complete realm of what is allowed to determine the best possible scenario. At least a molder can determine what the very best process is, how repeatable it will be, and what final part quality is attainable. Two very common problems molders encounter are; AUTONOMOUS OPTIMIZATION 2
3 1. Best gate location 2. Fastest cycle time However, there are other objectives too, all involving part quality. Parts must meet dimensional, aesthetic, and mechanical requirements. Multiple objectives are used simultaneously now to ensure molders don t end up with undesirable outcomes; - Lowest pressure to fill a cavity but creates weak weld lines, or - Least amount of trapped air but produces highest melt pressure LSR Melt Pressure, Gate Location, Air Entrapment Figure 2a & b - Melt pressure progression during fill shows trapped bubble For LSR production, cavity pressure at the parting line is critical because the material viscosity is typically very low and the material can flash the parting line relatively easily. The pressure rises as the cavity fills so gate location is directly related to the cavity pressure. Figure 2 a, b shows melt pressure rising as cavity filling progresses. The challenge for this product is to determine if there is a geometric solution for the trapped air, i.e. new gate location. The autonomous optimization begins with the identification of the objectives, variables, and constraints. Objectives are to minimize air trapped in the cavity during fill. It is described to the software as minimize: air entrapment where air entrapment is a specific simulation output. The results is based on the temperature and pressure of trapped air bubbles and is resolved against the liquid melt pressure to calculate if melt pressure rises above the air pressure, it will begin to dissolve into the flowing LSR before curing initiates. Notice the location of the air entrapment and the way in which it becomes trapped. Also notice the trapped air bubbles being squeezed out of the initial air pocket and into the melt stream (Figure 3 a, b). AUTONOMOUS OPTIMIZATION 3
4 Figure 3a & b Air pocket on actual (left) vs simulated part (right) The variables in this design will be limited to three; two geometric and one process. Geometric: vent locations, gate location Process: Filling time (6s and 8s) The two filling times are added to the optimization to make sure the best gate location can also absorb some process variation. Since LSR is susceptible to jetting (Figure 4) due to its low viscosity, the best gate location must still be valid while being subject to variations in viscosity. This objective is named minimize: free surface. Less free surface of the melt will always come from a design with less jetting. Figure 4 - Jetting effect due to LSR low viscosity AUTONOMOUS OPTIMIZATION 4
5 Changes to the vent locations must also be considered (and coupled to the gate locations). This avoids situations where the software finds potentially optimal solutions to the filling pattern but disregards them due to improper venting. The gate locations are also variable, but limited to certain areas of the part. In this case, a trajectory line (path) is extracted from the part geometry and used to keep the definition of where the gate can be, relatively straightforward (Figure 5). The gate can move anywhere along the line in 1 degree increments. Since the beginning and ending positions of the gate cover 240 degrees, there are 240 different potential gate locations which the software can use to find the optimal gate location. The vent locations are dependent on the gate locations so additional designs are not required for this variable. Two filling times are combined with 240 different gate locations for a total design space of 480 possible variants. All other inputs for this design were constrained (melt/mold temperature, gate size, material grade, etc. Figure 5- Potential Gate Locations The autonomous optimization runs multiple designs in parallel for each generation and then runs multiple generations, seeking the gate location which provides the lowest air entrapment within the 6-8s range of filling times. Figure 6 - Scatter chart showing each simulated design vs maximum air trapped pressure AUTONOMOUS OPTIMIZATION 5
6 The software has found the best gate location after creating and simulating 96 possibilities. All of the designs are shown in a scatter chart (Figure 6), plotted against the objectives of lowest air entrapment and lest amount of free surface. The best design is identified and exported. The free surface and air entrapment results from the best design and shown and compared to the original design (Figure 7 a, b). Figure 7 a & b - Cavity pressure comparison from original (left) vs optimal gate location (right) The calculation time for the autonomous optimization was 2 hours and the labor to set it up was only 30 minutes. In contrast, using a manual approach with both filling times, it would have taken at least 24 designs to be within 10 degrees of the optimal location. Even at only 20 minutes (of labor) per design, it would have required a full workday and it would still not be as good as the optimal. If it were as good as the optimal, it would have been by accident and the autonomous approach consistently finds more optimal solutions, purposefully, using larger sample sizes and basing decisions on data. The calculation time is extremely inexpensive compared to the cost of labor; the average hourly cost for software and hardware using a three year amortization schedule is only $5.00 and it works 24/7. The average hourly cost of a trained software operator is $50.00 (including salary, health insurance, retirement, unemployment, SS, etc). So, it makes complete sense to focus on reducing the human labor factor since it s 10 times greater. It also makes sense to focus on software development which computes more quickly. As more data is required for software to make decisions, more simulated variants are required to improve the accuracy of these decisions. However, this approach is statistically proven to find better solutions. Most molders use live molding trials and DoE to make these data-driven decisions already. The cost of a live DoE trial (8 hr sample including start-up and shutdown) ($1,000.00) compared to a virtual molding trial ($50.00) vary greatly and will help molders achieve levels of profitability not previously possible. AUTONOMOUS OPTIMIZATION 6
Autodesk Moldflow Communicator Process settings
Autodesk Moldflow Communicator 212 Process settings Revision 1, 3 March 211. Contents Chapter 1 Process settings....................................... 1 Profiles.................................................
More informationHuntsman Polyurethanes smart simulation software. Process optimization by simulation
Huntsman Polyurethanes smart simulation software Process optimization by simulation Understanding material behavior is fundamental to the design of new products. For non-linear materials such as molding
More informationD-M-E Company Stephenson Hwy. Madison Heights, Michigan 48071
Pressure Sensor Tutorial Page 1 of 5 D-M-E Company 29111 Stephenson Hwy. Madison Heights, Michigan 48071 A SHORT TUTORIAL ON CAVITY PRESSURE TRANSDUCER USAGE 06-22-93 by Thomas Linehan This document is
More informationComputer Simulation Helps Improve Vertical Column Induced Gas Flotation (IGF) System
JOURNAL ARTICLES BY FLUENT SOFTWARE USERS JA187 Computer Simulation Helps Improve Vertical Column Induced Gas Flotation (IGF) System Computer simulation has helped NATCO engineers make dramatic improvements
More informationA Computational Assessment of Gas Jets in a Bubbly Co-Flow 1
A Computational Assessment of Gas Jets in a Bubbly Co-Flow 1 Melissa Fronzeo*, 1 Michael Kinzel 1 The Pennsylvania State University, University Park, PA, USA Abstract In this effort, Computational Fluid
More informationROSE-HULMAN INSTITUTE OF TECHNOLOGY Department of Mechanical Engineering. Mini-project 3 Tennis ball launcher
Mini-project 3 Tennis ball launcher Mini-Project 3 requires you to use MATLAB to model the trajectory of a tennis ball being shot from a tennis ball launcher to a player. The tennis ball trajectory model
More informationENHANCED PARKWAY STUDY: PHASE 2 CONTINUOUS FLOW INTERSECTIONS. Final Report
Preparedby: ENHANCED PARKWAY STUDY: PHASE 2 CONTINUOUS FLOW INTERSECTIONS Final Report Prepared for Maricopa County Department of Transportation Prepared by TABLE OF CONTENTS Page EXECUTIVE SUMMARY ES-1
More informationZIN Technologies PHi Engineering Support. PHi-RPT CFD Analysis of Large Bubble Mixing. June 26, 2006
ZIN Technologies PHi Engineering Support PHi-RPT-0002 CFD Analysis of Large Bubble Mixing Proprietary ZIN Technologies, Inc. For nearly five decades, ZIN Technologies has provided integrated products and
More informationSIMULATION OF ENTRAPMENTS IN LCM PROCESSES
Douai, FRANCE - July 6 SIMULATION OF ENTRAPMENTS IN LCM PROCESSES René Arbter, Paolo Ermanni Centre of Structure Technologies ETH Zurich, Leonhardstr. 7, 89 Zurich, Switzerland: rarbter@ethz.ch ABSTRACT:
More informationAn Overview of Types of Isolation Valves
Isolation Valves 101 An Overview of Types of Isolation Valves To control flow without contaminating media such as blood, pharmaceuticals or reagents, a wide variety of medical devices and analytical equipment
More informationAC : MEASUREMENT OF HYDROGEN IN HELIUM FLOW
AC 2010-2145: MEASUREMENT OF HYDROGEN IN HELIUM FLOW Randy Buchanan, University of Southern Mississippi Christopher Winstead, University of Southern Mississippi Anton Netchaev, University of Southern Mississippi
More informationAppendix E-2: Microsimulation Report
Appendix E-2: Microsimulation Report London Bus Rapid Transit Transit Project Assessment Process Environmental Project Report DRAFT April 2018 P R E PA R E D BY LONDON BUS RAPID TRANSIT PROJECT TRAFFIC
More information1.2 Example 1: A simple hydraulic system
Note: It is possible to use more than one fluid in the Hydraulic library. This is important because you can model combined cooling and lubrication systems of a library. The hydraulic library assumes a
More informationRICK FAUSEL, BUSINESS DEVELOPMENT ENGINEER TURBOMACHINERY CONTROL SYSTEM DESIGN OBJECTIVES
RICK FAUL, BUSINESS DEVELOPMENT ENGINEER TURBOMACHINERY CONTROL SYSTEM DESIGN OBJECTIVES The primary design objective for any turbomachinery control system should be to maintain or maximize machine and
More informationTaranaki Tsunami Inundation Analysis. Prepared for Taranaki Civil Defence Emergency Management Group. Final Version
Taranaki Tsunami Inundation Analysis Prepared for Taranaki Civil Defence Emergency Management Group Final Version June 2012 AM 12/07 HBRC Plan Number 4362 Asset Management Group Technical Report Prepared
More informationAC : A LABORATORY EXERCISE TO DEMONSTRATE HOW TO EXPERIMENTALLY DETERMINE THE OPERATING POINT FOR A FAN
AC 2007-206: A LABORATORY EXERCISE TO DEMONSTRATE HOW TO EXPERIMENTALLY DETERMINE THE OPERATING POINT FOR A FAN Robert Edwards, Pennsylvania State University-Erie Robert Edwards is currently a Lecturer
More informationHow to Optimize the Disposal System With Staggered Analysis Using BLOWDOWN Technology. Jump Start Guide
How to Optimize the Disposal System With Staggered Analysis Using BLOWDOWN Technology Jump Start Guide Problem Statement In this guide, you will be introduced to the tools in BLOWDOWN that can be used
More informationUninformed Search (Ch )
1 Uninformed Search (Ch. 3-3.4) 3 Terminology review State: a representation of a possible configuration of our problem Action: -how our agent interacts with the problem -can be different depending on
More informationPress Release. Friction Stir Welding: Grenzebach extends its portfolio
Friction Stir Welding: Grenzebach extends its portfolio Higher dynamics, higher welding speeds, lower process forces and even higher quality welding seams and welding surfaces: at the Düsseldorf Schweissen
More informationAssignment for Next Class. Information Systems ISM Put In Nonsense, Get Out Chaos. System and Modeling Concepts. Components of a System.
Assignment for Next Class Information Systems ISM 3011 Read and prepare the case studies 1, 2, and 3. Fall 2004 Unit 2A Dr. Martin Hepp 1 Dr. Martin Hepp 2 Put In Nonsense, Get Out Chaos Accurate data
More informationCalculation of Trail Usage from Counter Data
1. Introduction 1 Calculation of Trail Usage from Counter Data 1/17/17 Stephen Martin, Ph.D. Automatic counters are used on trails to measure how many people are using the trail. A fundamental question
More informationCFD SIMULATIONS OF GAS DISPERSION IN VENTILATED ROOMS
CFD SIMULATIONS OF GAS DISPERSION IN VENTILATED ROOMS T. Gélain, C. Prévost Institut de Radioprotection et de Sûreté Nucléaire (IRSN), Saclay, France Abstract In order to better understand the risks due
More informationElectronics the Art of Blasting turned Blasting Science. Sandy Tavelli / John Alkins
Electronics the Art of Blasting turned Blasting Science Sandy Tavelli / John Alkins The Search for a Better Way Detonator technology has evolved over the decades from goose quills filled with black powder
More informationSoundCast Design Intro
SoundCast Design Intro Basic Design SoundCast and Daysim 3 Land use attributes Households & Individuals SoundCast DaySim Travel demand simulator Trips and Households, Excel Summary Sheets, EMME network
More informationEFFICIENCY OF TRIPLE LEFT-TURN LANES AT SIGNALIZED INTERSECTIONS
EFFICIENCY OF TRIPLE LEFT-TURN LANES AT SIGNALIZED INTERSECTIONS Khaled Shaaban, Ph.D., P.E., PTOE (a) (a) Assistant Professor, Department of Civil Engineering, Qatar University (a) kshaaban@qu.edu.qa
More informationDobbin Day - User Guide
Dobbin Day - User Guide Introduction Dobbin Day is an in running performance form analysis tool. A runner s in-running performance is solely based on the price difference between its BSP (Betfair Starting
More informationImprove Process Reliability
Convenient Conductivity Calibration to Meet Pharmacopeia Regulations Pharmacopeias require that conductivity measurement systems be periodically calibrated to ensure their precision. The range of accessories
More informationChapter 5 5. INTERSECTIONS 5.1. INTRODUCTION
Chapter 5 5. INTERSECTIONS 5.1. INTRODUCTION Intersections are the physical component of the roadways where two highways intersect. They are the most complex element of roadways, since it requires more
More informationEvaluating chaff fire pattern algorithms in a simulation environment. JP du Plessis Institute for Maritime Technology South Africa
Evaluating chaff fire pattern algorithms in a simulation environment JP du Plessis (jdp@imt.co.za) Institute for Maritime Technology South Africa Overview What is seduction chaff? Chaff solution algorithm
More informationAutonomous blimp control with reinforcement learning
University of Wollongong Research Online University of Wollongong Thesis Collection 1954-2016 University of Wollongong Thesis Collections 2009 Autonomous blimp control with reinforcement learning Yiwei
More informationProcess Simulator Evaluates Blower and Valve Control Strategies for WWTP Aeration
Process Simulator Evaluates Blower and Valve Control Strategies for WWTP Aeration inshare By Steve Kestel and Tilo Stahl (BioChem Technology) and Matthew Gray (Keystone Engineering Group) Introduction
More informationAnalysis of Variance. Copyright 2014 Pearson Education, Inc.
Analysis of Variance 12-1 Learning Outcomes Outcome 1. Understand the basic logic of analysis of variance. Outcome 2. Perform a hypothesis test for a single-factor design using analysis of variance manually
More informationOPTIMIZATION OF SINGLE STAGE AXIAL FLOW COMPRESSOR FOR DIFFERENT ROTATIONAL SPEED USING CFD
http:// OPTIMIZATION OF SINGLE STAGE AXIAL FLOW COMPRESSOR FOR DIFFERENT ROTATIONAL SPEED USING CFD Anand Kumar S malipatil 1, Anantharaja M.H 2 1,2 Department of Thermal Power Engineering, VTU-RO Gulbarga,
More informationIEEE RAS Micro/Nano Robotics & Automation (MNRA) Technical Committee Mobile Microrobotics Challenge 2016
IEEE RAS Micro/Nano Robotics & Automation (MNRA) Technical Committee Mobile Microrobotics Challenge 2016 OFFICIAL RULES Version 2.0 December 15, 2015 1. THE EVENTS The IEEE Robotics & Automation Society
More informationEvaluating Roundabout Capacity, Level of Service and Performance
Roundabouts with Metering Signals ITE 2009 Annual Meeting, San Antonio, Texas, USA, August 9-12, 2009 Evaluating Roundabout Capacity, Level of Service and Performance Presenter: Rahmi Akçelik rahmi.akcelik@sidrasolutions.com
More informationChapter 14 Coal Boiler Flue Gas Scrubber II
Chapter 14 Coal Boiler Flue Gas Scrubber II The Application The following case study is a continuation of the base case scenario created previous chapter. The base case scenario contained four process
More informationTechTalk. Purging for Delayed Coking. Understanding purging system design in heavy-fouling applications. Outline
Page 1 of 6 TechTalk Understanding purging system design in heavy-fouling applications Purging for Delayed Coking Outline Introduction In high-fouling applications such as heavy oil processing and What
More informationLine Following with RobotC Page 1
Line Following with RobotC Page 1 Line Following with By Michael David Lawton Introduction Line following is perhaps the best way available to VEX Robotics teams to quickly and reliably get to a certain
More informationDistributed Control Systems
Unit 41: Unit code Distributed Control Systems M/615/1509 Unit level 5 Credit value 15 Introduction With increased complexity and greater emphasis on cost control and environmental issues, the efficient
More informationAnti-g-Garment Development and Testing
Anti-g-Garment Development and Testing 1) Anti-g-Garment. Introduction and Use in space flights. A g-suit, or anti-g suit, is a flight suit worn by pilots and astronauts who are subject to high levels
More informationDesign of Turn Lane Guidelines
Design of Turn Lane Guidelines CTS Transportation Research Conference May 24, 2012 Howard Preston, PE Minnesota Department of Transportation Research Services Office of Policy Analysis, Research & Innovation
More informationIncorporating 3D Suction or Discharge Plenum Geometry into a 1D Compressor Simulation Program to Calculate Compressor Pulsations
Purdue University Purdue e-pubs International Compressor Engineering Conference School of Mechanical Engineering 2012 Incorporating 3D Suction or Discharge Plenum Geometry into a 1D Compressor Simulation
More informationUNITY 2 TM. Air Server Series 2 Operators Manual. Version 1.0. February 2008
UNITY 2 TM Air Server Series 2 Operators Manual Version 1.0 February 2008 1. Introduction to the Air Server Accessory for UNITY 2...2 1.1. Summary of Operation...2 2. Developing a UNITY 2-Air Server method
More informationCS 221 PROJECT FINAL
CS 221 PROJECT FINAL STUART SY AND YUSHI HOMMA 1. INTRODUCTION OF TASK ESPN fantasy baseball is a common pastime for many Americans, which, coincidentally, defines a problem whose solution could potentially
More informationInternational Journal of Technical Research and Applications e-issn: , Volume 4, Issue 3 (May-June, 2016), PP.
DESIGN AND ANALYSIS OF FEED CHECK VALVE AS CONTROL VALVE USING CFD SOFTWARE R.Nikhil M.Tech Student Industrial & Production Engineering National Institute of Engineering Mysuru, Karnataka, India -570008
More informationRoundabout Design 101: Principles, Process, and Documentation
Design 101: Principles, Process, and Documentation Part 1 March 7, 2012 Well designed roundabouts should minimize accidents, delay and costs for everyone using the intersection. This session covers the
More informationGeometric Categories as Intersection Safety Evaluation Tools
Geometric Categories as Intersection Safety Evaluation Tools John R. Campbell Ayres Associates N19 W24075 Riverwood Drive, Suite 300 Waukesha, WI 53188 campbellj@ayresassociates.com Keith K. Knapp Engineering
More informationS-CO 2 Brayton Recompression Loop Design and Control
S-CO 2 Brayton Recompression Loop Design and Control 1) Background 2) Recommended Design Features 3) Modeling Strategy IST Model Changes Transient Results Prepared by: Mike Hexemer Advanced Concepts Knolls
More informationFree Surface Flow Simulation with ACUSIM in the Water Industry
Free Surface Flow Simulation with ACUSIM in the Water Industry Tuan Ta Research Scientist, Innovation, Thames Water Kempton Water Treatment Works, Innovation, Feltham Hill Road, Hanworth, TW13 6XH, UK.
More informationErmenek Dam and HEPP: Spillway Test & 3D Numeric-Hydraulic Analysis of Jet Collision
Ermenek Dam and HEPP: Spillway Test & 3D Numeric-Hydraulic Analysis of Jet Collision J.Linortner & R.Faber Pöyry Energy GmbH, Turkey-Austria E.Üzücek & T.Dinçergök General Directorate of State Hydraulic
More informationLesson 8 Piles Bearing & Acceptance Transcript. Welcome to the Pile Driving Inspector Course. This is Lesson 8 Piles Bearing & Acceptance.
Lesson 8 Piles Bearing & Acceptance Transcript Welcome to the Pile Driving Inspector Course. This is Lesson 8 Piles Bearing & Acceptance. To begin, select the start button or press Shift+N on your keyboard.
More informationDIGITAL SOLUTIONS TRAINING CATALOGUE. QRA and CFD simulation. Phast, Safeti and KFX SAFER, SMARTER, GREENER
DIGITAL SOLUTIONS TRAINING CATALOGUE QRA and CFD simulation Phast, Safeti and KFX SAFER, SMARTER, GREENER 02 PHAST, SAFETI AND KFX Training catalogue Global training Our increased focus on global training,
More informationThe Incremental Evolution of Gaits for Hexapod Robots
The Incremental Evolution of Gaits for Hexapod Robots Abstract Gait control programs for hexapod robots are learned by incremental evolution. The first increment is used to learn the activations required
More informationAnalysis of Highland Lakes Inflows Using Process Behavior Charts Dr. William McNeese, Ph.D. Revised: Sept. 4,
Analysis of Highland Lakes Inflows Using Process Behavior Charts Dr. William McNeese, Ph.D. Revised: Sept. 4, 2018 www.spcforexcel.com Author s Note: This document has been revised to include the latest
More informationAUTOMATIC DREDGING PROFILE AND CONTOUR CONTROL
AUTOMATIC DREDGING PROFILE AND CONTOUR CONTROL Jay Wise 1 ABSTRACT Phillips and Jordan, a leading excavating and disaster recovery contractor, was faced with the challenge to manage a civil contract involving
More informationINTRODUCTION TO PATTERN RECOGNITION
INTRODUCTION TO PATTERN RECOGNITION 3 Introduction Our ability to recognize a face, to understand spoken words, to read handwritten characters all these abilities belong to the complex processes of pattern
More informationi) Linear programming
Problem statement Sailco Corporation must determine how many sailboats should be produced during each of the next four quarters (one quarter = three months). The demand during each of the next four quarters
More informationCOST ESTIMATION. Fully Allocated Causal Factor Models Temporal Variation Models Incremental Fixed Variable Cost Models
COST ESTIMATION Outline 1. Roles for Cost Models 2. Conventional Model Types Fully Allocated Causal Factor Models Temporal Variation Models Incremental Fixed Variable Cost Models 3. New Approaches HASTUS
More informationA STUDY OF THE LOSSES AND INTERACTIONS BETWEEN ONE OR MORE BOW THRUSTERS AND A CATAMARAN HULL
A STUDY OF THE LOSSES AND INTERACTIONS BETWEEN ONE OR MORE BOW THRUSTERS AND A CATAMARAN HULL L Boddy and T Clarke, Austal Ships, Australia SUMMARY CFD analysis has been conducted on a 100m catamaran hull
More informationA Chiller Control Algorithm for Multiple Variablespeed Centrifugal Compressors
Purdue University Purdue e-pubs International Compressor Engineering Conference School of Mechanical Engineering 2014 A Chiller Control Algorithm for Multiple Variablespeed Centrifugal Compressors Piero
More informationCOST COMPARISON OF FSW AND MIG WELDED ALUMINIUM PANELS
COST COMPARISON OF FSW AND MIG WELDED ALUMINIUM PANELS Jukka Mononen 1 Mika Sirén 2 Hannu Hänninen 1 jukka.t.mononen@hut.fi mika.siren@vtt.fi hannu.hanninen@hut.fi 1) Helsinki University of Technology
More informationComputer Integrated Manufacturing (PLTW) TEKS/LINKS Student Objectives One Credit
Computer Integrated Manufacturing (PLTW) TEKS/LINKS Student Objectives One Credit Suggested Time Ranges First Six Weeks History of Manufacturing PFD 1.1(A) The student will describe why and how manufacturing
More informationReferences: Hi, License: Feel free to share these questions with anyone, but please do not modify them or remove this message. Enjoy the questions!
Hi, To assist people that we work with in Scrum/Agile courses and coaching assignments, I have developed some Scrum study-questions. The questions can be used to further improve your understanding of what
More informationAn Analysis of the Travel Conditions on the U. S. 52 Bypass. Bypass in Lafayette, Indiana.
An Analysis of the Travel Conditions on the U. S. 52 Bypass in Lafayette, Indiana T. B. T readway Research Assistant J. C. O ppenlander Research Engineer Joint Highway Research Project Purdue University
More informationACCURATE PRESSURE MEASUREMENT FOR STEAM TURBINE PERFORMANCE TESTING
ACCURATE PRESSURE MEASUREMENT FOR STEAM TURBINE PERFORMANCE TESTING Blair Chalpin Charles A. Matthews Mechanical Design Engineer Product Support Manager Scanivalve Corp Scanivalve Corp Liberty Lake, WA
More informationOIL AND GAS INDUSTRY
This case study discusses the sizing of a coalescer filter and demonstrates its fouling life cycle analysis using a Flownex model which implements two new pressure loss components: - A rated pressure loss
More informationBioequivalence: Saving money with generic drugs
The Right Stuff: Appropriate Mathematics for All Students Promoting the use of materials that engage students in meaningful activities that promote the effective use of technology to support mathematics,
More informationGas Accumulation Potential & Leak Detection when Converting to Gas
Gas Accumulation Potential & Leak Detection when Converting to Gas Coal to Gas / PCUG Conference Chattanooga, TN October 29, 2013 Robert G. Mudry, P.E. Airflow Sciences Corporation Introduction Coal to
More informationAnalysis of Pressure Rise During Internal Arc Faults in Switchgear
Analysis of Pressure Rise During Internal Arc Faults in Switchgear ASANUMA, Gaku ONCHI, Toshiyuki TOYAMA, Kentaro ABSTRACT Switchgear include devices that play an important role in operations such as electric
More informationRanger Walking Initiation Stephanie Schneider 5/15/2012 Final Report for Cornell Ranger Research
1 Ranger Walking Initiation Stephanie Schneider sns74@cornell.edu 5/15/2012 Final Report for Cornell Ranger Research Abstract I joined the Biorobotics Lab this semester to gain experience with an application
More informationFIRE PROTECTION. In fact, hydraulic modeling allows for infinite what if scenarios including:
By Phil Smith, Project Manager and Chen-Hsiang Su, PE, Senior Consultant, Lincolnshire, IL, JENSEN HUGHES A hydraulic model is a computer program configured to simulate flows for a hydraulic system. The
More informationAn Engineering Approach to Precision Ammunition Development. Justin Pierce Design Engineer Government and International Contracts ATK Sporting Group
An Engineering Approach to Precision Ammunition Development Justin Pierce Design Engineer Government and International Contracts ATK Sporting Group 1 Background Federal Premium extensive experience with
More informationThermodynamic Modeling and Mechanical Design of a Liquid Nitrogen Vaporization and Pressure Building Device
Thermodynamic Modeling and Mechanical Design of a Liquid Nitrogen Vaporization and Pressure Building Device Brian J. Leege A thesis submitted in partial fulfillment of the requirements for the degree of
More informationIT S HOW THE GAME IS ONE! Introducing Sync
Introducing Sync Sync is Brunswick s revolutionary new scoring and management system. It was developed with one goal in mind: to help centers increase sales and profits through addressing their most pressing
More informationGMS 10.0 Tutorial SEAWAT Viscosity and Pressure Effects Examine the Effects of Pressure on Fluid Density with SEAWAT
v. 10.0 GMS 10.0 Tutorial SEAWAT Viscosity and Pressure Effects Examine the Effects of Pressure on Fluid Density with SEAWAT Objectives Learn how to simulate the effects of viscosity and how pressure impacts
More informationAvailable online at Procedia Engineering 200 (2010) (2009)
Available online at www.sciencedirect.com Procedia Engineering 200 (2010) (2009) 000 000 2413 2418 Procedia Engineering www.elsevier.com/locate/procedia 8 th Conference of the International Sports Engineering
More informationFour common PRESSURE CALIBRATION PAIN POINTS
Four common PRESSURE CALIBRATION PAIN POINTS Pressure calibration is often critical to process control systems, helping to optimize operations and ensure plant safety. While pressure instrumentation can
More informationEffect of Argon Gas Distribution on Fluid Flow in the Mold Using Time-Averaged k-ε Models
Effect of Argon Gas Distribution on Fluid Flow in the Mold Using Time-Averaged k-ε Models B. G. Thomas, T. Shi and L. Zhang Department of Materials Science &. Engineering University of Illinois at Urbana-Champaign
More informationSALARY SURVEY OF SCRUM PROFESSIONALS sponsored by scrum alliance
SALARY SURVEY OF SCRUM PROFESSIONALS 2017-2018 sponsored by TABLE OF CONTENTS 03 WELCOME FROM BENNIE COVINGTON 04 EXECUTIVE SUMMARY 06 ENTRY TO SCRUM 07 EDUCATION 08 GROWTH OF SCRUM PRACTICE 09 EXPERIENCED
More informationA Novel Approach to Evaluate Pedestrian Safety at Unsignalized Crossings using Trajectory Data
A Novel Approach to Evaluate Pedestrian Safety at Unsignalized Crossings using Trajectory Data Ting Fu Supervisor: Luis Miranda-Moreno, Nicolas Saunier Ting FU Outline 1. Motivation & Literature Review
More informationOlympus Production Contour Plot
Olympus Production Contour Plot Overview An alternative to the Scale Scenario calculation is the Contour Diagram. The conditions defined in the Scale Scenario are specific to production locations (wellhead,
More informationSoftware Engineering. M Umair.
Software Engineering M Umair www.m-umair.com Advantages of Agile Change is embraced With shorter planning cycles, it s easy to accommodate and accept changes at any time during the project. There is always
More informationStandard 3.1 The student will plan and conduct investigations in which
Teacher Name: Tammy Heddings Date: April 04, 2009 Grade Level: 3-6 Subject: Science Time: 30 minutes Concept: Scientific Investigation Topic: Variables SOLs: Standard 3.1 The student will plan and conduct
More informationMotion Control of a Bipedal Walking Robot
Motion Control of a Bipedal Walking Robot Lai Wei Ying, Tang Howe Hing, Mohamed bin Hussein Faculty of Mechanical Engineering Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia. Wylai2@live.my
More informationDESIGN OPTIMIZATION OF WORK ROLL CHOCK AND BACKUP ROLL CHOCK IN COLD ROLLING MILL
DESIGN OPTIMIZATION OF WORK ROLL CHOCK AND BACKUP ROLL CHOCK IN COLD ROLLING MILL Tukesh Sahu 1, Prof. G.R.Kesheory 2 1M.Tech Scholar, Department of Mechanical Engineering, VITS Indore, MP, India 2Assistant
More informationGas Transportation Planning System in the Department of Economy of Gazprom
Gas Transportation Planning System in the Department of Economy of Gazprom Victor Dochin Deputy head of the Department, Head of gas balance section Gazprom! The company is the world's largest gas company,
More informationUNIVERSITY OF WATERLOO
UNIVERSITY OF WATERLOO Department of Chemical Engineering ChE 524 Process Control Laboratory Instruction Manual January, 2001 Revised: May, 2009 1 Experiment # 2 - Double Pipe Heat Exchanger Experimental
More informationCharacterizing Flow Losses Occurring in Air Vents and Ejector Pins in High Pressure Die Castings
This paper is subject to revision. Statements and opinions advanced in this paper or during presentation are the author s and are his/her responsibility, not the Association s. The paper has been edited
More informationInfrared Thermal Imaging, Inc.
www.itimaging.com Infrared Inspection Data and Addressing Discrepancies in A Fired Heater Program By Ty Keeth Infrared inspection of fired heaters has quickly become the standard for fired heater inspection.
More informationRescue Rover. Robotics Unit Lesson 1. Overview
Robotics Unit Lesson 1 Overview In this challenge students will be presented with a real world rescue scenario. The students will need to design and build a prototype of an autonomous vehicle to drive
More informationAmmonia Synthesis with Aspen Plus V8.0
Ammonia Synthesis with Aspen Plus V8.0 Part 2 Closed Loop Simulation of Ammonia Synthesis 1. Lesson Objectives Review Aspen Plus convergence methods Build upon the open loop Ammonia Synthesis process simulation
More informationAn Analysis of Reducing Pedestrian-Walking-Speed Impacts on Intersection Traffic MOEs
An Analysis of Reducing Pedestrian-Walking-Speed Impacts on Intersection Traffic MOEs A Thesis Proposal By XIAOHAN LI Submitted to the Office of Graduate Studies of Texas A&M University In partial fulfillment
More informationElimination of Percent Level H 2 S Calibration Gas from Flare Gas Monitoring Systems Measuring Total Sulfur, H 2 S and BTU.
Elimination of Percent Level H 2 S Calibration Gas from Flare Gas Monitoring Systems Measuring Total Sulfur, H 2 S and BTU. Control Analytics, Inc 6017 Enterprise Dr Export, PA 15632 (724) 387 CEMS (2367)
More information1 Currents. TAKE A LOOK 2. Read a Map In what direction does the Gulf Stream flow?
CHAPTER 5 1 Currents SECTION The Movement of Ocean Water BEFORE YOU READ After you read this section, you should be able to answer these questions: What factors affect ocean currents? Why are ocean currents
More informationName: Class: Date: (First Page) Name: Class: Date: (Subsequent Pages) 1. {Exercise 5.07}
Name: Class: Date: _ (First Page) Name: Class: Date: _ (Subsequent Pages) 1. {Exercise 5.07} The probability distribution for the random variable x follows. Excel File: data05 07.xls a. f(x) is greater
More informationIon-atom interactions in a gas jet - coupling of a gas catcher to a linear RFQ cooler
Ion-atom interactions in a gas jet - coupling of a gas catcher to a linear RFQ cooler Emil Traykov, IPHC, SIMION Day, GANIL 11/06/2015 Several existent add-on models allow the inclusion of a gas-ion interaction
More informationCOMPARISON DRIVO - DIRETO
COMPARISON DRIVO - DIRETO EN DRIVO Interactive hometrainer with direct transmission Simply choose the course or the training program and Drivo will automatically adjust resistance. Simulates Challenging
More informationHEATEC TEC-NOTE. Setting Siemens Pressure Transmitter. Used on Heatec Vertical Asphalt Tanks. Publication No , Revised
HEATEC TEC-NOTE, Revised 1-5-15 Setting Siemens Pressure Transmitter Used on Heatec Vertical Asphalt Tanks This document provides information on setting Siemens pressure transmitters used on Heatec vertical
More informationPEPSE Modeling of Triple Trains of Turbines Sending Extraction Steam to Triple Trains of Feedwater Heaters
PEPSE Modeling of Triple Trains of Turbines Sending Extraction Steam to Triple Trains of Feedwater Heaters Gene L. Minner, PhD SCIENTECH, Inc 440 West Broadway Idaho Falls, ID 83402 ABSTRACT This paper
More informationOPTIMIZING THE LENGTH OF AIR SUPPLY DUCT IN CROSS CONNECTIONS OF GOTTHARD BASE TUNNEL. Rehan Yousaf 1, Oliver Scherer 1
OPTIMIZING THE LENGTH OF AIR SUPPLY DUCT IN CROSS CONNECTIONS OF GOTTHARD BASE TUNNEL Rehan Yousaf 1, Oliver Scherer 1 1 Pöyry Infra Ltd, Zürich, Switzerland ABSTRACT Gotthard Base Tunnel with its 57 km
More information