PALLET STORAGE AND RETRIEVAL SYSTEM
|
|
|
- Horatio Payne
- 9 years ago
- Views:
Transcription
1 PALLET STORAGE AND RETRIEVAL SYSTEM The materal n ths chapter wll focus on pallet load storage and retreval operatons n warehouse. Ths handlng unt s very often present n warehousng processes BUT, WHEN WE ARE TALKING ABOUT PALLET WHAT DOES IT MEAN? Usually, t s somethng lke that A lot of dfferent models are developed and materals used Dfferent materals, szes, shapes, and somethng new Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 1
2 Dfferent palletzng systems are developed Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006
3 The materal n ths chapter wll focus on pallet load storage and retreval operatons n warehouse. Ths handlng unt s very often present n warehousng processes PALLET STORAGE SYSTEMS The most popular pallet storage systems are Block stackng Stackng frames Sngle-deep selectve pallet rack Double-deep pallet rack Drve-n rack Drve-thru Pallet-flow rack Push-back rack Moble racks Also, t could be found deep-lne racks as well as some specal constructons Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 3
4 Block stackng Typcally loads stacked on top of each other and stored on the floor n storage lanes, to 10 loads deep. Stacks may range a heght dependng a lot of factors (safe lmts, weght, pallet condtons ) Typcal queston s concerned on lne depth Frst queston of the lane Let w, d are standard pallet wdth and depth Lane s x pallets deep g gap between adjacent lnes a asle wdth, then footprnt of the lane (dedcated for a sngle SKU) s (g+w)(dx+a/) We have to store N pallets where n dfferent tems to be stored In floor storage SKU s stored wth z x pallets per lane and occupes [q / (z x)] lnes. Assumng that average about half of each SKU s present n the warehouse, there are lnes occuped. To elmnate (mnmze) roundng max. error, we assume that lne occuped for tem could be expresses as [q / ( z x)] + 1/ N n q 1 Multplyng by the footprnt of a lane gves average floor area S occuped by whole populaton of SKUs: n q 1 a ( ) (g w) (d x ) z x 1 Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 4
5 Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 5, z q x a n d follows : 0, ) x z 4 q a d ( w) (g dx ds ) 4 a x z 4 q a x d z q ( w) (g S ) a x (d w) (g ) 1 x z q ( S n 1 n 1 n 1 n 1 Example: Asle a = 4m, Pallet (w d) =1, 0,8 m n = 3 n 1 * z q n d a L (x) SKU q z A 50 3 B 40 4 C 36 (pallets) * 6 6,06 6,68 0,91 ) ( 3 0,8 4 L Of course, n practce, d has to be corrected (typcally addng at least 0,1 m) The result then follows settng the dervate of average floor space S to zero and solvng for optmal lne depth x:
6 Ths system support FILO dscplne, when nventory turns n large ncrements Concernng lmtatons, generated wth loads removed from a storage lane, a space loss phenomenon referred to as honeycombng occurs. That s the reason that lne depth must be carefully determned. The nvestment n a block system s low, near nfnte flexblty for floor space confguraton Pallet stackng frames Stackng frames are commonly used when loads are not stackable and other rackng alternatves are not justfable. They are useful to ncrease storage densty as normally open floor-space. A sngle stackng frame costs $100 - $300 Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 6
7 Sngle deep (selectve) pallet rack They are smple metal constructon provdng mmedate (pck-face) access to each unt (wthout honeycombng) 100% FIFO enabled. Stackng heght s not lmted by stackablty, (t could be up to 40 m), dependng on materal handlng system nvolved. Typcal prce of rack poston s $40 - $50. Major dsadvantage s amount of space devoted to asles. Most storage systems beneft from the use of at least some selectve pallet rack for SKUs whose storage requrements s less then 3 to 5 pallet loads. Pallet Rack Accessores for Maxmum Versatlty Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 7
8 Asle wdth s very mportant. There are many techncal solutons n fork-lft technques Here s one comparson > m 3,5 m,5 m Vehcle Type Space Utlzaton Productvty Cost Flexblty Standard Wde Asle Forklft Baselne Narrow Asle Reach +0% to +5% Narrow Asle Double Deep Reach -0% to +60% VNA Turret +40% to +50% VNA Swng Mast or Bend +35% to +45% $ $ $ $ $ $ $ $ $ $ $ $ $ Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 8
9 Double deep pallet rack The advantage of two deep pallet rack s that fewer asles are needed (50% asle savngs acheved versus sngle deep selectve rack. But, here s utlzaton les due to honeycombng. Ths type of rack s used when the storage requrement for SKU s >5 pallets, when product s receved and pcked frequently n multples of pallets. Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 9
10 Drve n rack Drve n racks extend the reducton of asle space begun wth double deep pallet rack by provdng storage lanes to 10 load deep and 3 5 loads hgh; constructon enables a lft truck to drve nto the rack several pallet postons and store/retreve a pallet. Dsadvantages are a reducton of lft truck travel speed and honeycombng losses; LIFO Drve n rack s best used for slow to medum velocty SKUs wth 0 or more pallets Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
11 Drve thru rack Drve thru rack are smlarly drve n rack that s accessble from both sdes of the rack. It s for stagng loads n a flow thru fashon where a pallet s loaded at one end and retreved at the other end. FIFO s also acheved. Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
12 Pallet flow rack In pallet flow rack loads are conveyed (FIFO) on dfferent types of conveyors, form one end of storage lane to the other. As a load s pcked, the next load (f any) advances to pck face. The man purpose of pallet flow rack s to provde hgh throughput pallet storage and retreval and good space utlzaton. Prce s the major dsadvantage: $00 - $300 per storage poston. Push back rack Ths type provdes LIFO to 5 pallets deep lne. Durng storng, force of putaway vehcle pushes the other loads n the lane back to create room for the addtonal load. As a load s removed from the front of a storage lane, the weght of remanng automatcally advances remanng loads to the rack face. Push back racks are approprate for medum to fast movng SKUs. Cost s n the range of $150 per pallet poston. Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 1
13 Moble rack Essentally, they are sngle-deep pallet racks on wheels and tracks permttng entre row of racks to move away from adjacent rack rows. As result, les then 10% OF floor space s devoted to asles and the storage densty s the hghest. But productvty of pallet retreval s lowest. So, they are acceptable where space s expensve, wth slow movng SCUs. The costs are typcally n range of $50 per pallet poston. Pallet storage system selecton Fgure s desgned to assst n storage system confguraton. The example s taken from partcular case and cannot be generalzed because the preference regons vary wdely as a functon of the cost and avalablty of labor and space. Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
14 PALLET STORAGE/RETRIEVAL SYSTEM The most popular pallet S/R systems are based on: Walke trucks Counterbalance lft truck Straddle trucks Straddle reach trucks Sdeloader trucks Hybrd trucks Automated storage and retreval (AS/RS) systems Walke trucks Walke trucks enables a pallet to be transported on a shorter dstances, and some types enables a pallet to be lfted and stacked. They are typcally approprate where short dstances, low vertcal storage heght and low cost solutons and low throughput are desred. Some are motorzed and desgned for hgher stackng (walke stackers) Pallet truck Pallet jack Motorzed hand truck Walke low lft Motorzed hand/rder Walke low lft rder Motorzed walke stacker Walke stacker manually powered Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
15 Counterbalanced lft trucks They can be gas, ol or battery powered. Besdes forks, other attachments may be used. Lftng heght s typcally below 7 7,5 m and capacty up to 50 t. They are used ordnary for selectve pallet racks, push back but they are used as well for putaway/retreve operatons as for truck load/unload operatons. Flexblty, coupled wth relatve low cost make them for benchmark for all pallet retreval vehcles. The major drawback s wde turnng radus and wde asles (wth 1 t capacty around 3,5 m). Straddle trucks Ths truck provdes load and vehcle stablty usng outrggers to straddle the pallet load, nstead a counterbalanced weght, resultng wth asle wth,5 3 m. It s necessary to support the floor level load on rack beams. Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
16 Straddle reach trucks They are Developed from conventonal straddle trucks by shortenng the outrggers and provdng reach capablty wth two type of mechansms (fork and mast reach). So they do not need to be drven under the floor load level to enable storage poston. Also, double deep reach truck s avalable. Sdeloadng trucks A sdeloadng truck loads and unloads rack from one sde, thus elmnatng the need to turn n the asle to access storage postons. Ether mast moves on a set of tracks transversely or the fork project from a fxed mast on a pantograph. The major drawback s the need to enter the correct end of the asle to access a partcular locaton, thus addng routng complexty. Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
17 Turret trucks Turret trucks (swngmast or swngreach models) do not requre the vehcle to make a turn wthn the asle to store or retreve pallet. Load s lfted by forks that swng on the mast, a mast that swngs from the vehcle, or a shuttle fork mechansm. AS/RS Automated storage/retreval system AS/RS conssts on ntegrated that mplement storage/warehousng elements (storage medum, transport mechansm and controls) wth varous levels of automaton for fast and accurate random storage of products, wth hgh productvty. Ths s based on smultaneously vertcal and horzontal travel of S/R machne. Racks are hgh up 30m or more, S/R machne operates n narrow asle. It s connected wth recevng/shppng ponts by varous technques. Some of possble confguraton alternatves are: Double deep storage wth sngle load wdth asle Double deep storage wth double load wdth asle Deep lane storage wth sngle load wdth asle Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
18 Storage racks comparson Type of Rack Storage Pattern All Loads Accessble FIFO Retreval Prncpal Advantage Prncpal Dsadvantage Standard sngle deep yes yes - cube utl. Narrow Asle sngle deep yes yes cube utl. truck cost Deep Reach > 1 deep no no cube utl. truck cost Drve In > 1 deep no no cube utl. honeycomb loss potental Drve Thru > 1 deep no yes cube utl. honeycomb loss potental Flow Thru > 1 deep no yes cube utl. rack cost Push Back > 1 deep no no cube utl. rack cost Sldng Racks sngle deep yes yes cube utl. rack cost + T S/R tme Pallet retreval system comparson (typcal data) Counter - balance Straddle Straddle Reach Sde loader Turret AS/RS Vehcle cost $30,000 $35,000 $40,000 $75,000 $95,000 $00,000 Lft heght Capacty m 7 6, Asle wdth m 3,5,5-3 -,5 1,5-1,5-1.5 Weght capacty t 3,5,5 3 3 Lft speed m/mn Travel Speed /mn Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
19 Storage/retreval machnes use a transport shuttle to place unt loads n storage lanes that are one to seven postons deep Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester
20 ALTERNATIVE BULDING CONSTRUCTIONS FOR PALLET RACK WHs Momčlo Mljuš LM506 Warehouse management and modelng Izmr Unversty of economcs - Logstcs department Fall semester 006 0
Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy
4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.
The OC Curve of Attribute Acceptance Plans
The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4
CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol
CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL
UTILIZING MATPOWER IN OPTIMAL POWER FLOW
UTILIZING MATPOWER IN OPTIMAL POWER FLOW Tarje Krstansen Department of Electrcal Power Engneerng Norwegan Unversty of Scence and Technology Trondhem, Norway [email protected] Abstract Ths
IMPACT ANALYSIS OF A CELLULAR PHONE
4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng
2008/8. An integrated model for warehouse and inventory planning. Géraldine Strack and Yves Pochet
2008/8 An ntegrated model for warehouse and nventory plannng Géraldne Strack and Yves Pochet CORE Voe du Roman Pays 34 B-1348 Louvan-la-Neuve, Belgum. Tel (32 10) 47 43 04 Fax (32 10) 47 43 01 E-mal: [email protected]
Time Value of Money Module
Tme Value of Money Module O BJECTIVES After readng ths Module, you wll be able to: Understand smple nterest and compound nterest. 2 Compute and use the future value of a sngle sum. 3 Compute and use the
Question 2: What is the variance and standard deviation of a dataset?
Queston 2: What s the varance and standard devaton of a dataset? The varance of the data uses all of the data to compute a measure of the spread n the data. The varance may be computed for a sample of
How To Trade Water Quality
Movng Beyond Open Markets for Water Qualty Tradng: The Gans from Structured Blateral Trades Tanl Zhao Yukako Sado Rchard N. Bosvert Gregory L. Poe Cornell Unversty EAERE Preconference on Water Economcs
Course outline. Financial Time Series Analysis. Overview. Data analysis. Predictive signal. Trading strategy
Fnancal Tme Seres Analyss Patrck McSharry [email protected] www.mcsharry.net Trnty Term 2014 Mathematcal Insttute Unversty of Oxford Course outlne 1. Data analyss, probablty, correlatons, vsualsaton
SPILL PALLETS & CONTAINMENT
SPILL PALLETS & CONTAINMENT SPILL CREW SPILL PALLETS & CONTAINMENT ENCAPSULATED DATA PLATES Know your lmts - encapsulated data plates delver payload confdence All Spll Crew drum bunds, spll pallets and
DEFINING %COMPLETE IN MICROSOFT PROJECT
CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,
Number of Levels Cumulative Annual operating Income per year construction costs costs ($) ($) ($) 1 600,000 35,000 100,000 2 2,200,000 60,000 350,000
Problem Set 5 Solutons 1 MIT s consderng buldng a new car park near Kendall Square. o unversty funds are avalable (overhead rates are under pressure and the new faclty would have to pay for tself from
Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College
Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure
An MILP model for planning of batch plants operating in a campaign-mode
An MILP model for plannng of batch plants operatng n a campagn-mode Yanna Fumero Insttuto de Desarrollo y Dseño CONICET UTN [email protected] Gabrela Corsano Insttuto de Desarrollo y Dseño
The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis
The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna [email protected] Abstract.
Help is a tou ch of a button away. Telecare - keeping you safe and independent in your own home. i Personal emergency equipment
Help s a tou ch of a button away Telecare - keepng you safe and ndependent n your own home Personal emergency equpment 24/7 moble response - ncludng a dgnty savng lftng servce Professonal support Welcome
Minimal Coding Network With Combinatorial Structure For Instantaneous Recovery From Edge Failures
Mnmal Codng Network Wth Combnatoral Structure For Instantaneous Recovery From Edge Falures Ashly Joseph 1, Mr.M.Sadsh Sendl 2, Dr.S.Karthk 3 1 Fnal Year ME CSE Student Department of Computer Scence Engneerng
Rob Guthrie, Business Initiatives Specialist Office of Renewable Energy & Environmental Exports
Fnancng Solar Energy Exports Rob Guthre, Busness Intatves Specalst Offce of Renewable Energy & Envronmental Exports Export-Import Bank of the U.S. Independent, self-fundng fundng agency of the U.S. government
Damage detection in composite laminates using coin-tap method
Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea [email protected] 45 The con-tap test has the
benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).
REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or
Optimization of network mesh topologies and link capacities for congestion relief
Optmzaton of networ mesh topologes and ln capactes for congeston relef D. de Vllers * J.M. Hattngh School of Computer-, Statstcal- and Mathematcal Scences Potchefstroom Unversty for CHE * E-mal: [email protected]
Implementation of Deutsch's Algorithm Using Mathcad
Implementaton of Deutsch's Algorthm Usng Mathcad Frank Roux The followng s a Mathcad mplementaton of Davd Deutsch's quantum computer prototype as presented on pages - n "Machnes, Logc and Quantum Physcs"
Vembu StoreGrid Windows Client Installation Guide
Ser v cepr ov dered t on Cl enti nst al l at ongu de W ndows Vembu StoreGrd Wndows Clent Installaton Gude Download the Wndows nstaller, VembuStoreGrd_4_2_0_SP_Clent_Only.exe To nstall StoreGrd clent on
Traffic State Estimation in the Traffic Management Center of Berlin
Traffc State Estmaton n the Traffc Management Center of Berln Authors: Peter Vortsch, PTV AG, Stumpfstrasse, D-763 Karlsruhe, Germany phone ++49/72/965/35, emal [email protected] Peter Möhl, PTV AG,
Calculation of Sampling Weights
Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample
An Alternative Way to Measure Private Equity Performance
An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate
SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:
SPEE Recommended Evaluaton Practce #6 efnton of eclne Curve Parameters Background: The producton hstores of ol and gas wells can be analyzed to estmate reserves and future ol and gas producton rates and
Logistic Regression. Lecture 4: More classifiers and classes. Logistic regression. Adaboost. Optimization. Multiple class classification
Lecture 4: More classfers and classes C4B Machne Learnng Hlary 20 A. Zsserman Logstc regresson Loss functons revsted Adaboost Loss functons revsted Optmzaton Multple class classfcaton Logstc Regresson
Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts
Power-of-wo Polces for Sngle- Warehouse Mult-Retaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)
Hosted Voice Self Service Installation Guide
Hosted Voce Self Servce Installaton Gude Contact us at 1-877-355-1501 [email protected] www.earthlnk.com 2015 EarthLnk. Trademarks are property of ther respectve owners. All rghts reserved. 1071-07629
Politecnico di Torino. Porto Institutional Repository
Poltecnco d Torno Porto Insttutonal Repostory [Artcle] A cost-effectve cloud computng framework for acceleratng multmeda communcaton smulatons Orgnal Ctaton: D. Angel, E. Masala (2012). A cost-effectve
denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node
Fnal Report of EE359 Class Proect Throughput and Delay n Wreless Ad Hoc Networs Changhua He [email protected] Abstract: Networ throughput and pacet delay are the two most mportant parameters to evaluate
SUPPLIER FINANCING AND STOCK MANAGEMENT. A JOINT VIEW.
SUPPLIER FINANCING AND STOCK MANAGEMENT. A JOINT VIEW. Lucía Isabel García Cebrán Departamento de Economía y Dreccón de Empresas Unversdad de Zaragoza Gran Vía, 2 50.005 Zaragoza (Span) Phone: 976-76-10-00
What is Candidate Sampling
What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble
Laser Distancer LD 420. Operating instructions
Laser Dstancer LD 40 en Operatng nstructons Table of Contents Instrument Set-up - - - - - - - - - - - - - - - - - - - - - - - Introducton- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Overvew
行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告
行 政 院 國 家 科 學 委 員 會 補 助 專 題 研 究 計 畫 成 果 報 告 期 中 進 度 報 告 畫 類 別 : 個 別 型 計 畫 半 導 體 產 業 大 型 廠 房 之 設 施 規 劃 計 畫 編 號 :NSC 96-2628-E-009-026-MY3 執 行 期 間 : 2007 年 8 月 1 日 至 2010 年 7 月 31 日 計 畫 主 持 人 : 巫 木 誠 共 同
A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña
Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION
Chapter 4 ECONOMIC DISPATCH AND UNIT COMMITMENT
Chapter 4 ECOOMIC DISATCH AD UIT COMMITMET ITRODUCTIO A power system has several power plants. Each power plant has several generatng unts. At any pont of tme, the total load n the system s met by the
Section 5.4 Annuities, Present Value, and Amortization
Secton 5.4 Annutes, Present Value, and Amortzaton Present Value In Secton 5.2, we saw that the present value of A dollars at nterest rate per perod for n perods s the amount that must be deposted today
IS-LM Model 1 C' dy = di
- odel Solow Assumptons - demand rrelevant n long run; assumes economy s operatng at potental GDP; concerned wth growth - Assumptons - supply s rrelevant n short run; assumes economy s operatng below potental
Many e-tailers providing attended home delivery, especially e-grocers, offer narrow delivery time slots to
Vol. 45, No. 3, August 2011, pp. 435 449 ssn 0041-1655 essn 1526-5447 11 4503 0435 do 10.1287/trsc.1100.0346 2011 INFORMS Tme Slot Management n Attended Home Delvery Nels Agatz Department of Decson and
Systems. Power Distribution. Power Distribution Systems 1.0-1. Contents
August Sheet 00.0- Power Dstrbuton Systems Contents System Desgn Basc Prncples............- Modern Electrc Power Technologes............- Goals of System Desgn....- Voltage Classfcatons; BILs Basc Impulse
VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika.
VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths user-frendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual
1. Math 210 Finite Mathematics
1. ath 210 Fnte athematcs Chapter 5.2 and 5.3 Annutes ortgages Amortzaton Professor Rchard Blecksmth Dept. of athematcal Scences Northern Illnos Unversty ath 210 Webste: http://math.nu.edu/courses/math210
Multiple stage amplifiers
Multple stage amplfers Ams: Examne a few common 2-transstor amplfers: -- Dfferental amplfers -- Cascode amplfers -- Darlngton pars -- current mrrors Introduce formal methods for exactly analysng multple
Introduction CONTENT. - Whitepaper -
OneCl oud ForAl l YourCr t c al Bus nes sappl c at ons Bl uew r esol ut ons www. bl uew r e. c o. uk Introducton Bluewre Cloud s a fully customsable IaaS cloud platform desgned for organsatons who want
Multi-Resource Fair Allocation in Heterogeneous Cloud Computing Systems
1 Mult-Resource Far Allocaton n Heterogeneous Cloud Computng Systems We Wang, Student Member, IEEE, Ben Lang, Senor Member, IEEE, Baochun L, Senor Member, IEEE Abstract We study the mult-resource allocaton
"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
Simple Interest Loans (Section 5.1) :
Chapter 5 Fnance The frst part of ths revew wll explan the dfferent nterest and nvestment equatons you learned n secton 5.1 through 5.4 of your textbook and go through several examples. The second part
14.74 Lecture 5: Health (2)
14.74 Lecture 5: Health (2) Esther Duflo February 17, 2004 1 Possble Interventons Last tme we dscussed possble nterventons. Let s take one: provdng ron supplements to people, for example. From the data,
7.5. Present Value of an Annuity. Investigate
7.5 Present Value of an Annuty Owen and Anna are approachng retrement and are puttng ther fnances n order. They have worked hard and nvested ther earnngs so that they now have a large amount of money on
ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING
ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 610-519-4390,
Project Networks With Mixed-Time Constraints
Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.
Corporate Polces & Procedures Human Resources - Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:
Forecasting the Direction and Strength of Stock Market Movement
Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye [email protected] [email protected] [email protected] Abstract - Stock market s one of the most complcated systems
APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT
APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedo-cho
Staff Paper. Farm Savings Accounts: Examining Income Variability, Eligibility, and Benefits. Brent Gloy, Eddy LaDue, and Charles Cuykendall
SP 2005-02 August 2005 Staff Paper Department of Appled Economcs and Management Cornell Unversty, Ithaca, New York 14853-7801 USA Farm Savngs Accounts: Examnng Income Varablty, Elgblty, and Benefts Brent
An RFID Distance Bounding Protocol
An RFID Dstance Boundng Protocol Gerhard P. Hancke and Markus G. Kuhn May 22, 2006 An RFID Dstance Boundng Protocol p. 1 Dstance boundng Verfer d Prover Places an upper bound on physcal dstance Does not
In some supply chains, materials are ordered periodically according to local information. This paper investigates
MANUFACTURING & SRVIC OPRATIONS MANAGMNT Vol. 12, No. 3, Summer 2010, pp. 430 448 ssn 1523-4614 essn 1526-5498 10 1203 0430 nforms do 10.1287/msom.1090.0277 2010 INFORMS Improvng Supply Chan Performance:
The Greedy Method. Introduction. 0/1 Knapsack Problem
The Greedy Method Introducton We have completed data structures. We now are gong to look at algorthm desgn methods. Often we are lookng at optmzaton problems whose performance s exponental. For an optmzaton
Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008
Rsk-based Fatgue Estmate of Deep Water Rsers -- Course Project for EM388F: Fracture Mechancs, Sprng 2008 Chen Sh Department of Cvl, Archtectural, and Envronmental Engneerng The Unversty of Texas at Austn
Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
The Safety Board recommends that the Penn Central Transportation. Company and the American Railway Engineering Association revise
V. RECOWNDATONS 4.! The Safety Board recommends that the Penn Central Transportaton Company and the Amercan Ralway Engneerng Assocaton revse ther track nspecton and mantenance standards or recommended
SPILL PALLETS & CONTAINMENT
SPILL PALLETS & CONTAINMENT SPILL CREW SPILL PALLETS & CONTAINMENT BUNDING. The safe storage, handlng and transportaton of drums, contaners, tanks, machnery and equpment n the workplace s essental n protectng
A Performance Analysis of View Maintenance Techniques for Data Warehouses
A Performance Analyss of Vew Mantenance Technques for Data Warehouses Xng Wang Dell Computer Corporaton Round Roc, Texas Le Gruenwald The nversty of Olahoma School of Computer Scence orman, OK 739 Guangtao
Schedulability Bound of Weighted Round Robin Schedulers for Hard Real-Time Systems
Schedulablty Bound of Weghted Round Robn Schedulers for Hard Real-Tme Systems Janja Wu, Jyh-Charn Lu, and We Zhao Department of Computer Scence, Texas A&M Unversty {janjaw, lu, zhao}@cs.tamu.edu Abstract
We assume your students are learning about self-regulation (how to change how alert they feel) through the Alert Program with its three stages:
Welcome to ALERT BINGO, a fun-flled and educatonal way to learn the fve ways to change engnes levels (Put somethng n your Mouth, Move, Touch, Look, and Lsten) as descrbed n the How Does Your Engne Run?
Frequency Selective IQ Phase and IQ Amplitude Imbalance Adjustments for OFDM Direct Conversion Transmitters
Frequency Selectve IQ Phase and IQ Ampltude Imbalance Adjustments for OFDM Drect Converson ransmtters Edmund Coersmeer, Ernst Zelnsk Noka, Meesmannstrasse 103, 44807 Bochum, Germany [email protected],
Site Plan / Survey Scale: 1/16" = 1'-0" 246 Ellis Ave Design Study
Proposed addtons 75 m rear yard setback sdeyard setback Lot area = 4290 sf Allowable GFA = 35% of Lot area = 1501 sf sdeyard setback Exstng house 1450 sf (approx) 55'-9" Max Buldng Length [17] Ste Plan
An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services
An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsn-yng Wu b a Professor (Management Scence), Natonal Chao
1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)
6.3 / -- Communcaton Networks II (Görg) SS20 -- www.comnets.un-bremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes
A G E N E R A L I Z E D H Y B R I D F I X E D I N C O M E AT T R I - B U T I O N M O D E L
A N D R E W C O L I N A N D K ATA L I N K I S S A G E N E R A L I Z E D H Y B R I D F I X E D I N C O M E AT T R I - B U T I O N M O D E L F L A M E T R E E T E C H N O L O G I E S P T Y LT D Copyrght
Multiple-Period Attribution: Residuals and Compounding
Multple-Perod Attrbuton: Resduals and Compoundng Our revewer gave these authors full marks for dealng wth an ssue that performance measurers and vendors often regard as propretary nformaton. In 1994, Dens
Architectures and competitive models in fibre networks
WIK-Consult Report Study for Vodafone Archtectures and compettve models n fbre networks Authors: Prof. Dr. Steffen Hoerng Stephan Jay Dr. Karl-Henz Neumann Prof. Dr. Martn Petz Dr. Thomas Plückebaum Prof.
1 Battery Technology and Markets, Spring 2010 26 January 2010 Lecture 1: Introduction to Electrochemistry
1 Battery Technology and Markets, Sprng 2010 Lecture 1: Introducton to Electrochemstry 1. Defnton of battery 2. Energy storage devce: voltage and capacty 3. Descrpton of electrochemcal cell and standard
Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic
Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange
Single and multiple stage classifiers implementing logistic discrimination
Sngle and multple stage classfers mplementng logstc dscrmnaton Hélo Radke Bttencourt 1 Dens Alter de Olvera Moraes 2 Vctor Haertel 2 1 Pontfíca Unversdade Católca do Ro Grande do Sul - PUCRS Av. Ipranga,
Problem Set 3. a) We are asked how people will react, if the interest rate i on bonds is negative.
Queston roblem Set 3 a) We are asked how people wll react, f the nterest rate on bonds s negatve. When
Allocating Collaborative Profit in Less-than-Truckload Carrier Alliance
J. Servce Scence & Management, 2010, 3: 143-149 do:10.4236/jssm.2010.31018 Publshed Onlne March 2010 (http://www.scrp.org/journal/jssm) 143 Allocatng Collaboratve Proft n Less-than-Truckload Carrer Allance
Proceedings of the Annual Meeting of the American Statistical Association, August 5-9, 2001
Proceedngs of the Annual Meetng of the Amercan Statstcal Assocaton, August 5-9, 2001 LIST-ASSISTED SAMPLING: THE EFFECT OF TELEPHONE SYSTEM CHANGES ON DESIGN 1 Clyde Tucker, Bureau of Labor Statstcs James
MONITORING METHODOLOGY TO ASSESS THE PERFORMANCE OF GSM NETWORKS
Electronc Communcatons Commttee (ECC) wthn the European Conference of Postal and Telecommuncatons Admnstratons (CEPT) MONITORING METHODOLOGY TO ASSESS THE PERFORMANCE OF GSM NETWORKS Athens, February 2008
Feasibility of Using Discriminate Pricing Schemes for Energy Trading in Smart Grid
Feasblty of Usng Dscrmnate Prcng Schemes for Energy Tradng n Smart Grd Wayes Tushar, Chau Yuen, Bo Cha, Davd B. Smth, and H. Vncent Poor Sngapore Unversty of Technology and Desgn, Sngapore 138682. Emal:
TECHNICAL NOTES 4 VIBRATING SCREENS
TECHNICAL NOTES 4 VIBRATING SCREENS Copyrght R P Kng 2000 SIZE CLASSIFICATION It s always necessary to control the sze characterstcs of partculate materal that s fed to process equpment that separates
Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application
Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdo-dong,
INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS
21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech-2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS
Formulating & Solving Integer Problems Chapter 11 289
Formulatng & Solvng Integer Problems Chapter 11 289 The Optonal Stop TSP If we drop the requrement that every stop must be vsted, we then get the optonal stop TSP. Ths mght correspond to a ob sequencng
FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES
FREQUENCY OF OCCURRENCE OF CERTAIN CHEMICAL CLASSES OF GSR FROM VARIOUS AMMUNITION TYPES Zuzanna BRO EK-MUCHA, Grzegorz ZADORA, 2 Insttute of Forensc Research, Cracow, Poland 2 Faculty of Chemstry, Jagellonan
