The Grapes of Wrath by John St... free essay sample

The Grapes of Wrath by John Steinbeck has many themes that most readers can relate to. The importance of the fambly or family, the group, is always stressed throughout the book. Staying together and suffering together in these rough times is certainly better than suffering alone. The Joad family used to have a farm in Oklahoma, but because of the dust bowl they fled to California in hopes that they could start over again. They didnt have much money or supplies, just themselves what they could fit in the truck with them. They all had dreams of eating peaches and grapes right off the vine. Grandpa Joad never got to feel the sweet juice drip down his chin, because died from a stroke on the side of the road. Two people also moving west, the Wilsons, lent the Joad family their tent to the family to tend to the dying man. We will write a custom essay sample on The Grapes of Wrath by John St or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page They said, Were proud to help. I aint felt sosafe in a long time. People needsto help (Steinbeck 141) They would ask the Joads to help with their car. Al joad figured out that they would need another connecting rod. Mr. Joad suggests that the group should split up while the car gets fixed. Mrs. Joad, the mother of the protagonist, threatened him with a jack handle saying the group cant split up. Mrs. Joad is the cornerstone of the family. Mas strength is what allows the family to hold up as long as they do. (Monika 1) Both of these actions, one of kindness and one of desperation, show the bonds between these people. The Wilsons were strangers on the side of the road. They didnt have to help each other, treating to a dying man or fixing a car, but they did because were all people. They realized that they had more in common than they thought and stuck together for a while. Much later in the book after a shopkeeper gives Mrs Joad a little more than she can afford, she says,Learnin it all a time, ever day. If youre in trouble or hurt or needgo to poor people. Theyre the only ones thatll helpthe only ones. (Steinbeck 376) We can only assume that she is referring back to the Wilsons and all the other people in other communities taking care of each other because the government wouldnt. Family is all the Joad family thought they had, but not their sense of community. They continue to work themselves into new groups of their fellow workers to continue to take care of each other as they always had.This theme continues in the book when Tom Joad was reunited with Jim Casey, the preacher from his childhood. Casey told Tom that he was leading a strike because workers wage rates dropped too low to feed a family. Casey was killed by people who wanted to break the strike, prevent these workers from living good lives.Mas worst fears came true when Tom kills a man and has to go into hiding†¦ (Brooks 1) Tom had to run away for the safety of his family. He tells his mom about what Casey had told him. But now I been thinkin what he said, an I can remember—all of it. Says†¦ But I know now a fella aint no good alone. (Steinbeck 418) He understands that everyone is struggling to be getting these jobs that the Joads have luckily been able to get. At first, Tom is intensely individualistic, interested mainly in making his own way. (Mazzeno 1) When Mrs. Joad tells her son that shell miss him, he tells her he will be with her in all of the struggling people. He leaves to continue the work Casey started uniting all the reds or strikers to fight injustice

Sustainability In The Peak District National Park Tourism Essays

Sustainability In The Peak District National Park Tourism Essays Sustainability In The Peak District National Park Tourism Essay Sustainability In The Peak District National Park Tourism Essay The purpose of this study is to explicate how to develop sustainability in the Peak District National Park, Castleton ( PDP ) . The study will see chiefly and concentrate on the societal portion in peak territory national park, Castleton, and alterations that can be made. First of wholly, the study will state the reader some brief history of Peak District national park, Castleton ( PDP ) and so specify the term sustainable touristry and touristry development. Then secondly, the writer will present the demand that can be done to develop sustainable touristry in Castleton and how to advance sustainable touristry in the Peak District National Park in Castleton, the literature will so urge development that can be done in Castleton and decision will be drawn. Castleton is an outstandingly pretty small town situated at the caput of the lovely Vale of Hope, in the bosom of the Derbyshire Peak District National Park. Castleton is surrounded on 3 sides by steep hills and the mighty majority of Mam Tor looms high, 2 stat mis to the north West of the small town. On a hill, overlooking Castleton is the ancient Peveril Castle Sustainable touristry can be defined as Sustainable touristry is merely sustainable development achieved through touristry. Sustainable development is economic development that takes a long-run position. It balances the benefits of economic development against environmental and societal costs ( greentourism.org.uk, 2010 ) . Sustainable Development in Castleton Sustainable touristry nastily focuses on the environment, societal and environment values. However, to accomplish sustainable development in the peak territory national park Castleton, ( PDP ) the community has to affect in the partnership. Harmonizing to Sinclair ( 2003:404 ) define as sustainable development is expected to run into the demands of the present without compromising the ability of future coevals to run into their ain demands . Sustainability is chiefly focused so that development is positive for the local people, the visitants and touristry companies. To advance touristry in Peak District National Park, Castleton they have to hold more events, activities and exhibitions by making that it will pull more visitants as it used to make. For illustration the Garland festival and the Oak apple twenty-four hours which runs every twelvemonth attracts visitants to Castleton. Castleton has to construct more cafe bars for the local people and visitants themselves. These festivals attract more visitants to Castleton and it helps better the economic system impact and besides makes the attractive force really popular. In 2001, the population in Castleton was around 1,200 ( visit Castleton.com, 2010 ) . Because visitants visit different or several Parkss so Castleton needs to convey more activities so that the finish can be sustainable. However, the communities do non hold to destruct the wild life in the country with hike and walking in the country. In the other manus, the community has proctor and step the sustainable touristry in the country. Harmonizing to the Miller and Ward ( 2005:177 ) stated that since 1993, the WTO has organized sustainable touristry monitoring pilot undertakings in different parts of the universe where WTO advisers have worked together with national and local touristry direction to develop indexs for peculiar sites . Attraction in Castleton Castleton has local attractive force, for illustration the Peveril, Castleton palace and more. The Castleton palace do non pull more visitants because it needs more betterment and development for it to pull more tourer and visitants. Peak territory national park, Castleton ( pdp ) . Castleton is a topographic point where it suite all sort of demands and people, for illustration, Education Old people John walkers Peoples who wish to remain nightlong Hikers Peveril Castle from across Cave Dale, with Mam Tor Beginning from: visit Castleton The above image nevertheless shows the local attractive force in the Peak District National Park, Castleton ( pdp ) . The palace in Castleton needs more betterment. In other manus, it will pull more visitants from the nearer villages or towns like for illustration, Edale, Buxton, bakewell and many more. By making so, it will pull occupations for the local communities. Conveyance in Castleton Castleton lies at the western terminal of the Hope Valley in the Peak District National Park, mid-way between Manchester and Sheffield. Transport in Castleton is dependable. Hope railroad station is 3km from the Centre of Castleton is served by the Manchester Sheffield railroad line with direct trains to both metropoliss, plus connexions to the remainder of the railroad system. Beginning from Castleton. Improvement in Castleton The local people and visitants in the communities has to take attention with the by non falsifying the wild life in the country. Harmonizing to Shaw and Williams ( 2004:182 ) suggested that to prolong touristry the followers can be look at: To run with engagement and consent of local communities, which of class links straight with the thoughts of communities engagement Be in place to portion net income fairly with the local community Involve communities than persons. Promoting touristry in Castleton Harmonizing to Waugh ( 2002 ) said that national park must besides further the economic and societal good being of the local communities. They are besides required to prosecute a policy of sustainable development by which they must take to better the quality of people s lives without destructing the environment ( model 16, p499 ) . To advance touristry in Castleton the community has to lend in the activities that has been brought and are taking topographic point. By making so it besides creates occupations for the local people in the town or metropolis. The publicity has to be besides enjoyed the qualities by the local communities and the visitants . The local people have participated in touristry developments. Harmonizing to Ottinger et Al ( 2005 ) suggested that to advance touristry in a certain countries the followers has to be done: It enhances International Corporation, foreign direct investing and partnerships with both private and public sectors, at all degrees. Develop plans, including instruction and preparation plan that encourage people to take part in eco- touristry to enable autochthonal and local communities to develop and profit from eco- touristry and enhance stakeholder s cooperation in touristry development . Number people who visit the peak territory national park, Castleton There are many people or visitants who visit the peak territory national park, Castleton, every twelvemonth. ANNUAL VISITS TO THE MOST POPULAR AREAS IN THE PEAK DISTRICT NATIONAL PARK A Entire Visits % Hiking % rubber-necking Lower Derwent ( inc Chatsworth ) 3,120,000 4 33 Wye Valley ( inc. Bakewell ) 2,560,000 11 18 Hope Valley ( inc. Castleton ) 2,220,000 8 15 Dove A ; Manifold Valleys 2,050,000 21 9 Upper derwent 1,240,000 13 6 Beginning from: the peak territory national park. Decision Recommendation The application of the literature suggests that the local community has to lend to prolong touristry in peak territory national extremum, Castleton ( pdp ) . The application of literature suggest that the local people has to maintain the environment clean so that it does non harm the wild life The application of the literature suggest that the local people and the visitants has to utilize public conveyance or walk to take down the air pollution The application of the literature suggests that visitants have to hold to command their pets or animate being when they visit the peak territory national park, Castleton.

Camel Rating Of Brac Bank

Camels rating system is a common phenomenon for all banking system all over the world. It is used in all over the country in the world. It is mainly used to measure a ranking position of a bank on the basis of few criteria. Camels rating system is an international bank-rating system where bank supervisory authorities rate institutions according to six factors. The six factors are represented by the acronym CAMELS. The six factors examined are as follows: C Capital adequacy A Asset quality M Management quality E Earnings L Liquidity S Sensitivity to Market Risk Bank supervisory authorities assign a score on a scale of one (best) to five (worst) for each factor to each bank. If a bank has an average score less than two it is considered to be a highquality institution, while banks with scores greater than three are considered to be less-thansatisfactory establishments. The system helps the supervisory authority identify banks that are in need of attention. Origin of Camels Rating System: There were many banks rating system available in the world. However, Camels rating system is the most successful bank rating system in the world. The ‘Uniform Financial Institutions Rating System (UFIRS)’ was created in 1979 by the bank regulatory agencies. Under the original UFIRS a bank was assigned ratings based on performance in five areas: the adequacy of Capital, the quality of Assets, the capability of Management, the quality and level of Earnings and the adequacy of Liquidity. Bank supervisors assigned a 1 through 5 rating for each of these components and a composite rating for the bank. This 1 through 5 composite rating was known primarily by the short form CAMEL. A bank received the CAMEL rate 1 or 2 for their sound or good performance in every respect of criteria. The bank which exhibited unsafe and unsound practices or conditions, critically deficient performance received the CAMEL rate 5 and that bank was of the greatest supervisory concern. While the CAMEL rating normally bore close relation to the five component ratings, it was not the result of averaging those five grades. Supervisors consider each institution’s specific 3 situation when weighing component ratings and review all relevant factors when assigning ratings to a certain extent. The process and component and composite system exist similar for all banking companies. In 1996, the UFIRS was revised and CAMEL became CAMELS with the addition of a component grade for the Sensitivity of the bank to market risk. Sensitivity is the degree to which changes in market prices such as interest rates adversely affect a financial institution. The communication policy for bank ratings was also changed at end of 1996. Starting in 1997, the supervisors were to report the component rating to the bank. Prior to that, supervisors only reported the numeric composite rating to the bank. Six Factors of Camels Ratings System: Capital Adequacy Capital adequacy focuses on the total position of bank capital. It assures the depositors that they are protected from the potential shocks of losses that a bank incurs. Financial managers maintain company’s adequate level of capitalization by following it. It is the key parameter of maintaining adequate levels of capitalization. Asset quality determines the robustness of financial institutions against loss of value in the assets. All commercial banks show the concentration of loans and advances in total assets. The high concentration of loans and advances indicates vulnerability of assets to credit risk, especially since the portion of non-performing assets is significant. Management quality of any financial institution is evaluated in terms of Capital Adequacy, Asset Quality, Management, Earnings, Liquidity and Sensitivity to market risk. Moreover, it is also depended on compliance with set norm, planning ability; react to changing situation, technical competence, leadership and administrative quality. A Sound management is the most important pre-requisite for the strength and growth of any financial institution. Earning and profitability is the prime sources of increasing capital of any financial institution. Strong earnings and profitability profile of a bank reflect its ability to support present and future operations. Increased earning ensure adequate capital and adequate capital can absorb all loses and give shareholder adequate dividends. An adequate liquidity position refers to a situation, where an institution can obtain sufficient funds, either by increasing liabilities or by converting its assets quickly at a reasonable cost. 4 It access in terms of asset and liability management. Liquidity indicators measured as percentage of demand and time liabilities (excluding interbank items) of the banks. It means that the percentage of demand and time liabilities gets a bank as per its liquid assets. The sensitivity to market risk is evaluated from changes in market prices, notably interest rates; exchange rates, commodity prices, and equity prices adversely affect a bank’s earnings and capital. Process of Camels Reporting: The reporting process of CAMELS rating is given below: Figure : Reporting Process of CAMELS rating Process: 1. Data collection of reschedule status of overdue loans from CRM, Retail, SME and Ops. 2. Data collection of lending rates and deposit rates from Treasury. Data collection of average borrowed amount and rate of interest expenses from Treasury. 4. Data collection of maturity wise investments from Treasury. 5. Collect information of training programs arranged by the Bank’s training institute from Human Resources Division. 6. Collection of other required reports and statements from other divisions. 7. Preparation of CAMELS report as per guideline of BB Core Risk Management Guidelines. 8. Meeting arranged with MANCOM. 5 Camels Rating System of Bangladesh: All over the world, CAMELS rating is a common figure to all banking industry. Like all other countries, it is also used in Bangladesh. In Bangladesh, the five components of CAMEL have been used for evaluating the five crucial dimensions of a bank’s operations that reflect in a complete institution’s financial condition, compliance with banking regulations and statutes and overall operating soundness since the early nineties. In 2006, Bangladesh Bank has upgraded the CAMEL into CAMELS. ‘Sensitivity to market risk’ or ‘S’ is the new rating component which is included in CAMEL and make it into CAMELS. The new rating component makes the system more effective and efficient. The new system needs bank’s regular condition and performance according to predetermined stress testing on asset and liability and foreign exchange exposures, procedures, rules and criteria and on the basis of the results obtained through risk-based audits under core risk management guidelines. A bank’s single CAMELS rating has come from off-site monitoring, which uses monthly financial statement information, and an on-site examination, from which bank supervisors gather further â€Å"private information† not reflected in the financial reports. The development of credit points examination result is ranging from 0 to 100. The six key performance dimensions – capital adequacy, asset quality, management, earnings, liquidity and sensitivity to market risk – are to be evaluated on a scale of 1 to 5 in ascending order. Following is a description of the graduations of rating: Rating 1 indicates strong performance: BEST rating. Rating 2 reflects satisfactory performance. Rating 3 represents performance that is flawed to some degree. Rating 4 refers to marginal performance and is significantly below average and Rating 5 is considered unsatisfactory: WORST rating. Table : Composite CAMELS and their Interpretation Rating Composite range Description Rating Analysis interpretation 1 1 to 1. 4 Strong Sound in every respect, no supervisory responses required. 2 1. 5 to 2. 4 Satisfactory Fundamentally sound with modest correctable weakness, supervisory response limited. Combination of weaknesses if not redirected will become severe. 3 2. 5 to 3. 4 Fair Watch category. Requires more than normal supervision. Immoderate weakness unless properly addressed could impair future 4 3. 5 to 4. 4 Marginal viability of the bank. Needs close supervision. High risk of failure in the near term. Under constant supervision/cease 5 4. 5 to 5 Unsatisfactory and desist order. Capital adequacy: Capital adequacy focuses on the total position of bank capital. It focuses on the risk weighted assets which proposed to protect from the potential shocks of losses that a bank might incur. It is assessed according to: the volume of risk assets, the volume of marginal and inferior assets, bank growth experience, plans, and prospects; and the strength of management in relation to all the above factors. The major financial risk like credit risk, interest rate risk and risk involved in off-balance sheet operations are absorbed by it. The CAMELS components are also required for Basel Committee of Bangladesh Bank. As regards the capital adequacy, they grouped the factors like a) size of the bank, b) volume of inferior quality assets, c) bank’s growth experience, plans and prospects, d) quality of capital, e) retained earnings, f) access to capital markets, and g) non-ledger assets and sound values not shown on books (real property at nominal values, charge-offs with firm recovery values, tax adjustments). Capital to Risk-Weighted Assets ratio (CRWA) is the most widely used indicator for capital adequacy ratio. According to Bangladesh Bank, a bank has to maintain a minimum capital adequacy ratio (CAR) of not less than 10 percent of their risk weighted assets (RWA, with at least 5 percent in core capital) or Taka 2 billion, whichever is higher. Basel II Basel II is a capital adequacy management framework for banks. Basel II is the second of the Basel Accords, which are recommendations on banking laws and regulations issued by the Basel Committee on Banking Supervision; adopted by Bangladesh Bank. The main objectives of Basel II are as follows: Promote safety and soundness in the financial systems Constitute a more comprehensive and more sensitive approach to addressing risks Better alignment of regulatory capital to underlying risk Encourages banks to improve risk management These guidelines are structured on following three aspects: a) Minimum capital requirements to be maintained by a bank against credit, market, and operational risks. b) Process for assessing the overall capital adequacy aligned with risk profile of a bank as well as capital growth plan. c) Framework of public disclosure on the position of a banks risk profiles, capital adequacy, and risk management system.

Energy and Balance Essay Example | Topics and Well Written Essays - 500 words

Energy and Balance - Essay Example Contamination of the food potions interferes with the energy requirement in the oxidation of the food. The amount of energy required in the breakdown or oxidation of the foods, which contain the carbohydrates, proteins and fats, can be obtained by computation of the energy required in breaking these food components (Hervera, et al, 2008). The figures gotten are then computed and thus the energy requirement for the oxidation of the food can easily be determined. There are specific values of energies required to break down the food components in the various portions. This implies that as the food increase in volume and mass, the amount of energy in them is higher than the ones outlined in the formulation of the energy determination in the foods contain. The determine values of the contained calories in the given foods and the feeding stuffs; will provide exact estimation of the energy present in the foods being tested. The higher the amount needed to oxidize the foods, the higher the number of calories in the foods under examination (Hervera, et al, 2008). Nitrogen balance is the measurement of the input nitrogen and the output of nitrogen within a given set of products in the production line. This involves the nitrogen being taken in by the organism and finding a possible amount of nitrogen the substance produces. The difference between the nitrogen intake and output will determine the amount of nitrogen that the substance is giving out to balance the surrounding (Moya, Tenorio & Bond, 2013). Nitrogen balance can be portrayed in the Blood Urea Nitrogen and urea concentration in urine. The urea is a component of the nitrogen balance of the substance, organism, ecosystem or environments. Energy balances is the outcome of the comparison of the amount calories taken by a body and the amount of the elements or calories taken out. The energy in, involves the energy that is taken in through eating

Affirmative action debate pt2 Thesis Example | Topics and Well Written Essays - 500 words

Affirmative action debate pt2 - Thesis Example The enforcement of affirmative action in admission into universities and higher education for those minority groups in the community will act to motivate those oppressed by the discrimination to join in the campaign for its implementation and to work even harder in school. Children of immigrant parents and children from poor families will benefit from the affirmative action. Awareness creation campaigns can be carried out through the media and at the local government level to ensure that the minority groups understand how they can benefit from the action and can therefore support the debate of implementing this action in all institutions of higher education. There has been existing stereotypes that only whites are high achievers and the elites of the US society. This has been majorly because the other races have not been having equal access to higher education equally as the white people. If affirmative action is enforced therefore, this will soon change and the stereotypes will be abolished. One way of ensuring this is by having the stereotyped races sign petitions for the implementation of this policy. If the signatures are more, the policy can be passed to be a law for all states and all institutions of higher learning. In most employment sectors (especially the prestigious jobs), there is domination by certain genders only and the other minority gender (mostly women) are crowded in lesser positions of authority. This has been the case because fewer women have been accessing certain causes in universities and colleges which may lead them to authority positions in the job market. Most women are concentrated in art courses, home economics and secretarial courses, whereas men are in the managerial and science courses. If affirmative action is present in admission into these institutions, there can be an equal number of men and women in certain professionals hence reducing the discrimination and

Assessment Of mice and men Essay Example for Free

Assessment Of mice and men Essay Of mice and men is a novel by john Steinbeck about two migrant agricultural labourers George Milton and Lennie Small. At the outstart they are working at a ranch in northern California. The ranch is a microcosm of the macrocosm that was in America at that time in 1939. During this period of failed businesses, harsh poverty, and long-term unemployment, we see how people attempted to survive on the ranch. In this essay I am going to clarify how Steinbeck presents the theme of discrimination in chapter 3. Discrimination seems particularly unpleasant on the ranch because there are lonely, isolated characters, who looking are for friends and an escape from solitariness. In chapter 3 we see discrimination in the form of racism, ageism and sexism. The victims of discrimination in this novel are: Crooks, a black stable buck; Curleys Wife, the farm owners neglected daughter-in-law; and Candy, an old, disabled housekeeper. Crooks, is terribly discriminated against because of his natural skin colour, which he has no choice to change it. Spose you couldnt go into the bunk house and play rummy cause you was black this illustrates that the migrants on the ranch discriminate against him by having him left out of the gang. Furthermore he lives in a little shack on his own. They dont treat him equally; in fact it almost feels like as if they dont see him as human being. They dont care about his feelings and emotions; nevertheless this isolation has consequently affected his mental and physical well being. Crooks is not allowed to enter the Bunk house, whereas Candys dog can. Therefore clearly this shows that they treat animals better than him. Although the dog has someone that looks out for him, crooks has no one except his books. Despite him believing that Books aint no good. Crooks had a bright childhood where he could play with white children and socialise with them, but this discrimination against him has affected him deeply. He never accepted this way of life unlike other slaves of his time, I got a right to have a light this shows that he is aware of his rights, even when he is having a simple conversation with mentally ill Lennie, who has no idea about rights not even his. Evidently this discrimination made crooks desperate for a companionship, A guy goes nuts if he aint got nobody this demonstrates that crooks has gone to the point where he is dying for a shoulder to cry on, even Lennie with a childlike brain. Dont make no difference who the guy is, longs hes with you, This implies that he doesnt care if the friend is white or black, furthermore it shows that crooks is not racist. He plays horseshoes all day as an attempt to be liked and be accepted for what he is. Similarly Candy is discriminated against because of his age. As they know that he hasnt got the physical strength to defend himself or his dog, they take advantage of him and forced him to allow his only friend to be killed. Steinbeck used this to clarify that within the society the powerful ones rule the helpless and no matter what we do there will always be evil around us. Whynt you get candy to shoot his dog. This makes candy think that this could be the prospect for him when he gets useless. It drove him to the desperation point of putting his life saving into the hands of complete strangers wanting to escape from the same ending as his beloved dog. The men on the ranch describe the dog as a stinking hound and an old bastard. Candy feels dejected as he says I wish somebody would shoot me when I become useless. He feels left out and not respected because of his age as they killed his only friend, he feels that he doesnt wish to live without his precious dog anymore. Candy, a lost old man, hes missing a hand and his most reliable and trust worthy companion. i lost my hand my hand right here on this ranch, thats why they gave me a job swampin' this worries candy that he will get fired soon because if he can no longer work he will be dispensable. Steinbeck used this character because the older generation would relate to him. Curleys wife is the only women on the ranch. Everybody makes fun of her; they dont talk to her as a friend because shes a woman. Aint I got a right to talk to nobody? Whatta they think I am anyways?.This quotation shows that she is quarantined from the other migrants just like crooks and candy they are all isolated characters. The men on the ranch dont give a chance to get to know her personally, they just labelled her a trouble maker, and being Curleys wife doesnt do her any favour. As we never hear her real name in the book it shows how belittled she is, she is seen as a property of Curleys. Steinbeck did this because back in those days men were dominant and women were just seen as house wives. The men on the ranch act on their prejudice calling her nasty names such as a rattrap, jailbait, and tart. Due to this she feels alone and discriminated against, because she is only seeking for attention to make friends, shes is not what they describe to be. Curleys wife is desperate for a companion just like candy and Crooks; she wants someone to listen to her because Curley is never around, he never gives her the attention she needs, I dont like Curley, he aint a nice fella, clearly shows that she isnt happy, she feels trapped and lonely. Due to this she wonders around the ranch looking something to do, someone to talk to. Overall in conclusion Steinbeck carefully used these types of characters, because they each represent different society at that time of the book. Racism was very high and discrimination against women and the elderly were very common. I think the novel has relevance in our culture; it portrays the issues of discrimination and racism. I think Steinbeck wrote this book to show the world that within our society we have a disgusting habit of making other feel down.

Microscopic Boundary Examination :: essays research papers

MICROSCOPIC EXAMINATION OF METALS In this experiment, our aim is examining the microstructure of metals. By studying microscopic structures of metals, we determine which material fits best to a given application. We used the most common method, optical technique, to examine the microstructure. We used a small specimen cut from the metal to be examined. To be able to see the structure clearly, we first cleaned and polished the specimen. First we start polishing with emery paper no: 1 and some finer grades. One should be careful about the coarse abrasive particles and striations from them. Cleaning and rotating the specimen 90Â ° during the transfer can prevent these. The next step is polishing, yet washing the sample before polishing gives a more successful result. Finally, we polished the specimen on a rotating cloth covered with an effective abrasive like Al2O3-Water suspension. We kept polishing until we obtained a mirror like face. After we finished polishing, the crystalline structure of the specimen, any cracks, seams, non-metallic inclusions and inhomogenities, could be revealed. Before start etching we first applied mounting process. In this step we used a matched die set. We placed our sample into the die set in the way that the rough face of the specimen was the lower surface and the polished face looked upward. We filled the die cavity with Bakelite and then we transferred our die to a mounpress. Mounting not only protects our sample but also by making its base flat and stable helps us while we are examining the sample under the microscope. In etching process, depending upon chemical composition, energy content and grain orientation, we determine the grain boundaries and the presence of chemically different phases. To reveal these micro structural details of the polished mount we used an etchant like 1% Nital.

Research on Warehouse Design

European Journal of Operational Research 203 (2010) 539–549 Contents lists available at ScienceDirect European Journal of Operational Research journal homepage: www. elsevier. com/locate/ejor Invited Review Research on warehouse design and performance evaluation: A comprehensive review Jinxiang Gu a, Marc Goetschalckx b,*, Leon F. McGinnis b a b Nestle USA, 800 North Brand Blvd. , Glendale, CA 91203, United States Georgia Institute of Technology, 765 Ferst Dr. , Atlanta, GA 30332-0205, United States a r t i c l e i n f o a b s t r a c tThis paper presents a detailed survey of the research on warehouse design, performance evaluation, practical case studies, and computational support tools. This and an earlier survey on warehouse operation provide a comprehensive review of existing academic research results in the framework of a systematic classi? cation. Each research area within this framework is discussed, including the identi? cation of the limits of previous research and of potential future research directions. O 2009 Elsevier B. V. All rights reserved.Article history: Received 5 December 2005 Accepted 21 July 2009 Available online 6 August 2009 Keywords: Facilities design and planning Warehouse design Warehouse performance evaluation model Case studies Computational tools 1. Introduction This survey and a companion paper (Gu et al. , 2007) present a comprehensive review of the state-of-art of warehouse research. Whereas the latter focuses on warehouse operation problems related to the four major warehouse functions, i. e. , receiving, storage, order picking, and shipping, this paper concentrates on warehouse design, performance evaluation, case studies, and computational support tools.The objectives are to provide an all-inclusive overview of the available methodologies and tools for improving warehouse design practices and to identify potential future research directions. Warehouse design involves ? ve major decisions as illustrated in Fig. 1: deter mining the overall warehouse structure; sizing and dimensioning the warehouse and its departments; determining the detailed layout within each department; selecting warehouse equipment; and selecting operational strategies. The overall structure (or conceptual design) determines the material ? ow pattern within the warehouse, the speci? ation of functional departments, and the ? ow relationships between departments. The sizing and dimensioning decisions determine the size and dimension of the warehouse as well as the space allocation among various warehouse departments. Department layout is the detailed con? guration within a warehouse department, for example, aisle con? guration in the retrieval area, pallet block-stacking pattern in the reserve storage area, and con? guration of an Automated Storage/Retrieval System (AS/RS). The equipment selection deci* Corresponding author. Tel. : +1 404 894 2317; fax: +1 404 894 2301. E-mail address: marc. [email  protected] gatech. edu (M. G oetschalckx). 0377-2217/$ – see front matter O 2009 Elsevier B. V. All rights reserved. doi:10. 1016/j. ejor. 2009. 07. 031 sions determine an appropriate automation level for the warehouse, and identify equipment types for storage, transportation, order picking, and sorting. The selection of the operation strategy determines how the warehouse will be operated, for example, with regards to storage and order picking. Operation strategies refer to those decisions about operations that have global effects on other design decisions, and therefore need to be considered in the design phase.Examples of such operation strategies include the choice between randomized storage or dedicated storage, whether or not to do zone picking, and the choice between sort-while-pick or sortafter-pick. Detailed operational policies, such as how to batch and route the order picking tour, are not considered design problems and therefore are discussed in Gu et al. (2007). It should be emphasized that w arehouse design decisions are strongly coupled and it is dif? cult to de? ne a sharp boundary between them. Therefore, our proposed classi? ation should not be regarded as unique, nor does it imply that any of the decisions should be made independently. Furthermore, one should not ignore operational performance measures in the design phase since operational ef? ciency is strongly affected by the design decisions, but it can be very expensive or impossible to change the design decisions once the warehouse is actually built. Performance evaluation is important for both warehouse design and operation. Assessing the performance of a warehouse in terms of cost, throughput, space utilization, and service provides feedback about how a speci? design or operational policy performs compared with the requirements, and how it can be improved. Furthermore, a good performance evaluation model can help the designer to quickly evaluate many design alternatives and narrow down the design space durin g the early design stage. Performance operational cost for each alternative is estimated using simple analytic equations. Gray et al. (1992) address a similar problem, and propose a multi-stage hierarchical approach that uses simple calculations to evaluate the tradeoffs and prune the design space to a few superior alternatives.Simulation is then used to provide detailed performance evaluation of the resulting alternatives. Yoon and Sharp (1996) propose a structured approach for exploring the design space of order picking systems, which includes stages such as design information collection, design alternative development, and performance evaluation. In summary, published research ndco4h lar02. 8659(war,. 0320Td[(pro2k evaluation methods include benchmarking, analytical models, and simulation models.This review will mainly focus on the former two since simulation results depend greatly on the implementation details and are less amenable to generalization. However, this should not obs cure the fact that simulation is still the most widely used technique for warehouse performance evaluation in the academic literature as well as in practice. Some case studies and computational systems are also discussed in this paper. Research in these two directions is very limited. However, it is our belief that more case studies and computational tools for warehouse design and operation will help to bridge the signi? ant gap between academic research and practical application, and therefore, represent a key need for the future. The study presented in this paper and its companion paper on operations, Gu et al. (2007), complements previous surveys on warehouse research, for example, Cormier (2005), Cormier and Gunn (1992), van den Berg (1999) and Rowenhorst et al. (2000). Over 250 papers are included within our classi? cation scheme. To our knowledge, it is the most comprehensive review of existing research results on warehousing.However, we make no claim that it includes all the literature on warehousing. The scope of this survey has been mainly focused on results published in available English-language research journals. The topic of warehouse location, which is part of the larger area of distribution system design, is not addressed in this current review. A recent survey on warehouse location is provided by Daskin et al. (2005). The next four sections will discuss the literature on warehouse design, performance evaluation, case studies, and computational systems, respectively. The ? al section gives conclusions and future research directions. 2. Warehouse design 2. 1. Overall structure The overall structure (or conceptual design) of a warehouse determines the functional departments, e. g. , how many storage departments, employing what technologies, and how orders will be assembled. At this stage of design, the issues are to meet storage and throughput requirements, and to minimize costs, which may be the discounted value of investment and future operating costs. We can identify only three published papers addressing overall structural design.Park and Webster (1989) assume the functions are given, and select equipment types, storage rules, and order picking policies to minimize total costs. The initial investment cost and annual J. Gu et al. / European Journal of Operational Research 203 (2010) 539–549 541 Levy (1974), Cormier and Gunn (1996) and Goh et al. (2001) consider warehouse sizing problems in the case where the warehouse is responsible for controlling the inventory. Therefore, the costs in their models include not only warehouse construction cost, but also inventory holding and replenishment cost.Levy (1974) presents analytic models to determine the optimal storage size for a single product with either deterministic or stochastic demand. Assuming additional space can be leased to supplement the warehouse, Cormier and Gunn (1996) propose closed-form solution that yields the optimal warehouse size, the optimal amount of space to lease in each period, and the optimal replenishment quantity for a single product case with deterministic demand. The multi-product case is modeled as a nonlinear optimization problem assuming that the timing of replenishments is not managed.Cormier and Gunn (1999) developed a nonlinear programming formulation for the optimal warehouse expansion over consecutive time periods. Goh et al. (2001) ? nd the optimal storage size for both single-product and multi-product cases with deterministic demand. They consider a more realistic piecewise linear model for the warehouse construction cost instead of the traditional linear cost model. Furthermore, they consider the possibility of joint inventory replenishment for the multi-product case, and propose a heuristic to ? nd the warehouse size.The effects of inventory control policies (e. g. , the reorder point and ordering quantity) on the total required storage capacity are shown by Rosenblatt and Roll (1988) using simulation. Our a bility to answer warehouse sizing questions would be signi? cantly enhanced by two types of research. First, assessing capacity requirements should consider seasonality, storage policy, and order characteristics, because these three factors interact to impact the achievable storage ef? ciency, i. e. that fraction of warehouse capacity that can actually be used effectively.Second, sizing models all employ cost models, and validation studies of these models would be a signi? cant contribution. 2. 2. 2. Warehouse dimensioning The warehouse dimensioning problem translates capacity into ? oor space in order to assess construction and operating costs, and was ? rst modeled by Francis (1967), who used a continuous approximation of the storage area without considering aisle structure. Bassan et al. (1980) extends Francis (1967) by considering aisle con? gurations. Rosenblatt and Roll (1984) integrate the optimization model in Bassan et al. 1980) with a simulation model which evaluates the s torage shortage cost, a function of storage capacity and number of zones. They assume single-command tours in order to evaluate the effect of warehouse dimension on the operational cost, and therefore their approach is not applicable to warehouses that perform multi-command operations (e. g. , interleaving put-away and retrieval, or retrieving multiple items per trip). The work discussed so far has approached the sizing and dimensioning problem assuming the warehouse has a single storage department.In reality, a warehouse might have multiple departments, e. g. , a forward-reserve con? guration, or different storage departments for different classes of Stock Keeping Units (SKUs). These different departments must be arranged in a single warehouse and compete with each other for space. Therefore, there are tradeoffs in determining the total warehouse size, allocating the warehouse space among departments, and determining the dimension of the warehouse and its departments. Research stud ying these tradeoffs in the warehouse area is scarce.Pliskin and Dori (1982) propose a method to compare alternative space allocations among different warehouse departments based on multi-attribute value functions, which explicitly capture the tradeoffs among different criteria. Azadivar (1989) proposes an approach to optimally allocate space between two departments: one is ef? cient in terms of storage but inef? cient in terms of operation, while the other is the opposite. The objective is to achieve the best system performance by appropriately allocating space between these two departments to balance the storage capacity and operational ef? iency tradeoffs. Heragu et al. (2005) consider a warehouse with ? ve functional areas, i. e. , receiving, shipping, cross-docking, reserve, and forward. They propose an optimization model and a heuristic algorithm to determine the assignment of SKUs to the different storage areas as well as the size of each functional area to minimize the total material handling and storage costs. A key issue with all research on the dimensioning problem is that it requires performance models of material handling; these models are often independent of the size or layout of the warehouse.Research is needed to either validate these models, or develop design methods that explicitly consider the impact of sizing and dimensioning on material handling. 2. 3. Department layout In this section we discus layout problems within a warehouse department, primarily a storage department. The storage problems are classi? ed as: (P1) pallet block-stacking pattern, i. e. , storage lane depth, number of lanes for each depth, stack height, pallet placement angle with regards to the aisle, storage clearance between pallets, and length and width of aisles; (P2) storage department layout, i. . , door location, aisle orientation, length and width of aisles, and number of aisles; and (P3) AS/RS con? guration, i. e. , dimension of storage racks, number of cranes. These layout problems affect warehouse performances with respect to: (O1) construction and maintenance cost; (O2) material handling cost; (O3) storage capacity, e. g. , the ability to accommodate incoming shipments; (O4) space utilization; and (O5) equipment utilization. Each problem is treated in the literature by different authors considering a subset of the performance measures, as summarized in Table 1. 2. 3. 1.Pallet block-stacking pattern (P1) In the pallet block-stacking problem, a fundamental decision is the selection of lane depths to balance the tradeoffs between space utilization and ease of storage/retrieval operations, considering the SKUs’ stackability limits, arriving lot sizes, and retrieval patterns. Using deep lane storage could increase space utilization because fewer aisles are needed, but on the other hand could also cause decreased space utilization due to the ‘‘honeycombing† effect that creates unusable space for the storage of other i tems until the whole lane is totally depleted.The magnitude of the honeycombing effect depends on lane depths as well as the withdrawal rates of individual products. Therefore, it might be bene? cial to store different classes of products in different lane depths. A careful determination and coordination of the lane depths for different products is necessary in order to achieve the best storage space utilization. Besides lane con? guration, the pallet block-stacking problem also determines such decisions as aisle widths and orientation, stack height, and storage clearance, which all affect storage space utilization, material handling ef? iency, and storage capacity. 542 J. Gu et al. / European Journal of Operational Research 203 (2010) 539–549 Table 1 A summary of the literature on warehouse layout design. Problem P1 Citation Moder and Thornton (1965) Berry (1968) Marsh (1979) Marsh (1983) Goetschalckx and Ratliff (1991) Larson et al. (1997) Roberts and Reed (1972) Bassan et al. (1980) Rosenblatt and Roll (1984) Pandit and Palekar (1993) P3 Karasawa et al. (1980) Ashayeri et al. 1985) Rosenblatt et al. (1993) Objective O4 O2, O4 O3, O4 O4 O2, O4 O1, O2 O1, O2 O1, O2, O3 O2 O1, O2, O3 O1, O2 O1, O2, O3 O1, O5 O1, O5 O1 Method Analytical formulae Analytical formulae Simulation models Heuristic procedure Heuristic procedure Dynamic Programming Optimal design using analytical formulation Optimal two-dimensional search method Queuing model Nonlinear mixed integer problem Nonlinear mixed integer problem Nonlinear mixed integer problem NotesMainly on lane depth determination For class-based storage Consider the con? guration of storage bays (unit storage blocks) Consider horizontal and vertical aisle orientations, locations of doors, and zoning of the storage area Based on Bassan et al’s work with additional costs due to the use of grouped storage Include not only the ordinary travel time, but also waiting time when all vehicles are busy The model is so lved by generalized Lagrange multiplier method Given rack height, the model can be simpli? d to a convex problem System service is evaluated using simulations, if not satisfactory, new constraints are added and the optimization model is solved again to get a new solution A more elaborated variation of Zollinger’s rules that consider explicitly operational policies For the design of an automated carousel system. The model is solved with a simple search algorithm P2 Zollinger (1996) Malmborg (2001) Lee and Hwang (1988) Rule of thumb heuristic Rule of thumb heuristic Nonlinear integer program A number of papers discuss the pallet block-stacking problem.Moder and Thornton (1965) consider ways of stacking pallets in a warehouse and the in? uence on space utilization and ease of storage and retrieval. They consider such design factors as lane depth, pallet placement angle with regards to the aisle, and spacing between storage lanes. Berry (1968) discusses the tradeoffs between stor age ef? ciency and material handling costs by developing analytic models to evaluate the total warehouse volume and the average travel distance for a given storage space requirement.The factors considered include warehouse shape, number, length and orientation of aisles, lane depth, throughput rate, and number of SKUs contained in the warehouse. It should be noted that the models for total warehouse volume and models for average travel distance are not integrated, and the warehouse layout that maximizes storage ef? ciency is different from the one that minimizes travel distance. Marsh (1979) uses simulation to evaluate the effect on space utilization of alternate lane depths and the rules for assigning incoming shipments to lanes.Marsh (1983) compares the layout design developed by using the simulation models of Marsh (1979) and the analytic models proposed by Berry (1968). Goetschalckx and Ratliff (1991) develop an ef? cient dynamic programming algorithm to maximize space utilizati on by selecting lane depths out of a limited number of allowable depths and assigning incoming shipments to the different lane depths. Larson et al. (1997) propose a three-step heuristic for the layout problem of class-based pallet storage with the purpose to maximize storage space utilization and minimize material handling cost. The ? st phase determines the aisles layout and storage zone dimensions; the second phase assigns SKUs to storage con? gurations; and the third phase assigns ? oor space to the storage con? gurations. The research addressing the pallet block-stacking problem suggests different rules or algorithms, usually with restrictive assumptions, e. g. , the replenishment quantities and retrieval frequencies for each SKU are known. In reality, not only do these change dynamically, but the SKU set itself changes, and pallet block-stacking patterns that are optimized for current conditions may be far from optimum in the near future.Research is needed that will identify a robust solution in the face of dynamic uncertainty in the storage and retrieval requirements. 2. 3. 2. Storage department layout (P2) The storage department layout problem is to determine the aisle structure of a storage department in order to minimize the construction cost and material handling cost. The decisions usually include aisle orientations, number of aisles, length and width of aisles, and door locations.In order to evaluate operational costs, some assumptions are usually made about the storage and order picking policies; random storage and single-command order picking are the most common assumptions. By assuming a layout con? guration, or a small set of alternative con? gurations, models can be formulated to optimize each con? guration. Roberts and Reed (1972) assume storage space is available in units of identical bays. Bassan et al. (1980) consider a rectangular warehouse, and aisles that are either parallel or perpendicular to the longest walls.In addition, they also discuss the optimal door locations in the storage department, and the optimal layout when the storage area is divided into different zones. Roll and Rosenblatt (1983) extend Bassan et al. (1980) to include the additional cost due to the use of grouped storage policy. Pandit and Palekar (1993) minimize the expected response time of storage and/or retrieval requests using a queuing model to calculate the total response time including waiting and processing time for different types of layouts. With these response times, an optimization model is solved to ? nd the optimal storage space con? urations. Roodbergen and Vis (2006) present an optimization approach for selecting the number and length of aisles and the depot location so as to minimize the expected length of a picking tour. They developed models for both S-shaped tours and a largest gap policy, and concluded that the choice of routing policy could, in some cases, have a signi? cant impact on the size and layout of the department . The conclusion from Roodbergen and Vis (2006) is quite significant, since it calls into question the attempt to optimize storage department layout without knowing what the true material handling performance will be.There is a need for additional research that helps to identify the magnitude of the impact of layout (for reasonably shaped departments) on total costs over the life of the warehouse, considering changing storage and retrieval requirements. J. Gu et al. / European Journal of Operational Research 203 (2010) 539–549 543 2. 3. 3. AS/RS con? guration (P3) The AS/RS con? guration problem is to determine the numbers of cranes and aisles, and storage rack dimension in order to minimize construction, maintenance, and operational cost, and/or maximize equipment utilization.The optimal design models or rule-ofthumb procedures summarized in Table 1 typically utilize some empirical expressions of the costs based on simple assumptions for the operational policies, and known s torage and retrieval rates. Karasawa et al. (1980) present a nonlinear mixed integer formulation with decision variables being the number of cranes and the height and length of storage racks and costs including construction and equipment costs while satisfying service and storage capacity requirements. Ashayeri et al. 1985) solve a problem similar to Karasawa et al. (1980). Given the storage capacity requirement and the height of racks, their models can be simpli? ed to include only a single design variable, i. e. , the number of aisles. Furthermore, the objective function is shown to be convex in the number of aisles, which allows a simple one-dimensional search algorithm to optimally solve the problem. Rosenblatt et al. (1993) propose an optimization model that is a slight modi? cation of Ashayeri et al. (1985), which allows a crane to serve multiple aisles.A combined optimization and simulation approach is proposed, where the optimization model generates an initial design, and a simulation evaluates performance, e. g. , service level. If the constraints evaluated by simulation are satis? ed, then the procedure stops. Otherwise, the optimization model is altered by adding new constraints that have been constructed by approximating the simulation results. Zollinger (1996) proposes some rule of thumb heuristics for designing an AS/RS. The design criteria include the total equipment costs, S/ R machine utilization, service time, number of jobs waiting in the queue, and storage space requirements.Closed form equations compute these criteria as functions of the number of aisles and the number of levels in the storage rack. Malmborg (2001) uses simulation to re? ne the estimates of some of the parameters which then are used in the closed form equations. The design of automated carousel storage systems is addressed by Lee and Hwang (1988). They use an optimization approach to determine the optimal number of S/R machines and the optimal dimensions of the carousel sy stem to minimize the initial investment cost and operational costs over a ? ite planning horizon subject to constraints for throughput, storage capacity, and site restrictions. Some other less well-discussed AS/RS design problems include determining the size of the basic material handling unit and the con? guration of I/O points. Roll et al. (1989) propose a procedure to determine the single optimal container size in an AS/RS, which is the basic unit for storage and order picking. Container size has a direct effect on space utilization, and therefore on the equipment cost since the storage capacity requirement needs to be satis? ed. Randhawa et al. 1991) and Randhawa and Shroff (1995) use simulations to investigate different I/O con? gurations on performance such as throughput, mean waiting time, and maximum waiting time. The results indicate that increased system throughput can be achieved using I/O con? gurations different from the common one-dock layout where the dock is located at the end of the aisle. There are two important opportunities for additional research on AS/RS con? guration: (1) results for a much broader range of technology options, e. g. , double deep rack, multi-shuttle cranes, etc. ; and (2) results demonstrating the sensitivity of con? urations to changes in the expected storage and retrieval rates or the effects of a changing product mix. 2. 4. Equipment selection The equipment selection problem addresses the level of automation in a warehouse and what type of storage and material han- dling systems should be employed. These decisions obviously are strategic in nature in that they affect almost all the other decisions as well as the overall warehouse investment and performance. Determining the best level of automation is far from obvious in most cases, and in practice it is usually determined based on the personal experience of designers and managers.Academic research in this category is extremely rare. Cox (1986) provides a methodology t o evaluate different levels of automation based on a cost-productivity analysis technique called the hierarchy of productivity ratios. White et al. (1981) develop analytical models to compare block stacking, single-deep and doubledeep pallet rack, deep lane storage, and unit load AS/RS in order to determine the minimum space design. Matson and White (1981) extend White et al. (1981) to develop a total cost model incorporating both space and material handling costs, and demonstrate the effect of handling requirements on the optimum storage design.Sharp et al. (1994) compare several competing small part storage equipment types assuming different product sizes and dimensions. They considered shelving systems, modular drawers, gravity ? ow racks, carousel systems, and mini-load storage/retrieval systems. The costs they considered include operational costs, ? oor space costs, and equipment costs. In summary, research on equipment selection is quite limited and preliminary, although it is very important in the sense that it will affect the whole warehouse design and the overall lifetime costs.There are two fundamental issues for equipment selection: (1) how to identify the equipment alternatives that are reasonable for a given storage/retrieval requirement; and (2) how to select among the reasonable alternatives. A very signi? cant contribution would be to develop a method for characterizing requirements and characterizing equipment in such a way that these two issues could be addressed in a uni? ed manner. 2. 5. Operation strategy This section discusses the selection of operation strategies in a warehouse.The focus is on operation strategies that, once selected, have important effects on the overall system and are not likely to be changed frequently. Examples of such strategies are the decision between randomized and dedicated storage, or the decision to use zone picking. Two major operation strategies are discussed: the storage strategy and the order picking strat egy. Detailed operation policies and their implementations are discussed in Gu et al. (2007). 2. 5. 1. Storage The basic storage strategies include random storage, dedicated storage, class-based storage, and Duration-of-Stay (DOS) based storage, as explained in Gu et al. 2007). Hausman et al. (1976), Graves et al. (1977) and Schwarz et al. (1978) compare random storage, dedicated storage, and class-based storage in single-command and dual-command AS/RS using both analytical models and simulations. They show that signi? cant reductions in travel time are obtainable from dedicated storage compared with random storage, and also that class-based storage with relatively few classes yields travel time reductions that are close to those obtained by dedicated storage.Goetschalckx and Ratliff (1990) and Thonemann and Brandeau (1998) show theoretically that DOS-based storage policies are the most promising in terms of minimizing traveling costs. Historically, DOS-based policies were dif? cult to implement since they require the tracking and management of each stored unit in the warehouse, but modern WMS’s have this capability. Also the performance of DOS-based policies depends greatly on factors such as the skewness of demands, balance of input and output ? ows, inventory control policies, and the speci? cs of implementation. In a study by Kulturel et al. (1999), class-based 544 J. Gu et al. European Journal of Operational Research 203 (2010) 539–549 storage and DOS-based storage are compared using simulations, and the former is found to consistently outperform the latter. This conclusion may have been reached because the assumptions of the DOS model rarely hold true in practice. All the results on operational strategies are for unit-load AS/RS. Studies on other storage systems are rarely reported. Malmborg and Al-Tassan (1998) develop analytic models to evaluate the performance of dedicated storage and randomized storage in lessthan-unit-load warehouses, but no general conclusions comparable to the unit-load case are given.A strong case can be made that additional research is needed, especially to clarify the conditions under which the storage policy does or does not have a signi? cant impact on capacity or travel time. 2. 5. 2. Order picking In a given day or shift, a warehouse may have many orders to pick. These orders may be similar in a number of respects; for example, some orders are shipped using the same carrier, or transportation mode, or have the same pick due date and time.If there are similarities among subsets of orders that require them to be shipped together, then they also should be picked roughly during the same time period to avoid intermediate storage and staging. Thus, it is common practice to use wave picking, i. e. , to release a fraction of the day’s (shift’s) orders, and to expect their picking to be completed within a corresponding fraction of the day (shift). In addition to wave picking, two ot her commonly used orderpicking strategies are batch picking and zone picking.Batch picking involves the assignment of a group of orders to a picker to be picked simultaneously in one trip. In zone picking, the storage space is divided into picking zones and each zone has one or more assigned pickers who only pick in their assigned zone. Zone picking can be divided into sequential and parallel zone picking. Sequential zone picking is similar to a ? ow line, in which containers that can hold one or more orders are passed sequentially through the zones; the pickers in each zone pick the products within their zone, put them into the container, and then pass the container to the next zone. Bartholdi et al. (2000) propose a Bucket Brigades order picking method that is similar to sequential zone picking, but does not require pickers to be restricted to zones). In parallel zone picking, an order is picked in each zone simultaneously. The picked items are sent to a downstream sorting system to be combined into orders. The organization and planning of the order picking process has to answer the following questions: 1. Will product be transported to the picker (part-to-picker) or will the picker travel to the storage location (picker-to-part)? . Will orders be picked in waves? If so, how many waves of what duration? 3. Will the warehouse be divided into zones? If so, will zones be picked sequentially or concurrently? 4. Will orders be picked in batches or separately? If they are batched, will they be sorted while picking or after picking? Depending on the operating principles selected, the order picking methods will be:        Single order picking. Batching with sort-while-pick. Batching with sort-after-pick. Sequential zoning with single order picking. Sequential zoning with batching.Concurrent zoning without batching. Concurrent zoning with batching. Research on the selection of an order picking strategy is very scarce, which might be a result of the complexity of the problem itself. Lin and Lu (1999) compare single-order picking and batch zone picking for different types of orders, which are classi? ed based on the order quantity and the number of ordered items. Petersen (2000) simulates ? ve different order-picking policies: singleorder picking, batch picking, sequential zone picking, concurrent zone picking, and wave picking.Two control variables in the simulation study are the numbers of daily orders and the demand skewness, while the other factors such as warehouse layout, storage assignment, and zone con? guration (when zone and wave picking are used) are ? xed. The performance measures used to compare the different policies include: the mean daily labor, the mean length of day, and the mean percentage of late orders. For each order picking policy, the simplest rules regarding batching, routing, and wave length are used. It also should be noted that the performance measures are mainly related to order picking ef? iencies and service quality; additional costs caused by downstream sorting with batch, zone, and wave picking are not considered. Furthermore, comparison of these policies are made mainly with regards to the order structures, while other important factors such as storage assignment and detailed implementations of the order picking policies are assumed to be ? xed. Therefore, the results should not be considered generic and more research in this direction is required to provide more guidance for warehouse designers. Order picking strategy selection remains a largely unresolved design problem.Additional research would be valuable, especially if it could begin to characterize order picking alternatives in ways that were easy to apply in design decision making. As an example, could researchers develop performance curves for different order picking strategies? 3. Performance evaluation Performance evaluation provides feedback on the quality of a proposed design and/or operational policy, and more importantl y, on how to improve it. There are different approaches for performance evaluation: benchmarking, analytic models, and simulations. This section will only discuss benchmarking and analytic models. 3. 1.Benchmarking Warehouse benchmarking is the process of systematically assessing the performance of a warehouse, identifying inef? ciencies, and proposing improvements. Data Envelopment Analysis (DEA) is regarded as an appropriate tool for this task because of its capability to capture simultaneously all the relevant inputs (resources) and outputs (performances), to construct the best performance frontier, and to reveals the relative shortcomings of inef? cient warehouses. Schefczyk (1993), Hackman et al. (2001), and Ross and Droge (2002) shows some approaches and case studies of using DEA in warehouse benchmarking.An Internet-based DEA system (iDEAS) for warehouses is developed by the Keck Lab at Georgia Tech, which includes information on more than 200 warehouses (McGinnis, 2003). 3. 2. Analytical models Analytic performance models fall into two main categories: (1) aisle based models which focus on a single storage system and address travel or service time; and (2) integrated models which address either multiple storage systems or criteria in addition to travel/service times. J. Gu et al. / European Journal of Operational Research 203 (2010) 539–549 545 3. 2. 1.Aisle based models Table 2 summarizes research on travel time models for aislebased systems. A signi? cant fraction of research focuses on the expected travel time for the crane in an AS/RS, for either single command (SC) or dual command (DC) cycles. For both, there is research addressing three different storage policies: in randomized storage, any SKU can occupy any location; in dedicated storage, each SKU has a set of designated locations; and in class based storage, a group of storage locations is allocated to a class of SKUs, and randomized storage is allowed within the group of storage locati ons.The issue with DC cycles is matching up storages and retrievals to minimize the dead-head travel of the crane, which may involve sequencing retrievals, and selecting storage locations. The results in this category usually assume in? nite acceleration to simplify the travel time models, although some develop more elaborate models by considering acceleration for the various axes of motion (see, e. g. , Hwang and Lee, 1990; Hwang et al. , 2004b; Chang and Wen, 1997; Chang et al. , 1995).There are a few papers that attack the more mathematically challenging issue of deriving the distribution of travel time (see Foley and Frazelle (1991) and Foley et al. (2002)). The research on carousel travel time models generally parallels corresponding AS/RS research. Given some knowledge of travel time, AS/RS service time models can be developed, considering the times required for load/unload and store/retrieve at the storage slot. Queuing models have been developed assuming various distribution s for travel time, see e. g. Lee (1997), Chow (1986), Hur et al. (2004), Bozer and White (1984), Park et al. (2003a) for AS/RS, Chang et al. (1995) for conventional multi-aisle systems, and for end-of-aisle picking systems, see Bozer and White (1991, 1996), Park et al. (2003a), and Park et al. (1999). Stochastic optimization models have been developed for estimating AS/RS throughput, with constraints on storage queue length and retrieval request waiting time (Azadivar, 1986). The throughput of carousel systems is modeled by Park et al. (2003b) and Meller and Klote (2004).The former consider a system with two carousels and one picker, and derive analytic expressions for the system throughput and picker utilization assuming deterministic and exponential pick time distributions. Meller and Klote (2004) develop throughput models for systems with multiple carousels using an approximate two-server queuing model approach. For conventional multi-aisle storage systems (bin shelving, e. g. ), two kinds of travel time results have been developed: (1) models which estimate the expected travel time; and (2) models of the pdf of travel times.These models require an assumption about the structure of the tour, e. g. , traversal (Hall, 1993), return (Hall, 1993 or Caron et al. , 1998), or largest gap (Roodbergen and Vis, 2006). As long as these models are parameterized on attributes of the storage system design, they can be used to support design by searching over the relevant parameters. As with AS/RS and carousels, there has been research to incorporate travel time models into performance models. Chew and Table 2 Literature of travel time models for different warehouse systems. Randomized storage Unit-load AS/RS Single-command Hausman et al. 1976) Bozer and White (1984) Thonemann and Brandeau (1998) Kim and Seidmann (1990) Hwang and Ko (1988) Lee (1997) Hwang and Lee (1990) Chang et al. (1995) Chang and Wen (1997) Koh et al. (2002) Lee et al. (1999) Graves et al. (1977) Boze r and White (1984) Kim and Seidmann (1990) Hwang and Ko (1988) Lee (1997) Han et al. (1987) Hwang and Lee (1990) Chang et al. (1995) Chang and Wen (1997) Koh et al. (2002) Lee et al. (1999) Meller and Mungwattana (1997) Potrc et al. (2004) Hwang and Song (1993) Bozer and White (1990) Bozer and White (1996) Foley and Frazelle (1991) Park et al. 1999) Han and McGinnis (1986) Han et al. (1988) Su (1998) Hwang and Ha (1991) Hwang et al. (1999) Hall (1993) Jarvis and McDowell (1991) Chew and Tang (1999) Hwang et al. (2004a) Caron et al. (1998) Caron et al. (2000) Jarvis and McDowell (1991) Chew and Tang (1999) Hwang et al. (2004a) Park et al. (2003a) Dedicated storage Hausman et al. (1976) Thonemann and Brandeau (1998) Kim and Seidmann (1990) Class-based storage Hausman et al. (1976) Thonemann and Brandeau (1998) Rosenblatt and Eynan (1989) Eynan and Rosenblatt (1994) Kouvelis and Papanicolaou (1995) Kim and Seidmann (1990) Pan and Wang (1996) Ashayeri et al. 2002) Dual-command Graves et al. (1977) Kim and Seidmann (1990) Graves et al. (1977) Kouvelis and Papanicolaou (1995) Kim and Seidmann (1990) Pan and Wang (1996) Ashayeri et al. (2002) Multi-shuttle Man-on-board AS/RS End-of-aisle AS/RS Carousel and rotary racks Ha and Hwang (1994) Conventional multi-aisle system Jarvis and McDowell (1991) Chew and Tang (1999) Hwang et al. (2004a) 546 J. Gu et al. / European Journal of Operational Research 203 (2010) 539–549 Tang (1999) use their model of the travel time pdf to analyze order batching and storage allocation using a queuing model.Bhaskaran and Malmborg (1989) present a stochastic performance evaluation model for the service process in multi-aisle warehouses with an approximated distribution for the service time that depends on the batch size and the travel distance. de Koster (1994) develops queuing models to evaluate the performance of a warehouse that uses sequential zone picking where each bin is assigned to one or more orders and is transported using a conveyer. If a bin needs to be picked in a speci? c zone, it is transported to the corresponding pick station.After it is picked, it is then put on the conveyor to be sent to the next pick station. The proposed queuing network model evaluates performance measures such as system throughput, picker utilization, and the average number of bins in the system based on factors such as the speed and length of the conveyor, the number of picking stations, and the number of picks per station. Throughput analysis of sorting systems is addressed in Johnson and Meller (2002). They assume that the induction process is the bottleneck of the sorting process, and therefore governs the throughput of the sorting system.This model is later incorporated into a more comprehensive model in Russell and Meller (2003) that integrates order picking and sorting to balance the tradeoffs between picking and packing with different order batch sizes and wave lengths. Russell and Meller (2003) also demonstrate th e use of the proposed model in determining whether or not to automate the sorting process and in designing the sorting system. 3. 2. 2. Integrated models Integrated models combine travel time analysis and the service quality criteria with other performance measures, e. g. storage capacity, construction cost, and operational cost. Malmborg (1996) proposes an integrated performance evaluation model for a warehouse having a forward-reserve con? guration. The proposed model uses information about inventory management, forward-reserve space allocation, and storage layout to evaluate costs associated with: storage capacity and space shortage; inventory carrying, replenishing, and expediting; and order picking and internal replenishment for the forward area. Malmborg (2000) evaluates several performance measures for a twin-shuttle AS/RS.Malmborg and Al-Tassan (2000) present a mathematical model to estimated space requirements and order picking cycle times for less than unit load order pick ing systems that uses randomized storage. The inputs of the model include product parameters, equipment speci? cations, operational policies, and storage area con? gurations. Malmborg (2003) models the dependency of performance measures such as expected total system construction cost and throughput on factors such as the vehicle ? eet size, the number of lifts, and the storage rack con? gurations for warehouse systems that use rail guided vehicles.Table 3 A Summary of the literature on warehouse case studies. Citation Cormier and Kersey (1995) Yoon and Sharp (1995) Zeng et al. (2002) Kallina and Lynn (1976) Brynzer and Johansson (1995) Burkard et al. (1995) van Oudheusden et al. (1988) Dekker et al. (2004) Luxhoj and Skarpness (1986) Johnson and Lofgren (1994) Problems studied Conceptual design Analytic travel time and performance models of storage systems represent a major contribution to warehouse design related research, and a rich set of models is available. Yet despite this wea lth of prior results, there is no uni? d approach to travel time modeling or performance modeling for aisle based systems – every system and every set of assumptions leads to a different model. A signi? cant research contribution would be to present a uni? ed theory of travel time in aisle-based systems. 4. Case studies There are some published industrial case studies, which not only provide applications of the various design and operation methods in practical contexts, but more importantly, also identify possible future research challenges from the industrial point of view. Table 3 lists these case studies, identifying the problems and the types of warehouse they investigated.It is dif? cult to generalize from such a small set of speci? c cases, but one conclusion is that substantial bene? ts can achieved by appropriately designing and operating a warehouse, see for example Zeng et al. (2002), van Oudheusden et al. (1988), and Dekker et al. (2004). On the other hand, one mig ht conclude from these cases that there are few generic simple rules. As just one example, the COI-based storage location assignment rule proposed by Kallina and Lynn (1976) ignores many practical considerations, such as varying weights, item-dependent travel costs, or dependencies between items.Some of these complications have been addressed in the academic research (for example see Table 3 in Section 5. 2 of Gu et al. (2007)), but many others remain unexplored. What these cases illustrate is the gap between the assumption-restricted models in research publications and the complex reality of most warehouses. There is a signi? cant need for more industrial case studies, which will assist the warehouse research community in better understanding the real issues in warehouse design. In turn, research results that have been tested on more realistic data sets will have a more substantial impact on practice.A warehouse design problem classi? cation, such as we have proposed here, might be used to structure such future case studies. 5. Computational systems There are numerous commercial Warehouse Management Systems (WMS) available in the market, which basically help the warehouse manager to keep track of the products, orders, space, equipment, and human resources in a warehouse, and provide rules/algorithms for storage location assignment, order batching, pick routing, etc. Detailed review of these systems is beyond the scope of this paper.Instead, we focus on the academic research addressing computational systems for warehouse design. As previous sections show, research on various warehouse design and Type of warehouse A warehouse for perishable goods that requires Just-In-Time operations An order picking system A distribution center A distribution center Kitting systems that supply materials to assembly lines An AS/RS where a S/R machine can serve any aisle using a switching gangway A man-on-board AS/RS in an integrated steel mill A multi-aisle manual order picking system A distribution center A distribution centerConceptual design Storage location assignment; warehouse dimensioning; storage and order picking policies Storage location assignment using the COI rule Process ? ow; batching; zone picking; Vehicle routing Storage location assignment; batching; routing Storage and routing policies Manpower planning Simulation by decomposition J. Gu et al. / European Journal of Operational Research 203 (2010) 539–549 547 operation problems has been conducted for almost half a century, and as a result, a large number of methodologies, algorithms, and empirical studies have been generated.However, successful implementations of these academic results in current commercial WMS systems or in engineering design software are rare. The prototype systems discussed in this section might shed some light on how academic research results could be utilized to develop more sophisticated computer aided warehouse design and operation systems. Perlmann and Bai ley (1988) present computer-aided design software that allows a warehouse designer to quickly generate a set of conceptual design alternatives including building shape, equipment selection, and operational policy selection, and to select from among them the best one based on the speci? d design requirements. To our knowledge, this is the only research paper addressing computer aided warehouse design. There are several papers on the design of warehouse control systems. Linn and Wysk (1990) develop an expert system for AS/ RS control. A control policy determines decisions such as storage location assignment, which item to retrieve if multi-items for the same product are stored, storage and retrieval sequencing, and storage relocation.Several control rules are available for each decision and the control policy is constructed by selecting one individual rule for each decision in a coherent way based on dynamically changing system state variables such as demand levels and traf? c intensi ty. A similar AS/RS control system is proposed by Wang and Yih (1997) based on neural networks. Ito et al. (2002) propose an intelligent agent based system to model a warehouse, which is composed of three subsystems, i. e. , agent-based communication system, agent-based material handling system, and agent-based inventory planning and control system.The proposed agent-based system is used for the design and implementation of warehouse simulation models. Kim et al. (2002) present an agent based system for the control of a warehouse for cosmetic products. In addition to providing the communication function, the agents also make decisions regarding the operation of the warehouse entities they represented in a dynamic real-time fashion. The absence of research prototypes for computer aided warehouse design is particularly puzzling, given the rapid advancement in computing hardware and software over the past decade.Academic researchers have been at the forefront of computer aided design i n other disciplines, and particularly in developing computational models to support design decision making. Warehousing design, as a research domain, would appear to be ripe for this kind of contribution. 6. Conclusions and discussion We have attempted a thorough examination of the published research related to warehouse design, and classi? ed papers based on the main issues addressed. Fig. 1 shows the numbers of papers in each category; there were 50 papers directly addressing warehouse design decisions.There were an additional 50 papers on various analytic models of travel time or performance for speci? c storage systems or aggregates of storage systems. Benchmarking, case studies and other surveys account for 18 more papers. One clear conclusion is that warehouse design related research has focused on analysis, primarily of storage systems rather than synthesis. While this is somewhat surprising, an even more surprising observation is that only 10% of papers directly addressing w arehouse design decisions have a publication date of 2000 or later.Given the rapid development of computing hardware and solvers for optimization, simulation, and general mathematical problems, one might reasonably expect a more robust design-centric research literature. We conjecture two primary inhibiting factors: 1. The warehouse design decisions identi? ed in Fig. 1 are tightly coupled, and one cannot be analyzed or determined in isolation from the others. Yet, the models available are not uni? ed in any way and are not ‘‘interoperable†. A researcher addressing one decision would require a research infrastructure integrating all the other decisions.The scope and scale of this infrastructure appears too great a challenge for individual researchers. 2. To properly evaluate the impact of changing one of the design decisions requires estimating changes in the operation of the warehouse. Not only are future operating scenarios not speci? ed in detail, even if they w ere, the total warehouse performance assessment models, such as high ? delity simulations, are themselves a considerable development challenge. From this, we conclude that the most important future direction for the warehouse design research community is to ? d ways to overcome these two hurdles. Key to that, we believe, will be the emergence of standard representations of warehouse elements, and perhaps some research community based tools, such as open-source analysis and design models. Other avenues for important contributions include studies describing validated or applied design models, and practical case studies that demonstrate the potential bene? ts of applying academic research results to real problems, or in identifying the hidden challenges that prevent their successful implementation.Finally, both analytic and simulation models are proposed to solve warehouse problems and each has its respective advantages and disadvantages. Analytic models are usually design-oriented in the sense that they can explore many alternatives quickly to ? nd solutions, although they may not capture all the relevant details of the system. On the other hand, simulation models are usually analysis-oriented – they provide an assessment of a given design, but usually have limited capability for exploring the design space. There is an important need to integrate both approaches to achieve more ? exibility in analyzing warehouse problems.This is also pointed out by Ashayeri and Gelders (1985), and its applicability has been demonstrated by Rosenblatt and Roll (1984) and Rosenblatt et al. (1993). There is an enormous gap between the published warehouse research and the practice of warehouse design and operations. Cross fertilization between the groups of practitioners and researchers appears to be very limited. Effectively bridging this gap would improve the state-of-the-art in warehouse design methodology. Until such communication is established, the prospect of meaningfu l expansion and enhancement of warehouse design methodology appears limited.Warehousing is an essential component in any supply chain. In the USA, the value of wholesale trade inventories is approximately half a trillion dollars (BEA, 2008), and 2004 inventory carrying costs (interest, taxes, depreciation, insurance, obsolescence and warehousing) have been estimated at 332 billion dollars (Trunick, 2005). To date the research effort focusing on warehousing is a very small fraction of the overall supply chain research. There are many challenging research questions and problems that have not received any attention.The challenge for the academic research community is to focus on the integrated design and operation of warehouses, while the challenge for industrial practitioners is to provide realistic test cases. References Ashayeri, J. , Gelders, L. F. , 1985. Warehouse design optimization. European Journal of Operational Research 21, 285–294. 548 J. Gu et al. / European Journal of Operational Research 203 (2010) 539–549 Goh, M. , Ou, J. , Teo, C. -P. , 2001. Warehouse sizing to minimize inventory and storage costs. 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IIE Transactions 25 (4), 76–87. Han, M. H. , McGinnis, L. F. , 1986. Carousel Application for Work-in-process: Modelling and Analysis. Material Handling Research Center, Georgia Institute of Technology, Atlanta, Georgia. Han, M. H. , McGinnis, L. F. , Shieh, J. S. , White, J. A. , 1987.On sequencing retrievals in an automated storage/retrieval system. IIE Transactions 19 (1), 56–66. Han, M. H. , McGinnis, L. F. , White, J. A. , 1988. Analysis of rotary rack operation. Material Flow 4, 283–293. Hausman, W. H. , Schwarz, L. B. , Graves, S. C. , 1976. Optimal storage assignment in automatic warehousing systems. Management Science 22 (6), 629–638. Heragu, S. S. , Du, L. , Mantel, R. J. , Schuur, P. C. , 2005. Mathematical model for warehouse design and product allocat ion. International Journal of Production Research 43 (2), 327–338. Hung, M. S. , Fisk, C. J. , 1984.Economic sizing of warehouses – A linear programming approach. Computers and Operations Research 11 (1), 13–18. 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Balloon Car

Jesse Pinkman Balloon Car Project DESIGN COMPANY INFORMATION Well our business company is comprised of Nick Wilson and I, Thomas Kinley. Our Company’s name is That Company ®. I am the President, The CFO, and the Director of all Operations of That Company. My engineering experience will really enhance our chances of winning this and making even more cars. I’ve worked for many toy companies to get cars running. I think our idea will help Iowa’s kid have fun and save the world because of the recycled materials. This will benefit students by giving them something to play within their free time instead of watching TV. PROJECT STATEMENT The project that is at hand is very simple it is making a balloon powered car out of simply recycled materials. This will help kids of Iowa learn about wheels and axles. It will also teach them how to make the most out of materials that could be recycled. This will also teach the kids about the Laws of Motion, friction, and acceleration. Basically our project will be distributed to teach kids about many different things in science. PRELIMINARY DESIGN My design will start with an empty pop can, and then I will screw holes for the axles (pencils) to go into. Then I will shave the pencils for the least amount friction, and then I will stick the milk carton caps on as my wheels. I will spray WD-40 on to really loosen up the axle. I am going to cut some of the can off for aerodynamics. My car will win because it will be aerodynamic, little friction, but still a lot of acceleration.

Japanese unique ways of thinking essays

Japanese unique ways of thinking essays Lying in the Far East of Asia, surrounded by the oceans, Japan is very understandable to be isolated from the rest of the continent. Through Kokoro, the heart within and the feature films about Japan, we can see that this country has a long and unique history. According to Japan tradition, the year 660 B.C. is the date of founding of Japan as a nation under the mythological Emperor Jimmu. At that time, Japans Shinto religion was established leading people to the beliefs of reverence for nature and ancestor worship. Since Shinto reflects Japans history and traditions, it has become known as Japans national religion and it plays a key role throughout the history of the country. In Kokoro, the heart within, the producer starts out by depicting the importance of looking at Japanese people to find the heart within Japan. The simple life of the men living by the sea illustrates a part of Japan: the plain and peaceful but hard working life in the middle of the ocean. Another unique picture of Japan is the scene of the woman going to the temple everyday washes her hands and mouth with the pure water and praying for happiness. This image is a great example to demonstrate the value of Japanese people cherishing the purity of nature versus the impurity of evil which they need to wash off. Yet, the most significant part of the unique of Japan is the belief in Shinto which contributes to every aspects of life in Japan, even daily activities. Shinto emphasizes both Japanese deities and the forces of nature. Nature plays a central role in the religious worship. They believe that all natural objects including trees, mountains, rivers, the sun or the moon are imbued with living spirit and that God is within that everything so people can seek for when they need. This belief also leads to the unique way of thinking in Japans building structure. All the temples and houses are constructed in harmony to natu...