Developing A Warranty Cost Model

Developing A Warranty Cost Model Chapter 2: literature review. 2.1. Introduction to Reliability: The reliability expression may sometimes be unclear in general logic due to the differences in understanding it among customers. Each customer can define reliability from a different point a view. As an example; a customer may define it as cheap product which has a long guaranteed life cycle period and in the meanwhile works hardly enough. Whereas another customer may define it as a reasonable price product which has a life cycle period and will definitely work as intended. (Institute et al., 1968) The concept reliability is very clear and understandable in the practical and industrial world. Reliability of a product, process, or system is the probability that it will perform as specified, and under certain condition, for a specified period of time.(2Blank, 2004) Reliability is known as the likelihood of a product, machine or a component, to keep doing its intended task without breaking down under precise conditions for a given period of time. (Yang, 2007) (Yang, 2007) The above expression holds three significant essentials to ensure the full understanding of reliability: To know the planned function or task of a product, machine and component. To know the planned duration specified relating to a product, machine and component. To know the environment surrounding where the product, machine, and component, suppose to be working at. Knowing these three essentials conditions will allow us to estimate the product, machine or component reliability capability from the first instance. 2.1.2. Reliability Engineering Studies: The purpose of reliability engineering studies is to control, or to make sure that a product, machine or component will be reliable under normal operation in a specified studied manner, as well as away from breaking downs. (Smith, 1972) Reliability engineering studies are science used to minimize the outcome effects and possible behaviour which will result in maximizing reliability. There are three necessary conditions to achieve the previous statements: To build a maximum reliability consideration into a product, machine and component, during the design and development stages; this consideration is known to be the most critical point due to its responsibility in inherent reliability. To cut down production process differences; this will guarantee that the process will not deliberately degrade the inherited reliability. Once a product is manufactured. A well maintained operation should be commenced; this will prevent the performance degradation and will extend the product life.(Hartman, 2007) These considerations are presented within a large selection of reliability techniques, as an instance; reliability planning and specification, fault tree analyses, accelerated life testing, degradation testing, reliability verification testing and warranty analysis.(Yang, 2007) 2.1.3. Reliability Main Factors: To judge on the reliability of any product, there are factors should be known, as an instance: Intentional usage or application. Product, machine and component specification. Price. Customer expectations. Level of inconvenience caused by product, machine or component breakdown. 2.1.4. Reliability Measurements: In a view of the fact that reliability is measured by probability or likelihood, any effort to measure it will engage the usage of statistical methods. Therefore statistics are very important tools in relating to reliability studies. (Yang, 2007) 2.1.5. Reliability Formula: Warranty and reliability share the same patterns for an economic sense to be observed. Reliability has been identified as the likelihood of a product to keep performing its intended task without breaking down. R= reliability. P (s): success probability. N: number of attempted trails. S: number of success. F: number of failures. Reliability mainly presents the successes and failures in a process, where a good economic warranty cost model has high accuracy in reliability prediction. Design for Reliability: Overview of the Process and Applicable Techniques. 2011. Design for Reliability: Overview of the Process and Applicable Techniques. [ONLINE] Available at: http://www.reliasoft.com/newsletter/v8i2/reliability.htm. [Accessed 19 March 2011]. 2.1.6. Reliability Improvement: There are many ways by which the reliability can be affected, below are two ways: Quality is the integration of features and characteristics of a product or a service, to enable us to meet the needs and specific requirements. Repetition of the same task causing financial and labor waste. (6Condra, 2001) 2.1.7. Reliability Applications: Various phases of a power plant such as construction, production and maintenance shall apply the reliability data analysis. Such a data might be (Heyman, 1988)applicable for production planning, benchmarking , trend analysis, plant components improvement, risk issues, RCM , spare parts optimization, Design review , Structural reliability. (Heyman, 1988) Data on existing units can be effectively useful for benchmarking the unit performance, during RCM, failure preventions, the spare parts optimization.(Heyman, 1988) 2.1.8. Reliability Prediction Science: It is considered to estimate the effects of the choices made prior the system is built or put into service. Reliability prediction handles the analysing of products with the help of models better than real systems to supply a solid foundation for testing, analysing, planning, manufacturing, and estimating reliability. An ideal example of reliability prediction is to predict the system of specified design and specified group of components in an ideal working environment. At the end of the prediction the reliability of the same system should be tested in a different surroundings from those which data and prediction were obtained from earlier.(3Blischke and Murthy, 2000) Reliability prediction procedure is attempted at the very first steps of improving a program to hold up the design procedure. Commencing a reliability prediction helps in supplying clear demands of reliability enhancement within the improvement stage, and the knowledge of the possibilities of failure of the equipment in its operation life. The advantage of applying reliability prediction, machinery designs are able to develop, money is saved rather than spending on poor designs and time is preserved concerning testing. A widely used way for prediction the reliability of machinery is based on database usage, however this way is not probable due to variety types of failure rates which dramatically happen to similar products.(Geitner and Bloch, 2006) 2.1.9. Objective of Reliability Prediction: The importance of reliability prediction lies down under several points: The reliability prediction should be implemented as an assurance program in different sections of a plant. Repairing decisions are taken when and where problems appear.(Kececioglu, 2002) 2.1.10. Taxonomy Related to Reliability: Availability: It can be defined as the probability that the component will function at any random time. Mean time to failure (MTTF): The time that elapses until a failure occurs. Mean time between failures (MTBF): It is the average time between failures. It is used for repairable systems. Failure Rate: The failure rate in a time interval which is the probability that a failure per unit time occurs in the interval given. Hazard Function: The failure rate limit as the interval approaches zero.(Pham, 2006) 2.2. Reliability Centred Maintenance: The word maintenance from the engineering point of view is: to take the necessary action to maintain or restore equipment and machinery, or system to determine the practical requirement to achieve maximum validity. This includes corrective maintenance, preventive maintenance, and predictive maintenance. What is maintenance? Definition and Meaning. 2011. What is maintenance? Definition and Meaning. [ONLINE] Available at: http://www.businessdictionary.com/definition/maintenance.html. [Accessed 19 March 2011]. Reliability centred maintenance or (RCM) can be expressed as an advanced study into maintenance, which joins the maintenance of interactive applications, preventive, predictive, and proactive, as well as the formation of plans to make the most of the life of the product, and also to ensure proper function for the product, machine and component at the lowest possible cost. Introduction to Reliability Centered Maintenance (RCM) Part 1. 2011. Introduction to Reliability Centered Maintenance (RCM) Part 1. [ONLINE] Available at: http://www.plant-maintenance.com/RCM-intro.shtml. [Accessed 19 March 2011]. 2.2.1. Preventive Maintenance: Preventive maintenance is the programme of planned maintenance, which aims to prevent the collapse and failure. The main objective of preventive maintenance is to prevent the failure of equipment before it happen. It is designed to maintain and improve equipment reliability by replacing worn components before they fail in practice. Preventive maintenance activities include equipment checks and repairs, partial or complete checks at fixed intervals, oil changes, and lubrication and so on. In addition, workers can record equipment deterioration so they know when to replace or repair defective parts before they cause system failure. It would be an ideal preventive maintenance program to prevent all equipment failure before it happens. Preventive Maintenance. 2011. Preventive Maintenance. [ONLINE] Available at: http://www.weibull.com/SystemRelWeb/preventive_maintenance.htm. [Accessed 19 March 2011]. 2.2.2. Predictive Maintenance: Techniques help to determine the status of equipments in service in order to predict when you must perform maintenance. This approach offers cost savings over routine preventive maintenance. What Is Predictive Maintenance?. 2011. What Is Predictive Maintenance?. [ONLINE] Available at: http://www.wisegeek.com/what-is-predictive-maintenance.htm. [Accessed 19 March 2011]. 2.2.3. Terms and Goals of Using Reliability Cantered Maintenance: The majority of maintenance organizations classify the goals of using (RCM) by the below listed steps: Scheduling the tasks by its priority. Consider the safety prospective. To be familiar with the machinery capabilities; each type of machinery will have different performance type. Knowing the failure causes; to recognize when the right moment to reduce it is. Using skilled staff; to help out in scheduling priorities. Practicing preventative tasks; to help in knowing the machinery status. Disposing and replacing the damaged components; to ensure the effectiveness of the other related parts. Standards must be identified for each step mentioned above. It is important that the steps are done by the same staff who are responsible of the function and operation of the plant.(Tweeddale, 2003) The conditions to develop a sufficient (RCM) program depend on the success of using the observation and statistical methods, because sometimes both methods depend on each other. 2.3. Failure Mode and Effects Analysis: Mechanical failures are introduced as any significant changes regarding size, shape or material characteristics in a system. The first and main responsibility of any mechanical designer is to make sure that the design produced is capable of doing its function properly, meets the designated life time and most important is to be competitive in the market. Estimating and identifying all possible modes of failure which may restrict the functionality of the design will ensure the success in designing. The designer must be familiar with the variety collection of failure modes presented in the work sites as well as the circumstances leading to it, so the designer becomes ready to prevent failure from occurring once again. The designer should preferably have an on hand experience to investigate predictable failures in a professional manner, thus failures could be prevented in future. It is clear that the failure analysis, prediction, and preventative are significant to be known to every designer.(5Collins, 1993) The term behind the failure can be known as the failure to meet some specific performance measurements. Different between definitions terms such as defects, malfunction, fault and reject are usually vital in comparing causes of failures, as well as in the categorizing and analyzing of provided information. The different between the terminologies is mainly to define the types of failure, reasons, and level of failure. For any introduced definition of failures there are no doubts in introducing reliability. Because the failure is the absent of the specification and so changes in performance capabilities occur. (Smith, 2005) The estimation of the data could be done by two methods, first by using history data; this will enable us to have a look at similar machinery which may had experienced identical problems, warranty data, and customer feedback. Second method is conducted, by using several mathematical methods, models and simulations. Dealing with (FMEA) does not always mean that one way is better or more accurate than the other; both of the methods can be used if applied correctly. The proper way in commencing (FMEA) will result is providing helpful data which can help in reducing the hazards relating to work load in a system, product and service. The (FMEA) is one of the most efficient ways considered in preventative maintenance. The (FMEA) will help in having knowledge about what is suitable correction tasks should be done to keep failures away from happening. An effective and successful (FMEA) system could be recognized by meeting these objectives, first recognize the known and possible failures modes, and then reasons of failures. Schedule the failures modes according to the highest risk level, and finally follow up the work done to ensure the correction of the failure.(Stamatis, 2003) 2.3.1. When and Where To Use Failure Mode and Effects Analysis: The (FMEA) procedure is extensively used in different stages, regarding product designing and manufacturing processes. It offers a well organized structure and an easy way to communicate amongst the team of manufacturers. It can be used as well in developing services which will help production process.(McDermott et al., 1996) Traditional failure modes and effects analysis (FMEA) are mainly used models in warranty cost among other models in the automobile industry. (Majeske, 2003) An essential term to inherent reliability into a product or system is by recognizing the failure causes, and making sure they are removed or that their likelihood of happening once again is low. This thought can be done by conducting tests, or logically by using models. Failure mode and effects analysis is a planned way in clarifying the origin of failures modes, and it is considered to be a sufficient reliability schedule, especially it links to reliability development throughout design stage.(7Denson, 2006) 2.4.4. Hazard and Operability Study (HAZOP): Risk analysis is an orderly and systematic method for Examination system and risk management. In particular, are often used as a risk and operating Technique to identify potential hazards in the system and identify interoperability problems. It assumes that events are caused by the risk of design or operating intentions. This approach is a unique feature of risk and vulnerability to treatment methodology that helps to stimulate the imagination of the team Members when exploring potential deviations. Figure (2) shows a sample of HAZOP system.(Organisation and Safety, 1988) Figure (1) a sample of HAZOP system Hazard Operability Studies (Hazops) 1 of 2. 2011. Hazard Operability Studies (Hazops) 1 of 2. [ONLINE] Available at: http://www.lihoutech.com/hzp1frm.htm. [Accessed 19 March 2011]. 2.3.2. Failure Prevention: Failures are predictable, sooner or later all products, machines and component will experience failure due to many reasons.(Yang, 2007) In any engineering system failures are expected. The effects of failures differentiate from little inconvenience costs to financial drops. Failures happen due to various factors, such as: Bad engineering design. Manufacturing process errors. Insufficient testing. Human mistakes. Poor maintenance. Misuse. In order to reduce failures or breakdowns in any engineering systems, there are some methods should be followed: Identify the cause and the way the failure happened. Identify how many times do the failure tends to repeat. Reliability handles the failure concepts in details via different statistical approaches. Whereas safety tries to study, specify, measure, determine, and analyze the failure.(Verma et al., 2010) 2.4. Introduction to Hazard: The accurate understanding of hazard is appreciated due to its criticality. It supplies us with the base foundation of a system safety. Hazard analysis is conducted to identify hazards consequences, and hazard main factors, As well as to determine the risks facing the system. To carry out hazard analysis in a proper manner, it is essential to recognize what causes hazards and how to define hazards. Understanding the hazard character is an important issue to improve the skills needed to identify potential hazards and their results in a system design.(Ericson, 2005) 2.4.1. Hazard Analysis: This analysis involves describing the complete process first, and then collecting the answers for a set of systematic questions. The purpose is to identify how exactly the deviations from the design can arise.   These deviations are further assessed by any negative effect of their consequences on the safe and efficient operation of the plant.   The assessment would provide a basis for any action to be taken to cure this situation. From an engineering point of view, hazard analysis process is the best tool for analyzing reliability data. It can be used to make conclusions about the reliability of a component. (12002) 2.4.2. Survival Analysis: Survival function, also known as a reliability function of the survivors, is a property of any random variable that maps a set of events, usually associated with failure of some system. 2.4.3. Hazard Rate Function: Hazard rate function can be obtained by an equation which assumes a constant hazard rate. 2.4.5. Bathtub Curve: Figure (2) illustrates the bathtub curve which demonstrates the product failure rate against time. Any product cycle life can be divided into three separate durations: The first duration (early life): This duration where the failure probability is decreased to minimum. . It what happens in the early life of most new products, sometimes the first period is mentioned as the mortality period. The second duration (normal life or useful life): This is represented in the graph by a flat line. Failures and breakdowns happen randomly within this duration. In this period the failure rate tends to become somehow constant. During this period the lowest failure rate is observed, so it is the most appropriate time to make reliability predictions. The third duration (wear out): this begins where the slope starts to rise till the end. This typically happen to products when they get old, thus the failure rate increases. Wear out is usually caused by break down due to various reasons such as physical wear and stress.(speaks, 2005) Figure (2) a bathtub curve. A Brief Introduction to Reliability. 2011. A Brief Introduction to Reliability. [ONLINE] Available at: http://www.weibull.com/LifeDataWeb/a_brief_introduction_to_reliability.htm. [Accessed 19 March 2011]. 2.5. Statistical Models for Life Data: Statistical models for life data such as weibull distribution, survival analysis and warranty help in producing high accuracy in prediction. The automobile manufacturing having relied heavily on warranty interval in its warranty provision inclines more in reliability and therefore seek such analysis. (Ward and Christer, 2005) 2.5.1. Weibull Distribution: The weibull distribution is named after a Swedish professor Waloddi Weibull. He explained the ability to use the weibull distribution in small sizes measurements and it is easiness to supply an accurate model for a broad data sets. At the beginning of his exploring weibull distribution he faced some obstacles and doubts form his colleagues. However, the weibull distribution has ended now to be widely practised in reliability.(8Dodson, 2006) A reason for the wide spread of the weibull distribution is that it has a large different shapes, which makes it easy to fit any data. Also, it is perfect to show the weakest connection of a product. For example, if a system has more than one part, the weibull distribution will present each failure time of each part at the same distribution no matter how insignificant they are .(Nelson, 2003) Figure (3) is a sample of weibull a distribution plot. Figure (3) a sample of weibull distribution plot. Guidelines for Burn-in Justification and Burn-in Time Determination. 2011. Guidelines for Burn-in Justification and Burn-in Time Determination. [ONLINE] Available at: http://www.reliasoft.com/newsletter/v7i2/burn_in.htm. [Accessed 19 March 2011]. 2.5.2. Kaplan Meier Survival Estimator: The Kaplan Meier estimator is named after Edward L. Kaplan and Paul Meier. It estimates the survival function. In engineering this method is used to measure the time until failure of different products, machine and components. Kaplan EL, Meier P. J Am Stat Assoc 1958; 53:457-81. [Cited by: McKenzie S, et al. JOP. J Pancreas (Online) 2010 Jul 5; 11(4):341-347. (Reference 14)]. 2011. Kaplan EL, Meier P. J Am Stat Assoc 1958; 53:457-81. [Cited by: McKenzie S, et al. JOP. J Pancreas (Online) 2010 Jul 5; 11(4):341-347. (Reference 14)]. [ONLINE] Available at: http://www.joplink.net/prev/201007/ref/02-014.html. [Accessed 19 March 2011]. 2.5.2.1. Formulation: Where: t (1) 2.5.3. Exponential Distribution: This is the most commonly used distribution in reliability, and is often used to predict the probability of survival to time (t) figure (4) shows a sample of exponential distribution graph.(9Dovich, 1990) Figure (4) a standard exponential distribution graph Continuous Random Variables: The Exponential Distribution. 2011. Continuous Random Variables: The Exponential Distribution. [ONLINE] Available at: http://cnx.org/content/m16816/latest/. [Accessed 19 March 2011]. 2.5.3.1. Formulation: The probability density function is: Where Mean time to failure = Or, where 2.5.4. Disadvantages and Advantages of Statistical Method: Cost; studying and analyzing a quantity of data of different products within a system are an expensive job. The results revealed are not sufficient enough to build an understanding of the type of maintenance needed in this particular situation. The only disadvantage of the observation method appear is when applying it carelessly and without keeping record of foundings, this will result in mixing up different judgements.(4Chalifoux and Baird, 1999) 2.6. Introduction to Warranty: Warranty is a provision for a seller to provide assurance to a buyer that the product will perform as implied. (Zhou and Tang, 2008) Warranty brings confidence to the buyer; automotive vehicles like any other automated system consider warranty to a buyer. (Wu and Li, 2007) Unlike the quality loss function which assumes a fixed target and accounts for immediate issues, warranty loss occurs during the customer use. (Zhou and Tang, 2008) In automotive industry, data is tracked and analyzed regularly (Zhou and Tang, 2008). The interval can be evaluated on the basis of their costs. The effect of warranty especially in the context of the interval, affects the performance of the company especially if the number of returns on warranty is high. (Wu and Li, 2007) Neglecting the fact that warranty cost is a result of conflict between the customer expectation and the performance of the product, the interval of the warranty liability disturbs the economic sense of warranty. (Wu and Li, 2007) Warranty costs have in many companies been positioned as operational costs. (Ward and Christer, 2005) The impact of warranty in the whole business performance has challenged vehicle manufacturers to develop vehicles that are less costly to repair (Metric: Warranty $s) and are more reliable within a longer period of time. (Metric: annual failure rates, AFR) For this purpose to be done, warranty cost models that make the impact of reliability on cost and costs associated with repair of specific failure modes should be economically healthy. (Wu and Li, 2007) 2.6.1. Warranty Probability: The ratio as Pw is termed as the warranty probability (Ward and Christer, 2005). The warranty probability is the ratio of the number of complaints N against the total number of products Tp. Pw Another factor that is important in warranty cost analysis is the complaint factor. (Ward and Christer, 2005) The complaint factor is the ratio of the actual number of complaints and the potential number of complaints where the actual number of complaints is the number of actual complaints fixed. (Ward and Christer, 2005) The method for calculating the warranty probability depends on product performance and customer expectations. (Wang et al., 2010) The distance of performance is a function of the warranty interval. (Ward and Christer, 2005) It is supposed that as time passes, the distance of performance increases, this is the common feature referred to as mileage. In motor vehicles the time age of the car has been consistently assumed to be a factor representing its use. (Manna et al. 2008) Despite the fact that mileage can be determined, the correlation between mileage and age of the car is strong and positive. (Manna et al. 2008) Since vehicles manufacturing designs and model change with time, the automobile industry prefer attaching warranty to age of the vehicle rather than calibrated mileage. Warranty is a key factor in bringing confidence to a buyer. The higher the warranty time, the more the confidence is the buyer. (Manna et al. 2008) 2.6.2. Warranty Distribution Analysis: Feedback from warranty returns provides a solid basis in determining use failure distribution. (Murthy, and Blischke, 2006) The time interval as a factor contributes significantly to predictions. The warranty intervals are the most solid factor that can be used in assessing the failures prediction. By maintaining warranty and assessing failures for a longer period of time, more knowledge on the performance especially for automated systems is achieved. (Murthy, and Blischke, 2006) Reasons for carrying out warranty data analysis are the following: Forecasting warranty claims. To determine risk assessment and monitoring. Reliability assessment.(12002) 2.6.3. Reduction strategies for cost drivers There are two factors that have been identified as primary warranty cost drivers. The number of occurrence of an event which can be noticed by the analysing failure rate and the cost of the process are the identified cost drivers. (Attardi et al., 2005) The strategies employable for reduction of costs are by reducing the factors. (Attardi et al., 2005) 2.6.4. Cost model in product development The cost model has been used in product development in making economic sense of organizational existence. (Karim and Suzuki, 2005) Through its impact in influence of decision making by providing design alternatives that come handy in warranty cost, the model establishment should be in advisory of the product development through calculation of estimates of product total warranty cost. (Aldridge, and Dustin, 2006) Difference in warranty costs based on design alternatives provides a short projection of the optimized design that maintains both customer confidence through warranty and economic advantage to the organization. (Attardi et al., 2005) Identification of necessary product features, capabilities and diagnostic tools that are required in automobile projected warranty savings for the warranty intervals is achievable through the cost model in product development. (Aldridge, and Dustin, 2006) Under the foundation of the cost model, the risk involved in the warranty interval can be evaluated by analyzing the risk involved in an extension of warranty in automobiles. (Aldridge, and Dustin, 2006) It should be taken into consideration that the cost model economic impact is dependent on the period of warranty especially with automobiles that are known to wear and tear. (Karim and Suzuki, 2005) Chapter 3: case study (from notes given by doctor) Introduction: Field data in the automotive industry often comes in two types, the first is grouped data expressed by months in service. The second is ungrouped data available from company owned but customer operated fleets and expressed as miles to failure. In many scenarios, data which comes from late stages have a greater importance over the former because of the following reasons: Mileage is more objective measure of the component life than time in service. There are types of failures are not tracked by the warranty system. The complexity of censoring mechanism in relating to reliability analysis of grouped warranty data. Therefore, this theoretical case study will focus on the analysing of ungrouped mileage data which is not represented by time in service, because it comes from the company owned fleets. Aim and objective: To discuss a procedure to estimate the censoring mileage and the reliability function for a component of interest (e.g.: battery). Data: Table 1 shows a format of failure data from a customer operated fleet. The vehicle mileage is reported only at failure or service events. VIN failed / serviced comopnent failure / service mileage X009 battery 45000 X018 fuel pump 91680 X021 brake pads 78470 X006 front wipers 77350 X028 head lamp 4007 X015 clutch disks 150400 X031 front wipers 51420 X003 ign.switch 3961 X013 battery 16890 X007 front struts 27160 X026 battery 72280 X031 battery 131900 X027 door lock 7298 X017 fuel pump 4734 X

Rights :: essays research papers

One would think that the story of Matthew Shepard would bring people together over a tragic event. On the contrary, Matthew Shepard’s death seemed to pull the nation apart, due to people’s conflicting points of view. Should Matthew’s heartbreaking death be seen as any other killing, or should everyone take it upon himself or herself to be responsible for what happened to Matthew?   Ã‚  Ã‚  Ã‚  Ã‚  When reading the article â€Å"Blood on our Hands†, I believe that the writer had a strong position about his argument. Phil Martin states that everyone should take responsibility for Matthew’s death because people everywhere reject the unfamiliar and label others without thinking about the consequences of their actions. I believe that he is correct that we in the United States do not take the time to understand people who are different than we are. Being in a minority group as a young Jewish woman, I can empathize with the writer when he talks about being angry with self-sanctimonious religious leaders. When religious officials speak out about gays, Jews, Muslims or any other minority they need to realize that people may take their words and apply them. How can anyone be shocked about the death of a gay man, when it is being taught that gay people are not deserving of God?   Ã‚  Ã‚  Ã‚  Ã‚  Nobody’s cause is more important than anyone else’s. Everyone should educate themselves about the differences we face in America. Understanding is the key component to making change happen. If gay activists stood for the equality of women, and if women activists would stand for the equality of African Americans, then everyone would stand for something. They would stand for the equality of all Americans in this country.   Ã‚  Ã‚  Ã‚  Ã‚  The problem with this theory of mine is that people automatically put the blame on others and points the finger the other way. In â€Å"Matthew Shepard: What is the Big Deal?† Colby Carter uses personal attacks at gays to bolster his opinion. He states that protestors at a Gay March in New York waved signs reading, â€Å"Where is your rage?† in response to the death of Matthew. I think the writer takes the word rage out of context because he insists that gay protestors were using violence to solve the problem. I see people waving signs that display the same message outside of abortion clinics. Anyone can be angry about something they believe in strongly without having someone jumping to the conclusion that they are violent.

Global and U.S. Economy Essay

After a low-key performance for about three consecutive years, prospects for growth of the world economy significantly improved in 2004. This improvement in the economic outlook was widespread across the nations of the world. However, differences in economic robustness among regions and countries persisted. In the preceding two years, macroeconomic policies had been crucial for stimulating the global recovery, but the emerging challenge was for policies to simultaneously sustain robust growth and maintain stable inflation (United Nations, Economic and Social Development Affairs, â€Å"2004† 3) Following a temporary slowdown in mid-2004, global GDP growth picked up through the first quarter of 2005, with robust services sector output more than offsetting slowing global growth in manufacturing and trade. In the second quarter, however, in part reflecting the impact of higher oil prices, signs of slowness emerged, with leading indicators turning downward and business confidence weakening in most major countries. Subsequently, while global manufacturing and trade were strengthened, and leading indicators picked up, the continuing rise in crude oil and refined product prices, which was exacerbated by the catastrophic effects of Hurricane Katrina, acted as a major downward force (World Economic Outlook, â€Å"2005† 1). Nonetheless, the resilience of the global economy in 2005 continued to exceed expectations. Despite higher oil prices and natural disasters, activity in the third quarter of 2005 was in fact stronger than earlier projected, particularly among emerging market countries; global GDP growth was estimated at 4.8 percent, 0. 5 percentage point higher than projected previously (World Economic Outlook, â€Å"2006†1). Global industrial production has gone up from mid-2005; the services sector today remains strong; global trade growth is at a high level; consumer confidence and labor market conditions are on an optimistic note; and forward-looking indicators such as business confidence have risen. Asia is forging ahead, with China enjoying double-digit expansion and India growing very rapidly as well. Growth in most emerging and developing countries remains solid, with a marked buoyancy of activity in China, India, and Russia. After years of deflationary weakness, Japan has embarked on a new path, with personal consumption and labor income joining exports and business investment as the main drivers of growth. Japanese expansion is well established. In continental Europe, activity weakened again late last year, partly reacting to rising oil prices, but accelerated in early 2006 (Organization for Economic Co-operation and Development). There are signs of a more sustained recovery in the Euro area, although domestic demand growth remains subdued in that region. The impressive performance of the global economy in recent years is, truly, a cause for celebration. Accelerated growth is vital prerequisite for poverty reduction in developing countries. Without sustained and rapid growth, lasting poverty reduction will prove elusive (Krueger). Though hurricanes had a damaging impact in the United States, it was but a transient one, and the activity was already bouncing back early in 2006. Among industrial countries, the United States remains the main engine of growth. In 2005, the U. S. economy expanded by 3.5%, a rate slightly above potential growth for the U. S. economy, leading to a decline in the unemployment rate from 5. 4% in the fourth quarter of 2004 to 4. 9% in the final quarter of 2005. The economy added nearly two million jobs in 2005, averaging 165,000 jobs per month. Yet the economy experienced a substantial swing in economic activity beginning in the third quarter of last year. Real gross domestic product (GDP) expanded by 4. 1% in the third quarter, slowed drastically to 1. 7% in the fourth quarter, and then bounced back up to 5. 6% in the first quarter of 2006. (Strauss and Engel).

`` The Cask Of Amontillado `` By Edgar Allan Poe - 1848 Words

Edgar Allan Poe and Nathaniel Hawthorne are two American Literature short story writers. Poe’s short stories focused on the gothic and mystery genre while Nathaniel Hawthorne focused his work on the dark romanticism genre. Both of their works, explored the conflicts between good versus evil, madness in the human mind and the psychological effects of guilt and sin on a human being. But the way that these two writers create these effects for the readers is their different approaches in the way they choose to tell their stories. Edgar Allan Poe’s short stories are in the first person point of view where the narrator is the main character while Nathaniel Hawthorne’s stories are in the third person point of view where the narrator tells the†¦show more content†¦This allows the narrator to talk to the audience as if they trust and already know the reader. This type of narration style allows Poe’s stories to create the madness in the human mind where the narrator is terrorized by his own realizations and the horrors of what human beings are capable of. For example, The Tell-Tale Heart and The Cask of Amontillado. The short story â€Å"The Cask of Amontillado†, is being narrated by the killer Montresor. As the story opens, the narrator talks to the reader as if he already knows him/her by saying, â€Å"You, who so well know the nature of my soul, will not suppose, however, that I gave utterance to a threat.† (Poe 289). The reader will now able to look in Montresor state of mind throughout the story and see his thoughts and intentions. Montresor talks about his friend Fortunato and how we wants revenge by saying, â€Å"I must not only punish, but punish with impunity†¦.A wrong is undressed when the avenger fails to make himself felt as such to him who has done the wrong.† (Poe 289). By Montresor saying this the reader can see his intentions on what he wants done with Fortunato for doing him wrong. The reader oversees Montresor’s plan to ask Fortunato to have a drink of wine with him down in his families’ tombs. While they are down in the tombs, the narrator describes the start of the killing, â€Å"In an instant he had reached the extremity of the niche, and finding his progress arrested by the rock†¦.. A moment more and I had fettered him to the