BUSINESS LAW ( REPORT ) Essay Example | Topics and Well Written Essays - 1500 words

BUSINESS LAW ( REPORT ) - Essay Example Even in America itself, it is not possible for a company to function with a unique law in to different states. In other words, companies need to function with respect to the laws prevailing in the location where they operate. Separate legal personality and limited liability are two common terms associated with company law. Wiss (2010) describes separate legal personality as an incorporated company, â€Å"united or combined into an organised body† having rights and liabilities. In her opinion a company is a fictitious person who can enter into contracts, own property and even commit crimes. At the same time when a private company limited by shares, the creditors deal with the company, not with the individuals and it can be termed as a limited liability company. In such cases, if the company become bankrupt, the creditors or the investors do not get paid regardless of the personal financial capabilities of its memebrs (Wiss 2010). Separate legal personality and limited liability are two advantages of corporate status. But under certain circumstances these advantages will become invalid and this paper briefly explains such circumstances in which separate legal personality and limited liability will b ecome invalid. It is not possible for a company to take undue advantages in the name of limited liability or separate legal personality. Corporate law has mainly identified seven instances in which the corporate veil (law that protect the members or founders of a company in case a problem arises) can be lifted; fraud, agency, trust, group enterprise, tort enemy character, tax (Sadhu, n. d) Richard Wachman (2005) has mentioned that fraud is costing British business  £72 billion a year, 6% of the annual revenue of British businesses (Wachman, 2005). The recent corporate scandals involving Enron, WorldCom, Parmalat and Refco, have not taught any lessons to the authorities or the investors. Fraud can attain many forms; some companies may overstate their profits, some

Patient safety in the operating room Term Paper - 1

Patient safety in the operating room - Term Paper Example ip, culture and behavior---rather than the science that proves to be the weak link in the chain of health-care delivery and patient safety.† In fact, patient’s safety in the operating room has a direct impact on nursing. Therefore, the procedure and methodologies used to ensure ultimate objective of patient safety are required to be studied for effects on nursing behavior and practices. Throughout the history of healthcare and especially in the recent decades the operating room nursing practices are primarily influenced by the patient safety. Operating Room (OR) nursing is gauged by the preventive measures and safe handling of the patient. The Operating room safe handling is closely monitored, and a mere negligence can bring the devastating results. Under these circumstances pressures and stress are the natural outcome in OR nursing practices.   â€Å"Focusing on the structure, processing and outcomes of care, a behavioral health patient safety program continually emphasizes changing the system to make treatment safer for consumers through evolution of the evidence.† (Fowler & Susan, n. page). This focus and monitoring at all levels demand an extra bit of vigilance and strict compliance with laid down procedures and standing orders to ensure patient safety. However, it reduces the margin of decisions, which is a major instrument for safety management in op erating rooms. Drawing on the importance and sensitivity of decision in operating rooms Pikaar, Ernst &, Paul (239) states, â€Å"The surgical domain is a fragile and a complex web of experts with constant decision making and uncertainties linked to patient safety. Any unwanted technological interference in key treatment strategies or surgical tasks can lead to fatalities.† The complexities of decision-making are not limited to technological domains, the psychological pressures and overriding stress can be equally distressing for nursing staff. The Patient Safety precautions can also affect the operating

Marijuana-A description of the drug and its aeffects Essay Example for Free

Marijuana-A description of the drug and its aeffects Essay Marijuana is the most commonly used illegal drug in the United States. It is made from the dried leaves and flowering tops of the Indian hemp plant Cannabis Sativa. People smoke, chew, or eat marijuana for its hallucinogenic and intoxicating effects. The flowering tops of the Cannabis plant secrete a sticky resin that contains the active ingredient of marijuana, known as Delta-9-Tetrahydrocannabinol (THC). The plant has both male and female forms. The sticky flowers of the female plant are the most potent. Hashish is a similar drug prepared from the same plant. It differs from marijuana in that it is made of only the resin from the plant, but where marijuana is made up of flowering tops and leaves. The main active chemical in marijuana is THC (delta-9-tetrahydrocannabinol). The membranes of certain nerve cells in the brain contain protein receptors that bind to THC. Once securely in place, THC initiates a series of cellular reactions that lead to the high that users experience when they smoke marijuana. There are usually phases in marijuana use there are: intoxication, initial stimulation, which includes giddiness and euphoria, followed by sedation and pleasant tranquility. Mood changes are often accompanied by altered perceptions of time and space. Thinking processes become disrupted by fragmentary ideas and memories. Other feelings include increased appetite, heightened sensory awareness, and general feelings of pleasure. Negative effects of marijuana use can include confusion, acute panic reactions, anxiety attacks, fear, a sense of helplessness, and loss of self-control. Like alcohol intoxication, marijuana intoxication impairs judgment, comprehension, memory, speech, problem-solving ability, reaction time, and driving skills. Although marijuana is not physically addicting and no physical withdrawal symptoms occur when use is discontinued, psychological dependence develops in some 10 to 20 percent of long-term regular users. Smoking marijuana can damage the lungs, and long-term use may increase the risk of lung cancer . Even infrequent use of marijuana can cause burning and stinging of the mouth and throat, often accompanied by a heavy cough. Someone who smokes marijuana regularly may have many of the same respiratory problems that tobacco smokers do, such as daily cough and frequent chest illness, a heightened risk of lung infections, and a greater tendency to obstructed airways. Cancer of the respiratory tract and lungs may also be promoted by marijuana smoke. Marijuana use has the potential to promote cancer of the lungs and other parts of the respiratory tract because it contains irritants and carcinogens. Marijuana smoke contains 50 to 70 percent more carcinogenic hydrocarbons than does tobacco smoke. It also produces high levels of an enzyme that converts certain hydrocarbons into their carcinogenic form, levels that may accelerate the changes that produce malignant cells. Marijuana users usually inhale more deeply and hold their breath longer than tobacco smokers do, which increases the lungs exposure to carcinogenic smoke.Some other effects of marijuana may occur because THC impairs the immune systems ability to fight off infectious diseases and cancer. In laboratory experiments that exposed animal and human cells to THC or other marijuana ingredients, the normal disease-preventing reactions of many of the key types of immune cells were inhibited. In other studies, mice exposed to THC or related substances were more likely than unexp osed mice to develop bacterial infections and tumors Depression, anxiety, and personality disturbances are all associated with marijuana use. Because marijuana compromises the ability to learn and remember information, the more a person uses marijuana the more he or she is likely to fall behind in accumulating intellectual, job, or social skills. Students who smoke marijuana get lower grades and are less likely to graduate from high school, compared to their non-smoking peers. Workers who smoke marijuana are more likely than their coworkers to have problems on the job. Several studies associate workers marijuana smoking with increased absences, tardiness, accidents, workers compensation claims, and job turnover. A study of municipal workers found that those who used marijuana on or off the job reported more withdrawal behaviors such as leaving work without permission, daydreaming, and spending work time on personal matters. Although no medications are currently available for treating marijuana abuse, recent discoveries about the workings of the THC receptors have raised the  possibility of eventually developing a medication that will block the intoxicating effects of THC. Such a medication might be used to prevent relapse to marijuana abuse by lessening or eliminating its appeal.

Purpose And Definition Of OEE Engineering Essay

Purpose And Definition Of OEE Engineering Essay 2.1 Introduction These days, in this demanding world, the total elimination of waste is for the survival of the organization. The waste caused due to the failure or shutdown of facilities that has been built with enormous investment, and also waste such as defective products ought to be completely eliminated. In a manufacturing sector, companys facilities have to be functioning efficiently in order to gain desirable productivity, inventory cost, delivery as well as quality. In this context, the motive of OEE analysis and measurement is to reduce the equipment losses to zero and has been recognized as a necessity for many organizations. According to Bamber et al. (1999) [5], the role of teamwork, small group activities and the participation of all employees is crucial to accomplish equipment improvement aims. Hence, OEE is use as metrics to determine the Total Productive Maintenance (TPM) activities. On the other hand, it can also be said that OEE shows a consistency approach to measure the effectiven ess of TPM as well as other programs by providing an overall structure for measuring production efficiency. As explained by (Dal et al., 2000) [6], the role of OEE goes far beyong not only monitoring and controlling, but also takes into consideration of process improvement initiatives/programs, provides a systematic method for establishing production targets, prevents the sub-optimization of individual machines or product lines, as well as incorporates practical management tools and techniques. This ensures the attainment of a balanced view of process availability, quality and performance. Another statement made by Lesshammar and Patrik (1999) [7], in their case studies, have presented how OEE is being used in industry and as well have reported that this metric forms a useful part of an overall system of measurement. In other words, it provides a useful method to measure the effectiveness of manufacturing operations from a single piece of equipment to the whole manufacturing plant of several manufacturing plants in a group. In doing so, OEE not only provides a complete scenario of where productive manufacturing time and money is being lost, but at the same time uncovers the true , hidden capability of the industry. Thus, it becomes the key manufacturing decision support tool for constant improvement programmes [8]. Apart from that, OEE is an established method of measuring followed by optimizing the efficiency of a machines performance or that of a whole industry plant. The effectiveness of a plants production highly depends on the effectiveness with which it makes use of equipment, materials, man and methods as explained by Suzuki (1999) [9]. Besides, OEE can have a significant impact on the productivity of a manufacturing unit. Therefore, through OEE manufacturers may systematically direct their business towards attainment of continuous improvement operating margins, optimized competitive position and maximized utilization of capital. Some of the more prominent firms have benefited from OEE as a measurement gauge for implementing improvement activities that increases company profits and costs. . 2.2 History of OEE OEE is an essential metric and basic methodology for manufacturers practicing a Lean manufacturing strategy that is zero waste in their value streams. This metric element follows the well-founded principle: If you cant measure it, you cant manage it [10]. Some advocates are fond of the view If youre not taking score, youre only practicing [10]. In 1972, the Japanese Plant Maintenance Institute (JPMI) developed a theory called Total Productive Maintenance [11]. The preliminary aim of TPM was to eradicate the six big losses and subsequently the eight wastes. It was first implemented and developed in Toyotas automotive plants, soon after evolving into world renowned Toyota Production System. An organizational culture was formed by Toyota that focused on the systematic identification and elimination of all waste from their production process where the technical / human contributions to production are maximized. Reengineering and organizational change is used to maximize yield, minimize cost and time-compress the supply chain by fully excluding non-value added activities and not right first time events. The OEE gauge came forward from the Japanese production focused, equipment management framework of TPM [10]. OEE is the key measure of the tangible benefits accessible from TPM by Seiichi Nakajima, the founder of Total Productive Maintenance who initially used OEE to depict a fundamental measure for tracking production performance. He (Seiichi Nakajima) challenged the complacent view of effectiveness by focusing not merely on keeping equipment running smoothly, but on creating a sense of joint responsibility between maintenance workers and operators to optimize the Overall Equipment Performance. OEE symbolized in the first of the original pillars of TPM. Guided all TPM activities and measured the results of these loss focused activities. Therefore, the use of OEE had evolved into the current focused improvement pillar, one of eight TPM pillars. During the mid 1990s, coordinated by SEMATECH the semiconductor wafer fabrication industry has adopted to improve the productivity of the fabrication [11]. Since then, manufacturers in other industries throughout the world have embraced OEE ways to improve their asset utilization. 2.3 The purpose of OEE The OEE metric can be applied at a number of different levels within a manufacturing environment. First, OEE can be used as a benchmark for measuring the initial performance of a manufacturing industry as a whole. Thereby, the initial OEE measure can be compared with future OEE values, hence quantifying the level of enhancement made. Subsequently, an OEE value calculated for one manufacturing line can as well be used to compare line performance across the industry, thus highlighting any poor line performance. If the machines processes work individually, an OEE measure can discover which machine performance is worst, and therefore indicate where to focus TPM resources ( Nakajima 1988) [5]. Dal et al. (2000) [6] declared that by utilizing largely existing performance data, such as preventive maintenance, absenteeism, accidents, material utilization, conformance to schedule, labor recovery, set-up and changeover data, etc., the OEE measure may possibly provide topical information for daily decision making. Due to this, the OEE measurement method within a industry becomes the elementary measure of TPM activities, as well as a basis of improvements for the TPM process. 2.4 Definition of OEE In the era of globalization today, manufacturers are forced to look for creative ways to maximize additional investment due to the continuous pressure of global competition which results in lower margin. In this state, OEE has becoming a hot topic. In its most basic form, OEE offers a straightforward ways to keep track of manufacturing performance as well as to measure the total equipment performance- the degree to which the asset is doing what it is supposed to do. However, the true power of OEE as a dedicated application lies in the ability to use it as a change-enabler, or tool for continuous improvement and lean manufacturing programs [8]. There are various methodologies to gauge manufacturing efficiency. Generally most companies will have a number of measures already in place. Nevertheless, many now disagree that none of these approaches are as comprehensive or far reaching as the OEE achievement, since OEE provides a way to measure the effectiveness of manufacturing operations from single piece of equipment to the manufacturing plant in entirety, or several manufacturing plants in a group. as a result, OEE can be well thought-out as a central KPI (key performance indicator). It drives an organization to examine all aspects of asset performance in order to ensure gaining the maximum benefits from a piece of equipment that is already bought and paid for [12]. Thus, it is obvious that OEE acts as an approach for monitoring and managing the lifecycle of manufacturing assets. On the other hand, OEE can be expressed as a commonly accepted set of metrics that bring clear focus to the key success drivers for manufacturing enterprises [13]. In other words, it measures both efficiency (doing things right) and effectiveness (doing the right things) with the equipments. These measurement comprises of three fundamental elements where each one is expressed as a percentage and accounting for a different kind of waste in the manufacturing process. Thus, it is understood that OEE is a function of the three factors. The three factors mentioned below are briefed as: Availability or uptime (downtime: planned and unplanned, tool change, tool service, job change etc.) A measure of the time the plant was in fact available for production compared to the manufacturing requirements. Any losses in this area would attribute to major breakdowns or extended set up time [14]. Performance efficiency (actual vs. design capacity) The rate that concrete units are produced compared to the designed output. Losses in this area would attribute to slow speed running, minor stoppages or adjustments [14]. Rate of quality output (Defects and rework) A measure of good quality, saleable product, minus any waste. Losses in this element would attribute to damage rejects or products needing rework [14]. Measuring OEE can be done simply by capturing the five basic pieces of information as stated below: Planned Production Time the planned amount of time in which production is planned for a specific line. Down Time specify as the amount of time the process is not running during the planned production time (interrupts to production). Ideal Cycle Time represent as the theoretical minimum of time needed to produce a single piece of product. Total Pieces denote as the total number of pieces produced during the planned production time. Good Pieces signify as the total number of pieces produced that meet quality standards. Figure 2.1 The Overall Equipment Effectiveness flow chart 2.5 Objectives of OEE Overall Equipment Effectiveness records and data informations are used to categorize a single asset (machine or equipment) and/or single stream process related losses in order to improve total asset reliability and performance. Besides, the information is useful and essential as it helps to identify and categorize major losses or reasons for poor performance. OEE offers the basis for setting enhancement priorities as well as for the root of measurement and analysis. In addition, the percentage determined is used to track and trend for improvement, or decline, in equipment effectiveness over a period of time. Hidden or untapped capacity in a manufacturing process can be pointed out through these percentages and lead to balance flow. On top of that, OEE can be used to develop and enhance collaboration between asset operations, maintenance, purchasing, and equipment engineering to jointly identify and reduce (or eliminate) the 2 major causes of poop performance since maintenance alone cannot improve OEE. 2.6 The use of OEE The root why companies uses OEE is to avoid making inappropriate purchases, and help them focus on improving the performance of machinery and also plant equipment they already own. Companies should also start with the area that will provide the greatest return on asset because OEE is able to find the greatest areas of improvement. These OEE formula with the major factors involves will show how improvements in quality, changeovers, machine reliability improvements, working through breaks and more. In business world today, when many manufacturers strive towards world class productivity in their facility, this simple method will perform an excellent benchmarking tool [15]. Besides, the simple derived OEE percentage makes a great motivational system as it is easy to understand and this single number is displayed where all facility personnel can view it. By giving employees such as operators and workers an easy way to see how they are doing in overall equipment utilization, production speed, and quality, in return they will strive for a higher number instead. 2.7 Defining Six Big Losses One of the major goals of TPM and OEE programs is to reduce and/or eliminate what are named as the Six Big Losses, the most common causes of efficiency loss in manufacturing sectors. This was put forwarded by Nakajima in 1989 [16]. There are basically 3 categories of OEE loss which include: Down Time Loss, Speed Loss and Quality Loss. Each of these types has been divided into two sub-losses. They are known or called the Six Big Losses. Basically, OEE is generally measured in terms of these six losses as showed below. They are categorized as stated below: Breakdown Losses Setup and Adjustments Losses Small Stops Losses (Idling and Minor Stop Losses) Reduced Speed Losses Startup Rejects (reduced yield losses) Production Rejects (quality defects and re-work) Categorizing these data makes addressing the Six Big Losses much easier, and a key goal should be fast and efficient data collection, with data put to used throughout the day in the real time. 2.2 Addressing the Six Big Losses Measurement is essential to establish appropriate metrics. It is important necessity of continuous improvement processes. As stated by Nakajima (1988), an efficient way of analyzing the efficiency of a single machine or an integrated manufacturing process is through OEE measurement [17]. It is a function of availability, performance rate, and quality rate. In fact, the three dimensions are measures in terms of equipment losses. Following this, Nakajima (1988) defined these losses into six major categories as follows [17]: 2.7.1.1 Availability Losses Based on the mechanism principle, a machine most likely is available 24/7/365. However, this comes from an ideal perspective, from which one can measure true machine availability. There are few genuine factors that affect on availability, some of which are planned, and some unplanned. For planned downtime, it takes into account of holidays, scheduled maintenance and vacation. While for unplanned downtime, it includes equipment failures and setup and adjustments. It is possible to factor in the planned downtime; however it is the losses due to unplanned downtime that can negatively affects machine availability. Breakdowns Breakdown Losses are classified as by far the biggest of the Six Big Losses. These losses are significant due to the fact of its sudden, dramatic failure in which the equipment stops completely [18]. In the view of the fact that there is no production therefore this unexpected breakdown are undoubtedly elements of losses. The breakdown can cause all equipment functions to be terminated even though the source lies in a single specific function. Nevertheless, deterioration related to problem and losses are also regard as break down losses. It is important to improve OEE by eliminating unplanned downtime. But if the process is down, other OEE factors cannot be dealt with. Therefore, it is not merely important to know how much downtime your process is experiencing (and when) at the same time to be able to attribute the lost time to the specific reason or cause for the loss [19]. Setup and Adjustments Whenever the production of one product stops and the equipment is adjusted to meet the requirements of another product, this is where setup and adjustment take place. The loss of time due to this delay is known as setup and adjustments Basically, setup and adjustments period of time is normally measured as the time between the last good parts produced before setup to the first consistent good parts produced after setup. In order to constantly produce parts that meet the quality standards, it should generally include substantial adjustment and/or warm-up time. Various innovative ways have been used by companies to reduce setup time. These comprises assembling changeover carts with all tools and supplies necessary for the changeover in one place, pinned or marked settings so that coarse adjustments are no longer necessary, and use of prefabricated setup measures [20]. 2.7.1.2 Performance Losses Machine performance referred to as the net production time during which products are produced. The more the machine produces, the greater the OEE metric. However, speed losses and small stops will inhibit the overall performance of machine. If such losses is not recognized and addressed, the machine performance cannot be fully optimized. Reduced Speed Reduced Speed can be classified as one of the most difficult of the Six Big Losses to monitor and record. This is due to the reason that there is a significant difference between the theoretical maximum speed and what people think the maximum speed is. In most cases, in order to prevent other losses such as quality rejects and breakdowns, the production speed needs to be optimized. Losses due to reduce speed are therefore, often ignored or underestimated [21]. It happens when the equipment runs slower than its optimal or maximum speed. Apart from that, reduced speed is the difference between designed speed and the actual operating speed [21]. There are various reasons where equipment may be running at less than its designed speed, for instance non-standard or difficult raw materials, history or past problems, mechanical problems, or fear of overloading the equipment. This loss of speed is actually converted into time during the OEE calculation. Small Stops We can also assume small stops as one of the most difficult of the Six Big Losses to monitor and record. Whenever a machine shows short interruptions and does not have a constant speed, this will not result in a smooth flow of production. Minor stoppages and the subsequent loss of speed can be the cause from products blocking sensors or products getting stuck in the conveyor belts. The machines effectiveness will be diminished drastically if these hitches occur frequently [21]. The occurrence of these losses happens whenever equipment stops for a short time as the result of a temporary problem. As an example, a work-piece is jammed in a chuck or when a sensor activates and shut down the machines, this will definitely result in a minor stoppage. As soon as someone removes the jammed work-piece or resets the sensor instantly, it operates normally again. These losses also include idling losses that occur when equipment continues to run without producing. Thus, since idling and minor stoppages interrupt jobs, therefore they can also be categorized as breakdowns. Despite that, the two are fundamentally different in that a minor stoppage and the duration are usually less than 10 minutes. 2.7.1.3 Quality Losses A scrap is when the final product is not saleable, and the entire process has been wasted on product that will never make it to the customer. Thus, it is very essential to take into account the quality of the product while evaluating OEE. Availability and speed often has been the main focus, and quality is left behind. The key to keep in mind is that without a good product, the rest of the operation is a white elephant. Generally, quality losses are generated during startup while the machine is ramping up, during adjustment, or during normal production, as rejected/unwanted product due to process instabilities. Startup Rejects Products that do not meet the quality standards are called scraps, even if they can be sold as sub-spec. A specific type of quality loss is the startup losses where these losses occur due to when: Starting up of the machine: the production is not stable as soon as the machine starts and the first products do not meet the quality standards. The process of the machine at the end of a production run is no longer stable and the products no longer to be able to meet the specifications require. Quantities of products are no longer counted as part of the production order and consequently are considered as loss. These are usually hidden losses, which are often considered to be unavoidable. The scale of these losses can be surprisingly large [21]. Certain adjustments and warm-up time is required for several equipments to obtain optimum output. Losses that happen in the early stages of production during machine setup to stabilization of product quality are called the startup losses. The losses differ with degree of stability of processing condition, operators technical skill, maintenance level on equipment, and many more. Production rejects A product that does not meet the quality specifications/standards for the first time, but can be reprocessed into good products is known as rework products. Reworking products is not a disadvantage as the product can be sold to fit other demand needs. However, the product was not right first time and is therefore a quality loss just like scrap [21]. Production rejects are classified as quality losses that are not caused by startup. These losses arise only when products produced are not conforming to the specifications. Parts that require rework of any kind should be considered reject and this happens during steady state production. Example of the Downtime loss, Speed loss, and Quality loss is depicted in the following page. The Six Big Losses with three categories are shown in figure below. The following table shows how this Six Big Losses are categorized with examples given. Figure 2.3: Classification of Six Big Losses. The table below lists the Six Big Losses, and show how they are relate to the OEE Loss categories. A typical major loss, the categories of OEE as well as examples of events is shown as follow: OEE Loss Category   Six Big Loss Category   Event Examples   Down Time Loss   Breakdowns   à ¢Ã¢â€š ¬Ã‚ ¢ Tooling Failures à ¢Ã¢â€š ¬Ã‚ ¢ Unplanned Maintenance à ¢Ã¢â€š ¬Ã‚ ¢ General Breakdowns à ¢Ã¢â€š ¬Ã‚ ¢ Equipment Failure   Setup and Adjustments à ¢Ã¢â€š ¬Ã‚ ¢Ã‚  Setup/Changeover à ¢Ã¢â€š ¬Ã‚ ¢ Material Shortages à ¢Ã¢â€š ¬Ã‚ ¢ Operator Shortages à ¢Ã¢â€š ¬Ã‚ ¢ Major Adjustments à ¢Ã¢â€š ¬Ã‚ ¢ Warm-Up Time Speed Loss   Idling and Minor stops   à ¢Ã¢â€š ¬Ã‚ ¢ Obstructed Product Flow à ¢Ã¢â€š ¬Ã‚ ¢ Component Jams à ¢Ã¢â€š ¬Ã‚ ¢ Misfeeds à ¢Ã¢â€š ¬Ã‚ ¢ Sensor Blocked à ¢Ã¢â€š ¬Ã‚ ¢ Delivery Blocked à ¢Ã¢â€š ¬Ã‚ ¢ Cleaning/Checking   Reduced Speed à ¢Ã¢â€š ¬Ã‚ ¢ Rough Running à ¢Ã¢â€š ¬Ã‚ ¢ Under Nameplate Capacity à ¢Ã¢â€š ¬Ã‚ ¢ Under Design Capacity à ¢Ã¢â€š ¬Ã‚ ¢ Equipment Wear à ¢Ã¢â€š ¬Ã‚ ¢ Operator Inefficiency Quality Loss   Start-up Losses à ¢Ã¢â€š ¬Ã‚ ¢ Scrap à ¢Ã¢â€š ¬Ã‚ ¢ Rework à ¢Ã¢â€š ¬Ã‚ ¢ In-Process Damage à ¢Ã¢â€š ¬Ã‚ ¢ In-Process Expiration à ¢Ã¢â€š ¬Ã‚ ¢ Incorrect Assembly   Defect Losses à ¢Ã¢â€š ¬Ã‚ ¢ Scrap à ¢Ã¢â€š ¬Ã‚ ¢ Rework à ¢Ã¢â€š ¬Ã‚ ¢ In-Process Damage à ¢Ã¢â€š ¬Ã‚ ¢ In-Process Expiration à ¢Ã¢â€š ¬Ã‚ ¢ Incorrect Assembly Table 2.1 : The Six Big Losses in OEE 2.8 OEE factors As explained in previous subsequent chapter, the OEE calculation is based on the three OEE factors. This comprises of Availability, Quality and Performance. They are as well referring as Effectiveness Factors. Here is how each of these factors is calculated. Availability The Availability part of OEE represents the percentage of scheduled time that the equipment is available to function [18]. This Availability element is a measurement of the uptime that is designed to exclude the effects of performance, quality, and scheduled downtime events. Since Availability takes into account of Downtime loss, the formula is calculated as: 20 Availability = Operation time Planned Production time Where, Operation time = Planned production time Unscheduled Downtime Production time = Planned production time Scheduled Downtime Downtime losses zero indicates the availability is 100%, where the gross operating time equals the available time for production. i.e. Operation time equals Planned Production time. Therefore, it can be said that 100% Availability means the process has been running without any recorded stops. Performance Performance can be denoted as the ratio between Net Operating Time and Operating Time. Since Performance takes into account of speed loss, the formula is calculated as: 22 Performance = Net Operating Time Operating Time The Performance portion of OEE corresponds to the speed at which the machine runs as a percentage of its designed speed. This Performance element is a measurement of speed that is designed to exclude the effects of availability and quality [18]. Performance does not penalize for rejects, which imply even if the work is rejected or rework, it will still be included in the planned and actual hours accordingly. Since Performance takes into account Speed Loss, the formula is calculated as: Performance = Ideal Cycle Time Operating Time / Total Pieces 23 Where, Ideal Cycle Time = the minimum cycle time that the process can be expected to achieve in optimal circumstances. It is at times called, Theoretical Cycle Time, Nameplate Capacity or Design Cycle Time. Since Run Rate is the reciprocal of Cycle Time, Performance can also be calculated as: Performance = Total Pieces / Operating Time Ideal Run Rate 24 Performance is limited at 100%, to make sure that if an error is made in specifying the Ideal Cycle Time of Ideal Run Rate, the effect on OEE will be limited. Therefore, it can be said that 100% Performance means the process has been consistently running at its theoretical maximum speed. Quality Rate The Quality portion of the OEE signifies the good units produced as a percentage of the total units produced [18]. The Quality metric is a measurement of process yield that is designed to exclude the effects of availability and performance. Quality is the ratio of Fully Productive Time to Net Operating Time. Quality = Fully Productive Time / Net Operating Time 25 Quality = Good Pieces / Total Pieces Since Quality takes into account of Quality Loss, the formula is calculated as: 26 (Total no of units of processed products- No of units of no good products)/(total no of units of processed products). Thus, it can be said that 100% Quality means there is no rework or reject pieces. Therefore, since OEE takes into account all three OEE factors, the formula is calculated as: 27 OEE = Availability x Performance x Quality Therefore OEE is the product of its effectiveness factors; Availability, Performance and Quality. The study of each of these effectiveness factors will improve the Overall Equipment Effectiveness. Below diagrams shows the three major elements of OEE together with formula calculated . Figure 2.4à ¢Ã¢â€š ¬Ã‚ ¦.Shows the formula on how to calculate OEE Figure 2.5à ¢Ã¢â€š ¬Ã‚ ¦Shows the OEE Factors Loss OEE Factor Planned Shutdown Not included in OEE calculation Down Time Loss Availability is the ratio of Operating Time to Planned Production Time (Operating Time is Planned Production Time less Down Time Loss). Calculated as the ratio of Operating Time to Planed Production Time. 100% Availability means the process has been running without any recorded stops. Speed Loss Performance is the ratio of Net Operating Time to Operating Time (Net Operating Time is Operating Time less Speed Loss). Calculated as the ratio of Ideal Cycle Time to Actual Cycle Time, or alternately the ratio of Actual Run Rate to Ideal Run Rate. 100% Performance means the process has been consistently running at its theoretical maximum speed. Table 2.1 indicates the 3 main factors of OEE Quality Loss Quality is the ratio of Fully Productive Time to Net Operating Time (Fully Productive Time is Net Operating Time less Quality Loss). Calculated as the ratio of Good Pieces to Total Pieces. 100% Quality means there have been no reject or rework pieces. 2.9 OEE Components of Plant Operating Time 2.9.1 Components of Plant Operating Time In order to establish an accurate measurement, OEE analysis begins with Plant Operating Time. Basically, this Plant Operating Time implies as the amount of time the facility is open and available for equipment process. It can also be refer as the maximum amount of time and is a constant. One day consists of 24 hours of 60 minutes. While, for one week, it consists of 7 days of 24 hours. Whereas, in one year consists of 52 weeks. At times, Plant Operating Time is also referred to as Theoretical Production Time. It consists of different losses like speed and quality loss as well as fully productive time 2.9.1 Plant Production Time Once a category of called Planned Shut Down is subtracted from Plant Operating Time, the remaining available time is called Planned Production Time. The Planned Shut Down shall include any events that should be excluded from efficiency analysis since there was no intension of running production [22]. For example, tea breaks, lunch breaks, scheduled maintenance or periods where there is nothing to produce. Nevertheless, Planned Production Time is also known as Available Production Time. OEE initiates with Planned Production Time and analyze efficiency as well as productivity losses that occur, with the aim of eliminating or reducing these losses. OEE starts with Plant Operating Time and end up with Fully Productive Time, screening the source of productive loss that occur in between. 2.9.1.1 Operating Time From Planned Production Time, the downtime loss is subtracted to gain Operating Time. The downtime losses inclusive of any events that stop planned production for an appreciable length of time (normally several minute-long enough to log as a traceable event) [22]. Examples of these include material shortages, equipment failures, and changeover time. Since it is also includes as type of downtime, the changeover time is included in OEE analysis. Even though it may not be possible to reduce 9 changeover times, however, it can be reduced in most cases. The remaining available time is called Operating Time and also known as Gross Operating Time [22]. 2.9.1.2 Net Operating Time From the Operating Time, the speed loss is deducted to obtain Net Operating Time. The speed losses take account of any factors that cause the process to operate less than the maximum possible speed while running. Examples of these include machine wear, substandard materials, miss-feeds, and operator inefficiency. 2.9.1.3 Fully Productive Time As for Net Operating Time, the Quality Loss is subtracted and the remaining available time is called the Fully Productive Time. These quality losses accounts for produced pieces that do not meet quality standards, together with pieces that require rework. The goal here is to maximize Fully Productive Time w

Aztecs 5 :: essays research papers

Analysis of an Aztec Encounter   Ã‚  Ã‚  Ã‚  Ã‚  The Spaniard and Aztec civilizations were two completely different worlds whose fated encounter caused some surprising reactions from both parties. Neither of these nations knew exactly what to expect or how to react to each other’s behaviors. Differences in religion, customs and weaponry became the deciding factors of who would be the dominant aggressor in these encounters. Even though both parties were unsure of what to expect, the Spaniards had already set a goal for themselves before they set foot in Mexico. They wanted to conquer the other nation and exploit them for anything of value.   Ã‚  Ã‚  Ã‚  Ã‚  The climax of the Aztec Empire and the conquistadors occurred when Motecuhzoma and Cortes met face to face for the first time. The Spaniards as well as the Aztecs had no clue what to expect. Motecuhzoma told Cortes, “Our lord, you are weary. The journey has tired you, but now you have arrived on earth… to sit on your throne, under its canopy.'; This was due to the fact that the Aztec religion told of a god, Quetzalcoatl, who would come from the heavens and take his place as ruler of the Aztec Empire. Thus Motecuhzoma showered the Spaniards with many fine gifts. Unlike the Spaniards believed, these fine gifts were not really a sign of Aztec submission but rather as a sign of wealth and power. In order to give proper respect to their so-called god, the Aztecs had to show that they were a worthy and powerful nation. The Spaniards took this as a weakness. They thought the Aztecs feared them, which boosted up their confidence level even though they were gre atly outnumbered.   Ã‚  Ã‚  Ã‚  Ã‚  The Spaniards had to communicate with the Aztecs by using La Malinche as an interpreter. She basically made the Aztecs believe that Cortes was a good man and would be cause them no harm. They also had other indigenous people who were allied with the Spanish. The Aztecs must have viewed this as a sign that these strangers would be peaceful since they had others of their kind on the Spaniard’s side. La Malinche translated all that Motecuhzoma had said to Cortes. On page sixty-four of The Broken Spears it says, “Cortes replied in his strange and savage tongue…'; In other passages in the book it depicts the Spaniards as wild and uncivilized. This brings up another point that just as the Spaniards thought of the Aztecs as being barbaric, some Aztecs felt the same way about the Spaniards.

Rapid Urbanization Upsurge Noncommunicable Diseases Health And Social Care Essay

Rapid urbanisation, modernisation and population growing in developing states has led to an rush of non-communicable diseases which are associated with important morbidity and mortality. Metabolic Syndrome besides described as â€Å" Deadly Quartet † and X syndrome ( 2, 3 ) is one of these disease entities defined by bunch of cardiovascular hazard factors which to a greater extent is influenced by ethnicity/race. This encompasses atherogenic dyslipidemia, high blood pressure, dysglycemia and splanchnic fleshiness and pro coagulator province. Apart from increasing prevalence, the age of oncoming is besides worsening among South Asiatic ( SA ) population due to familial sensitivity, ingestion of easy available energy dense nutrients from an early age. This tendency has got major wellness deductions since South Asians constitute one fifth of population all over the universe ( 4 ) and the wellness attention system is non really fit to cover with this medical crisis. Evidence sugge sts that it non merely amplifies the hazard of coronary bosom disease ( 5 ) but besides gives rise to cerebrovascular diseases. Five diagnostic standards have been put frontward since the origin of this syndrome which has created perplexity among practicians. In 1998, World Health Organization ( WHO ) ab initio proposed a definition for metabolic syndrome ( 6 ) with chief accent on gluco-centricity. In 1999, the European Group for the survey of Insulin Resistance ( EGIR ) recommended more or less similar standards with lower cut offs for high blood pressure ( 7 ) . Thereafter in 2001, National Cholesterol Education Program Adult Treatment Panel III ( NCEP ATP III ) proposed another definition for the diagnosing of metabolic syndrome with less focal point on insulin opposition as compared to WHO standards but non turn toing separate cut off points of waist perimeter for Asiatic population ab initio ( 8 ) . In 2003, American Association of Clinical Endocrinologist ( AACE ) proposed another set of standards for the diagnosing of metabolic syndrome. The chief restriction of the above mentioned standards is that the diagnosing is based on clinical judgement alternatively of presence of specific figure of hazard factors ( 9 ) . Sing that SA have a higher per centum of organic structure fat chiefly in the signifier of abdominal adiposeness at a lower BMI in comparing with other population, International Diabetes Federation ( IDF ) in 2005 suggested separate cutoff points of waist perimeter for Asiatic population and defined cardinal fleshiness as waist perimeter of more than 80 centimeter for adult females and 90 centimeter in work forces based on local statistics from the corresponding country ( 10 ) . The revised NCEP ATPIII modified for South Asiatic population incorporated the same cut off points for Asiatic population as given by IDF ( Table 1 ) . Apart from the cut off differences, NCEP ATP III gives equal weight to each constituent of metabolic syndrome as compared to IDF for which abdominal fleshiness remains a requirement for the diagnosing ( 10 ) . Furthermore, microalbuminuria which is a controversial variable of WHO criteria is non included in other definitions. Among these definitions, WHO, NCEP ATPIII & A ; IDF have been the chief 1s which are used most widely ( Table 1 ) . Type 2 diabetes is besides emerging as a planetary epidemic with increasing prevalence in developing states. Pakistan is among top 10 states estimated to hold the highest figure of diabetics busying 6th place on the diabetes prevalence naming presently ( 11 ) and it is estimated that prevalence would be doubled by 2025. Metabolic syndrome in combination with diabetes increases the hazard of both macro vascular, micro vascular complications and coronary artery disease patterned advance due to associated high blood pressure, lipoprotein abnormalcies and splanchnic fleshiness ( 12 ) . There are surveies that have looked into the differences in most widely used definitions of metabolic syndrome in general ( 13-17 ) , but merely few surveies have compared these definitions in the diabetic population ( 18-20 ) . Therefore we decided to find the frequence of metabolic syndrome in Type 2 diabetics harmonizing to NCEP ATPIII, IDF and WHO definitions and so to compare and contrast these traits within Pakistani population. Methods: This survey was conducted at the out-patient clinics of one of the big third attention infirmaries at Karachi, Pakistan. Data was collected retrospectively of type 2 diabetic patients sing clinics between June till November 2008 by utilizing a questionnaire which included demographic features and single constituents of metabolic syndrome i.e. weight, tallness, waist perimeter and BMI etc. Both hip and waist perimeter were recorded in centimetres and waist/hip perimeter was calculated ( WHR ) . BMI was calculated as a ratio of weight in kilogram to height in metres squared.Lab checks:All the research lab trials which are routinely done for patients with type 2 diabetes including triglycerides and high denseness lipoprotein ( HDL-C ) were recorded. Patients already on anti hypertensive and anti lipid medicines specifically in the signifier of fibric acid derived functions and nicotinic acids were taken as instances of high blood pressure and hypertriglyceridimia severally irrespective of their blood force per unit area and lipid degrees. Since all the patients in the survey were diabetics, insulin degrees were non taken into history. Statistical Analysis: The information was analyzed individually harmonizing to NCEP ATP III, IDF and WHO definitions and the consequences were so compared. The frequence of Metabolic syndrome was calculated with 95 % CI based on three different standards ‘s. The informations were presented as the mean A ± SD or per centum ; uninterrupted variables were compared by agencies of independent sample t-test and categorical variables were compared by chi-square. All analyses were conducted by utilizing the statistical bundle for societal scientific disciplines SPSS 14. A kappa trial was done to find the concurrency between three definitions. In univariate analyses, comparing between metabolic syndrome and without metabolic syndrome was done for each variable of involvement. Multivariable logistic arrested development analysis was conducted to place the factors associated with metabolic syndrome. All P values were two tailed and considered statistically important ifA a†°Ã‚ ¤ 0.05. Out of entire 210 type 2 diabetic patients, 112 ( 53.3 % ) were males and 98 ( 46.7 % ) were females. Their average age ( standard divergence ) was 53.35 A ± 11.46 old ages. The mean ( SD ) continuance of diabetes mellitus was 8.48 A ± 7.18 old ages. One hundred and ninety three ( 91.9 % ) were found to hold metabolic syndrome harmonizing to NCEP ATP III in comparing to 182 ( 86.7 % ) based on IDF standards. Lower frequence was documented with WHO standards of 171 ( 81.4 % ) . The frequence increased to 179 ( 85.2 % ) by WHO by utilizing the new cut offs for specifying corpulence ( BMI of 23 vs. 30 ) . The grade of understanding ( kappa statistic ) between WHO and ATP III and WHO and IDF definitions were 0.436 95 % CI 0.26-0.60 and 0.417 95 % CI 0.25-0.57respectively. In contrast kappa statistic between IDF and ATP III definitions was found to be 0.728 95 % CI 0.57-0.87.The overall understanding between three definitions was 0.37 ( 95 % CI 0.26-0.51 ) .The cardinal fleshiness was present in 162 patients ( 77 % ) by WHO followed by 197 ( 90.5 % ) based on IDF & A ; NCEP ATP III. Hypertension was found in 116 patients ( 55.2 % ) harmonizing to WHO in comparing to 147 ( 70 % ) by NCEP & A ; IDF cut off of blood force per unit area. Presence of low HDL cholesterin once more differed being present in 77 ( 36.7 % ) when WHO definition was applied and 144 ( 68.6 % ) by ATP III and IDF. Furthermore, gender wise dislocation of frequence of metabolic syndrome by WHO showed that 84 ( 85.7 % ) of females suffered from metabolic syndrome as compared to 87 ( 77.7 % ) in males a difference non statistically important ( p=0.13 ) . However, by all other standards metabolic syndrome was significantly more common among females as compared to males, 95.9 % vs. 88.4 % ( p=0.04 ) by ATP III & A ; 95.9 % vs. 78.6 % ( p & lt ; 0.001 ) by IDF. For prevalence of hypertriglyceridemia, no statistically important difference between both genders was found. However, for low HDL cholesterin, prevalence was higher in males 44 ( 57.14 % ) than in females 33 ( 43 % ) by WHO standards ( P & lt ; 0.001 ) . In contrast on the footing of ATP III and IDF definitions, prevalence of low HDL cholesterin degrees was higher ( p=0.009 ) in females 77 ( 57.46 % ) than in males 57 ( 42.53 % ) . Likewise, cardinal fleshiness was found to be more common among female patients based on IDF & A ; NCEP ( ATPIII ) cutoffs 64.8 % females vs. 35.2 % ( & lt ; 0.001 ) but demoing rearward form with WHO criteria,57.14 % males vs. 43 % females ( p-value & lt ; 0.001 ) . Discussion: Our survey showed a high frequence of metabolic syndrome in type 2 diabetics based on NECP ( ATPIII ) and IDF standards. This frequence was rather high ( 91.9 % ) as compared to 46 % found in another infirmary based survey from Pakistan ( 21 ) . This difference could non be merely attributed to the different waist cutoffs used based on modified NCEP ( ATPIII ) in our survey because even comparing with WHO categorization revealed important difference between two surveies from the same part. This difference in frequence is really interesting maintaining in position that both of these surveies were done in the same part but different vicinities. The disparity could be due to low frequence of fleshiness found in the old survey ( 30 % ) in comparing to our survey ( 90.5 % ) . It is speculated that this intra regional difference could be due to the fact that certain communities have high inclination to develop fleshiness and metabolic syndrome despite of belonging to the same state due to differences in life manner, eating wonts and degree of physical activity. On the other manus, another infirmary based survey another metropolis revealed comparable frequence of metabolic syndrome harmonizing to NCEP standards ( 22 ) . In infirmary based survey from Iran the prevalence in type 2 diabetics on footing of NCEP ( ATPIII ) standards utilizing BMI alternatively of waist perimeter was found to be 65 % ( 23 ) .This difference highlights the importance of abdominal adiposeness which is a better marker of metabolic syndrome as compared to BMI. A multicenter infirmary based survey in Brazil showed instead close frequence ( 85 % ) in type 2 diabetics ( 24 ) although the survey population was rather different being white people of European descent. Likewise, in Finnish survey prevalence was found to be 91.5 % in diabetic work forces and 82.7 % in adult females ( 25 ) . Our information was besides consistent with Indian survey demoing prevalence of 91.1 % ( 16 ) utilizing the same NCEP ( ATPIII ) definition. However, separate constituents of metabolic syndrome were found to be more common in our population as compared to South Indians ( 16 ) . The higher frequence of metabolic syndrome in diabetic population fou nd in our survey is a beginning of major concern since diabetes itself is an of import hazard factor for atherosclerotic cardiovascular disease ( ASCVD ) and presence of metabolic syndrome in combination plants as a two border blade. Evidence suggests that combination of the constituents of the metabolic syndrome is associated with both micro and macro vascular complications and distal neuropathy in patients with type 2 diabetes mellitus ( 24 ) . In position of the high frequence, type 2 diabetic patients should non merely be screened for this deathly syndrome but besides offered intensive direction in order to avoid complications. Similarly highly high frequence of cardinal fleshiness ( 90.5 % ) in our diabetic population is besides unreassuring since there is ample grounds associating cardinal fleshiness with coronary bosom disease ( 26 ) and insulin opposition is besides significantly associated with waist girth ( 27 ) . The higher frequence of metabolic syndrome in adult females harmonizing to all standards besides consistent with other surveies from South Asiatic states ( 28 ) could be attributed to less physical activity in adult females due to cultural and cultural limitations on out-of-door activities. This besides highlights the importance of instruction of our adult females in footings of bar of the development of metabolic syndrome with life manner intercession which would indirectly act upon life manner and eating wonts of whole household. The presence of multiple definitions of metabolic syndrome has been really confusing and argument ever exist which standards should be used in footings of diagnosing of metabolic syndrome particularly in diabetic patients. The somewhat higher prevalence of metabolic syndrome by ATP III definition in comparing to IDF ( 91.9 % vs. 86.7 % ) was likely due to the comparative flexibleness of the ATP III definition in footings of non taking abdominal fleshiness as a requirement for the diagnosing. Except for this difference the ATP III and IDF definitions are basically indistinguishable reflected in the grade of understanding ( kappa statistic ) between the two definitions which was in a good scope at 0.728. Harmonizing to this, NCEP ( ATPIII ) and IDF are the most dependable standards ‘s for naming metabolic syndrome in type 2 diabetic patients, with NECP capturing more patients in comparing with IDF definition. In contrast WHO showed lower frequence of metabolic syndrome due to different cutoffs used for HDL degrees and fleshiness. This difference remained important even after seting it with BMI cutoffs for Asiatic population of 23 vs.30 endorsed by WHO expert audience every bit good ( 29, 30 ) pointing towards the fact that waist perimeter or cardinal fleshiness is more valuable tool for sensing of metabolic syndrome in Asiatic population.Decision:On the footing of these findings NCEP ( ATPIII ) modified standards should be sooner used in Pakistani population since do ing waist perimeter as an obligatory standard would still lose out 5.2 % of the instances of metabolic syndrome harmonizing to our survey. But to farther validate these recommendations we need surveies to gauge the prognostic power for micro vascular and macro vascular complications to set up the most appropriate definition of metabolic syndrome to be used in South Asiatic population with a diagnosing of type 2 diabetes. The alarmingly high frequence of metabolic syndrome in type 2 diabetes found in our survey points towards the fact that our wellness attention system needs to take emergent stairss in bar of this syndrome through life manner intercession plans.

How a Christian might apply their beliefs Essay

In this, my second piece of coursework I will be looking at how a Christian might apply the beliefs that I just outlined in A01 and will refer to specific situations of conflict to illustrate this. A Christian could apply the beliefs I recently mentioned in A01 through all different means. The most recent event of late to do with war conflict is the Iraq war. Saddam Hussian we were told and could see was not a particularly pleasant man. I heard in papers and through television what he was doing to people and how he treated them. As Christians then in one point of view from the Sermon on the Mount we should forgive this man for his wrong doings and let him repent his own sins. This belief of forgiveness decelerates that should he recognise his wrongs and change his behaviour he could then be forgiven of his previous sins. Unfortunately Saddam was tolerant of the pain and suffering caused under his regime and unwilling to recognise a need to change his behaviour. However once captured Saddam was not subjected to the torture that he imposed but treated in a Christian and humane manner. Though as the passage states we should still maintain our Christian values and be forgiving, `to turn the other cheek`. An issue closer to home regarding conflict and Christianity is the fighting in Northern Ireland regarding the Catholics and Protestants. The two communities are constantly at war with one another over their faiths and in doing so are abandoning the core values of their religions. These two sets of people are following the `eye for an eye, tooth for a tooth`, way of dealing with their problems and issues, which has proven itself through twenty years of conflict to be ineffective and destructive. As again the passage from the Sermon on the Mount comes into effect and the two sides should realise that when a person of one side is killed they should not seek revenge and to kill, but to `live and let live`. Then this may result in an end to the violence and tragedies that are so often occurring. In the other effect towards Saddam Hussian issues we as Christians could most notice the quote of `An eye for and eye and a tooth for tooth`, from the Old Testament and do to Saddam the horrific things that we hear of him doing. Not many Christians, today I believe see this way of dealing with things. More to the point would not be really able as out generation of law and order would just not allow it. When people saw Saddam Hussian damaging an empire and country most I would have believed that they were angry and human instinct gets the better of belief. It is a natural feeling to become angry and upset with something or somebody. And this combining with believing that it is right to acknowledge the passage from the Old Testament results in terrible effects to peoples lives. Also this relates to the Wars going on around Northern Ireland. The two religions are constantly battling each other. We have seen the results of this situation and there is no justice to the trauma and deaths that are carried out.