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Quality Systems and Forecasting Techniques - Assignment Example

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This assignment "Quality Systems and Forecasting Techniques" focuses on Feigenbaum who is considered the originator of Total Quality Control. Quality control is the driving force for successful business undertakings. He considered human relations as a foundational factor in quality control…
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Name: Institution: Topic: Quality Systems and Forecasting Techniques Date: Question 1 a) Feigenbaum’s Contributions to Total Quality Management Feigenbaum is considered the originator of Total Quality Control. According to him, quality control is the major driving force for successful business undertakings. His contribution to quality control was not only narrowed to ideas but he went a step further to write a book on quality control. In his work, he strove to delineate himself from conventional considerations of technical methods of quality control, to a business oriented technique of quality control. As a result, his main objective was to stress on the management perception. He considered human relations as a foundational factor in quality control. Personal techniques like statistics or preventive maintenance are taken as the key elements of comprehensive quality control programme. He went ahead and defined quality as the total composite product and service characteristics of marketing, engineering, manufacture and maintenance through which product and service in use will meet the expectation of a client. According to Feigenbaum, quality does not imply best but best for the clientele use and cost for the producer. As such, he proposed that the word control in quality control is a management tool comprising of: Setting quality standards Appraising conformance to the standards Acting when standards are exceeded Planning for improvements in the standards For these reasons, quality can be taken as a move into all phases of industrial production process. This runs a long way from client needs and sales through design type, engineering and putting together, and ultimately shipment of the goods to the consumer who is satisfied with its quality. b) Feigenbaum’s nine fundamental factors (9M’s) affecting quality Through his spirited work on quality control, Feigenbaum established nine fundamental factors (9M’s) that affect quality. These include: market, money, men, motivation, material, machines and mechanization, modern information methods, and mounting product requirements. In essence, markets affect quality in such a way that whenever there is a need to penetrate a market and be competitive, the product must be of good quality to beat other competitors. Money in this case is the power to influence resources or inputs to achieve quality. This draws reference to the fact that quality has to be expensive in being attained. Men on the other hand refer to the customers and the manpower in place for the product and service. They affect quality based on their perception and satisfaction gap. Employees on the other hand need motivation to deliver quality services to clients. This is affected by management techniques employed as well as materials available in the manufacture of a particular product to good quality. Machines and mechanizations have to do with tools in place for the production of quality goods to meet men’s needs. These tools go hand in hand with the information methods employed to update on recent discoveries. Technology applied hence, affects the quality of products being delivered to the customer. Question 2 a) Categories of Quality Cost It is often said that prevention is cheaper based on the costs incurred in process trying to recover failures in products. It is noted that prevention occurs at the initial stage of manufacturing to ensure that products being delivered to customer are free of flaws that may be drawn back to factory. This case can be well illustrated in the two categories of quality costs. These are the control costs and failure costs. Each of the two broad categories has sub-categories as shall be indicated below to draw their differences. Control costs comprise of prevention costs and appraisal costs. As shall be noted in the example which shall be given, control costs are much less than the failure costs. Under the failure costs we have internal and external failure costs. Prevention costs as suggested in the term itself are those costs concerned with attempting to prevent defaults and errors in the product or along the supply chain. This implies that the task has to be done well at the first trial. This requires that planning stages are done well to reduce on the costs incurred following poor planning. Since every product has to be designed, the prevention cost may involve product design cost so that the product being designed is of quality. In addition, for a product to be of good quality and conform to the desired standards, it is imperative they go through a process. This brings about the process costs. Employees involved in designing the product require expertise and this can only be achieved through proper training. As such, training cost is required as well as information cost that facilitates updated information on the product. On the other hand, appraisal costs include the costs for measuring, testing and analysing material, parts, products as well as the entire process of production. This ensures that product quality particulars are being achieved. The second broader category of quality cost is the failure costs, which comprise of internal and external failure costs. The only difference between the internal and external failure costs is that internal costs emanate before the product leaves the factory. However, external failure costs come up after the product has been delivered to the client. This means that if there are any errors, the product has to take a full backward supply chain trend for corrective measures to be taken. A good example is taking a TV that costs $500 to reach the final user. It is noted that at the prevention stage, only 22% of the total cost are incurred to ensure tat the TV is of the required quality. This implies that failure costs will amount to 78% of $500. This is actually attributed to the backward movement of the production process after having been delivered to the customer. b) Essential Themes of Six Sigma The Six Sigma has three essential themes of quality. These include the client, process and the employee. Any corporation that has to remain in the global competitive market must channel its energies to these three essential elements. In this regard, we shall focus on the GE Corporation to show the application of the three essential themes of the Six Sigma. In most cases, customers expect performance, reliability and prices that are competitive. According to the Six Sigma, aspects such as timely delivery of good, clear and correct transaction are imperative in the competitiveness of a company. The customers’ necessities are therefore the centre of GE in the entire world. On the other hand, quality is all about the process taken to produce the products. The GE is accountable in this area through looking at the clientele perspective. Any transaction has to be understood from the customer’s viewpoint. It is only through this that vulnerable areas are identified in the corporation and improvements made. In the case of employee, leadership competency is at the centre of employee satisfaction. This is based on the fact that employees produce results. As a result, they need to have the necessary expertise which is only attained through proper training. The most significant training for employees is the Master Black Belt, Black Belt, Green Belt and Yellow Belt training that equips the employees with advanced statistical tools. Question 3 a) The difference between short, mid, and long-range forecast The major differences among the short-range, medium-range and long-term forecast are established based on; time frame, people involved in decision making, what is done and the tool used in the work done. Short-term forecast is often referred to as operational and takes up to 12 weeks. The core decision makers in the short-term forecast are the foremen of supervisors, and this involves work scheduling using exponential smoothing. Medium-range forecast usually take from 1 to 18 months with department managers being key decision makers. The forecast involves sales and production planning or budgeting using the time-series decomposition. On the contrary, long-term forecast take 3 or more years. Based on the long period involved, this is a sensitive stage and requires decision making at the executive, vice-president or manager’s level. Activities undertaken are new product planning as well as facility location using Delphi and other consensus techniques. A trend is usually a slow, long-term up or down movement of demand which is similar to the movement of the graph in (a). However, a cycle is an up-and-down repetitive movement in demand of a product. Cycle graph may be represented such as in figure (b). The only difference between a cycle and a seasonal pattern is that the seasonal one occurs periodically as indicated in figure (c). a. Trend b. Cycle c. Seasonal Pattern b) The Grofast Fertilizer Company Exponential Smoothing Ft+1 = αDt + (1- α) Ft F2 = (0.3×162) + (0.7×162) = 162.0 F3 = (0.3×163) + (0.7×162) = 162.3 F4 = (0.3×168) + (0.7×162.3) = 164.0 F5 = (0.3×166) + (0.7×164.01) = 164.6 F6 = (0.3×168) + (0.7×164.607) = 165.6 F7 = (0.3×165) + (0.7×165.6) = 165.4 F8 = (0.3×168) + (0.7×165.4) = 166.2 F9 = (0.3×169) + (0.7×166.2) = 167.04 F10 = (0.3×167) + (0.7×167.04) = 167.03 F11 = (0.3×170) + (0.7×167.03) = 167.92 F12 = (0.3×163) + (0.7×167.92) = 166.44 Month Demand for Fertilizer (ton) Forecast Ft+1 (α = 0.3) 1 162 - 2 163 162.00 3 168 162.30 4 166 164.00 5 168 164.60 6 165 165.60 7 168 165.40 8 169 166.20 9 167 167.04 10 170 167.03 11 163 167.92 12 169 166.44 Demand (ton) Months Linear Trend Line Y= a + bx Where: a = y intercept (at period x = 0); b = slope of the line; x = time period; y = demand for period x Mean of x = = 6.5 Mean of y = = 166.5 But b =; n = number of periods Therefore, b =  = 0.36 But a = mean of y – b ×mean of x = 166.5- (0.36×6.5) = 164.16 Linear trend line, y = 164.16 + 0.36x x (Period) y (Demand) Xy x2 1 162 162 1 2 163 326 4 3 168 504 9 4 166 664 16 5 168 840 25 6 165 990 36 7 168 1176 49 8 169 1352 64 9 167 1503 81 10 170 1700 100 11 163 1793 121 12 169 2028 144 Total 78 1998 13038 650 x (Period) y (Demand) Linear Trend y Xy x2 1 162 164.52 162 1 2 163 164.88 326 4 3 168 165.24 504 9 4 166 165.6 664 16 5 168 165.96 840 25 6 165 166.32 990 36 7 168 166.68 1176 49 8 169 167.04 1352 64 9 167 167.4 1503 81 10 170 167.76 1700 100 11 163 168.12 1793 121 12 169 168.48 2028 144 Total 78 1998 1998 13038 650 Demand (ton) Months Mean absolute Variation/Deviation Months Demand(D) Forecast (F) Absolute Deviation /D-F/ 1 162 2 163 162 1 3 168 162.3 5.7 4 166 164 2 5 168 164.4 3.6 6 165 165.6 0.6 7 168 165.4 2.6 8 169 166.2 2.8 9 167 167.04 0.04 10 170 167.03 2.97 11 163 167.92 4.92 12 169 166.44 2.56 Total 78 1998 1818.33 28.79 MAD =  = = 2.3992 Therefore, the Linear Trend Line forecast appears to be more accurate since its first intersection point is 2.5 as opposed to exponential smoothing having its first intersection point at 5.45. Bibliography: Bagad, V.S., 2008, Total Quality Management, Chicago, Technical Publications Berger, R.W., 2002, The Certified quality engineer hand book, New York, ASQ Quality Press. Black, K., 2009, Business Statistics: Contemporary Decision Making, New York, John Wiley and Sons Chaman L. Jain & Jack Malehorn, 2005, Practical guide to business forecasting, Sidney, Institute of Business Forec Charantimath, 2003, Total Quality Management, Pearson, Pearson Education India Hakes, C., 1991, Total quality management: the key to business improvement: a Pera International executive briefing, New York, Springer. Hirschey, M., 2008, Managerial economics, California, Cengage Learning Hyndman, R.J., 2008, Forecasting with exponential smoothing: the state space approach, New York, Springer Makridakis, S.G. & Wheelwright, S., 1989, Forecasting methods for management, New York, Wiley Pekar, J.P., 1995, Total quality management: guiding principles for application, London, ASTM International. Peratec Ltd., 1994, Total quality management: the key to business improvement, New York, Springer. Wang, J. & Wang, S., 2010, Business Intelligence in Economic Forecasting: Technologies and Techniques, London, Idea Group Inc (IGI). Read More
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