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Operational Management - Quality, Capacity, and Lean Systems - Assignment Example

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The paper "Operational Management - Quality, Capacity, and Lean Systems " is a perfect example of a management assignment. This method is quite efficient in the situation that it meets the set standards and measurements, and it creates necessary parts or results. The processability is surveyed and contrasted with the variables as to provide a result that is wide as possible…
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OPERATIONAL MANAGEMENT – QUALITY, CAPACITY AND LEAN SYSTEMS Name Class Instructor Institution City State Date Operational Management – Quality, Capacity, and Lean Systems a) It is evident that it does, Yes. Mean value is 163.32 gms This method is quite efficient in the situation that it meets the set standards and measurements, and it creates necessary parts or results. The processability is surveyed and contrasted with the variables as to provide a result that is wide as possible. In the problem, control charts and diagrams are used to provide an excellent screen quality. Consequently, the levels of the quantity of the problem are reviewed. In essence, there are two types of outlines of control. The first one is the multivariate control representation whereas the second one is the unvaried control framework. The unvaried one is in the graphical representation of the quality of the trademark. Multivariate represents the measurements of the outlines and shows the quality of a brand. In the event that a single quality mark is measured or picked as an example to the rest, the control measurement represents the estimate of the quality score, that is used as a gauge with the specimen that has a number. The overall results are checked in comparison to time. This diagrammatic representation shows the focal point line that shows the mean state of the process in the control system. (Hummel, 2012, p.35).  The other flat graphical lines are the lower control limit and the upper control limit. This is later represented in the outline. The cutoffs are stated so that most of the relevant data and information is focused on, and the points that fall in the range is the ones that are taken into account in the control system problem-solving technique. The data and information are plotted in the representation of the time request. The control measure is dependent on the focal line that determines the standard variations. There is an upper line for the high breaking point levels and also a control limit for the lower limits. The dead set of data and information is represented by the graphical lines. The information is differentiated in between the lines and the results elaborated from them. The results can be erratic, stable or unstable. According to Weber, the charts of controls show the data and information of variables that are arranged in groups called sets. The diagram represented at the top illustrates the normal variations and focuses on the data and information that is appropriate whereas the baseline shows the levels of change. In essence, the information is displayed in target rehearsals, where the average variations groupings represent the extent in which they data are deviating. The independent results of control measures stipulate the quality of information. b) Cp and Cpk are 171.389 and 3.799 respectively The calculated standard deviation in a unique area of data is derived from the below formula. Investigation: The problem of Cpk with 2.0 (+/-6 sigma capacity is defined as the problem methodology of 6 sigma and is represented away from the closest variation that is means to be 0.0002 and is in every million part. The results are nonconforming. The defined procedure is taken for the values of the methodology that range from +/- 1.5 sigma within the stipulated system, and it derives 3.39 parts in every million. The results are non-adjusting. Standard Deviation (SD) In essence, the Standard deviation illustrates a range of how the variables are spreading. The unit for SD is σ (the Greek letter sigma). The equation representation is straightforward, and the standard deviation is the foundation square of the variance of the variables. In problem measurements, the SD is an analysis of the variables utilized to show the measure of variety and the scattering of variables in the chosen range. The SD that is almost zero shows the data field is approaching the mean value of the dataset. The expectation of the deviation shows the information focusing on the range of the spread over a specified range of data situations. The SD is an array variable of a dataset that shows an expectation or likelihood in the range of the variance. The statement of standard deviation is not complicated as the average deviation. An essential property of the standard deviation shows that the units are not a fluctuation of the levels but a representation of the groups of data. The estimations are concurrent with a rate in the set, and the SD focuses on the rate as the unit of data. Similarly, the variables are measures of the deviation from the standard. This includes the total difference mean and it gives many properties that are associated with the SD. Furthermore, the standard deviation relays the variability of the population as well as the facts that are in the data conclusions. In the problem, the survey of data and information is thereby controlled by finding the SD of the ranges. The situations of data are repeated severally, and the wiggle room is almost double the SD of the information used as a sample. There is a 95% interim certainty rule that is given to show the scientific analysis of test data. The data values that fall outside the range of the standard deviation mean could be termed as irregular or inaccurate data that does not exist in the estimations. The function of standard deviation is applied to financial systems and money. For instance, to elaborate the rate of investment profits and prediction of a possible outcome in future. The most significant qualities of the standard deviation are to highlight the likeliness of a data case to be happening outside the range. This information is appearing outside the lower boundaries and the upper limits. There are events of slip-ups that occur when managing well especially while the transformation of the data into percentages is done. The exact points of range confinement are not clear and may be inaccurate. For example, the methodology of a payment system may produce correct or wrong receipts. The apparent variables illustrate the perfection of 100% mistake of free handling. The showing of measurable controls such as Cp, Cpk, Pp, and Ppk are deemed to be inapplicable to other cases. (Jackson, 1999, p. 326)  Similarly, non-stop variables are treated as measures of facts and are important when assembling the data ranges. The difference between Cp and Cpk and Pp and Ppk in the system modules is used for evaluating the data population’s standard deviation. In other words, the difference is extracted in the rates of Cp and Pp on rates that are one sided such as Cpk and Cpk that represent the actual average or mean decentralization of the problem’s data sets. c) 170.99 and 2.88 In this case, the impact of the plant is shown in the indicator as well as the variable of reaction that imminently stays constant and does not vary. The other variable has a change that occurs in them. This case can be taken into account whereby the value of X2 is not considered. In this scenario, the system data will be identical to the monolingual mean that the information product is expressed from the first instance. For example; Where Cpkl is, the lower limit and Cpku is the upper limit d) 162((170.9-166/3); (166 -162/3) =162((1.66 ; 1.33) =216;269 In this calculation, the Cpk is differentiated by a value of 3. The most quality in data ranges corresponds to the nearest details. The calculation of Cpk gives an indication that the problem meets the necessary requirements. In this case, Cpk of less than 1 is required, however, +1.333 is needed. The Cpk is identified as well as the Cp and the difference in the midsection of data of Cpk and Cp illustrate the average potential to rise from the typical deviation of the problem. (Hughes, 2011 p. 32).  Question 2: a) The equations highlighted below are used in the calculation. The table below shows the data fields that have been used in the calculations. The number of Years 1 2 3 4 5 Cost in £ millions 1.00 1.35 1.40 1.45 2.55 The calculation is as follows; NPV Machine 1= -500,000 + 1.0/1.15 + 1.35/1.15 + 1.40/1.15 + 2.55/1.15 Meanwhile, -500,000 + 0.87 + 1.17 + 0.0132 + 0.0136 + 0.0151 + 0.0263= 0.37 No of Year 1 2 3 4 5 Cost in £ millions 1.00 1.35 1.40 1.45 2.55 Solution: Item Cash Flow in US $ Present Value at 15% Yr.1 500,000 75000 Yr.2 500,000 75000 Yr.3 500,000 75,000 Yr.4 500,000 75,000 Reversion Yr. 4 500,000 75,000 Total $500,000 In this case, the NPV is the Net cash flow minus the Equity Investment 500,000 - $315,000 = $185,000. Therefore, NPV = $185,000. The ultimate decision is to buy the machine A because the Net Present Value, NPV is more than zero, and the investment will grow by $185,000. The discount rate is represented in the equation below; Dr = (1+r) ^n = (1 +0.15) ^5 = 6.667 b) This case illustrates that if the discounted rate is further lowered to about 8%, the initial NVP shall be reduced to a figure less than zero. This situation will force the Net Present Worth of the problem to be characterized with a range of properties that approach very active streams in a given period. The approach of money streams is mostly viewed as an added advantage at the expense of capital flows. When time is taken into account in cash management data of money flows, it has a major effect on the money equivalent over a given period. This brings about diverse and viable opportunities in money streams. In fact, some money flows may be deemed to be less important over some period of years. In such a situation, there is a time arrangement and planning for the capital flows. The trade values that are currently in the calculation of hard money are necessary for the sense that the future or expected incomes may get less profitable than earlier returns. (Colane, 2001, p.34). This representation reveals that an income that is earned currently is more gainful than a future expectation. Relatively, the diminishing factor shows on the ground where the element of rebate reveals in the return of every sale value and the money stream. When time is taken into account, the estimation of present value starts to diminish. The Net Present Value of a venture is measured by calculating the Present value and the average profits from sales and expenses. This marks a representation of the future estimate of upcoming sales or incomes. The Net Present Value is an essential metric to be taken into account when undertaking a business venture because it shows the overall benefit or return on investment. The NPV also illustrates the overall result of profit or loss. A positive Net Present Value shows that the business is bound to succeed whereas a negative Net Present Value shows that the venture is bound to fail. The NPV metric can also show the deficiency of money streams or the oversupply of resources to an investment. This is shown in quality terms after calculation the fund expenses. In the planning of a venture, the available capital funding within an organization is considered after the calculation and result of a positive Net Present Value. Where capital funding limits the activities or sales of a company, it means that the money streams or the Net Present Value is surpassing the company's capital. In essence, Net Present Value is an essential ingredient in the estimation of reduced income levels and invokes the strategies of utilizing available resources in the running of the business venture. The NPV is mainly used in financial aspects such as backlog and accounts book-keeping. (Hosni, 2004, p.37).  In this case, the money streams are approaching in the future. The money streams include the essential and coupon installment of a security. The price tag shows the primary source of capital funding for sales and investment. Therefore, the Net Present value is the Present Value evaluated as a future price expectation. The NPV is shown as a sum of the values in the layer down investment and the cash inflows that are shown. This is taken into account as the sum of the capital estimates, the present, and the future returns, considering all the sales, returns, and sureties. Q3) The Product A and C bring out best investment returns using the bottleneck method. Model: A B C Price £450 £400 £500 Material Cost £50 £40 £110 Weekly Demand 100 75 40 Time Work Stations in minutes 1 60 0 30 2 0 0 60 3 10 60 0 4 20 30 40 Profit function = TR – TC Product A 45000 – 5000 = 40,000 Product B 30000 – 3000 =27,000 Product C 20000 – 4400 = 15,600 Cost = 35,000 The profits are; 56,500 – 35,000 = 21,500 b) Product A 450 – 350 = 100 * 100 = 10,000- 4,500 = 5,500 Product C 500 -350 = 150 * 75 =11,250 – 4,500 =6,750 Thus, A and C are the best investment opportunities as they present the highest levels of profits Q4) The inventory levels shows the maximum amount of available stocks = 400 + 500 + 200 + 1000 =2,100 This inventory levels are used to show the levels of stock that are in the business. In Economic terms the inventory levels show the amount of capital or goods that are bound to be sold. They can be calculated as future income or investment for the company. The inventory stock can be classified as the output of the company. b) The time that is spent producing output compared against the customer demands. The output of the company should be in line with the timelines of the consumer to avoid delay and eminent losses. The calculation is shown below; D = daily average of the product. W = working time per day, in seconds. T = W / D in seconds = Time taken Total demand Units = 500 Working hours = 23hours and 15minutes c) The statement is used to solve the optimized reorder and order quantities of stock bookkeeping. From the illustration, 4 minutes is the lead time.  d) Processing time 3 + 4 +2.3 = 9.3 minutes 9.3 minutes is the amount of time taken to produce an output. The processing time is the amount of time required to efficiently convert the raw material into a consumer output. The time taken affects the business since the consumer demand because profits depend on the availability of the product upon demand. e) Cell Capacity: The cell capacity is the amount of output that can be produced at a specific time. The total amount of units produced show the overall amount of business output that is expected. 400 + 500+ 200 = 1100 Total time needed to produce the output is 1100 X 9.3 = 10230 Minutes needed to produce 1100 units. References Hummel. H. (2012). The Science of Managerial Accounting. Jason, Ohio, South-Eastern University Press Jackson, T. (1999). The Accounting Principles. Hong Kong, Qinghai University Press. Hughes, R. (2011). Business and Net Present Value Principles. Cambridge, Cambridge University Press. Hosni, T. (2004). The Makespan of a Shop-Floor Using Integer Programming, Oxford, Oxford University Press Colane, E. (2001). The Design of Numerical Control Charts. Harvard, Harvard University Press Read More
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