z UNIVERSITY OF TECHNOLOGY, JAMAICA COLLEGE: Business and Management SCHOOL: Business Administration Assessment Examination, Semester 2, AY 2019/20 Module Name: SUPPLY CHAIN MANAGEMENT Module Code: POM4010 Date: May 11th, 2020 Theory/ Practical: Theory Groups: BBA4 POM & MKT Duration: 72 hours Instructions This Assessment paper has 11 questions and looks at all sectors covered. Do all questions and show all the necessary working. You will have 72 hours after the paper is made available to Download, Execute and Upload the Complete assessment. The Total Marks for this Assessment is 100 Name : Tanecea Campbell ID: 1702855 Group: Tuesday 1pm – 5pm Question1.( 4 marks) A prediction equation for starting salaries (in $1,000’s) and SAT scores was performed using simple linear regression. In the regression printout shown below, what can be said about the level of significance for the overall model? SUMMARY OUTPUT Regression Statistics Multiple R 0.93501812 3 R Square 0.87425889 Adjusted R 0.86028765 Square 5 Standard Error 3.30729594 9 Observations 11 ANOVA df SS MS F Significance F Regression 1 684.4652324 684.4652 62.5756 2.42144E-05 4 Residual Total 9 10 98.44385847 10.93821 782.9090909 Coefficients Standard Error t Stat P-value Lower 95% 8.660080997 -3.36493 0.00832 -48.73108387 29.1406046 4 8 0.06544384 0.008273059 7.910476 2.42E- 0.046728866 1 05 Intercept SAT (a) SAT is not a good predictor for starting salary. (b) Overall the model does not provide a good prediction equation. (c) The significance level for SAT indicates the slope is not equal to zero. (d) The significance level for SAT indicates the slope is equal to zero. (a) The significance level for the intercept indicates the model is not valid. Answer : C Question2.( 3 marks) . Given that the MAD for the following forecast is 2.5, what is the actual value in period 2? Perio Forecas Actua d 1 2 3 4 t 100 110 120 130 l 95 123 130 (a) 120 (b) 98 (c) 108 (d) 115 (e) none of the above Answer : C Question3( 2 marks) . . Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 135. The best forecast of enrollment next semester, based on a three-semester moving average, would be (a) 126. (b) 135. (c) 120. (d) 123. (e) 125. Answer : D Question4 Below is a table showing the demand (in ‘000 of boxes) for Red Stripe Beer. a) Calculate the 3, 4 and 5 Month Simple Moving Average forecasts( 4 marks) Period January 2011 February March April May June July August September October November December Demand ‘000’s of Cases of Beers 3 Month Simple MA 4 Month Simple MA 5 Month Simple MA 8 1 3 2 3 3 4 1 0 1 8 2 3 3 8 1 2 1 3 3 2 4 1 8+13+23= 14.7 3 13+23+34= 23.3 3 23+34+10=22.3 3 34+10+18=20.7 3 10+18+23= 17.0 3 18+23+38=26.3 3 23+38+12=24.3 3 38+12+13=21 3 12+13+32=19 3 8+13+23+34=19.5 4 13+23+34+10=20 4 23+34+10+18=21.3 4 34+10+18+23=21.3 4 10+18+23+38=22.3 4 18+23+38+12=22.8 4 23+38+12+13=21.5 4 38+12+13+32=23.8 4 8+13+23+34+10= 17.6 5 13+23+34+10+18= 19.6 5 23+34+10+18+23= 21.6 5 34+10+18+23+38= 24.6 5 10+18+23+38+12= 20.2 5 18+23+38+12+13= 20.5 5 23+38+12+13+32= 23.6 5 b) Calculate the Exponential Smoothing Forecasts at Alpha = 0.3, 0.45 and 0.65.( 4 marks) Period Demand ‘000’s Cases Beers of of Ex Smoothing Forecast @ a = 0.3 Ex Smoothing Forecast @a= Ex Smoothing Forecast @a= 0.45 0.65 January 2016 February 8 8 8 8 13 8+0.3(13-8)=8 8+0.45(8-8)= 8 8 March 23 8+0.3(5)=9.5 April 34 May 10 June 18 July 23 August 38 September 12 October 8+0.45(13-8)= 10.25 9.5+0.3(23-9.5)= 10.25 13.6 +0.45(23+10.25 )= 16 13.6+0.3(34-13.6)= 16.0+0.45(3419.72 16.0)=24.1 19.72+0.3(1017.8 19.72=16.8 16.8+0.3(18-16.8)= 17.9 17.2 11.3 21.1 13 17.2+0.3(23-17.2)= 20.2 18.9 18.9+0.3(3828.2 18.9)=24.6 20.8 20.9 November 32 18.5 17.3 15.1 December 41 22.6 23.9 26.1 18.9 28.7 16.5 17.5 32.1 19 c) Period Using the MAD error analysis method, which is the preferred Forecasting method to forecast the demand for Red Stripe Beer – 3 Month Simple Moving Average or Exponential Smoothing @ alpha = 0.4 ?( 4 marks) Demand ‘000’s Cases Beers of of 3 Month Simple Moving Average Ex Smoothing Forecast @ a = 0.4 January 2011 February 13 8+0.4(8-8)= 8 March 23 8+0.4(13-8)= 10 April 34 May 10 June 18 July 23 August 38 September 12 October 13 November 32 December 2011 January 2012 41 d) ERROR ActualSMA MSE MAPE Error/ actual 19.3 372.49 0.57 13.3 176.89 1.33 4.3 18.49 0.24 2.3 5.29 0.1 21 441 0.55 14.3 204.49 1.19 11.3 127.69 0.86 11 121 0.34 22 484 0.54 8 8+13+23= 14.7 3 13+23+34= 23.3 3 23+34+10=22.3 3 34+10+18=20.7 3 10+18+23= 17.0 3 18+23+38=26.3 3 23+38+12=24.3 3 38+12+13=21 3 12+13+32=19 3 13+32+41= 28.7 3 10+0.4(23-10)= 15.2 15.2+0.4(3415.2)=22.7 22.7+0.4(1022.7)=17.6 17.6+0.4(1817.6)=17.8 17.8+0.4(2317.8)= 19.9 19.9+0.4(3819.9)= 27.1 27.1+0.4(1227.1)=21.1 21.1+0.4(13=21.1) =17.9 17.9+0.4(3217.9)= 23.5 23.5+0.4(4123.5)=30.5 Use the preferred method to forecast demand for January 2012( 6 marks). e) Repeat Question c using the MSE ( 3 marks) f) Repeat Question c using the MAPE( 3 marks) g) What are your observations?( 6 marks) In conclusion, table one is showing the period of January 2011 to April, the total demand for cases of beer is 14.7. After four months the demand for cases of beer increased to 19.5. Then in five months the demand of Cases of beer declined to 17.6. In table two, the year 2016 January to April the demand of cases of beer there was a drastic increase each month. As examined the first two months of the year 2016 the Ex smoothing forecast of each moth is a total of 8. In March there was an increasing in the Ex smoothing forecast from 8 to 11.3 then from 11.3 to 18.9 in April. There was a declining at the starting of June. The months of July to September there was growth in the Ex smoothing forecast. At the final months of the year December the Ex Smoothing ended at 26.1. In table there, the demand of cases of beer for the first three months is the same of year 2016 in the previous table. After the first three month the total; moving average is 14.7 when compared to the first four months there was an increase to 23.3. According to the table the total number of MSE for the first 3 months is 372.49 then there was a greater decline in the 4th month to 176.89. The total amount of Error Actual- SMA in the 3rd month is 19.3unlike to the 4th month the Error Actual – SMA declined to 13.3. Question ( 9 marks) Based on the data collected from 30 shops island-wide by the producers of a new brand of vegetable loaf as at December 2010, the regression analysis was run which produced the summary output below: SUMMARY OUTPUT Regression Statistics Multiple R 0.952413257 R Square 0.907091012 Adjusted 0.675425058 R Square Standard Error 1.767131177 Observations 30 ANOVA Significanc Df Regression SS 4 Residual 25 Total 29 MS F 135.9587 33.9896 5.78000 8 46.84129 3.12275 3 182.8 0 e F 0.000241546 Standar Coefficients Intercept X Variable 1 -4,650.0001 -20.0005248 d Error 2.002465 19.50003 X Variable 2 30.0001546 1.400000 X Variable 3 6.95000038 0.080001 X Variable 4 0.3000075 0.220010 t Stat P-value Lower 95% 1.07E-07 20.4256009 0.00219 -0.1340466 2 0.67158 -0.2092916 2 0.00975 -0.12816526 2 0.23738 -0.02444292 1 Given: Q = Quantity sold per month P(in cents) = Price of the product = 700 shops are located = 13,500. Monthly advertising expenditure = 8,000 Using the information above, a) b) Develop the linear regression model for the Quantity of Vegetable Loaves demand per month. Y= - 4650.0001- 20.0005248x1 + 30.0001546x2 + 6.95000038x3 + 0.3000075x4 Ydemand – 4650 -20 (price) + 30 ( cp)+ 6.959 (PCI)+ 0.30 (MAE) What is the quality of the model (estimator) developed? R= 0.90 very good model c) What is the relationship and the strength of the relationship between Demand for the Vegetable Loaves and the Independent Variables as a group? r = 0.95 very strong positive relationship d) Compute the t-statistics for each variable and state whether it is statistically significant at the 5% level. - e) Forecast the Demand for Vegetable Loaves using the model developed in part a), based on the given information. Demand = - 4650 – 20 ( 700 ) + 30 ( 750)+ 6.95 (13500) + 0.3(8000) -4650 – 14000+ 22500+93825+ 2400 = 100075 Question 6 ( 9 marks) a) Using the data below, develop a multi-regression model for the demand for soft drink using excel. b) What is the quality of the estimator? Answer: A good estimator is the one which provides an estimate with the following qualities: unbiasedness, Consistency and efficiency c) What is the relationship and the strength of the relationship between the dependent and independent variables? Answer: The independent variable is the one that experimenter controls. The dependent variable is the variable that changes in response to the independent variable. The two variable maybe related by cause and effect. If the independent variable changes, then the dependent variable is affected. Correlation Coefficient ( r ) indicates both the strength and direction of the linear relationship between the independent and dependent variable. d) Use the model to forecast the demand for soft drinks based on the values given. Given the data below, gathered from 20 outlets in Kingston by the producers of a new Soft drink as at December 2015. Q 10 12 13 14 9 8 4 3 15 12 13 14 12 10 10 12 11 12 10 8 Given: P 100 100 90 95 110 125 125 150 80 80 90 100 100 110 125 110 150 100 150 150 I 14 16 8 7 11 5 12 10 18 12 6 5 12 10 14 15 16 12 12 10 E 100 95 110 90 100 100 125 150 100 90 80 75 100 125 130 80 90 95 100 90 B 4 3 2 8 7 9 12 15 8 7 13 10 9 25 39 44 61 63 30 40 Q = Quantity (‘000) sold per month P(in cents) = Price of the product = 70 I (in dollars) = per capita income of the persons in the area in which the outlets are located = 6,500. E (in dollars) = Monthly advertising expenditure = 1,000 B = Number of pizzas sold (per month in the area in which the outlets are located.= 8,000. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.862413257 0.743756625 0.675425058 1.767131177 20 ANOVA df Regression Residual Total Intercept X1 X2 X3 X4 4 15 19 Coefficients 26.38826301 -0.08495248 0.051155946 -0.074501538 0.033945775 SS MS F 135.9587 33.98968 10.88452 46.84129 3.122753 182.8 Significance F 0.000242 Standard Error t Stat P-value Lower 95% 2.797465 9.43292 1.07E-07 20.42561 0.023034 -3.68811 0.002192 -0.13405 0.118299 0.432428 0.671582 -0.20099 0.025177 -2.95908 0.009752 -0.12817 0.027582 1.230713 0.237381 -0.02484 Upper 95% 32.35092 -0.03586 0.303305 -0.02084 0.092736 Lowe 95.0% 20.425 -0.134 -0.200 -0.128 -0.024 Question7( 9 marks) Acne Electrical Company purchases a component used in the manufacture of automobile generators directly from the supplier. Acne’s generator production operation requires 4,500 components per month. Assume that the ordering costs are $50 per order, the unit cost is $85.50 per component, and the annual holding costs are 10% of the value of the inventory. Acne Electrical Company has 240 working days per year and a lead time of 5 days. Devise an inventory policy for Acne Electrical Company to include: Economic Order Quantity Q*= √2DS = √2*4500*12*50 = √5400000 = √6352941.18 = 2520.50 8.50*0.1 0.85 Ch Annual Holding Costs = Q* ch = 2520.50*0.85 = 1071.21 2 2 Annual Ordering Costs = D * S = 5400 * 50 = 1071.22 Total Annual Costs = holding cost+ ordering cost 1071.21 + 1071.22 = 2142.43 Maximum Inventory Level = EOQ Average Inventory Level = EOQ 2 2520.50 = 1260.25 2 Reorder Point = daily demand * lead time = 54000 * 5 = 270000 Number of Orders per year =D = 54000= 21.42 2520.50 Q* Cycle Time (Days) = Q* = 2520.50 = 1260.25 22 Question8.( 9 marks) a) Harley Davidson has its engine assembly plant in Milwaukee and its motorcycle assembly plant in Pennsylvania. Engines are transported between the two plants usingtrucks. Each truck trip costs $1,000. The motorcycle plant assembles and sells 300 motorcycles each day. Each engine costs $500 and Harley incurs a holding cost of 20 percent per year. How many engines should Harley load onto each truck? What is the cycle inventory of engines at Harley?( 3 marks) EOQ= √2DS Ch = √2 * 300*365*1000 0.2 * 500 =√219000000 100 = √2190000 Q*= 1479.86 Cycle Inventory = Q*/2 = 1479.86/2 =739.93 # of orders =D/Q* = 109500/1479.86 = 73.99 ( 74 ) engines Harley should load 0 b) Harley purchases components from three suppliers. Components purchased from Supplier A at price $5 each, and used at the rate of 20000 units per month. Components purchased from supplier B are priced at $4 each and used at the rate of 2,500 units per month. Components purchased from Supplier C are priced at $5 each and used at the rate of 900 units per month. Currently, Harley purchases a separate truck load from each supplier. As part of its JIT drive, Harley has decided to aggregate purchase from the three suppliers. The trucking company charges a fixed cost of $400 for the truck with an additional charge of $100 for each stop. Thus, if Harley asked for a pick up from one supplier, charges $500; from two suppliers $600; and from three suppliers it charges $700. Suggest a replenishment strategy for Harley that minimizes annual cost. Harley incurs a holding cost of 20 percent per year. Compare the cost of your strategy with Harley’s current strategy of ordering separately from each supplier. What is the cycle inventory of each component at Harley?( 6 marks) EOQA = √ 2*20000*12*500 0.2*5 = √240000000 1 =√240000000 Q*A= 15491.93 Cycle Inventory = Q* 2 = 15491.93 2 = 7745.97 EOQB = √2*2500*12*500 0.2*4 =√30000000 0.8 = √37500000 Q8B= 6123.72 Cycle Inventory = Q* 2 = 6123.72 2 = 3061.86 EOQc = √2*900*12*500 : 0.2*5 =√10800000 0.1 =√10800000 Q*c = 3286.34 Cycle Inventory= Q* 2 = 3286.34 2 = 1643.17 Question 9( 9 marks) Georgia Products offer the following discount schedule for its 4- by 8-foot sheets of good quality plyboard. Home Sweet Home Company orders plyboard from Georgia Products. Home Sweet Home has an ordering cost of $300. The carrying cost is 10%. And the annual demand is 6,000 sheets. What do you recommend? Discount Number ORDE Unit Price R (C) 1 0-100 $1,500 2 101 400 401 800 801 and over $1,450 3 4 $1,425 $1,400 Order Quantity (Q) Annual Annual Ordering Material Cost Cost (D/Q * S) (DC) Annual Carrying Cost Total (Q/2*Ch) Cost √2*6000*300/0.1*1 6000*1500=90 6000/ 100/2*150*0.1 9009300 500= 154.92 (100) 00000 100*300=18000 =7500 √2*6000*300/0.1*1 6000*1450=87 6000/157.6*300= 157.6/2*1450* 8722847.32 450=157.6 00000 11421.32 0.1=11426 √2*6000*300/0.1*1 6000 *1425= 6000/401* 300= 401/2*142.5*0. 8583060.03 425=158.9 (401) 8550000 4488.78 1= 28571.25 √2*6000*300/0.1*1 6000*1400= 6000/801*300=22 801/2*140*0.1 8458317.19 400=160.35 (801) 8400000 47.19 = 5607 Question 10( 10 marks) Michael’s limited, a manufacturer of Sliding Door Panels, is in need of an aggregate plan for 5 months of its operations. Its production manager was instructed to use the chase and level strategy methods. Data of forecasted demand and operational parameters for the 5 months are as shown below. Data 1 2 3 4 5 6 7 8 no overtime allowed no subcontracting allowed regular cost of production backorder cost of production hiring cost production/employee firing costs workforce 9 10 overtime cost of production inventory carrying/holding cost hiring and firing is allowed 11 = = = = = = = = $60/unit $9/unit $90/unit 300 units per month $300/unit 30 workers prior to start of production cycle $75/unit $3/unit/month Level Production Strategy start with 30 Quarter Demand Reg Inventory Back # of Produc orders workers tion 1 10500 14800 1480049 10500=4300 2 11500 14800 1480011500= 3300+ 4300= 7600 3 25000 14800 7600+14800=22 400-25000=2600 4 12000 14800 1480012000=2800= 2600=200 5 15000 14800 14800-12000= 2800 – 2600= 200-200= 0 74000 12100 2600 total cost total 7400/5= 14800 # Of workers = Production regular Production/employee Production Cost = 74000 x 60= 444000 Hiring Cost = 19 x 90 = 1710 Inventory cost = 12100 x 3 = 36300 Backorders= 2600x 9= 23400 505410 = 14800/ 300 = 49 # hired 19 # fired Chase Production Strategy Quarter Demand Regular # of prdn. worker s require d 1 10500 10500 49 2 11500 11500 3 25000 2500 4 12000 12000 5 15000 15000 total cost total 74000 10500/300= 35 11500/ 300= 38 2500/300= 8 12000/30= 40 15000/300= 50 start with 30 # of # hired # fired workers availabl e 30 35 8 40 50 19 35-30=5 35-8= 27 40-8=32 5040=10 47 46 74000 Production Cost = 74000 x 60 = 4440000 Firing Cost = 46 x 300 = 13800 Hiring Cost = 47 x 90 = 4230 4458030 Develop aggregate production plans using the tabular format shown above, and complete the table.( 8 marks) i ii Which plan should the manufacturer choose and why? (2 marks) Answer: Chase production strategy would be a better fit than level production strategy because it is cheaper. Question 11( 6 marks) Explain the six distinct distribution network designs that may be used to move products from factory to customer. ( 9 marks) Answer: In manufacture storage with direct shipping, product is shipped directly from the manufacture to the end customer, bypassing the retailer. This option is also referred to as drop shipping with product delivered directly from the manufacture to the customer location. Manufacture storage with direct shipping and in- transfer merge is similar to pure drop shipping, except that pieces of the order coming from different locations are combined so that the customer gets single delivery. Distributor Storage with package carrier delivery is being used when inventory is not held by manufactures at the factories, but is held by distributors/retailers in intermediate warehouses, and package carries are used to transport products from the intermediate location to final customer. Distributor storage with last mile delivery is being used when the distributor/retailer delivers the product to the customer’s home instead of using a package carrier. Manufacture/distributor storage with customer pickups is being used when inventory is stored at the manufacture or distribution warehouse but customer place their orders online or on the phone and then come to designed pickup point to collect their orders Retail storage with customer pickup is being used when inventory is stored locally at retail stores and customers walk into the retail store or place an order online or on the phone and pick it up at retail store. END OF EXAMINATION