Demand Forecasting in a Supply Chain & Aggregate Planning in a Supply Chain
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SUPPLY CHAIN MANAGEMENT –Chopra Meindl Sixth Edition
Chapter
7
Demand Forecasting in a Supply Chain
Exercise
2
and
4
.
EXERCISE 2
Weekly demand figures at HOT Pizza are as follows:
|
WEEK
|
DEMAND
($)
|
|
1
|
10
8
|
|
2
|
11
6
|
|
3
|
118
|
|
4
|
12
4
|
|
5
|
|
9
6
|
|
6
|
119
|
|
7
|
96
|
8
|
|
102
|
|
9
|
112
|
|
10
|
102
|
11
|
92
|
|
12
|
91
|
Estimate demand for the next 4 weeks using a 4-week moving average as well as simple exponential smoothing with a = 0.1 (long term soothing constant) . Evaluate the MAD, MAPE, MSE, bias and TS in each case. Which of the two methods do you prefer? Why?
EXERCISE 4
Consider monthly demand for the ABC Corporation as shown in Table 7-3. Forecast the monthly demand for Year 6 using moving average, simple exponential smoothing. Holt’s model, and Winter’s model. In each case, evaluate the bias, TS, MAD, MAPE, and MSE. Which forecasting method do you prefer? Why?
TABLE 7-3 Monthly Demand for ABC Corporation
|
SALES
|
YEAR 1
|
YEAR2
|
YEAR3
|
YEAR4
|
YEAR5
|
|
|
|
January
|
|
|
|
|
|
2,000
|
|
|
|
|
|
|
|
3,000
|
2,000
|
|
|
|
|
|
5,000
|
5,000
|
|
|
February
|
3,000
|
|
|
|
4,000
|
5,000
4,000
2,000
|
|
|
March
|
3,000
3,000
5,000
4,000
3,000
|
|
|
April
|
3,000
5,000
3,000
2,000
2,000
|
|
|
May
|
4,000
5,000
4,000
5,000
|
|
|
7,000
|
|
June
|
|
|
|
6,000
|
|
|
|
|
|
8,000
|
6,000
7,000
6,000
|
|
|
July
|
7,000
3,000
7,000
|
|
|
|
10,000
|
8,000
|
|
|
August
|
6,000
8,000
10,000
|
14,000
|
10,000
|
|
|
September
|
10,000
|
|
|
12,000
|
|
15,000
|
|
|
16,000
|
|
|
20,000
|
|
|
|
October
|
12,000
12,000
15,000
16,000
20,000
|
|
|
November
|
14,000
16,000
18,000
|
20,000
22,000
|
|
|
|
December
|
8,000
10,000
8,000
12,000
8,000
|
TOTAL
|
78,000
|
89,000
|
98,000
|
115,000
|
113,000
|
CHAPTER 8 Aggregate Planning in a Supply Chain
EXERCISE 1
and 4
EXERCISE 1
Skycell, a major European cell phone manufacturer, is making production plans for the coming year. Skycell has worked with its customers (the service providers) to come up with forecasts of monthly requirements (in thousands of phones) as shown in Table 8-10.
Manufacturing is primarily an assembly operation, and capacity is governed by the number of people on the production line. The plant operates for 20 days a month, eight hours each day. One person can assemble a phone every 10 minutes. Workers are paid 20 euros per hour and a 50 percent premium for overtime. The plant currently employs 1,250 workers. Component costs for each cell phone total 20 euros. Given the rapid decline in component and finished-product prices, carrying inventory from one month to the next incurs a cost of 3 euros per phone per month. Skycell currently has a no-layoff policy in place. Overtime is limited to a maximum of 20 hours per month per employee. Assume that Skycell has a starting inventory of 50,000 units and wants to end the year with the same level of inventory.
1. Assuming no backlogs, no subcontracting, and no new hires, what is the optimum production schedule? What is the annual cost of this schedule?
2. Is there any value for management to negotiate an increase of allowed overtime per employee per month from 20 hours to 40?
3. Reconsider parts (a) and (b) if Skycell starts with only
1,200
employees. Reconsider parts (a) and (b) if Skycell starts with 1,300 employees. What happens to the value of additional overtime as the workforce size decreases?
4. Consider part (a) for the case in which Skycell aims for a level production schedule such that the quantity produced each month does not exceed the average demand over the next 12 months (1,241,667) by 50,000 units. Thus, monthly production, including overtime, should be no more than 1,291,667. What would be the cost of this level production schedule? What is the value of overtime flexibility?
Table 8-10 Monthly Demand for Cell Phones, in Thousands
|
|
MONTH
|
DEMAND
|
January
|
|
|
|
1,000
|
February
|
|
1,100
|
March
1,000
April
|
|
1,200
|
May
|
|
|
1,500
|
|
|
June
|
|
|
|
1,600
|
July
1,600
August
|
|
|
900
|
September
1,100
October
|
|
|
|
800
|
November
|
|
|
|
1,400
|
December
|
|
1,
700
|
EXERCISE 4
FlexMan, an electronics contract manufacturer, uses its Topeka, Kansas, facility to produce two product categories: routers and switches. Consultation with customers has indicated a demand forecast for each category over the next 12 months (in thousands of units) to be as shown in Table 8-11.
Manufacturing is primarily an assembly operation, and capacity is governed by the number of people on the production line. The plant operates 20 days a month, 8 hours each day. Production of a router takes 20 minutes, and production of a switch requires 10 minutes of worker time. Each worker is paid $10 per hour, with a 50 percent premium for any overtime. The plant currently has 6,300 employees. Overtime is limited to 20 hours per employee per month. The plant currently maintains 100,000 routers and 50,000 switches in inventory. The cost of holding a router in inventory is $2 per month, and the cost of holding a switch in inventory is $1 per month. The holding cost arises because products are paid for by the customer at existing market rates when purchased. Thus, if FlexMan produces early and holds in inventory, the company recovers less given the rapidly dropping component prices.
1. Assuming no backlogs, no subcontracting, no layoffs, and no new hires, what is the optimum production schedule for FlexMan? What is the annual cost of this schedule? What inventories does the optimal production schedule build? Does this seem reasonable?
2. Is there any value for management to negotiate an increase of allowed overtime per employee per month from 20 hours to 40? What variables are affected by this change?
3. Reconsider parts (a) and (b) if FlexMan starts with only 5,900 employees. Reconsider parts (a) and (b) if FlexMan starts with 6,700 employees. What happens to the value of additional overtime as the workforce size decreases?
TABLE 8-11 Demand Forecast for FlexMan
MONTH
|
ROUTER DEMAND
|
SWITCH DEMAND
|
January
|
|
1,800
|
1,600
February
1,600
1,400
March
|
2,600
|
1,500
April
|
|
2,500
|
2,000
May
800
1,500
June
1,800
900
July
1,200
700
|
August
1,400
800
September
2,500
1,400
October
|
2,800
|
1,700
November
1,000
800
December
1,000
900
