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Integral Logistics Management: Operations and Supply Chain Management Within and Across Companies,

Paul Schönsleben, Steven R. Schmid, Bo O. Jacobson

Chapter 12

Time Management and Scheduling - all with Video Answers

Educators


Chapter Questions

01:54

Problem 1

Queues as an Effect of Random Load Fluctuations (1)

Answer the following questions using the relevant formulas in queuing theory (refer to Figure 12.2.2.4):
a. How many parallel workstations are needed to have an expected wait time of less than 10 hours, if capacity utilization is 0.95 , the mean of the operation duration is 2 hours, and the coefficient of variation of the operation duration is 1 ?
b. The capacity is 10 hours. How much does the expected wait time increase if load rises from 4 to 8 hours?
c. How is the expected wait time affected when the coefficient of variation increases from 1 to 2 ?

Gaurav Kalra
Gaurav Kalra
Numerade Educator
01:54

Problem 2

Queues as an Effect of Random Load Fluctuations (2)

Figure 12.2.2.3 shows the average wait time as a function of capacity utilization in a job shop environment with random arrivals, execution of operations in order of arrival (or according to random selection from the queue), as well as operation times (OT) subject to a determinate distribution with mean $\mathrm{M}(\mathrm{OT})$ and coefficient of variation $\mathrm{CV}(\mathrm{OT})$. We reproduced the effect shown in Figure 12.2.2.3 by means of a Flash simulation, which you can view at URL:
www.intlogman.lim.ethz.ch/queuing_theory.html
Start the simulation by clicking on the given arrival rate and execution (service) rate on the gray button to the far left at the bottom of the figure and watch the number of elements in the system. Stop the simulation by clicking on the middle of the three buttons (or empty the system by clicking the button to the far right). Now change the input rate to bring it closer and closer to the execution rate and observe the rising number of elements in the queue. You will see the exploding number of elements in the system as soon as, for an execution rate of 60 per unit of time, the arrival rate is 58 and higher.

Gaurav Kalra
Gaurav Kalra
Numerade Educator

Problem 3

Network Planning

Figure 12.7.3.1 shows a scheduled network with incomplete data for 6 operations and a start operation (administration time).
(GRAPH CANT COPY)
Fig. 12.7.3.1 Scheduled network (for you to complete).
a. For each process, please fill in the earliest start date (ESD) and the latest start date (LSD) in the scheduled network. What is the critical path, that is, the path with the longest duration? What is its lead-time margin, that is the slack time?
b. The operation time for operation 6 has not yet been determined. What is the longest possible time for operation $6($ lead-time $\operatorname{margin}=$ zero $)$ ?

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Problem 4

Backward Scheduling and Forward Scheduling

Here, you will practice some backward and forward scheduling. Figure 12.7.4.1 presents a simple network, including a legend showing the leadtime elements used.

Solve the forward and backward scheduling problems (calculation of start and completion dates for the order and each operation, as well as the critical path and lead-time margin) listed in Figure 12.7.4.2:
(GRAPH CANT COPY)
(COLUMNS CANT COPY)
a. Common forward scheduling.
b. Common backward scheduling.
c. Forward scheduling with different lead-time-stretching factor, that is, a different order urgency, to accelerate or slow down the order.
d. Forward scheduling with lead-time-stretching factor $=0$, which results in the lead time as the sum of operation times plus the technical interoperation times.

Some common problems in the calculation process lead to the following potential errors:
- Calculating incorrect start date and due dates, not respecting interoperation times multiplied by stretching factor
- Multiplying technical waiting time by stretching factor
- Not calculating correctly the longest path in a network
- Not understanding the principle of forward or backward scheduling

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Problem 5

The Lead-Time-Stretching Factor and Probable Scheduling

The following exercise will allow you to practice the use of the lead-timestretching factor as well as probable scheduling. It uses the same network example as in Figure 12.7.4.1.

Solve the two probable scheduling problems shown in Figure 12.7.5.1. Hint: First, calculate a new lead-time-stretching factor using the formula in the lower part of Figure 12.3.6.3, based on an appropriate solution of one of the four problems in the previous exercise (12.7.4) as an initial solution.
(COLUMNS CANT COPY)
Fig. 12.7.5.1 Two probable scheduling problems.

Some common problems in the calculation process that can lead to errors are
- Not understanding the goal and principles of probable scheduling
- Not understanding the formula for recalculation of the lead-timestretching factor in probable scheduling
- Not choosing the most appropriate last calculation as initial solution for recalculation of the lead-time-stretching factor

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