Chapter 5: Process Selection, Design, and Analysis
1. Process Selection: The strategic decision-making process of choosing the most
appropriate production process for a specific product or service.
2. Process Design: The creation of a production process to meet customer needs
and organizational goals.
3. Process Analysis: The evaluation of a production process to identify potential
improvements in efficiency, quality, or cost.
Chapter 6: Facility and Work Design
4. Facility Layout: The arrangement of equipment, machinery, and personnel within
a facility to optimize production efficiency.
5. Work Design: The creation of job tasks and responsibilities that maximize
employee productivity and satisfaction.
6. Job Enlargement: The process of expanding a worker's job responsibilities to
increase their sense of fulfillment and motivation.
Chapter 7: Forecasting and Demand Planning
7. Forecasting: The estimation of future demand for a product or service based on
historical data and other factors.
8. Demand Planning: The process of coordinating production and inventory levels
with anticipated customer demand.
Chapter 8: Capacity Management
9. Capacity Planning: The process of determining the appropriate level of production
capacity to meet customer demand.
10. Aggregate Planning: The development of a production plan that balances capacity
and demand over a specified time period.
11. Bottleneck: A process or operation within a production system that limits the overall
output.
Chapter 9: Managing Inventories in Supply Chains
12. Inventory Management: The process of optimizing inventory levels to meet
customer demand while minimizing costs.
13. Safety Stock: Additional inventory held as a buffer to protect against unexpected
demand or supply chain disruptions.
Chapter 10: Supply Chain Management and Logistics
14. Supply Chain: The network of suppliers, manufacturers, distributors, retailers, and
customers involved in the production and delivery of a product or service.
15. Logistics: The management of the flow of goods, services, and information within
a supply chain.
Chapter 11: Resource Management
16. Resource Allocation: The process of assigning personnel, equipment, and other
resources to specific tasks or projects.
17. Resource Utilization: The measurement of how efficiently resources are used in a
production system.
Chapter 12: Operations Scheduling and Sequencing
18. Scheduling: The assignment of start and end times for production activities to meet
customer demand and production constraints.
19. Sequencing: The determination of the order in which production activities should
be performed to maximize efficiency and quality.
Chapter 13: Lean Operating Systems
20. Lean Manufacturing: A production philosophy that emphasizes the elimination of
waste and continuous improvement.
21. Value Stream Mapping: A graphical tool used to analyze and improve production
processes by identifying areas of waste and inefficiency.
Chapter 14: Project Management
22. Project Planning: The process of defining project goals, objectives, and
deliverables and determining the resources required to achieve them.
23. Project Execution: The process of carrying out the activities defined in the project
plan.
Chapter 15: Introduction to Quality
24. Quality: The degree to which a product or service meets customer expectations
and requirements.
25. Quality Control: The process of monitoring and controlling the production process
to ensure that quality standards are met.
Chapter 16: Customer Focus
26. Customer Satisfaction: The degree to which a customer is satisfied with a product
or service.
27. Customer Relationship Management: The management of interactions with
customers to build and maintain strong relationships.
Chapter 17: Workforce Focus
28. Employee Empowerment: The process of giving employees the authority and
responsibility to make decisions and take action.
29. Training and Development: The process of providing employees with the
knowledge and skills required to perform their job duties effectively.
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Program evaluation and review technique (PERT)
Problem:
A construction company is planning to build a new office building. The project has 3 major
activities that need to be completed in a sequential order: excavation, building
construction, and interior finishing. The company has estimated the duration of each
activity as follows:
Excavation: 4 weeks Building Construction: 10 weeks Interior Finishing: 6 weeks
The company wants to know the earliest and latest completion time of the project and the
critical path.
Explanation:
The Program evaluation and review technique (PERT) is a project management tool that
is used to schedule, organize, and coordinate tasks within a project. It helps to estimate
the time required to complete a project and identify the critical path, which is the sequence
of activities that must be completed on time to ensure the project is completed on time.
Computation:
To use PERT, we need to determine the earliest start time (EST), earliest finish time
(EFT), latest start time (LST), and latest finish time (LFT) for each activity.
For the excavation activity:
EST = 0 (since it is the first activity) EFT = 4 (EST + duration)
For the building construction activity:
EST = 4 (the earliest possible start time for this activity is after excavation is complete)
EFT = 14 (EST + duration)
For the interior finishing activity:
EST = 14 (the earliest possible start time for this activity is after building construction is
complete) EFT = 20 (EST + duration)
Next, we need to calculate the slack for each activity, which is the amount of time an
activity can be delayed without delaying the project completion time.
For the excavation activity:
Slack = LST - EST = 0 - 0 = 0
For the building construction activity:
Slack = LST - EST = 14 - 4 = 10
For the interior finishing activity:
Slack = LST - EST = 20 - 14 = 6
Finally, we can determine the earliest and latest completion time of the project and the
critical path. The earliest completion time is the sum of the EFTs for all activities on the
critical path, which is the path with zero slack.
The critical path for this project is excavation -> building construction -> interior finishing.
The earliest completion time is:
EFT of excavation + EFT of building construction + EFT of interior finishing = 4 + 14 + 20
= 38 weeks
The latest completion time is the sum of the LFTs for all activities on the critical path.
The latest completion time is:
LFT of excavation + LFT of building construction + LFT of interior finishing = 4 + 24 + 26
= 54 weeks
In summary, the earliest completion time for the project is 38 weeks, and the latest
completion time is 54 weeks. The critical path is excavation -> building construction ->
interior finishing.
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Program evaluation and review technique PERT
Problem:
A company is developing a new product and needs to estimate the time required to
complete the project. The following tasks are identified:
Task Optimistic Time (O)
Most Likely Time (M)
Pessimistic Time (P)
A
4
6
2
Task Optimistic Time (O)
Most Likely Time (M)
Pessimistic Time (P)
B
4
8
12
C
1
3
5
D
3
6
9
a) Determine the expected completion time for each task.
b) Determine the expected completion time for the entire project.
c) Determine the variance for the entire project.
Explanation: This problem uses the Program Evaluation and Review Technique (PERT),
which is a tool used to estimate the time required to complete a project. PERT assumes
that the completion time for each task follows a beta distribution and uses the optimistic,
most likely, and pessimistic times to estimate the expected completion time and variance
for each task and the entire project.
Computation: a) The expected completion time for each task can be calculated using the
formula: E = (O + 4M + P) / 6
Optimistic Time Most Likely Time Pessimistic Time Expected
Task (O)
(M)
(P)
Time (E)
Completion
A
2
4
6
(2 + 4(4) + 6) / 6 = 4
B
4
8
12
(4 + 4(8) + 12) / 6 = 8
C
1
3
5
(1 + 4(3) + 5) / 6 = 3
D
3
6
9
(3 + 4(6) + 9) / 6 = 6
b) The expected completion time for the entire project can be calculated by adding the
expected completion times for all tasks: Expected completion time = 4 + 8 + 3 + 6 = 21
c) The variance for the entire project can be calculated using the formula: Variance = Σ((P
- O) / 6)^2
Optimistic
Task Time (O)
A
2
Most Likely Pessimistic
Time (M)
Time (P)
4
6
Expected
Completion
(E)
4
Time
Variance
((6 - 2) / 6)^2 =
0.11
Optimistic
Task Time (O)
Most Likely Pessimistic
Time (M)
Time (P)
Expected
Completion
(E)
Time
Variance
B
4
8
12
8
((12 - 4) / 6)^2
= 0.67
C
1
3
5
3
((5 - 1) / 6)^2 =
0.11
3
6
9
6
((9 - 3) / 6)^2 =
0.44
Total -
-
-
-
1.33
D
The variance for the entire project is 1.33.
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One example of a CPM problem in Capacity Management could involve a company
that manufactures furniture. The company has a demand for 500 units of furniture per
month, and they have a production line that can manufacture 100 units per day.
To ensure that the company meets the demand, they need to determine the number of
days required for production.
To do this, they can use the following steps:
1. Determine the number of units that can be produced per month: 100 units/day x
22 days/month (assuming there are no weekends) = 2,200 units/month
2. Calculate the number of days required to produce 500 units: 500 units / 2,200 units
per month = 0.227 months
3. Convert months to days: 0.227 months x 30 days/month = 6.81 days
Therefore, the company needs to produce furniture for 7 days (rounded up) to meet the
demand of 500 units per month.
This CPM problem helps the company plan and optimize their production capacity to meet
the demand effectively, ensuring customer satisfaction and business success.
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Forecasting and Demand Planning
Problem:
A retail store is planning to stock up on winter jackets for the upcoming winter season.
The store manager needs to forecast the demand for the winter jackets and plan the
inventory accordingly. The historical sales data for the winter jackets for the past 4 years
is given in the table below:
Year
Sales (in units)
2016
500
2017
600
2018
700
2019
800
Using the above data, forecast the demand for winter jackets for the upcoming season
using the following methods:
1. Simple Moving Average method with a 2-year period
2. Exponential Smoothing method with a smoothing constant of 0.3
Also, calculate the Mean Absolute Deviation (MAD) for each method to determine the
accuracy of the forecasts.
Solution:
1. Simple Moving Average method with a 2-year period:
To forecast the demand using Simple Moving Average method, we need to take the
average of the sales data for the last 2 years.

For year 2020:
Forecast = (Sales in 2018 + Sales in 2019) / 2 = (700 + 800) / 2 = 750 units

For year 2021:
Forecast = (Sales in 2019 + Sales in 2020) / 2 = (800 + 750) / 2 = 775 units
MAD = (|Actual - Forecast|) / n = (|500 - 750| + |600 - 775| + |700 - 800| + |800 - 775|) / 4
= 125 units / 4 = 31.25 units
2. Exponential Smoothing method with a smoothing constant of 0.3:
To forecast the demand using Exponential Smoothing method, we need to use the
following formula:
Forecast = α x Actual + (1 - α) x Forecast of previous period
where α is the smoothing constant (0 ≤ α ≤ 1)

For year 2020:
Forecast = 0.3 x 800 + (1 - 0.3) x 700 = 760 units

For year 2021:
Forecast = 0.3 x 500 + (1 - 0.3) x 760 = 667 units
MAD = (|Actual - Forecast|) / n = (|500 - 760| + |600 - 667| + |700 - 800| + |800 - 667|) / 4
= 141 units / 4 = 35.25 units
Conclusion:
Based on the MAD values, the Simple Moving Average method with a 2-year period is
more accurate in forecasting the demand for winter jackets than the Exponential
Smoothing method with a smoothing constant of 0.3. However, it should be noted that
these methods are only as good as the historical data used for forecasting and may not
accurately predict future demand. Therefore, it is important to continuously monitor and
adjust the forecasts based on actual demand.
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Sequencing problem in Operations Management:
A company produces two products, A and B. The company has a single machine that can
be used to produce both products. The processing times for each product are as follows:

Product A: 4 hours

Product B: 6 hours
The company can produce up to 8 units of each product per day. The company wants to
maximize the total production of both products each day.
What is the optimal sequence of production?
Solution:
To find the optimal sequence of production, we need to use a sequencing algorithm. One
commonly used algorithm is the Johnson's algorithm.
1. First, we need to determine the processing times of each product on the machine.
We can do this by finding the minimum processing time for each product. In this
case, the minimum processing time for Product A is 4 hours, and the minimum
processing time for Product B is 6 hours.
2. Next, we need to compare the minimum processing times of each product. If the
minimum processing time for Product A is less than the minimum processing time
for Product B, then we should produce Product A first. If the minimum processing
time for Product B is less than the minimum processing time for Product A, then
we should produce Product B first.
In this case, the minimum processing time for Product A is less than the minimum
processing time for Product B. Therefore, we should produce Product A first.
3. After producing Product A, we need to remove it from consideration and repeat the
process with the remaining products. In this case, we only have Product B left. The
minimum processing time for Product B is 6 hours, so we should produce 8 units
of Product B.
Therefore, the optimal sequence of production is to produce 8 units of Product A first,
followed by 8 units of Product B.
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