Operations Management
Operations Management
13th Edition
ISBN: 9780135173626
Author: HEIZER, Jay, RENDER, Barry, Munson, Chuck
Publisher: Pearson,
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Chapter E, Problem 11P

a)

Summary Introduction

To determine: The time required for the fourth and eighth installation for a learning rate of 92%.

Introduction:

Learning curve:

Learning curve is based on the premise that when a person is repeating a task or job again and again, the performance of the person on that job or task will improve. It will depict relationship between cost and output over a definitive period of time.

Doubling effect:

The concept is that each time when an output is doubled, the time it took to develop the doubled unit will be x% of the time it took to produce the base unit. Here ’x’ is the learning curve rate.

b)

Summary Introduction

To determine: The time required for the fourth and eighth installation for a learning rate of 84%.

Introduction:

Learning curve:

Learning curve is based on the premise that when a person is repeating a task or job again and again, the performance of the person on that job or task will improve. It will depict relationship between cost and output over a definitive period of time.

Doubling effect:

The concept is that each time when an output is doubled, the time it took to develop the doubled unit will be x% of the time it took to produce the base unit. Here ’x’ is the learning curve rate.

c)

Summary Introduction

To determine: The time required for the fourth and eighth installation for a learning rate of 77%.

Introduction:

Learning curve:

Learning curve is based on the premise that when a person is repeating a task or job again and again, the performance of the person on that job or task will improve. It will depict relationship between cost and output over a definitive period of time.

Doubling effect:

The concept is that each time when an output is doubled, the time it took to develop the doubled unit will be x% of the time it took to produce the base unit. Here ’x’ is the learning curve rate.

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Please help with the attached Capstone proposal Requirements:
Long term capacity plans and how to properly make decisions regarding long-term planning Long-term capacity plans cover periods longer periods of time. These plans are suitable for large businesses that want to scale their operations with a proven strategy for achieving production targets and meeting customer demands. Long-term capacity plans consider other factors apart from the productive requirements of the company. How important is it, in your mind, to properly make decisions regarding long-term capacity planning?  How does this decision impact the present and future profitability of an organization?  Be specific and give examples.
In addition to the Amazon case study you provided, I'm curious if you've encountered other examples of companies successfully applying Little's Law to enhance their supply chain risk management practices. For instance, have you seen organizations use queuing theory to assess the potential ripple effects of disruptions, stress-test their contingency plans, or identify critical control points that require heightened monitoring and agility? Please provide a reference
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