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Capacity Management: Design, Effectiveness, and Utilization

## The Importance of Capacity Management

Capacity Management is the “throughput or the number of units a facility can hold, receive, storage, or produce in a given time capacity decisions determine capital requirements and whether demand will be satisfied or whether facilities will be idle”

Explain how capacity affects organisational performance.

Define and explain the following terms.

1. Design capacity

2. Effective capacity

3. Utilisation

4. Efficiency

Complete the following calculations. Make sure you show all your calculations either in-text or in your appendix.

The bakery was operating at 80% efficiency in February 2017.

Calculate and explain the factory’s effective capacity, and its utilisation in that month.

Calculate the efficiency of the bakery in January 2018, and explain why the increase in production over this period may have contributed to the problems the bakery is now experiencing.

Based on the information provided in the case study - What short term and long term capacity strategies could dough bakery use to overcome some of their problems? Justify your answer.

What is the role/purpose of forecasting?

Using the monthly sales data provided in Table 1:

1. Calculate the 3-month simple moving average (SMA) for the months May 2017 to February 2018.

2. Calculate the 3-month weighted moving average (WMA) for the months May 2017 to February 2018, using the weightings of 0.5, 0.3, and 0.2.

3. Include your calculations in the appendix of your document. Templates have been provided at the end of this document that you can use to present your findings for both SMA and WMA (optional).

4. Using the actual sales data provided and your calculations from 2.2 above draw a line graph illustrating the actual sales, 3SMA and 3WMA for the months of May 2017 to February 2018.

5. Use a different colour for each graph line (Sales, SMA and WMA), and remember to clearly label the graph (title, axes, etc).

Explain the purpose of forecasting error.

Calculate the forecasting error for the months of May 2017 to January 2018 using the Mean Absolute Deviation (MAD) for both the SMA and WMA you calculated in 3.2 above.

1.  Present your findings in the table template provided and include your calculations in the appendix (clearly labelled). (4 marks)

Methods of Forecasting Demand:

1. Based on your calculations in 2.2, 2.3 and 2.4, identify AND explain which moving average forecasting methods (SMA or WMA) is the most appropriate to use for forecasting sales/production for Dough Bakery. Justify your answer based on your findings and the literature. (2 marks)

2. Productivity is defined as the ratio of outputs (goods and services) divided by the inputs (resources) and that an improvement in productivity means an improvement in efficiency (Heizer, Render and Munson, 2017).

3. Dough Bakery is worried about increased costs – particularly energy. Last year’s records (2017) can provide a fairly good estimate of the para meters for this year (2018). The owner does not believe things have changed much, but they did invest an additional \$3,000 for modifications to the bakery’s ovens to make them more energy efficient. The modifications were supposed to make the ovens at least 15% more efficient.

4. The owner has asked you to check the energy savings of the new ovens and also to look over other measures of the bakery’s productivity to see if the modifications were beneficial. You have the following data to work with:

 Last year (2017) Now (2018) Production (dozen) 1,500 1,500 Labour (hours) 350 325 Capital investment (\$) 15,000 18,000 Energy 3,000 2,750

1. Using the information in the table 3, calculate the single-factor productivity for 2017 and 2018, with energy as the common dominator.

2. Using the information in the table 3, calculate the multi-factor productivity for 2017 and 2018.

3. Using the calculations from 3.1 and 3.2 above, determine if modifications to the bakery ovens have improved the overall productivity by 15% or more. Justify your answer.