Ortiz Industries wants to introduce a new and improved Green Chile Processor, th
ID: 432527 • Letter: O
Question
Ortiz Industries wants to introduce a new and improved Green Chile Processor, the Ortiz GCP 4000, to replace the popular GCP 3000. Due to demand projections, the GCP 3000 will be out of stock on 1 January 2019 and will be immediately replaced by the GCP 4000. As the head production engineer, the CEO tasked you to provide a recommendation on production scheduling, workforce planning, and warehousing in order to seamlessly replace the GCP 3000 with the GCP 4000 in January 2019.
Product Forecast: Ortiz industries sells the GCP 3000 worldwide with most sales in the Northern Hemisphere. The CEO assumes that GCP 3000 sales over the previous 24 months to be the best forecasting tool for GCP 4000 sales in the ?rst 12 months following introduction. Monthly sales for the past 24 months are as follows:
What trends do you see in the previous sales demands? Why?
The GCP 4000 is similar to the GCP 3000, but requires completely new components. Components A, B, and C are assembled in house, but D, E, and F are sourced from vendors with the following shipment times:
Line Balancing Information: The GCP 4000 is produced with the following steps:
The CEO wants you to determine how the jobs should be scheduled in order to minimize the total makespan. Include an appropriate chart indicating the optimal schedule.
Additional Information:
• A backorder costs Ortiz Industries $10 per item.
• Storing an item at the warehouse costs $2 per item per month.
• Based on training and severance, there is a one-time $2000 cost for hiring a worker and a $3000 for ?ring a worker due to production. Based on these costs, what can you assume? You can arbitrarily set the worker count on 1 January based on your production line estimation from the previous month.
• The GCP 3000 and 4000 are high end machines retailing between $8000 and $10000 based on the market. What does that tell you?
Explanation / Answer
Qust:- What trends do you see in the previous sales demands? Why?
THE sales trend in comparison to year 2017 and 2018 is that the sales have dropped by little margin over last year. Or we can conclude that the sales are stagnant in the last two years. On this basis, what we can predict is that the company would hold the sales to the same level by introducing a more featured product in the first year of operation. We must note that there is a price increase of 25% of the new product GCP4000.
The cost of firing a worker is costing the company more $3000 and additionally the time and manpower effort. So, it will be beneficial for the company to retain the trained the workers and keep them on rolls.
The lead time for supply of stocks are as follows :-
F(1); F(2) & E(2) – ONE WEEK.
D(1) – TWO WEEKS.
The planning forecast for production line must be that, we must hold a stock of ONE WEEK for F(1); F(2) & E(2) and D(1) for TWO WEEKS. This would help us to keep the buffer stock with the company. The cost of stocking would be at $2 per item. The cost implication would be as:-
F(1); F(2) & E(2) X 2 = $6. For ONE week would be = 6/4 X 1 = $ 1.5.
D(1) X 2 = $ 2. For two weeks would be = 2/4 X 2 = $ 1.0
TOTAL COST TO HOLD THE PRODUCTS = $ 2.5.
The cost of back-orders would be higher than the cost of holding the product. Secondly, this would help the company in timely delivery of stocks to customers.
PROJECTION FOR 2019 BASED ON RUNNING AVERAGES.
3. GCP4000 is a more advanced product with advanced feature and it is the right time to replace it with GCP3000. This would help the company to increase sales and revenue of the company.
ASSUMPTION :- We assume that the per head output to produce one machine is 25 per person per day, so it would be recommended to appoint 20 manpower. so the euqation would be :-
20 Manpower X 25 machines = 500 machines per day.
500 machines X 25 mandays = 12500 machines.
We would require an additional work force of 5 - 7 person during peak season starting JULY. We could increase stock holding in the month of MAY & JUNE to cater the stock supply during peak season.
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