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Introduction to Operations Management
Case #12: Trans-European Plastics
Group# 30
1) Reasons for TEP’s inability to deliver all its products reliably within the target of one week are:
* There are 24 machines which are working on a standard (non-overtime) week of 105 hours. Thus, there are 2520(24 X 105) machine hours available per week.
* There are 500 + stock keeping units (SKUs), each requiring about 3 hours to set-up (costing Euro 500 per set up), and the minimum run length is 20 hours. Thus, any batch takes at least 23 hours of machine time. Theoretically, the maximum number of SKUs per standard (no-overtime) week is thus 2520/23 = 110.
* On average, each SKU could be made only after every 4.5 weeks (500/110 = 4.54) or even less frequently, because larger batches for popular items will occupy more machine time.
Such a situation clearly illustrates that it would be impossible to make all the company products within the one-week delivery window, and the company must operate a make to stock (MTS) system, where inventory levels are based on forecasts rather than actual orders.
2) Economic batch quantity (EBQ), also called "optimal batch quantity" or economic production quantity, is a measure used to determine the quantity of units that can be produced at minimum average costs in a given batch or production run. The formula is following:
EBQ = √[2DCo/Cc(1-d/p)] (http://cde.annauniv.edu/CourseMat/mba/sem2/dba1651/im.html)
D= Annual demand per year
Co= Setup costs
Cc= Holding costs
P= Production rate per year
So, Annual demand in our case is given that=50,000; Setup cost is given that=500euros; Holding cost is 20%of Variable cost that=3.75x20%=0,75euros; production rate= 90items per hour which is 90x105h=9450per week which is 9450x50weeks=472500per year
So, √[2x50000x500/0,75x(1-50000/472500)]= √(50000000/0,67)=8639
Approximate Economic batch quantity is 8639. So, 50000items of bath divided by 8639 batch quantity is approximately=5,8 production runs or batches needed.
This measure made by EBQ is not appropriate to seasonal products. Because their demand is up to season so that the demand is changeable, unpredictable. On the other hand it is good for measuring not seasonal products which have stable and predictable demand.
3) Initial EBQ (Economic batch quantity) = 8, 639
Change in EBQ=Initial EBQ* (Set-up costs/2) * Holding cost per unit = 8639 *(0.5/2)* 2=8639*
0.5= 4,319.5= 4,320
Now EBQ would become 4,320.
4.
| Description | Last 12 month's sales | Physical Inventory 2 Jan (000s) | Average Inventory |
| Storage bin large | |||
| Stoarge jar+lid | 4.2 | ||
| 10 litre bucket | |||
| Grecian-style pot | |||
| Bathroom mirror | |||
| 1 litre jug | |||
| Pack (10) bag clips | |||
| Baby bath | |||
| Baby potty | |||
| Barbecue table | |||
| Garden bith bath | |||
| Broom head | |||
| Pack (10) clothes pegs | |||
| Barbecue salad fork | |||
| Storage bin small | |||
| Round mixing bowl | |||
| Pasta jar | |||
| Wall hook | |||
| Dustbin+lid | |||
| Soap holder |
| Description | Reorder quantity (000s) | Estimate of stock turn |
| Storage bin large | 2.5 | |
| Stoarge jar+lid | ||
| 10 litre bucket | 7.3 | |
| Grecian-style pot | ||
| Bathroom mirror | 2.5 | |
| 1 litre jug | ||
| Pack (10) bag clips | ||
| Baby bath | ||
| Baby potty | ||
| Barbecue table | 2.5 | |
| Garden bith bath | ||
| Broom head | ||
| Pack (10) clothes pegs | 0.4 | |
| Barbecue salad fork | 1.3 | |
| Storage bin small | 8.3 | |
| Round mixing bowl | ||
| Pasta jar | 2.5 | 0.4 |
| Wall hook | 6.7 | |
| Dustbin+lid | ||
| Soap holder |
As is shown on the table, there are low inventory levels of Baby Bath, Baby potty, Storage
bin (large and small), Dustbin +lid and other. Many times inventory availability levels are less
than demanded i.e. they are out of stock. There are poor plannings of inventory in “Trans-
European Plastics” company which may result in lack of availability of them, especially during
high sale seasons. There would be unused capacity in operations in this company and loss of
future sales and profits, reputation, broken relationships with customers, distributors and other
business partners.
5) Pareto analysis (sometimes referred to as the 80/20 rule and as ABC analysis) is a method of classifying items, events, or activities according to their relative importance. Two possible factors appeared are the usage rate for an item and its unit value.
These two factors can be multiplied to give the annual requirement value (ARV) - the total value of the annual usage.
If the stock items are then listed in descending order of ARV, the most important items will appear at the top of the list. If the cumulative ARV is then plotted against number of items then a graph known as a Pareto curve is obtained.
In this case, typically, the first 20% of items in the list will account for approximately 80% of cumulative ARV. For a company with a stock list of 1,000 different items this means that paying more attention to the top 200 items (with a sophisticated stock control system) will give close control of about 80% of total stock investment.
| Product reference number | Unit manufacturing cost | Last 12 months’ sales (000s) | Annual requirement value (000s) |
| 4 (2*3) | |||
| 016GH | 2.40 | ||
| 033KN | 3.60 | ||
| 041GH | 0.75 | 1,650 | |
| 062GD | 4.50 | ||
| 080BR | 7.50 | 37.5 | |
| 101KN | 0.90 | ||
| 126KN | 0.45 | ||
| 143BB | 3.75 | 187.5 | |
| 169BB | 2.25 | ||
| 188BQ | 16.20 | ||
| 232GD | 3.00 | ||
| 261GH | 1.20 | ||
| 288KN | 1.50 | ||
| 302BQ | 0.30 | 1.5 | |
| 351GH | 1.50 | 37.5 | |
| 382KN | 0.75 | ||
| 421KN | 3.00 | ||
| 444GH | 0.75 | ||
| 472GH | 9.00 | ||
| 506BR | 1.20 |
A’s – 20% of the sample = 80% of the profit = 4 product categories
B’s – 30% of the sample = 15% of the profit = 6 product categories
C’s – 50% of the sample = 5% of the profit = 10 product categories
6) To us it is not right decision to extent their warehouse. To increase the warehouse first of all
they should have Supply which is approximately equal to Demand by customers. In this case
they have high ending inventory level which means they have excess supply. This Surplus will
be even higher if they would increase their warehouse which consequently will increase their
supply on hand. Nevertheless, if they do not increase Supply they would have warehouse for
nothing, which will occur expenses for nothing. Because of it we recommend to this company to
do research with customers in order to have information about stable demand for their both
seasonal and not seasonal products before the extension of their warehouse.
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