Materials Management Let us consider an example from the transportation industry where a single workshop looks after a

large fleet of, say, 10,000 vehicles. If the average requirements of fan belt per lead time (such as one month) was 10% then the workshop should place a demand when the stocks fall to 1000 fan belts (10%

to 10,000). Vehicles are now split into ten groups of 1000 each, and each group is supported by the different workshop (the lead time for procurement remaining the same as before) then, on the average, each workshop will experience a consumption of 100 fan belts during the lead time but the variation from workshop to workshop will be of the order of perhaps, 90 to 110. In their attempt to provide all the spares when required, each workshop will then tend to retain a stock of 110. Causing a total stock of 1100 amongst all the workshops.

Now if each of these groups of 1000 vehicles is further split up into 10 groups of 100 vehicles each, then there will be in all 100 groups of 100 vehicles, each experiencing .an average monthly demand of 10 fan belts per group. However, now the actual variation of requirement of fan belts from group to group would perhaps 'be of the order of 5 to 15. If 100 different workshops were to service these 100 groups, then each workshop would tend to keep a stock of 15 fan belts to ensure full availability when required so that the total 'deployed' stock would now rise to 1500 whereas the true requirement was only 1000. This can be carried on further. Intuitively, one can guess that the variation in consumption will increase as the usage rate goes down. Finally, when the usage rate becomes fractional, the variation can be from 0 to at least 1 or even 2. The deployed stocks will then rise as shown in the following table:

The above table clearly brings out the tremendous relative increase in the variation of usage below and above the average as the latter decreases and becomes fractional consequently, the safety stack, i.e.

the quantity to meet the excess requirement also goes up sharply. In fact, it

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also points to the method of reducing spares inventories. Thus, if the spares support is rendered from a central store, the effective usage rate increases and its variation is reduced so that the safety stock required is also small. Splitting vehicles into small pockets effectively reduces the usage rate, variation of. which then becomes greater and greater and safety stock increases very rapidly.

Statistical Analysis

Having noted the fact that there is random variation in the actual requirement of spares from period to period, the next step is to look for any pattern that may exist in this variation. Research conducted in Western countries and in the Armed Forces has proved that a statistical law governed the requirement of maintenance spares for every kind of equipment be it air-craft, submarine, ship, radar, tank, vehicle, machine tool, telephone or radio. To understand how these patterns can be used to determine the safety stock, a simple numerical example can be taken.

Assume that we had a large amount of data available relating to the requirement of a certain spare over a long period, Figure 7.1 above indicates this data. The height of the vertical bars represents the proportion of times that particular spare (on the horizontal axis) was required. Typically, the data pOl1rayed in Figure 7.1 shows that Qty. 8 spares were required 2% of the months Qty. 7 spares were required 6% of the months. Within the total number of months examined, it was observed that there were 1

% of the months during which no spare at all was required (The reference is to be one particular spare).

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Hence, average requirement 439/100 = 4.39 per month.

From these figures, we can calculate the risk, or assurance associated with each stocking policy. It should be noted that in the present case, the average consumption per month during the 100 month period is only 4.39 as calculated above.

If we had stocked exactly 4 spares we would have had a 50% assurance only i.e. there would be a 50-50 chance of having enough spares when required. If we wish to give a better assurance than this, we must increase the stock. This excess stock is the true/safety stock. The relationship between assurance and safety stock in the present case is as under :-

Stock at the time of Safety Stock Assurance % Risk%

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It will be seen that as the safety stock increases there is a progressively lesser and lesser addition to the assurance obtained by it. In other words, although the cost of spares increases, the additional assurance of availability does not increase in the same proportion.

This is a typical manifestation of the economic law of diminishing returns. This is why it is not economic or worthwhile to demand the same assurance of availability from all spares irrespective of their cost.

Safety Stock Calculations

Figure 7.1 indicated only a hypothetical situation regarding the requirement of spares and their frequencies. AS mentioned earlier, a statistical law (called POISSON DISTRIBUTION) influences these frequencies in the case of spares. This is indeed fortunate because when we know the average usage rate of spares, it is unnecessary for us to calculate individually the percentage of times different quantity of spares will be required during the lead time, as in the case of Fig. 7.1. Just as the area of circle is known immediately the radius is known, so also these frequencies are known once the average usage rate of spares is known. This enables the use of a simple formula given below for calculation of safety stock.

Where K is a constant which depends upon the level of assurance to be given and M is the average usage (During lead time). The Reorder Point (ROP) of a spare consists of two parts, viz., the average or expected usage M during lead time and the additional or safety stock, for the required level of assurance, hence

Depending upon the annual consumption value (ABC Analysis), criticality (VED Analysis) and availability (SDE Analysis), assurance level of a particular spare will vary. For 'c' items a thumb rule principle of keeping 3 months average consumption as safety stock can work very well. Following table has been prepared to select 'K' value for a spare part depending upon its classification against above mentioned three types of analyses:

Criticality Availability Annual Consumption

Value

A B

V S

D 1.5

E 1.3 1.9

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Criticality Availability Annual Consumption

Value

A B

E S 1.2 1.6

D 1.0 1.5

E 0.8 1.4

D S 0 0.8

D 0 0.8

E 0 0.8

k for an item classified as 'E-S-A' is 1.2 & for 'V-D-B' is 2.0

The k values proposed above provide assurance between 70 - 99.7% that items will not be out of stock. Assurance is more where k value is more and less where it is less i.e. for k = 2.1 it is 99.7% and for k = 0.8 it is 70%.

This simplification avoids the need for too many tables for various levels of assurance. In any case, it has been found that, in practice, the quantity of spares the tables would indicate at low levels of assurance would almost always be 0.

The above table shows that the cycle stock i.e. the 'average usage' part of the ROP becomes relatively an insignificant part as the usage rate diminishes where the safety stock becomes the predominant part for any given level of assistance. Typically, for a fast moving item having a monthly usage of 16, the

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stock for the same level of assurance comes to .330 which is 3.3 times the average usage during the lead time. This relationship also shows that the slow moving items (which form the bulk of the range of maintenance spares) are mostly held as safety stocks.

Insurance Spares

When the usage of spare parts (during Lead Time) falls below 0.5 even the above method fails.

Typically, for a usage of 0.36 and K = 0.8 (70% Assurance) the ROP = 0.36 + 0.8 x Y36 = 0.36 + .48 = .84.

A doubt now arises whether to round off the fraction 0.84 to nearest integer i.e. 1, since we cannot hold spares in fractional quantities

If we round off 1, the holing will be excessive. If we round off to 0, it will be insufficient. Strictly speaking, this problem would come in rounding off figures such as 1.8, 2.3 etc. also, but the relative error in rounding off a fraction such 1.8 to 2.0 is much less (10%) compared to the error in rounding off 0.8 to 1.0 (25%) ..

In such cases, the problem, therefore, is to decide whether to round off to 1, (i.e. hold the spare at all) or to 0 (i.e. not to hold it). Majority of the so-called maintenance spares have very low usages; such items are often very expensive.

The typical inventory manager, on the advice of the maintenance engineer, tends to play safe and decides to stock at least 1 of each such spare. This inflates the cost of the inventory enormously. In fact, in many organizations, the stock value of such insurance spares may be several times the stock value of the fast movers though their real requirement is very little.

To help the inventory manager select a sensible policy, a simple technique of determining their requirement has been developed. The technique consists of selecting a value C1 for the cost of not having the spare when required and comparing with C2, the present cost of the spare. The ratio C2 X 100% is

C2

compared with the engineers' estimate of the chance of requiring the spare at all during the life time of the machine or group of machines which use that spare.

Thus, for a certain machine (or a vehicle) let the present cost of a certain spare (C2) be Rs. 1000/-.

If the spare is not kept in stock and is needed, it will take time to get it from suppliers. Apart from the cost of downtime of the vehicle, the rush-actions required for getting the part (ie. telephone calls, cost of airfreight etc.) will cost money. Also the part may be now more costly, if it has to be specially made by

the supplier, or anyone else. All these costs can be roughly estimated. Let us say, this cost (C1) is estimated at Rs. 10000/-.

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This value is called the "indifference level", The maintenance engineer is now asked whether, in'his estimate, the chance of requiring that spare in the life-time of the affected vehicle fleet is as high as 10%. If his answer is 'yes', the spare is stocked. If the answer is 'No', the spare is not stocked but bought only when actually required,

It should be noted that the engineer will not be able to answer the questions "what is the probability of requiring a given spare during a given time" but when his thoughts are pegged against a specific figure (the indifference level) he will more often than not, be able to bring to bear his entire experience and engineering knowledge upon this question. It will be rare that he will not be able to answer even this question, because, just as there is never complete knowledge, there is also never complete ignorance.

If the cost of the slow moving spares is very low, the above analysis is not required. The spare parts-manager should stock them at quantity l or 2, if they are critical and none or 1 if they are not

Purchasing

Preliminary Considerations

It is a belief of long standing that purchasing is a matter of experience, contacts and bargaining skills. There exists, however, the other important side which helps economic purchasing and these are certain modern techniques that give a more systematic approach and help in giving a sharper edge to the experience and bargaining skills.

The five essentials of a good purchase are:

(1) Right Quality (2) Right Quantity (3) Right Price (4) Right Time (5) Right Source

/

Right Quality:

The quality is usually specified by the designers or the engineering personnel. The tendency is always to specify quality a step higher than necessary to doubly ensure the performance. The extra quality however adds nothing but costs to the product. The purchasing can always scrutinize the quality specifications by comparison with the quality the competitors are buying and bring it to the notice of the designers. The other aspects are being in touch with the markets. Purchasing can always supply to the designers with information about alternative materials that can meet the specified quality requirements. In many requisitions the quality is specified so vague that future troubles are guaranteed; in such cases purchasing must insist for explicit statement of quality requirements. The purchaser should consider following points for ensuring right quality:

- As per own requirements.

- Clear specifications (ISI).

- Simplification & Standardizations.

- Support to supplier.

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