Annual demand is 96,000 units. Daily demand = 20working days/month* 12 = 240 days. This implies that the shop would be open for 240 days in a year. Thus our daily demand would be [96,000/240] = 400 units.
But our EOQ for Kony is given by: [v2*40*96,000/598. 5] = 113 units represented by Q. On the other hand, our EOQ for Toshiki would be [v2* 90 * 96,000/598. 5] = 170 units also represented by Q.
This implies that 113 and 170 units are the number of units which when ordered would minimize the total ordering and holding costs should Steve decide to work with Kony and Toshiki respectively (Piasecki, 2001).
Our concern in this case however, is to get the reorder level. To calculate the reorder point; the point at which inventory should be replenished, the following approach would be necessary (Piasecki, 2001). Reorder level = dL; where d is the demand rate per period and L is the lead time. Lead time represents the time it takes from the moment the stock is ordered to the time the inventory is actually delivered (Piasecki, 2001).
The following variable are given; annual demand = 96,000 but the only 20 working days are allowed per month. This would therefore imply that the store would be open for (20 * 12) = 240 days in a year.
Thus, our daily demand would be [96,000/240] = 400 units/day. But our lead time should we opt for Kony would be 10 days thus our R = dL would be (400*10) = 4,000 units. On the other hand, the reorder level should we opt for Toshiki would be (400 * 20 * 3) = 24,000 units. This means that when the inventory reaches 4000 units, Steve would need to reorder since the stock could reach level zero after 10 days (Piasecki, 2001). From the above analyses, it can be seen clearly that the company which would best suit Steve as a supplier is Kony. Read also the Abco company manufactures electrical assemblies
As compared to Toshiki which takes up to 90 days to deliver new supplies, Kony delivers within 10 days. There are several reasons given for this. One is that fact that the company has a shorter delivery time (Terspine, 1993). One implication of a shorter lead-time is that it lowers transportation costs, which eventually reduces the costs of ordering (Piasecki, 2001). It is also important to note that the values of ordering and holding costs need to be examined and reviewed periodically owing to changes in the costs of operation (Hamblin et al. 1973).