Reorder point

An automatic signal shall get generated in the store control system and shall get transmitted by e-mails, general notification, or any other suitable means of communication to all concerned engineers, stores managers, and finance department for warning that new supplies must be immediately ordered to sustain present rate of production. Any further delay may cause slowing down the production or cause problems mentioned earlier. 

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Reorder point = [(review time + lead time)... 

Computer systems can be used to calculate the EOQ and reorder point so that a product is reordered automatically when the inventory falls below a mini-... 

Reorder point (ROP) = Demand rate (DR) x Lead time (LT) + Safety stock (SS)... 

It is also interesting to note that the Hepatolite reaction vials are stored in a so-called convenience pack carton. This 30-vial convenience pack has six 12-mm diameter circular openings for checking for reorder point of the cold kit supply without the need to open the outer box (Figure 8.2). In addition, the convenience pack has an 11- x 3-cm round rectangular opening for retrieval of the Hepatolite ... 

Provides for the creation and processing of purchase orders. This module manages the purchasing function, beginning with the automatic creation of a purchase order when the reorder point of a stock item is reached. 

In this context, in addition to the order size, we need a second parameter, the reorder point. Associated with the latter is the notion of inventory position, defined as the on-hand inventory minus any back orders plus any outstanding orders—orders that have been placed but have not yet arrived due to the lead time. Hence, whenever the inventory position falls below the reorder point, an order is placed. Note that since demand now fluctuates randomly and there is a lead time between placing and receiving an order, it is not desirable, in general, to order only when the inventory drops down to zero, as in the case of the EOQ model. 

The above describes exactly how the so-called Q, R) model works, with R being the reorder point and Q the order size. One way to set these parameters is to let Q take the EOQ value and let R be determined by service requirements. For instance, set the value of R sufficiently large so as to ensure that the stockout probability (i.e., the probability that the on-hand inventory is zero upon a demand arrival) is limited to, say, no more thm 5%, or the fill rate (the proportion of demand that is filled from on-hand inventory) is at least 95%. (Note that in general the no-stockout probability is not equal to the fill rate.) It is also possible to set up a cost objective and then optimize it to derive the best Q and R values jointly. 

Note that in this case, DRP effectively follows a base-stock control mechanism, with being the base-stock level (or, reorder point) for period t — L. The estimates for expected on-hand inventory and back orders (for period t) follow (17, 20) and (16, 18), respectively. 

Also note that the time index of the reorder point, s,, is consistent with the time when the order is placed. On the other hand, the safety factor k, is indexed by t since it relates more closely to the on-hand inventory and back orders in period t. 

That is, is the reorder point, since following the DRP logic, an order Q,-i is placed (at t — L) if and only if A, > 0. From the above expression. A, is the required quantity to bring the inventory position at t - L back to (This is consistent with the base-stock mechanism when there are no order-size restrictions.)... 

Stocks of all necessary raw materials and other inputs shall be monitored on a daily basis. Production planning engineers must know every day how long the available stocks will last to mn the plant as per (current rates of production) the product mix. The reorder point for replenishment (the lowest stock level) of these items shall be clearly known with automatic warning available. 

Reorder point for each important material shall be checked and revised if necessary. 

This enabled to reduce the dependence on special high-grade refiactoiy bricks. They were now procured in the usual manner on reaching the reorder point rather than procuring them as an emergency item. 

Reorder point is when new orders must be placed. 

To assess this point, we use the approximation to determine the optimal reorder point S. We first determine the lower bound for the downtime cost (see section 5 note that i >j cja > c/g in our example)... 

On a scheduled basis, the software calculates a reorder point for each item based on the movement data and any overrides contributed by the customer or supplier. These overrides might include information such as promotions, projects, seasonality, new items, etc. 

The VMl software compares the quantity available at the customer with the reorder point for each item at each location (SKU by location). This determines if an order is needed. 

Given the above background, we can look at inventory policies to answer the question of when to order. This inventory policy tells us when the level of inventory or the inventory position of an item should be reviewed to identify whether an item should be ordered. Until the computer took over most inventory functions, the inventory policy usually used was a periodic review policy. With this policy the inventory manager would count the amount of inventory available at prescribed times. Now that computers can continuously review the inventory status of thousands of item, most firms use a continuous review policy. This means that every time an item is used, the computer calculates the balance in stock (i.e., determines the item s inventory position) and evaluates whether this inventory position is at or below a reorder point. 

Fixed reorder quantity inventory model—A form of independent demand item management model in which an order for a fixed quantity, Q, is placed whenever stock on hand plus on order reaches a predetermined reorder level, R. The fixed order quantity Q may be determined by the economic order quantity, by a fixed order quantity (such as a carton or a truckload), or by another model yielding a fixed result. The reorder point R, may be deterministic or stochastic, and in either instance is large enough to cover the maximum expected demand during the replenishment lead time. Fixed reorder quantity models assume the existence of some form of a perpetual inventory record or some form of physical tracking, e.g., a two-bin system, that is able to determine when the reorder point is reached. These reorder systems are sometimes called fixed order quantity systems, lot-size systems, or order point-order quantity systems. 

Either type of inventory model will calculate a reorder point, which is the answer to the question of when to order. When calculating the reorder point, there are four factors to consider. The first is the length of time needed to replenish the order. The second is the average demand during the order replenishment lead time. And, the third is the variance in the demand pattern and the delivery time. Another piece of information is needed. That is, what is the level of customer demand that will be satisfied Do we want to carry enough inventory to meet the needs of 99% of our demand or just 80% of the demand This is a strategic decision that requires knowledge of the business and customer expectation to answer correctly. 

For example, if demand for shovels is 40 a week on average, with a delivery lead time of 1 week and a standard deviation of 5 shovels a week, the reorder point for a 95% service level is calculated below ... 

The service level desired in this system is 90%, which means that safety stock adequate to meet 1.282 standard deviations of demand on the warehouse must be carried at each warehouse. For example, if there is only one warehouse with a standard deviation of demand at the warehouse of283, then 283 1.282 = 363 units. The delivery time to the warehouse is 1 week. So, the required safety stock is added to the demand during the lead time to determine the reorder point (ROP) for each warehouse. For example, when there is one warehouse, the ROP becomes 8,000 + 363 units or 8,363 units. But, this is less than 1 truck load (LTL), which means the warehouse would have to pay higher transportation costs. 

In this chapter, we assume unit-size transactions to simulate the model. Hopefully, future field research can validate our results on larger transaction sizes. A possible approach may use a stuttering Poisson demand process (Ward, 1978) for simulation. Ours is a single-period model, so there is no replenishment necessary. The extension to a system with replenishment is less than straightforward because under a continuous review inventory system with dynamic demand, the determination of optimal reorder points and batch quantities can become quite complicated. 

Ward, J.B. (1978). Determining reorder points when demand is lumpy. Management Science, 24 6), 623-632. 

Often it is the economics implicit in the FOQ equation, or a similar thought process, that governs decisions such as those made by production control and transportation managers up and down the supply chain. The company selling to the final customer orders material in fixed amounts from suppliers according to reorder points and minimum order quantities. Others back up the chain duplicate the behavior, leading to a supply chain bloated with extra inventory and operating expense. 

Min-max A type of order point replenishment where the reorder point is the minimum and the maximum sets the order quantity. 

In the second paper, Thomas considers a related problem but incorporates a general stochastic demand function and backlogging of excess demand. Specifically, Thomas considers a periodic review, finite horizon model with a fixed ordering cost and stochastic, price-dependent demand. The paper postulates a simple policy, referred to by Thomas as (5,5,p), which can be described as follows. The inventory strategy is an (5, S) policy If the inventory level at the beginning of period t is below the reorder point, st, an order is placed to raise the inventory level to the order-up-to level, St. Otherwise, no order is placed. Price depends on the initial inventory level at the beginning of the period. Thomas provides a counterexample which shows that when price is restricted to a discrete set this policy may fail to be optimal. Thomas goes on to say ... 

Finally, we should point out that the matrix in Figure 3.1 presents what would appear to be reasonable approaches to managing demand in these four demand contexts, but not necessarily the only approaches. For example, non-stationary reorder point-order quantity systems are certainly possible, but probably not applied very often in practice due to the significant computational analysis that would be required. Indeed, the effort required to manage the system must clearly be considered in deciding which system to apply. While the "optimal" solution (at least from the standpoint of an objective that minimizes solely the costs that are directly impacted by inventory... 

Continuous-Review Reorder Point-Order Quantity Model... 

A continuous-review, reorder point-order quantity model is often called a (Q, R) model. In this notation, R represents the reorder point, the inventory value below which an order is placed, in this case for Q units. A sample plot of the inventory levels in a (Q, R) system is shown in Figure 3.4. Note that this graph contains both a solid line and a dashed line plotting inventory levels. Tire solid line represents the on-hand inventory level, which is the actual physical inventory present in the system. The dashed line represents the inventory position, which is defined as the sum of on-hand inventory and inventory on-order but not yet received, minus any backlogged demand not met in previous cycles. The inventory position is an important concept in the management of multi-period inventory systems since it is the basis on which ordering decisions are made. For example, let us denote the physical, on-hand inventory by y, and assume that y falls below the reorder point, R. If there is still an order of Q units due, and Q> R-y, the inventory position (equal to y + Q) still exceeds R, and another order will not be placed. Tlrus, the ordering rule for a (Q, R) system is When the inventory position falls below R, place an order for Q units. Note that an order can be placed at any point in time in a (Q, R) system, which is what makes it a continuous-review system. 

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