Safety inventory level

Since the size of the orders that has to be request is chosen between three values, and, in addition, there are four time instants in which an order has to be placed, there are 81 possible combinations for simulating in each scenario. For each one of these configurations, taking into account each scenario, the expected values of the profit (Eiprofit)) has been calculated and the one with the largest expected profit is picked. In the deterministic case the values for the demand have been chosen in 7 units of product A each five simulations steps and 3 units of B with the same frequency. Moreover, the value for the safety inventory level has been set in 50 units for all the entities except in SIP and PI where the selected value has been 100 units. In the first case below described, a variance of 3 and 2 has been added to both deterministic values of the demand size. In the second case, a variance of 30 has been added to the deterministic value of the safety inventory level. 

In this chapter, we discuss how safety inventory can help a supply chain improve product availability in the presence of supply and demand variability. We discuss various measures of product availability and how managers can set safety inventory levels to provide the desired product availability. We also explore what managers can do to reduce the amount of safety inventory required while maintaining or even improving product availability. 

In our discussion so far, we have assumed that each stage of the supply chain has a well-defined demand and supply distribution that it uses to set its safety inventory levels. In practice, this is not true for multiechelon supply chains. Consider a simple multiechelon supply chain with a supplier feeding a retailer that sells to the final customer. The retailer needs to know demand as well as supply uncertainty to set safety inventory levels. Supply uncertainty, however, is influenced by the level of safety inventory the supplier chooses to carry. If a retailer order arrives when the supplier has enough inventory, the supply lead time is short. In contrast, if the retailer order arrives when the supplier is out of stock, the replenishment lead time for the retailer increases. Thus, if the supplier increases its level of safety inventory, the retailer can reduce the safety inventory it holds. This implies that the level of safety inventory at aU stages in a multiechelon supply chain should be related. 

All inventory between a stage and the final customer is called the echelon inventory. Echelon inventory at a retailer is just the inventory at the retailer or in the pipeline coming to the retailer. Echelon inventory at a distributor, however, includes inventory at the distributor and all retailers served by the distributor. In a multiechelon setting, ROPs and OULs at any stage should be based on echelon inventory and not local inventory. Thus, a distributor should decide its safety inventory levels based on the level of safety inventory carried by all retailers supplied by it. The more safety inventory retailers carry, the less safety inventory the distributor needs to carry. As retailers decrease the level of safety inventory they carry, the distributor must increase its safety inventory to ensure regular replenishment at the retailers. 

Process technology information will be a part of the process safety information package and should include employer-established criteria for maximum inventory levels for process chemicals limits beyond which would be considered upset conditions and a qualitative estimate of the consequences or results of deviation that could occur if operating beyond the established process limits. Employers are encouraged to use diagrams that will help users understand the process. 

This section relates random services and random shortages to conditional demands as defined in Section 6.2.5. Conditional random service is the crucial quantity that has to be calculated when a safety stock level has to be determined. Conditional random service results from three quantities a demand density 5, an already ordered quantity r and an available inventory s. From these parameters we obtain two new densities, the conditional service density 5+,r,s and the conditional shortage density... 

Another important feature of the case study scenario and the resulting cost model is inventory control. High seasonality effects and long campaign durations necessitate considerable build-up of stocks. To avoid an unbalanced build-up of stock, soft constraints for safety stock and maximum stock levels are used. To achieve an even better inventory leveling across products and locations, piece-wise linear cost functions for falling below safety stock as well as for exceeding maximum stock levels are employed. 

The only way to avoid this is by strict analysis of the supply chain from the customer order to final product delivery. Definition of the optimized (theoretical) process and sequential work towards a high service level approach allow the identification of gaps, and of opportunities which might not always be the cheapest (ship versus train versus plane) but could be the most effective way to reduce capital costs and shorten planning scope - an important aspect, especially in volatile customer markets with long production processes on the (chemical) supplier side. As in the case of CIP, this needs clear parameters, KPIs, commitment from all players, and regular tracking. The most important parameters are the lead time for all products, optimal lot sizes, replenishment points, and safety inventories. 

Inventory Collect information on inventory turns and levels, fill rates, safety stock levels, and ABC analysis. By having this information, the savings of consohdating facilities can be determined. Also collect which, and how much, stock is slow moving or seasonal to help determine if it should be centralized in one location or whether public warehouse space should be used. Get future inventory goals. 

Two important databases relate to products and orders, respectively. The item master defines the products that are handled by the warehouse. Included in tMs database are product identification, physical characteristics, vendor sources, replenishment and safety stock levels, service level, and so forth (see Table 6). The order master contains the records of customer orders (see Table 7). In addition, closely related tables include a vendor master, a customer master, and an inventory master. The last table should reflect not only quantities and locations of products on hand, but tilso backordered quantities and quantities reserved for customers or other reasons. 

There are several planning functions precede the actual retrieval of products for customer orders. The first of these is to check current inventory levels in the forward pick areas and generate replenishment reports. Most warehouse operators prefer to replenish at the beginning of the shift, for reasons of safety and efficiency. Some replenishments may occur during the pick process, especially if the information about orders is incomplete, or if operators select full cartons from the item pick area when they should be selected from the carton pick area. The WMS should support workload balancing in the pick operation reflect different picker capabilities according to data in the personnel master (Table 10), and reflect different number of operators according to pick wave and shift. The abdity to balance workload over more than one day is desirable, but it is usually not available in the typical WMS. 

If each individual retailer carried its own inventory, it would maintain an inventory level of Lfi + (Zct-JL). Thus the total system inventory would be n LfX, + (Zct-JL)). The pooled inventory includes a safety stock of Z(Jy/nL while the individual locations would generate a safety stock of Z(7n-jL. Thus, the role of the warehouse in a distribution supply chain is to decrease the buffer capacity by a factor of Jn. This - fn effect is a rule of thumb to estimate the benefit of consolidating inventory in a supply chain. 

Safety stock costs If the demand time, the transit time, or both are uncertain, it may be necessary to carry inventory as a buffer against demand uncertainty. As discussed earlier, the extent of this inventory buffer depends on the magnitude of the demand uncertainty during the supply lead time and the planned in-stock service level. If the planned in-stock probability is expressed as service and the demand over lead time has a standard deviation of ct i, then the safety stock level is expressed as (Note that we assume that... 

With low forecast accuracy and/or high demand variability, companies usually have to increase safety stock levels or transship products from one warehouse to another, on an expedite basis, when a warehouse is short of inventory, otherwise they will lose profit margin and become less competitive. However, these operational initiatives despite allowing companies to achieve the required service level, hurt operational efficiency and increase supply chain costs. 

The basic logic of DRP is to compute the time-phased schedule of replenishments for each stock-keeping unit (SKU) in the distribution system that keeps the inventory level of that SKU at or above a specified safety stock level (which, of course, could be set to zero). Let the DRP horizon span planning periods t = and assume that the safety stock SS, the order lot size Q, and the... 

Note also that the last example in the chapter essentially entails determining the placement of safety inventory in the supply chain (since the reorder point specifies inventory carried over and above the level required to meet expected demand over the replenishment lead time), albeit a simple, serial supply chain. Magnanti et al. (2006) present a general formulation of fhis problem, specifically a non-linear optimization formulation subject to linear constraints, to solve for the optimal placement of safety stocks in a general supply chain network. Magnanti et al. actually generalize the problem... 

The Dow Fire and Explosion Index (FEI) (Dow, 1994 Van den Braken, 2002) and the Dow Chemical Exposure Index (CEI) have been developed and practiced hy Dow Chemicals for several decades. These tools measure process inherent safety characteristics, help to quantify the expected damage of potential fire and explosion incidents, and identify equipment that would likely contribute to the creation of the incident. The Mond Index was developed by ICI (UK) from the Dow Fire and Explosion Index. The Mond Index includes toxicity and covers a wider range of processes and storage installations than the FEI. The various aspects considered in the FEI are material factor (flammability and reactivity), general process hazards such as exothermic/endothermic reactions, and special process hazards such as toxic nature of the chemicals and dust explosion. For example. Table 8.6 shows the results of the FEI for various inventory levels of storage of ethyl acrylate. 

Inventory availability Inventory availability refers to on-hand inventory available to service current requirements. It is associated with inventory level, safety stock, and stock out (Zinn et al. 2002 Kumar and Rahman 2014). 

IVL Inventory level SAS Safety stock ALS Average lot size... 

The reduction of safety times and minimum inventory levels at the interfaces between the partners is finally possible,... 

Per Trent, volume relates to the amount of inventory a company owns at any time and key indicators will relate to total units on hand, including safety stock levels. Velocity refers to how quickly raw material and work-in-process inventory is transformed into finished goods that are accepted... 

---