Elements of Manufacturing, Distribution and Logistics

The forecast is perhaps the most important function in controlling the inventory. In a typical inventory entity, forecasts are needed for each of the future months up to the planning horizon, typically 12 months. Data from the past demands is needed to generate the forecasts. Assuming monthly time buckets, the demand for a fixed number of history months, (usually 12, 24 or 36), is saved in the database. The monthly demands represent the number of pieces ordered on an item for each month. Many entities also save the lines per month. These are the number of customer orders that arrive during a month. The history months are mostly saved in calendar months, but some entities use fiscal months of the 4, 4, 5 type. It behooves the entity to process the demand history prior to forecasting, by running a routine to seek if any outlier demands are found, and if so, to adjust them prior to forecasting. Another useful routine would seek to adjust the demand history if any demands are returned due to a ship-in-error by quantity or by part.

The standard deviation of the 1-month-ahead forecast error is used to determine how much safety stock is needed to satisfy the level of service to customers. An exact measure of the standard deviation is not easy to generate, however, estimates are used in its place. The way to estimate the standard deviation varies depending on the forecasting method in use (moving average, regression, discounting, smoothing). This chapter describes how to estimate the standard deviation for each of the forecast models presented in Chap. 1.

The order quantity, Q, is a planned amount of stock to replenish the inventory from the supplier when new stock is needed. In the ideal situation, Q is calculated to give the minimum cost of holding and ordering the stock, called the economic order quantity, EOQ. The EOQ is obtained from several factors: A is the annual forecast of the item, Co is the cost per order, c is the cost per unit, and h is the annual holding rate. Note, A comes from the forecast, c from the supplier, and Co and h are parameters from the stocking facility. In some facilities, the order quantity is restricted to fall in monthly buckets, but in most situations it is not limited in that way. A related cost measure is the stocking rate denoted as, s, which measures the rate of added cost on the item due to stocking the item via hold plus order. The stocking rate yields another measure labeled the stocking cost per unit denoted as \( \left(\mathrm{c}\times \mathrm{s}\right) \) which is a hidden added cost due to hold plus order. The effective cost per unit becomes: c` = c(1 + s). It is sometimes useful for the inventory management to realize the sensitivity between the four ingredients and the order quantity. When A changes, how does this affect Q? The same queries can be made with changes in Co, c and h. Another measure of interest is the change in the hold plus order cost when using an order quantity different from the EOQ. Note also, as the order quantity changes, the on-hand inventory also changes.

Safety stock is needed to attain a desired level of service when the demands exceed the forecasts over the lead-time duration. Four popular methods to generate the safety stock are in use: months supply, service level, percent fill and Lagrange. For each method, a safety stock parameter is assigned by the management to specify how to compute the safety stock. The months supply method is based on a specified number of future forecasts. The service level method is set so the probability of not having an out-of-stock condition during the lead-time is satisfied. The percent fill method seeks to accommodate the ratio of (demand fill)/(total demand) over the lead-time. The Lagrange method is a cost-benefit way to set the safety stock. The latter three methods are based on the distribution of forecast for the lead-time demand. The distribution for the lead-time demand can be normally distributed or not normally distributed. When normally distributed, the standard normal distribution is applied to set the safety stock. When not normally distributed, the truncated normal distribution is used to set the safety stock. The coefficient of variation for the lead-time demand is used to identify which of the two distributions to use.

Replenishing the stock is one of the most important functions in the control of the inventory. The goal is to replenish the stock that properly covers the customer demands at minimum cost in inventory. To accomplish, two measures are regularly computed: the order point and order level. Each day, these are compared to the current on-hand plus on-order inventory to determine if a new replenishment is needed now, and if so, how much. Each replenishment must conform with any constraints provided by the supplier, as minimum buy quantity and multiple buy quantity. For analysis sake, the inventory is partitioned into cycle stock and safety stock, where the sum is the total stock. The ingredients that affect the stock levels are the percent fill, lead-time, coefficient of variation, and month-in-buy. The sensitivity of each with the stock levels and with the turnover is described. In many retail entities, the demand for each item is low, and thereby the Poisson distribution is used to determine the order point and order level. For entities with low demand items, table entries are provided to guide the management on how to set the order point and order level.

For convenience here, a network (NW) is defined when two or more stock holding facilities are connected with one entity. This is a distribution system with two or more locations. Could be a system with distribution centers (DC), or two or more retail outlets. The individual stocking locations are here referred as locations. The goal is to control the inventory for the NW and for each location. Typically, once a month at the NW, forecasts, standard deviation of the forecast error, and the planned order quantity are generated. Also, at each location, the forecast, standard deviation and order quantity are also needed to compute the order point and order level. At each location, the on-hand and on-order are observed and compared to the order point and order level to determine if a location needs a replenishment buy, and if so, how much. Sometimes the location buys directly with the supplier, and other times, the NW buys for the total system.

The manufacturing plant consists of an assortment of raw materials, components, machines of various type, and an variety of skilled workers, with the goal to produce goods to a higher level, and some to finished-good-items. The management’s task of coordinating all this activity is difficult indeed. A first concern of the management is to periodically generate a production plan for the coming planning horizon. This plan pertains to the aggregate of all items in the plant and yields the volume of production for all. The plan depends on the type of items to produce: make-to-stock, make-to-order, or a combination of make-to-stock and to order. For each finished-good-item, a master production plan is generated to coordinate the schedule that satisfies the inventory status and customer demands. This schedule also yields the available-to-promise quantity that is a vital tool to the sales force. The concept of raw load and level load by future time periods for various production centers in the plant are described. To ensure the schedule of all items are doable, a rough-cut capacity planning analysis is calculated for each of the production centers in the plant. When the capacity does not meet the load, adjustments are required. For every item to be produced, a bill-of-material is used to identify each of the parts and components that are required in the build. From here, a materials requirement planning set of computations determines the build schedule for every item.

Just-in-time (JIT) is a philosophy of production based on the concept of adding value and eliminating waste. JIT and lean manufacturing have very similar goals. Value is added only by work performed on the product, and waste is anything other than a minimal amount of necessary resources—material, manpower, and the capital equipment—that is required for production, and does not add value to the product. The process called Kanban is a system where cards are used between send and receive stations in a way so that the stations produce only the necessary quantity of goods at the necessary time. JIT examples are presented where the components to a product are received from a supplier shortly after the customer order arrives. The relation between lean manufacturing and JIT is described. Smaller batch sizes are preferred in production, and this is accomplished as the setup time at a production process is reduced. The smaller the setup time, the lower the economic batch size. The safety stock to achieve a service level to the customer depends largely on the lead-time of replenish time from the supplier. As the lead-time becomes smaller, the amount of safety stock needed is lowered accordingly. The management should also seek to level the week-to-week aggregate production loads to avoid excess cost of overtime, backorders and outsourcing. When the finished good items are on a make-to-order basis, the strategy of postponement reduces the lead-time to the customers, and also eliminates much of the complication in the assembly.

A variety of assembly lines are applied in industry. For the smaller type of products, the assembly lines are often of the single model type, where one model of the product is produced on the line. The work elements to assemble one unit are gathered, and set in a precedence diagram showing the feasible work relations between the elements. The number of operators needed is computed and the work elements are assigned to each operator in a fair-share way. This latter function is called line balancing.

A process can be defined as a combination of components, tools, people and machines that together produce an item, like a part that subsequently is inserted into a finished good item. Although, the output of the process may vary, the final customer requires the product to satisfy the standards specified by the engineers. Management’s goal is to control the output units of a process so that it conforms to the standards set by the engineers. The output measures are of two types: attribute or variable. Attribute is when the output measure is defective or not defective. Variable is when some measure is taken from each sampled unit.

In a typical original equipment manufacturing (OEM) system, the suppliers ship stock to one or more distribution centers, that serves as the source to a series of retailers (dealers, stores), and the retailers sell the products to the customers. This could be a network that holds service parts for an automotive corporation. The dealers sell the autos to the customers and when repair or maintenance is needed, the customer seeks service from the dealer. The dealer carries a limited supply of parts for this purpose, and relies on the DC to have a full set of parts as needed. The OEM is faced with holding the minimal amount of stock needed to properly service the demands from the dealers. In the ideal situation, the DC system consists of a network of locations that are strategically near the dealers and to some extent, near to the suppliers. One location is the master stock location that serves as the headquarters for the entire system. The other locations are branch locations. The master location is often a much larger location and holds more variety of stock. Sometimes a small location is provided and is called a 2-level-service location. This location holds minimal stock and is supplied by the master stock location. The parts that have a high amount of demand are stocked in most locations and are called distributed parts. The low demand parts are labeled as non-distributed, and are mostly stocked only from the master stock location.

The supply chain management team in a manufacturing firm is concerned with the flow of raw materials, basic goods, components, work-in-process and finished goods from suppliers to warehouses, plants, distribution centers, retailers, and finally to the customers. The goal is to minimize throughput times and expenditure costs, while achieving a high level of service to the customers with a clean environment. To accomplish, the team remains vigilant on the use of all technology available to them. Data sharing with the customers and throughout the operation is needed so all can work efficiently. The team applies the technology of scan based tracking, electronic data interchange, bar codes, data matrix barcodes, quick response codes, and radio frequency identification where and when appropriate. In the inventory operations, vendor managed inventory and continuous replenishments are applied when suitable. In transportation, incoterms are applied along with tracing and tracking of the shipments; and whenever feasible, outsourcing and third-party providers are employed. Five examples are sited: a heavy-duty make-to-order manufacturer, a network of men’s shoe stores, an offshore automotive dealership, a replenishments of inventory at retail stores for seasonal style good, and a delivery system to stores for a popular bakery item.

Transportation pertains to the movement of items from one location to another. Could be from a plant to a distribution center to a retailer. Shipping categories is a way to classify the type of goods: household, express, parcel or freight. Transport modes are the access ways to transport: rail, road, air, water, or pipes. Transport vehicles are the trucks, trailers, barges, aircraft, and cargo ships. Cargo handling is by ports, container terminals, shipping containers, forklift trucks, cranes, pallets, and dunnage. The shipment of goods also concern dispatchers, bill of lading, manifest, truckload shipping, less than truckload shipping, parcel carriers, bulk cargo and break bulk cargo. Some industrial trading terms are: free on board, carriage and freight, carriage, insurance and freight, and best way.

Reverse logistics is the process of managing the operations concerned with any returned goods to the manufacturer. On average, near 5 % of the goods sold are returned to the original manufacturer for a variety of reasons as: worn out goods, damaged goods, unsold goods, recall goods, and so forth. The manufacturer is obliged to receive and process the return goods seeking any revenue that can be gained, or arranging for proper disposal. The role of processing return goods has expanded ever more as the environmental mandate of industrial growing green has gained strength. In the typical forward logistic way, the goods final destination is with the customer. As the goods become old, they may be replaced and returned to the manufacturer to begin the reverse logistics cycle. The returned goods are mostly one-model-at-a-time occurring in a disjointed manner. The return process is costly, perhaps 10 % of the total cost of the original sales price, requiring the manufacturer to seek as much value from the item as possible. In the typical situation, the returned goods are cleaned, tested for worthiness, and if accepted, are repaired and refurbished for resale. When not accepted, they are disposed in the proper manner.