BACKGROUND

The present invention relates to keeping equilibrium in non-fluid flow networks.

Research and development efforts to create equilibrium-seeking mechanisms have been mostly focused on fluid flow networks, such as gas pipelines or water systems. Others have applied to non-fluid flow networks that do not require individualized identification of the objects moving through, such as telecommunications networks, or where the move of each individual object cannot be controlled, such as intelligent transportation systems.

This invention relates to non-fluid flow networks where the movement of individual objects can be controlled, and where, item identification facilitates new management techniques. This is can be found in supply chains where items moving through the network often need to be rerouted, delayed or sped up as a consequence of variations supply chains are exposed to.

Flows of products and services can be typically characterized using flow networks. While some flow networks allow the movement of fluids such as a natural gas pipelines or a river, others permit non-fluid objects to flow, such as ants between their nest and the source of food, airplanes between airports or cars through highways.

Flow networks have stocks, which are accumulation mechanisms that help manage the flow of material through a system. Rivers have ponds, natural gas pipelines have tanks, and cars on roads can form traffic jams. The optimal point for a flow network is when its stocks don't change beyond the capacity of the system, a state known as equilibrium. The best-case scenario for a river is not to overflow and always have the same amount of water flowing through. However, rivers are not always in equilibrium and their increasing stocks create overflows. To keep a flow network in equilibrium, it is necessary to maintain a control on both flows and stocks. Existing controls have evolved around fluid and non-fluid flows. Several methods have been developed to determine optimal routes for flows, or how to keep the pressure in a pipeline by adjusting pressure valves. Other methods maintain equilibrium in non-fluid flows that do not require

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INCORPORATED BY REFERENCE (RULE 20.6) identifying and controlling each item individually. Traffic light control systems, for instance, seek to maintain equilibrium by continuously changing the frequency and duration of the traffic lights: the individual identification of each car is not required. Another example are the congestion control systems used in telecommunication networks: while individual packets of information travel through this network, the equilibrium seeking algorithms increase and decrease the available bandwidth with no need to identify and control the packets individually.

There are non-fluid flow networks that can take advantage of item identification to achieve even better control and maintenance of equilibrium. Supply chains, for example, will benefit if we can identify 'widgets' at production plants, distribution centers, warehouses, retail sites and in-transit mediums between these various facilities to keep inventory equilibrium within the system. By doing so, it is possible to associate meta-data with the 'widgets' so that we can expedite or reduce the speed of 'widget' flow to maintain network optimality.

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INCORPORATED BY REFERENCE (RULE 20.6) SUMMARY

In one aspect, systems and methods are disclosed to determine and keep the equilibrium in a flow network of items having a flow network having at least a source, a destination, and one or more nodes and arcs representing flows of separate identifiable items between the one more nodes and arcs, computer readable code to capture time for the items to move between each node, frequency or the amount of time that separates the movement of items in each arc, and speed or the sum of items per unit of time leaving the network at the sinks; and computer readable code to determine and keep equilibrium in the network.

In another aspect, systems and methods are disclosed for managing flow of items. The system includes a source; a sync; one or more nodes between the source and the sync, each node having an arc to a neighbor; and computer readable code to maintain equilibrium between in transit items and items already present in each node.

Implementations of the above aspects may include one or more of the following. The flow network can have various nodes and arcs, allowing the flow of separate identifiable items between them. The nodes giving origin to the items are called 'source'. The nodes consuming the items, or where items leave the network are called 'sinks'. Except for sources and sinks, nodes can store items. One or many arcs allow the movement of items between the node(s). The system tracks time length, or how much time it takes for the items to move between each node. The system tracks frequency, or the amount of time that separates the move of items in each arc. The system can track speed, or the sum of items per unit of time leaving the network at the sinks. Computer readable code are provided to:

Store primary and secondary flows between nodes;

Monitor the location and movement of items in the network;

Monitor the speed on a real time basis;

Monitor the amount of items inside each node;

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INCORPORATED BY REFERENCE (RULE 20.6) Determine the point of equilibrium for the entire network and each arc separately;

Determine the current status of the entire network and each node and arc separately;

Determine a gap between the optimal point of equilibrium and the current status;

Determine the nodes and arcs creating this gap;

Generate corrective actions to bring equilibrium back into the network; or

Identify items in the network.

The system can be used for supply chain management.

Advantages of the preferred embodiments may include one or more of the following. In contrast with conventional tools that work with summarized data by period of time such as a month of sales, a week of production, the system works with detailed data, down to a level of detail constrained only by the organization's cost structure. Additionally, the data is considered as it happens without summarization by period of time.

Other advantages can be seen as well. For example, conventional tools work with historical and projected data only. In contrast, the preferred embodiment considers real day-to-day data as it happens. In the preferred embodiment, levels of on-hand inventories are monitored against a limit, and if these levels go beyond these predefined limits, flows are changed by recalculating rate or by using other flows, as explained below. The preferred embodiment takes practices currently used at the strategic and tactical level into an operational level solution. Additionally, flow optimization procedures can be applied to manage a supply chain. Thus, the advantages of flow networks can be applied to managing on-hand and in-transit inventory to provide the following advantages for supply chain management as well:

* Provide total asset visibility

* Give full inventory history

* Allow reduced inventory-stocking levels

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INCORPORATED BY REFERENCE (RULE 20.6) * Facilitate "Just-in-Time" deliveries

* Provide full process control for products in the facility

* Reduce lead-time

* Shorten cross docking time

* Speed sort/pick rate

* Reduce shelf space

* Provide higher-level security

* Reduce errors

* Reduce overall cost of operations

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INCORPORATED BY REFERENCE (RULE 20.6) BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows exemplary components of a supply chain flow network.

FIG. 2 shows an exemplary application of time buckets to supply chains

FIG. 3 shows an exemplary graph showing the total number of days of inventory

FIG. 4 shows an exemplary time graph of an inventory level.

FIG. 5 shows an exemplary time graph of an on-hand inventory.

FIG. 6 shows an exemplary flow diagram of a process to balance inventory flows.

FIG. 7 shows an exemplary supply chain.

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INCORPORATED BY REFERENCE (RULE 20.6) DESCRIPTION

Before discussing details of the preferred embodiment, definitions of terms used next are discussed. A network is a group of similar parts connected together to allow a communication or movement between them. A flow is to move along or out steadily and continuously in a current or stream. A flow network is a group of similar parts connected together to allow a steady and continuous communication or movement between them. These parts are, for example, the production plants, distribution centers and warehouses in a supply chain, or the airports in the network of flying airplanes. Their similarity allows this movement and communication to occur.

As in the case of supply chains, individual items may move continually but not continuously. Continual describes frequently recurring; always happening, while continuous relates to forming an unbroken whole; without interruption. While items always move through its arcs, they don't move as an unbroken flow, but in groups, like inside trucks or containers for the case of supply chains. With this behavior, variables not usually considered in other flow network equilibrium-seeking methods have to be used, such as duration between nodes and the frequency these items move. Ultimately for a flow network to be in equilibrium, the non-continuous movement of items, with frequencies and durations in each arc, should be equivalent to the speed experienced at the sinks.

Equilibrium is a state in which no net change is occurring. Something in a state of equilibrium could be considered to be stable, balanced, or unchanging, and such a state is extremely rare, usually only existing for brief periods of time before something disturbs the balance. Typically, the term describes a stable state. Most things tend to change over time, sometimes slowly and sometimes rapidly. The constant tendency to change makes it difficult to establish a state of stability, even when such a state is critically important."

The present invention is a method to maintain equilibrium in non-fluid flow networks that require individual identification and control of the items flowing inside the network. The application of concepts discussed herein to a supply chain is discussed as

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INCORPORATED BY REFERENCE (RULE 20.6) an exemplary implementation, without limiting its applicability to only supply chain management.

FIG. 1 shows exemplary components of a flow network, as a supply chain. In telecommunications networks and in transportation systems, inventory is a signal of how in equilibrium the system is, as inventory or stock is a consequence of how balanced the flows are. If stock level starts to reach a pre-determined limit, control systems start to alter the flows such that this stock level returns to its normal status. This behavior can also be seen in simple systems such as a bathtub: the faucet needs to be closed or the sink needs to be opened if the water level is too high, or the faucet needs to be opened and the sink closed if the water level is low. So, by altering the inflow (faucet) and outflow (sink) the stock (water level) can be kept at a desired level or within desired levels. In supply chains, though considered flow networks, the inventory is kept through inventory management policies: when the inventory reaches a point (reorder point) more inventory is ordered (reorder quantity). In transit inventory is considered as a quantity arriving at a certain date and place, but as opposed to other flow networks, in transit inventory is not managed and on hand inventory is.

Turning now to FIG. 1, source 1 represents a node outside of a supply chain network, such as a supplier, among others. Nodes 2 represent facilities, physical or virtual, within the supply chain such as production plants, distribution centers, or warehouses. On-hand inventory lies inside nodes 2. Sink 3 represents the node where the product goes into, that is outside the network boundaries. Examples of sinks 3 are customers of final products, buyers of byproducts produced by the network or scrap generated by the process.

Primary flows 4 connect the source 1 with nodes 2, connect nodes 2 to each other, and connect nodes 2 with sink 3. Primary flows 4 are those used as default given the economies of each organization. For example, in the case of supply chains, if the most efficient mode of transportation from Houston to Memphis relies on trains, then primary flow 4 represents the train between these two locations. Auxiliary flows 5 are contingent flows, to be used as an alternative to primary flows 4, within the same origin and destination as primary flows 4 or between other origins and destinations. Auxiliary flows

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INCORPORATED BY REFERENCE (RULE 20.6) 5 may also trigger the use of auxiliary nodes 6. An auxiliary node may represent a temporary storage used, for instance, to slow down deliveries, to create a delay required to make a rerouting decision or to use contingent storage if disruptions occur. These uses are for supply chain implementations, while there might be other uses as well. Auxiliary flows 5 and auxiliary nodes 6 are used to speed up or slow down the flow of product between nodes 2: auxiliary flows and nodes are one of the means on how to bring equilibrium back into the network. Often, supply chains face disruptions caused by nature, accidents or terrorists acts. Currently, the corrective actions to outbalance the effects of these disruptions depend on decisions people make, being consequently exposed to human error. The use of auxiliary flows and nodes, and the code to manage them provides the means to create self-correcting supply chains reducing the effects of human mistakes.

In one embodiment, there are two dimensions of time: vertical and horizontal. The vertical dimension of time is the amount of time the inventory represents given its amount and its demand. This is what traditionally has been known as days of inventory, which could be months of inventory, hours of inventory, etc. depending on the specific dynamics of the industry.

The horizontal dimension of time is the time length within a supply chain, considering transit times and processing times in production plants, distribution centers or any other facility requiring time to transform a product. For example, if there is a 4 day long leg, feeding a warehouse with an inventory equivalent to 5 days, and an in-transit inventory equivalent to 2 days, the vertical dimension of time will be a total of 7 days (there is an inventory equivalent to 7 days of demand adding both in-transit and on-hand), and the horizontal dimension will be 4 days, assuming no extra time is required in the warehouse (that is, no processing occurs within the warehouse requiring additional inventory).

Given that both horizontal and vertical dimensions are in the same unit of measures, both can be related to each other as a ratio: how many days of inventory are per days of transit. To illustrate the relationship, an extreme example is discussed next with a one-year long leg with no in-transit inventory. If it takes one-year for the in-transit

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INCORPORATED BY REFERENCE (RULE 20.6) inventory to get from the supplier to the warehouse (horizontal time), there should be at any given moment at least one-year worth of stock sitting in the warehouse. From the moment the is one day less in the warehouse (364 days) with no in-transit inventory, there will be a stock-out.

Following the same example, if there are 180 days of inventory in the warehouse, there should be at least 185 days of in-transit inventory to prevent stocks. With 180 days in the warehouse and 185 days in-transit, no stockouts will occur. However, this may not be true. If the 185 days of in-transit inventory comes in a single shipment, one scenario will be that this shipment will arrive to the warehouse in 170 days, and another is if this shipment was dispatched yesterday! In the first scenario, the shipment will arrive at the warehouse when there will be 10 days of on-hand inventory (180 of on-hand inventory minus 170 days left of transit time). In the second scenario, in 180 days the warehouse will start a period of 184 days of stock-out (the shipment has one day in transit, 364 days for arrival, minus the 180 days of on-hand inventory). Thus, the location of the in-transit inventory is related to the amount of on-hand inventory. The amount of on-hand inventory should cover the time remaining before the arrival of the next in-transit shipment; in other words, the location of the in-transit shipment must be, at least, right after the part of transit time covered by the on-hand inventory. The amount of in-transit shipment must be enough until the next shipment is in-transit. The shipping frequency determines, therefore, the amount of time each in-transit shipment must cover.

The relationship between on-hand and in-transit inventories is key to maintain equilibrium in a supply chain flow network, as it guarantees the presence of inventory, which, in turn, provides a satisfactory service level to customers. However, for this relationship to be managed by a system, it is necessary, first, to see inventory as time, and second, to relate in-transit and on-hand inventories in a physical dimension to assure the location of in-transit shipments is in accordance to the amount of time covered by the on- hand inventory.

The first need, to see inventory as time, can be accomplished by dividing inventory in widgets by the demand rate experienced at the customer or sink. For example, 10 widgets can represent 1 day or 5 days if the demand, respectively, would be

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INCORPORATED BY REFERENCE (RULE 20.6) 10 widgets per day or 2 widgets per day. Today's technology allows monitoring the demand rate on a real-time basis, thus providing the means to update the amount of inventory from a time perspective.

The second need requires the creation of an element to relate transit time, with location of in-transit shipments and the amount of time the on-hand inventory represents. This element for the preferred embodiment is called 'time bucket'.

Time bucket has been used in MRP systems (SAP for instance) to describe how time is divided. So, for instance, if the time bucket is week, forecasts and all MRP related material information is given on a weekly basis: in other words, it defines the denominator of the rate.

In the preferred embodiment, the time bucket is different. The definition of time bucket is the virtual separator of the time length of the arc. The time bucket could be weeks, days, months, hours, depending on the industry dynamics and the nature of the leg.

A time bucket reflects the items moving through the arc as well as those stored in the node of destination. The amount each should have as well as its size will be determined by the user according to his need. For example, Figure 2 shows an arc and node in a supply chain. The node is a warehouse (3) and the arc is a transit time from the production plant (2) to this destination of 10 days. A truck (1) ships widgets from the production plant to the warehouse. As shown, the warehouse has a total of 60 widgets stocked, to support an average daily demand of 15 widgets/day. The truck is in its 4* day of transit time and carries a load of 45 widgets. As the desired time unit of measure, and based on said demand, the inventory in the warehouse has an equivalency of 4 days of inventory (60/15) and that inside the truck of 3 days of inventory (45/15). Below is how this operation is represented through the time bucket concept. As there are 10 days of transit time, 10 time buckets are configured along the arc. The 4 days of inventory stored in the warehouse fill time buckets 7 through 10: each time bucket is meant to hold an amount of inventory the same as the designated time unit of measure. On the other hand, the truck is on its 4 day of transit time, so its inventory starts to fill the time buckets 4 and backwards until the total amount is reflected. In this case, there are 3 days of

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INCORPORATED BY REFERENCE (RULE 20.6) inventory inside the truck, thus time buckets 2 through 4 are filled or occupied. By doing this, it becomes evident the need to replenish an amount of 3 days of inventory in no more than 3 days, as time buckets 1, 5 and 6 are empty.

Time buckets combine both dimensions of time: the horizontal for the supply chain time, or transit time and the vertical for the inventory time. The prior example shows its use, and shall not be interpreted as its implementation is solely for supply chain networks only, but also others with a similar need.

Next, Frequency and Lead Time concepts are discussed. Referring back to FIG. 2, the warehouse has 3 days of inventory, and there is an in-transit shipment with a lot size equivalent to 4 days of inventory, and its location is 6 days for arrival. Consequently, the time buckets can be represented as 1 1 1 10001 11.

There are 4 days of inventory filling the first 4 time buckets, (from the in-transit shipment size and location), 3 time buckets empty, and other 3 are filled with 1 day of inventory each, from the on-hand inventory. From this the system can determine the following:

1. There will be a period of 3 days of stock-outs in 3 calendar days. This can trigger a expedite shipment equivalent to 3 days of inventory that must arrive within the 3 day time period covered by the warehouse.

2. The optimal value per time bucket is 1 , and if the value is below 1 there will be a stock out. If for instance, the demand increases in the next days, those three days of inventory in the warehouse may become 2.8 days, resulting in a 0.2 days of required stock.

If 1 is the optimal value, then for every day and every time, each time bucket must have a value of 1 : variations below are stock-outs, and above are excess inventories. However, this may not be the case. For example, in the 10 day leg just discussed, the supplier can dispatch a shipment only once per year. So, though it only takes 10 days to reach the warehouse, only once a year is possible to receive a shipment. Similarly to what was discussed previously, if there are no shipments in transit, the minimum amount of

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INCORPORATED BY REFERENCE (RULE 20.6) inventory the warehouse should have to prevent stock outs is 10 days, assuming the dispatch day will be tomorrow. Tomorrow two things happen: on-hand inventory is 9 days and the shipment will appear in the first time bucket. Next day, the shipment will be one more day closer to the warehouse, appearing on time bucket 2, and the warehouse will have one day less of inventory. On the day prior to arrival, this leg's time buckets will have 36.5 days of inventory each, and the warehouse will have 0 days of inventory. So, 1 cannot be considered as a maximum. If that would be the case, in this scenario there would be 355 days of inventory as overstock, and obviously this is not the situation.

As frequency plays a role determining the load size of each in-transit shipment, optimal value cannot be 1 as, for instance, there is a 2-day transit time leg, with a frequency of 400 days. The load size must be equivalent to 400 days to maintain the flow. Thus, each time bucket would have a value of 200 days the day before arrival.

With the purpose of finding a pattern, different scenarios can be developed combining values of frequency and lead time. These scenarios are similar to the table elow:

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INCORPORATED BY REFERENCE (RULE 20.6)

For 20 calendar days (second column), in-transit inventory flows through a 2 day lead time leg (represented by 2 time buckets, 3rd and 4th columns), feeding an on-hand inventory, in widgets, in the fifth column, and adding a total amount of days of inventory in the last column. In-transit and on-hand inventories are separated in each calendar day on the gray shaded line and non-shaded line respectively. Demand is 10 widgets per day.

The first calendar days has an on-hand inventory of 40 widgets, equivalent to 4 days of inventory, and reflected as 2 days of inventory per time bucket. The total days of inventory in calendar day 1 are 4 as there is no in-transit inventory (non-shaded second line of calendar day 1 is empty).

After the second day, the on-hand inventory is down by 10 widgets or 1 day of demand (1 day inventory). As a consequence there are 3 days inventory as a total, all as on-hand inventory, reflected as 1.5 per time bucket in the gray-shaded line.

On day 3, on-hand inventory is again down by one day of inventory, or 10 widgets, bringing the total number of DOI to 2.

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INCORPORATED BY REFERENCE (RULE 20.6) On day 4, on -hand inventory is down to 1, reflected only in time bucket 1 (gray time bucket 2 is empty), but a new shipment appears in time bucket 1 (non-shaded line) with 4 DOI.

As previously explained, there is a relationship between demand (speed), frequency and lot size. Speed = frequency*lot_size. Therefore, lot size equals speed/frequency. Speed is 1 (1 day of demand per day), and, in this case, frequency is 4 days (every for days there is a dispatch). As frequency is 1/4, lot size equals 1/(1/4), 4 days of inventory.

Total days for day 4 is 5, 4 in-transit and 1 on-hand. On day 5, the in-transit shipment has moved one day, appearing as 2 DOIs in time buckets 1 and 2 in the shaded line, and on-hand inventory is down to zero. Given that this is the ending inventory of the day, we shall not consider this as a stock out. Nevertheless, the system can control the minimum amount of on-hand inventory. The total days of inventory for day 5 are four.

On day 6, the shipment was received and one day of inventory was sold. As a consequence, there is only on-hand inventory with an equivalent of 3 days of inventory. Analyzing the total number of days of inventory in the last column, a pattern can be determined. 5,4,3,2,5,4,3,2,5,4,3,2. The 5 occurs every time the in-transit shipment is at time bucket 1, next day goes down to 4, 3 when the shipment arrives and 2 the day before the first day of transit.

Following the same procedure, the patterns for various combinations of frequencies and lead times can be determined as follows: frequency of every 4 days, lead time of 2 days (above); frequency of every 5 days, lead time of 3 days; frequency of every 10 days, lead time of 3 days; frequency of every 1 days, lead time of 3 days;

frequency of every 3 days, lead time of 13 days.

FIG. 3 shows the total number of days of inventory per calendar day. Line 302 is the scenario above. As discussed, it fluctuates from 2 DOI to 5 DOI. Line 304 represents a frequency of every 5 days and a lead time of every 3 days. In comparison with the blue line, its maximum is 2 days more, its minimum 1 day more, and its length is one calendar day more (its maximum is 7 on calendar day 1, and its minimum is 3 on calendar day 5,

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INCORPORATED BY REFERENCE (RULE 20.6) where as the blue line 302 reaches its maximum and minimum on calendar days 1 and 4, 5 and 8). This graph tells interesting conclusions:

1. The lower the frequency, the longer the length between maximum and minimums. For instance, the yellow line represents the scenario with the lower frequency (every 10 days). This makes sense when comparing with the green line 308 showing a frequency of 1, the smallest. It is so small that it doesn't generate any fluctuations. This can be understood comparing it with a bath tub. If the water flows through the sink at a continuum rate (demand) and the water is filled once a day, the level of water inside the tub changes from a very low level up to a high level (the fluctuation has to be a one-day equivalent of flow through the sink). But, if the tub is continuously filled with the same rate as that of the sink, the level of water does not change at all.

2. The higher the lead time, the higher the value of both maximum and minimums. The purple line represents the scenario with a higher lead time - 13 days. The maximum level of days of inventory is 15 days and the lower is 13 days.

3. The minimum is always the lead time. This may sound too simplistic, but, if demand is constant, where every calendar day a day of inventory is sold, if the minimum represents the day before departure (that is, on next day there must be a shipment on time bucket 1), the on-hand inventory should be at least equal to the demand during lead time, in other words, the amount of days of inventory equal to the days of lead time.

4. The total number of DOI is given by the formula LT + (f- D) where LT is lead time, f is frequency and D is the calendar day relative to the first day of shipping (D=l is the first day where the new shipment is seen, in time bucket 1). f is the number of days that separates one shipment from the next one.

5. The maximum value, therefore, is when D = 1, which is the first day of shipping.

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INCORPORATED BY REFERENCE (RULE 20.6) By knowing how many days are left for departure, we can compare the number of DOI in the leg with the theoretical number. The difference is added or subtracted from the lot size. This difference as D (delta), and the lot size LT is:

LT = f + D

In other words, the lot size in days of inventory is equal to the frequency in days plus the difference between the current value of days of inventory in the leg minus the theoretical value. Obviously, the result is then translated into widgets according to the actual or forecasted rate of demand.

FIG. 4 shows an exemplary time graph of an inventory level. In this example, maximum level 6 is used as a point of comparison of the inventory level. The calculation of this limit can be done using current practices such as days of inventory, among others. A higher on-hand inventory may be required due to economies of scale in the system, e.g. the set-up costs of a production line are so expensive that a production-run produces a higher volume than what is actually required. Another reason for a required higher on- hand inventory is to reduce transportation costs of items needed to fill out a load. These inventories are therefore compared against maximum and minimum levels.

FIG. 5 shows an exemplary time graph of an on-hand inventory with a minimum limit of seven in this example. The comparison of the inventory level to the allowed limit can be absolute (binary, such as is within or is not within) or relative (how close or far is the inventory level to the limit, as a percentage), allowing the system to place an alarm based on the inventory limit.

FIG. 6 shows an exemplary flow diagram of a process to balance inventory flows. The process starts by determining differences between inventory levels and inventory limits (102). For required inventories, levels are checked against minimum and maximum limits; for non-required inventories, levels are checked against maximum levels. This calculation, as previously stated, can be absolute or relative giving a binary status or a numerical status. Based on these limits and the levels of closeness, it is determined whether the inventory levels are or are not within limits, in other words, if the network is in equilibrium or not (104). If inventory levels are within control limits, or in a zone close

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INCORPORATED BY REFERENCE (RULE 20.6) enough to be considered in equilibrium, the system determines differences between inflows and outflows (106). As difference in outflows and inflows are the cause of stock changes and non-equilibrium states, it is important to monitor these differences. Said differences need to be compared to a predetermined allowed limit of difference. There has to be predefined limits for the differences between flows.

Next, examples of flows traversing to and from a node for one embodiment is discussed. In this example, inflows and outflows are represented by fl, f2... f6, where each fx is expressed in units per time (boxes per day, widgets per hour, etc.). These inflows need not be equal, but in one implementation, for the stock in the node to be in equilibrium, that is to remain unchanged, the sum of fl , f2 and f3 equal to the sum of f4, f5 and f6. That is:

∑fl + f2 + f3 =∑ f4 + f5 + f6

If both terms are not equal:

∑fl + f2 + f3 < >∑ f4 + f5 + f6

This also may apply in implementations with no stocks.

Stock starts to increase or decrease, depending on which side is bigger. In supply chains, a perfect equality is hardly possible. So there has to be a predefined limit for this inequality that can be expressed relatively, as a percentage, predetermined by the user. For example, this limit can be of 3%, and is compared against, following the example above, to:

|∑(fl + f2 + 0) -∑ (f4 + f5 + f6)| /∑(fl + f2 + 0)

or, in another embodiment

|∑(fl + f2 + 0) -∑ (f4 + f5 + f6)| /∑(f4 + f5 + f6)

or, any other way to establish a relative difference of inflows and outflows as a percentage of throughputs. This is where, referring back to FIG. 6, the difference between limits (108) determines if the difference is acceptable or not. If this formula is lower than the predefined limit (3% as example) or is not close to 3% the flow goes back to 102 to calculate difference between inventory levels and inventory limits and the monitoring continues.

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INCORPORATED BY REFERENCE (RULE 20.6) If the difference between limits in 104 or if the difference between limits 106 detects stock levels or flow differences close to limits or over the limits, it means the system is not in equilibrium or is close to not being in equilibrium, the system estimates the net change required between inflows and outflows to bring the system back in equilibrium in 110, which determines how much should the flows need to be changed in order to bring the system back in equilibrium. This change can be accomplished by only changing the rate in the primary flow 4 used, or if it requires using an auxiliary flow 5 to speed up or slow down total flow. Next, the system determines if the rate change is enough (1 12), and determines if by changing the rate the equilibrium could be reached or not. To determine this it is required to do a projection of inflows and outflows considering current inventory at the node, its limits, and also the cost of transportation modes used in primary and auxiliary flows, its transit time, and the cost impact in the product under analysis. If rate change is enough, the system calculates a new rate in primary flow (1 14); if rate change only is not enough, the system identifies auxiliary flows to be used (1 16) and determines what auxiliary flows 5 are predefined and which one(s) should be used at what rate. In 118, the system calculates new rates in auxiliary flows") to bring equilibrium back into the node and system. Once changes have been determined, in the system generates orders (120) for all required orders of rate changes and/or use of auxiliary flows are created for execution. Then, the flow goes back to the initial monitoring (102).

This analysis for the sink requires a demand forecast. Not always the inflows have the same unit of conversion of the outflows: in these cases a bill of materials is used to convert the flows to a standard unit of measure for the whole system.

In contrast with the current art, the system classifies products in a make-to-flow as opposed to make-to-stock used in the current art. The total flow of the make-to-flow products will be composed of a base flow, which is the primary flow, delivering the constant part of the total flow, and the variations on top of the base will be delivered using both primary and auxiliary flows. Other change may come on how goods are transported by carriers: intermodal distribution points could occur along the trip of a vessel, train or truck, opening the opportunity of managing in transit inventory by splitting loads while in transit and sending part by faster or slower means of

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INCORPORATED BY REFERENCE (RULE 20.6) transportation, or to other supply chains, or to temporary warehouses. Incoterms may need to change as well, as in transit change of bill of ladings should be allowed.

FIG. 7 shows an exemplary supply chain. The chain consists of one or many production plants (202) receiving materials from one or many suppliers (201), converting materials to finished goods sent to one or many distribution centers/warehouses (203). These distribution centers/warehouses (203) may store these finished goods, and send them to one or many retailers (204) for their final sell to the external customers (205).

A data capturing system (206) retrieves the sales demand rate data flow (207) from retailers (204), the in-transit status data flow (208) from those finished goods sent from distribution centers/warehouses (203) to retailers (204), or from production plants (202) to distribution centers/warehouses (203) or from suppliers (201) to production plants (202), and the on-hand inventory data flows (209) from production plants (202), distribution centers/warehouses (203) and/or retailers (204).

Said data capturing mechanism (206) sends the operation status data (220), comprised of said flows, to a control center (211). The control center (21 1) creates rate adjustment orders (212) for said facilities, and expediting, delaying and/or rerouting transportation orders (213) for the different entities in control of in-transit inventories.

The above system manages on-hand inventory and in-transit inventory. In-transit is managed while traveling to the warehouse it is destined. This can be called "leg" or "feeding line". On-hand and in-transit are related. The amount of in-transit needs to be in accordance to what is on-hand.

The above embodiments allow equilibrium to be applied in a supply chain.

Similar techniques could be used to change the flows to balance the system.

The invention may be implemented in hardware, firmware or software, or a combination of the three. Preferably the invention is implemented in a computer program executed on a programmable computer having a processor, a data storage system, volatile and non-volatile memory and/or storage elements, at least one input device and at least one output device.

By way of example, a block diagram of a computer to support the system is discussed next. The computer preferably includes a processor, random access memory

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INCORPORATED BY REFERENCE (RULE 20.6) (RAM), a program memory (preferably a writable read-only memory (ROM) such as a flash ROM) and an input/output (I/O) controller coupled by a CPU bus. The computer may optionally include a hard drive controller which is coupled to a hard disk and CPU bus. Hard disk may be used for storing application programs, such as the present invention, and data. Alternatively, application programs may be stored in RAM or ROM. I/O controller is coupled by means of an I/O bus to an I/O interface. I/O interface receives and transmits data in analog or digital form over communication links such as a serial link, local area network, wireless link, and parallel link. Optionally, a display, a keyboard and a pointing device (mouse) may also be connected to I/O bus. Alternatively, separate connections (separate buses) may be used for I/O interface, display, keyboard and pointing device. Programmable processing system may be preprogrammed or it may be programmed (and reprogrammed) by downloading a program from another source (e.g., a floppy disk, CD-ROM, or another computer). The computer can be a server running a cloud-based server network, for example.

Each computer program is tangibly stored in a machine-readable storage media or device (e.g., program memory or magnetic disk) readable by a general or special purpose programmable computer, for configuring and controlling operation of a computer when the storage media or device is read by the computer to perform the procedures described herein. The inventive system may also be considered to be embodied in a computer- readable storage medium, configured with a computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner to perform the functions described herein.

The system can use various automatic identification technologies such as bar codes and RFID to identify items. Bar codes containing identifying information about items can be read by a reader and transmitted to a processor. RFID identify any object using a tag. Using both, products can be tracked in, out and through facilities in a supply chain. The system can manage the flows and use the on-hand inventories as signals telling how in equilibrium the whole system is. The system can manage a supply chain focusing on in-transit inventories, and using on-hand inventories as signals of system equilibrium.

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INCORPORATED BY REFERENCE (RULE 20.6) The system can use global positioning systems (such as GPS, Galileo, Beidou, COMPASS .GLONASS, IRNSS, and QZSS) to see and manage the flows, as well as other location mechanisms.

The invention has been described herein in considerable detail in order to comply with the patent Statutes and to provide those skilled in the art with the information needed to apply the novel principles and to construct and use such specialized components as are required. However, it is to be understood that the invention can be carried out by specifically different equipment and devices, and that various modifications, both as to the equipment details and operating procedures, can be accomplished without departing from the scope of the invention itself.

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INCORPORATED BY REFERENCE (RULE 20.6)