MXPA01000644A - Computer-implemented value management tool for an asset intensive manufacturer - Google Patents

Abstract

A method of valuing resources of an asset intensive manufacturer. Calculations provide an MAV for each resource (machine) for each time horizon. The inputs for the calculations include the prices of products made by the resource, probalistic demand for the products, usage of the resource by various products, and availability of the resource. A series of equations, one equation associated with each resource, is formulated and solved, using lagrangian methods, with the lagrangian multiplier representing the resource value.

Description

VALUE MANAGEMENT TOOL IMPLEMENTED BY COMPUTER FOR AN INTENSIVE MANUFACTURER OF GOODS TECHNICAL FIELD OF THE INVENTION This invention relates to computerized business management tools, and more particularly to a computer-implemented method for calculating resource values for an intensive goods manufacturer.

BACKGROUND OF THE INVENTION One of the unique challenges of a manufacturing company is the valuation of its products and resources. In the case of the valuation of products, traditionally, the prices are computed on the basis of a cost measurement plus some measurement of the customer's ability to pay. The resources conventionally valued in terms of price paid for them, for example, the price paid for a machine used to make products.

In recent years, the tools for business administration implemented by computer have been developed to help management decisions. These tools often include putting a price on the tools tried to help in the valuation process.

Notable among the tools for putting a price on products are those developed especially for airlines. These tools are not necessarily suitable for manufacturers. For example, intensive manufacturers of materials have limited materials (components) rather than capacity. In contrast, intensive goods manufacturers have a limited resource capacity and demand can be served before it is desired. In both cases, the probable demand is not in a particular order for different prices, as in the case of travel by airline.

SYNTHESIS OF THE INVENTION One aspect of the invention is the method of valuing the resources used to manufacture products. The method is especially useful for valuing intensive manufacturers, who have a limited capacity of their resources. The manufacturing process is modeled in terms of time period, resources used during each period of time, and products manufactured with resources. From this information, a use value for each product per resource and an availability value for each resource can be determined. The additional input data parameters are the gain and distribution for each product. A demand and probability function is used to represent the expected demand for each product. Given these values and the demand function, a value equation formulated for each resource. Each value equation is expressed as a lagrangian equation that has a lagrang multiplier that represents the resource value. The equations are then solved for the Lagrange multiplier to obtain a value for each resource.

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 illustrates how the time periods of products and resources of an intensive goods manufacturer are modeled for the purposes of the invention.

Figure 2 illustrates an example of the time periods, products and resources of an intensive manufacturer of goods.

Figure 3 illustrates additional problem data for the example of Figure 2.

Figure 4 illustrates how the MAV equations are established and resolved.

Figure 5 illustrates the MAV equations for the example of Figure 2.

Figure 6 illustrates the solutions of the MAV equations of Figure 5.

Figure 7 illustrates the solution to the example problem in terms of endowments and expected gains.

Figures 8A and 8B illustrate the functions Q and Q "respectively.

Figure 9 illustrates how a calculation machine MAV can be integrated into a larger product planning programming system.

DETAILED DESCRIPTION OF THE INVENTION The following detailed description is directed to a computer-implemented tool that implements a method of putting value management (VM) pricing. The tool is specially designed to be used by intensive goods manufacturers.

The patent application of the United States of America series number 09 / 195,332, entitled "Computer Applied Product Appraisal Tool", presented on November 18, 1998, describes the value administration in general, and the concept of MAVs ( minimum acceptable values).

It also describes how the minimum acceptable values can be calculated differently depending on the type of company and its primary manufacturing restrictions. For example, certain manufacturers, such as those who manufacture high-tech computing equipment, may be primarily constrained by the availability and price of the components. Other manufacturers may be constrained primarily by varying driving times. Still other manufacturers are manufacturing manufacturers to order, who are set for inventories and low driving times. The patent of the United States of America series number 09 / 195,332 describes the minimum acceptable value calculations for each of these types of manufacturers, and is incorporated herein by reference.

General principles The administration of value applied to intensive goods manufacturers requires special considerations. Intensive manufacturing of goods is characterized by limited capacity. The demand can be served before those that are desired. The demand is not in any particular order for different price ranges, unless a prize is charged for shorter driving times or for a discount that is given for longer driving times.

As an example of an intensive manufacturing d goods is the manufacture of steel. A primary constraint is the capacity of the machine, as opposed to the availability of raw materials. If demand is high, production is most likely limited by inadequate machine capacity rather than other constraints.

Value management for the intensive manufacture of goods is based on the following principle: based on an uncertain future demand for certain products, the expected prices for those products, and the available capacity for resources during the periods required to supply the demand when If a claim is made, a value for each resource during those periods can be calculated. The calculations result in threshold prices mentioned as minimum acceptable values (MAVs) for a given demand period.

For an intensive manufacturer of values, the minimum acceptable value of a resource monotonically decreases with the increase in availability. By increasing the use of a machine, each unit consumed is more expensive (presuming limited availability).

Figure 1 illustrates the time intervals (tO, ti) ... (tn-1, tn) for which the minimum acceptable values are to be computed. These intervals may represent seasons in which the demands and / or prices for the products are significantly different from those at other time intervals, even when the products may be the same. For simplification of the example given here, it is presumed that the time intervals are the same for all products, but in practice these may not be the case.

Three resources are designated as Rl, R2 and R3. Two products are designated as Pl and P2. The product Pl uses Rl during the interval (tOl, til), R2 during (tOl, tl2), and R3 during (tl3, t23). A resource can be used again in another time interval for the same product. Different products or the same product in different demand time periods can compete for the same resource by using one resource during the same time interval. It is this composition for the same resource that determines the value of the resource in each period of time.

Relevant to the manufacturing scenario in Figure 1 is that the actual demand on resources for the products takes place at earlier times than the demand period. The demand can be much earlier for some resources depending on the forward time. Many manufacturing companies use computer-implemented models and programmers to map product demand over a period of time to the appropriate time period of use of a resource.

As indicated above, solving the valuation problem involves determining the value of each recurs (machine). It should be noted that the physical article demanded in a period of time is considered as a separate product of the same article demanded in another period of time. The prices for these same items in different periods of time may also be different. Similarly, a resource in a period of time is different from the same resource in another period of time.

Let there be Np products denoted by P ,, P2 ... PNp. The indexes 1 to Np can be used to denote the products and the context for this clear. Similarly, there are resources NR, Rj, R2 ... RNR, and indexes 1 to NR can be used to denote them. The following parameters are used to formulate the problem: Sp¡ = product set using the resource i = resource set used by the product j L j = use of resource i by product j allocation for product j T, = time available (capacity) of the resource Sj = price charged (or income) per unit of product j Cj = cost per unit of product j Yj = yield for product j f, = probability of demand function density by product j Pr (x = a) = probability that the random variable x is greater than or equal to "a" Vj = value (profit) per unit of the sale of the product j 20 V, = total expected value of the sale of product j V = total expected value of the sale of all the products An example of a suitable allocation is a discrete assignment, as determined by the calculations available to promise.

The problem of resource valuation can be mathematically declared as: so that : Vi = vj J xfj () d + a jVj J f¡ (?) Dx (2) Equation (1) states that the total time (capacity) assumed by all products using a resource equals the time available (capacity) over that resource. It may be more appropriate to have a lack of equality (=), but false products can always be defended with a cer value to take the loosening so that equality and generally as a high of equality. However, negative loosening should not be allowed. If an overservice is used, the capacity used will be the overbooked capacity The lagrangian of the problem stated above is: where? 's are the lagrange multipliers, one for each equality constraint in equation (1).

The necessary conditions (of calculation) are: 5V * /? Aj where equation (5) is a redeclaration of the equality constraints in equation (1). There are the equations (NR + NP) and the same number of variables. Therefore, these can be solved. Due to non-linearity, a single solution may not exist. It is interesting to note that the problem is convex. Both the objective function and the restrictions are convex.

From equation (2): oo? Vj Idaj = v¡ajfJ (aj) da¡ - vJaJf (a) + v / (*) & = Vj Pr (demand for product j = a ,.}. (6) In the derivation of equation (6), the result has been used repeatedly from the calculation that helps integrals d differentiation whose limits can also be (along with and integrating) a function of the variable with respect to which the differentiation is brought to cape.

The demand for products can be modeled as one of several known distributions, such as normal poisson. Whatever the model, it is presumed that the term probability in equation (6) is defined as a function by G (a) (it is nothing but the complement of the cumulative distribution function (CDF).

The inverse function is defined by G "1 (b) = a, so that b = G (a). Therefore (4) and (6), it follows that: Substituting (7) in (5) results in; The following expression represents the total prorated value of product j on resource i: Using the prorated values, equation (8 can be rewritten as: (10) where VlT, / UJ, is the prorated value (po unit of capacity) of product j over resource i.

Even if the product has a high profit per product unit, and this has a high use of a resource then its prorated value (per unit resource capacity) over the resource is reduced. Therefore, the system of equations can be solved iteratively by assuming some initial? 'S, apportioning the value of each product used by a resource and solving for the new one? until all the? 's converge. The? 'S correspond to the minimum acceptable value (MAV) for a resource.

Example of Minimum Acceptable Value Calculations Figures 2-7 illustrate an example of calculating minimum acceptable resource values of an asset-intensive manufacturer. As indicated above, each resource is valued in terms of its use. In the example of this description, the minimum acceptable values are calculated as $ / unit-capacity with the unit of capacity being one hour. The minimum acceptable values can then be used to endow and value the products made from the resources.

Figure 2 illustrates a simple model of an asset-intensive manufacturer. The products are defined in terms of machine use, that is, what machines, how long and in what order. There are two resources (machine) Rl and R2. There are four periods of time. Because the resources are considered different and in different time periods, R1 is represented as R1-R4 and R2 is represented as R5-R8.

The products are different if they are demanded in different periods of time. Therefore, for example, P13 is the product demanded in the period of time 3. The product by resource use is in terms of resources and times. Therefore, Pl uses Rl for 2 hours, R5 for 3 hours and R2 for 5 hours. It can be noted that P3 is the same as Pl in terms of resource use, in the sense that R6 is the same as R5 but in a different period of time, and R3 is the same as R2 but in a different time period. Two resources are not used: R4 R7. The resource availability specifies how much time it leaves on each resource.

Figure 3 illustrates the additional problem data for the example in Figure 2. The cost of manufacturing each product, its price and its performance are specified. Typically, the numbers used for these parameters are hypothetical - assuming that the products will be made with certain costs, prices and yields that is the value of resources used to make the products ?. The value (profit) is calculated from cost, price and yield.

'The probable demand can be modeled in several ways. An example of a demand distribution is a truncated normal distribution, expressed mathematically as: Nt (μ, s: x) = N (μ, s: x) / Q (-μ / s), x = O where N (μ, s: x) is a normal distribution with a mean deviation, μ, and standard, s. Q (x) represents a normal distribution function.

N (m, s: x) = l / &e - ((? - ») / 0) '/ 2, xeR A probability density function can be expressed for each product: f, (X) = Nt (15.5) f5 (X) = Nt (15.6) f2 (X) = Nt (10.3) f6 (X) = Nt (10.3) f3 (X) = Nt (12.8) f7 (X) = Nt (20.8) f. (X) = Nt (15,3) fg (X) = Nt (22,8) f9 (x) = Nt (12, 4) fio (X) = Nt (17,7) The Lagrangian equations formulated above can now be specialized for the demand. Following the example mentioned above, the equations are specialized for truncated normal distributions. G (a) is a probability function, as described above in relation to equation (7).

= N (μ, s: x) / Q (-μ / s 00 00 G (a) = j Nr (μ, o: x) dx = 1 / y / 2pQ (-μ / &s)) j N (μ, c: xd Q ((a - μ) / a) / Q (-μ / s) Using equation (7) we obtain "G (aj) Qffaj-Hj / ajJfQf-Hj / OjH? ? yUJ) / v J kS " (aj-μj / aj-Qr'iQf-Vj / CjK??; U /) / vy] kSR to. = μj + OjQ'lQí-Vj OjX S? / u; > v / l kSR (12) From the equation (12) ? ? jVl? VjQHaj-μjJ Qf-μjtaj) SR (13) j An income function is used to calculate the expected income. The rotation given to, the normal demand truncated with the deviation s mean μ, standard, and the value v, which is the income R? . From the equation (6) established above, where x is the demand for a product: dR / dx (a) = Pr { Nt (μ, s) = a} = vQ ((a - μ) / s) / Q (-μ / s) where, the limits of integration are from a to 8. It follows that: R (a) = IQ ((x - μ) / s / Q (-μ / s) dx where, the integration limits are from 0 to "a". After some manipulation: R = vs [h (a - μ) / s) - h (-μ / s)] / Q (-μ / s) where, h (x) = xQ (x) - 1 / (2pe "xx * Mx / 2) \ 'A Each equation is now written in terms of a variable using pro-rated product prices. The prorated value of a product i over a resource j can be expressed as: VJ = V¡? J / S?, U, j where Vj is the value of. a unit of product i and where j is the minimum acceptable value for the resource jth. The sum is of about 1 e SjR, where Sj is the resource game used for the product j.

Figure 4 illustrates a method for placing the Lagrangian minimum acceptance value equations. Each of the equations contains a variable, such as the one corresponding to the resource. The system of equations is solved iteratively by assuming the initials (step 41), apportioning the value of each product used by a resource (step 42), and solving for a new one? for each equation until all the? 's converge (steps 43 - 45).

Figure 5 illustrates the MAV equations, one for each resource. As noted above, in relation to Figure 2, even though there are eight resources, there are two that are not used. Therefore, there are six MAV equations. Each is a sum of "terms of use of resource" (U is a factor) minus an availability term (T is a factor).

Figure 6 illustrates the solution of the equations MAV of Figure 5. An MAV has been calculated for each of the six resources.

Figure 7 illustrates the allocations and expected income for the ten products made with the resources. A determination of whether the allocation is optimal can now be made.

Additional remarks As indicated above, the minimum acceptable value calculations provide a minimum acceptable value for each resource (machine) for each time horizon. The inputs for the minimum acceptable value calculations include the prices of the products made through the resource, the probable demand for the products, the use of the resource for several products and the availability of the resource. The output can also include a total expected revenue for the manufacturing capacity available for the horizon time and for the product.

The relationship between the minimum acceptable value and the assignment can be expressed mathematically in a specific form. For a normal distribution, an equation d assignment can be expressed as: Qj?] UJ) / vJ) _ ?, = μ + s? -1 (Q (-μj, / s,) l) = > aj = μj +? jQrl. { Q { -μj / < rj)) = > aj = μj + sJ (-μj / sJ) = * aJ = μJ ~ μJ = ° If the value of a product is equal to or less than the sum (y,) given above, it has a zero assignment. In other words, the sum is analogous to the cost of opportunity consumed and? is the minimum acceptable value for a resource.

Figures 8A and 8B illustrate examples of the functions Q and Q "1, respectively, such as those of the equations of Figure 5.

Minimum Acceptable Value Integration in Larger Planning Systems Figure 9 illustrates how a resource valuation engineering 91 can be integrated into a larger planning system 90. In an engine 91 it performs the minimum acceptable value calculations described above. This has access to the database of minimum acceptable value 92, which stores the model data and other problem data described above. A computer implemented a price 94 tool or a demand predictor tool 95 and can be used to provide the price and demand data, respectively.

Once known, the minimum acceptable values can be used with other control variables, such as the ATP variables (available for promises) of the tool available for promise 96. The allocation data of the valuation engine 91 can be used to determine that so much of the product is available to promise it.

A scheduler 93 may be used in conjunction with the minimum acceptance value calculation engine 91, to receive and process the resource values. In this manner, the programmer 93 can be used to provide a scheduled manufacturing based on a deterministic demand model.

The output of the minimum acceptable value calculation engine 91 can also be used to negotiate contract prices and due dates for incoming orders, to prioritize orders and to add capacity using the minimum acceptable long term values. . Resource values, expected income and allocations can be provided to a master planning engine 97, which generates the optimal manufacturing scenarios.

Such data as price and allocation can flow both in and out of the valuation engine 91. For each of the resource values calculated by the engine 91 it can be provided for the price assignment tool 94. In this way the assumptions can be formulated, evaluated and applied.

Other additions Although the present invention has been described in detail, it should be understood that various changes, substitutions and alterations may be made thereto without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (31)

R E I V I N D I C A C I O N S

1. A method implemented by computer to value resources used in the manufacture of one or more products, comprises the steps of: modeling the manufacturing process in terms of at least a period of time, of at least one resource and of at least one product; provide a use value for each product per resource; provide an availability value for each resource; provide a gain value for each product; provide an allocation value for each product; generate a demand function for said products; generate a value equation for each resource based on the use value, said availability value, said profit value, said allocation value and said income function; Y Solve the value equations using a lagrangian process, each equation being expressed with a multiplier that represents a resource value.

2. The method as claimed in clause 1, characterized in that said demand function is based on a truncated normal distribution.

3. The method as claimed in clause 1, characterized in that said profit values are apportioned for each product on each resource.

4. The method as claimed in clause 1, further characterized in that it comprises the steps of generating an income function for each product based on said allocation value, said profit value, and said demand function, and of solving said function of income for each expected income of said product.

5. The method as claimed in clause 1, characterized in that said step of solving is carried out by formulating a set of lagrange equations of said value equations, each lagrange equation has a multiplier as the only unknown variable.

6. The method as claimed in clause 5, characterized in that each lagrangian equation is a sum of terms, each term associated with a use value, minus said availability value.

7. The method as claimed in clause 1, characterized in that the resolution step was carried out iteratively by setting the initial values of the lagrange multiplier and converging to new values of the lagrange multiplier.

8. The method as claimed in clause 1, characterized in that said resolving step is carried out using a binary tree.

9. The method as claimed in clause 1, further characterized in that it comprises the step of providing said resource values to a programming engine.

10. A computer-implemented system for valuing resources used in the manufacture of one or more products, comprising: memory that stores a manufacturing process model in terms of at least a period of time, at least one resource, and at least a product; a memory that stores the following values: a use value for each product per resource, an availability value for each resource, a profit value for each product, an allocation value for each product; a process to generate a demand function for said products; a valuation engine to generate a value equation for each resource, based on said use value, said availability value, said profit value, said allocation value and said income function; and to solve the value equations using a lagrangian process, each equation being expressed with a multiplier that represents a resource value.

11. The system as claimed in clause 10, characterized in that it also comprises a demand prediction tool for providing the demand data to said valuation engine.

12. The system as claimed in clause 10, further characterized in that it comprises a price assignment tool for providing product price data to said valuation engine.

13. The system as claimed in clause 10, characterized in that said valuation engine also calculates the expected revenue, the use of the allocation values, the gain values and the demand function.

14. The system as claimed in clause 10, further characterized in that it comprises a programming engine to generate manufacturing programs based on the resource values.

15. The system as claimed in clause 9, further characterized in that it comprises a master planning engine for determining the product prices based on the resource values.

16. A method implemented by computer to value a resource used in the manufacture of one or more products, comprising: model the manufacturing process in terms of at least a period of time, the resource, and one or more products that are to be manufactured using the resource; generate an equation of value for the resource based on the information related to the use of the resource by the products, the information related to the availability of the resource, the information related to the profits associated with the products, the information related to the endowment of the products , and one or more demand functions associated with the products, the value equation includes a multiplier that represents a value of the resource; Y Solve the value equation to determine the value of the resource.

17. The method as claimed in clause 16, characterized in that the value equation is solved using a lagrangian process.

18. The method as claimed in clause 17, characterized in that the solution comprises iteratively setting an initial value of a lagrange multiplier and converging to a new value of a lagrange multiplier.

19. The method as claimed in clause 16, characterized in that the demand function is based on a truncated normal distribution.

20. The method as claimed in clause 16, characterized in that the information relating to the gains associated with the products comprises the profit values that are apportioned for each product for the resource.

21. The method as claimed in clause 16, further characterized in that it comprises: generating an income function for each product based on the envelope information, the gain information, and the demand function; Y solve the income function for an expected income of the product.

22. The method as claimed in clause 16, characterized in that the solution is carried out using a binary tree.

23. The method as claimed in clause 16, further characterized in that it comprises providing the resource value to a programming engine.

24. A system implemented by computer to value resources used in the manufacture of one or more products, comprising: an operable process to generate a demand function for one or more products; Y an operable valuation engine for: generate an equation of value for the resource based on the information relative to the use of the resource by the products, the information related to the availability of the resource, the gains related to the information associated with the products, the information related to the endowment of the products , and one or more demand functions associated with the products, the value equation includes a multiplier that represents a value of the resource; Y Solve the value equation to determine the value of the resource.

25. The system as claimed in clause 24, characterized in that the valuation engine solves the value equation using a lagrangian process.

26. The system as claimed in clause 24, further characterized in that it comprises a demand prediction tool for providing demand data to the valuation engine.

27. The system as claimed in clause 24, characterized in that it comprises a tool to determine the price to provide the product price data to the valuation engine.

28. The system as claimed in clause 24, characterized in that the valuation engine also calculates the expected revenue, using the envelope information, the gain information and the demand function.

29. The system as claimed in clause 24, further characterized in that it comprises a programming engine to generate manufacturing programs based on the values of the resources.

30. The system as claimed in clause 24, further characterized in that it comprises a master planning engine for determining the product prices based on the values of the resources.

31. A resource valuation software embedded in a computer readable medium and operable to: generate an equation of value for a resource based on information related to the use of the resource in the manufacture of one or more products, the information related to the availability of the resource, the information related to the profits associated with the products, the information relative to the endowment of the products, and one or more demand functions associated with the products, the value equation includes a multiplier that represents a value of the resource; Y Solve the value equation to determine the value of the resource. E U M E N A method to value resources of an intensive manufacturer of goods. The calculations provide a minimum acceptable value for each resource (machine) for each time horizon. The inputs to the calculations include the prices of products made through the resource, the probable demand for the products, the use of the resource for various products, and the availability of the resource. A series of equations, an equation associated with each resource is formulated and solved using the lagrangian methods, with the lagrangian multiplier representing the resource value.