Patent Application
20150142500
1. Field of the Invention
This invention relates to decision support systems for inter-organizational inventory transshipments in complex build-to-order manufacturing environments.
2. Background of the Invention
Recent trends to globalize sourcing, production, and sales along with other environmental and labor-based factors force companies to provide multiple manufacturing and/or service sites located at different geographical locations around the globe. Companies may assign orders to these different sites in a way that fulfills their goals. Order assignment to these sites may be based on different factors, including shipping costs for customers, labor costs, raw material availability, capacity constraints, customer requirements, and the like. In some cases, orders may also be reassigned to different sites or parts may be transported between sites to avoid supply chain risks.
Companies may establish supply sources based on the demand in different geographical areas that purchase/utilize their products. Companies may also attempt to establish raw material suppliers based on where a product is assembled. In many cases, raw material suppliers may be single sourced and/or not geographically co-located. There is also uncertainty with demand forecasting as top level demand may be accurately forecasted but the demand at each geographical level may have a degree of variance, thereby forcing plants to rebalance purchased supply in order to meet overall demand.
Inter-organizational transshipping and order offloading are important decisions made by companies that have multi-site manufacturing systems. These decisions enable a company to be more adaptive and responsive to customer demand. The costs of inter-organizational transportation, however, may be very high and some customer orders may be at risk due to inventory shortage and/or capacity unavailability.
Given the inherent complexities associated with managing numerous operational variables when fulfilling orders, it is essential to make accurate and timely decisions. This is complicated by discrete finite time constraints for revenue recognition. Decisions on where to optimally source an order from multiple global plants may be based on inventory supply position (clear-to-build), plant capacity, time zones, tax advantages, and distribution costs. Decisions may be optimized (maximized or minimized) on any of these dimensions. However, it is imperative that decision makers be aware of impacts to secondary and tertiary variables to evaluate how and where to source orders.
In view of the foregoing, what are needed are apparatus and method to enable enhanced decision-making when fulfilling orders. Such apparatus and methods will ideally enable plant and order managers to quantitatively assess factors in a supply chain to determine how to manage risk, lower costs, as well as provide an improved customer experience and satisfaction.
The invention has been developed in response to the present state of the art and, in particular, in response to the problems and needs in the art that have not yet been fully solved by currently available apparatus and methods. Accordingly, apparatus and methods have been developed to enhance decision-making when shipping parts between sites within an organization. The features and advantages of the invention will become more fully apparent from the following description and appended claims, or may be learned by practice of the invention as set forth hereinafter.
Consistent with the foregoing, a method for enabling enhanced decision-making when shipping parts between sites within an organization is disclosed herein. In one embodiment, such a method includes receiving a plurality of orders to deliver parts from a first site to a second site. The method determines a shipping option for shipping the parts from the first site to the second site and, for each of the orders, a transportation risk associated with the shipping option. The transportation risk varies in accordance with a probability that the shipping option will result in a delay, and an amount of revenue that will be affected as a result of the delay. The transportation risk for each of the orders is displayed in a matrix. The position of each transportation risk value within the matrix is based on the probability that the shipping option will result in a delay, and the amount of revenue that will be affected as a result of the delay. The method further enables a user to modify the shipping option to adjust the position of each transportation risk within the matrix.
A corresponding apparatus and computer program product are also disclosed and claimed herein.
In order that the advantages of the invention will be readily understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered limiting of its scope, the invention will be described and explained with additional specificity and detail through use of the accompanying drawings, in which:
It will be readily understood that the components of the present invention, as generally described and illustrated in the Figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following more detailed description of the embodiments of the invention, as represented in the Figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of certain examples of presently contemplated embodiments in accordance with the invention. The presently described embodiments will be best understood by reference to the drawings, wherein like parts are designated by like numerals throughout.
As will be appreciated by one skilled in the art, the present invention may be embodied as an apparatus, system, method, or computer program product. Furthermore, the present invention may take the form of a hardware embodiment, a software embodiment (including firmware, resident software, microcode, etc.) configured to operate hardware, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer-usable storage medium embodied in any tangible medium of expression having computer-usable program code stored therein.
Any combination of one or more computer-usable or computer-readable storage medium(s) may be utilized to store the computer program product. The computer-usable or computer-readable storage medium may be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable storage medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a portable compact disc read-only memory (CDROM), an optical storage device, or a magnetic storage device. In the context of this document, a computer-usable or computer-readable storage medium may be any medium that can contain, store, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object-oriented programming language such as Java, Smalltalk, C++, or the like, conventional procedural programming languages such as the “C” programming language, scripting languages such as JavaScript, or similar programming languages. Computer program code for implementing the invention may also be written in a low-level programming language such as assembly language.
Embodiments of the invention may be described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus, systems, and computer program products. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, may be implemented by computer program instructions or code. These computer program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means which implement the function/act specified in the flowchart and/or block diagram block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
Referring to
As shown, the computing system 100 includes at least one processor 102 and may include more than one processor 102. The processor 102 may be operably connected to a memory 104. The memory 104 may include one or more non-volatile storage devices such as hard drives 104a, solid state drives 104a, CD-ROM drives 104a, DVD-ROM drives 104a, tape drives 104a, or the like. The memory 104 may also include non-volatile memory such as a read-only memory 104b (e.g., ROM, EPROM, EEPROM, and/or Flash ROM) or volatile memory such as a random access memory 104c (RAM or operational memory). A bus 106, or plurality of buses 106, may interconnect the processor 102, memory devices 104, and other devices to enable data and/or instructions to pass therebetween.
To enable communication with external systems or devices, the computing system 100 may include one or more ports 108. Such ports 108 may be embodied as wired ports 108 (e.g., USB ports, serial ports, Firewire ports, SCSI ports, parallel ports, etc.) or wireless ports 108 (e.g., Bluetooth, IrDA, etc.). The ports 108 may enable communication with one or more input devices 110 (e.g., keyboards, mice, touchscreens, cameras, microphones, scanners, storage devices, etc.) and output devices 112 (e.g., displays, monitors, speakers, printers, storage devices, etc.). The ports 108 may also enable communication with other computing systems 100.
In certain embodiments, the computing system 100 includes a network adapter 114 to connect the computing system 100 to a network 116, such as a LAN, WAN, or the Internet. Such a network 116 may enable the computing system 100 to connect to one or more servers 118, workstations 120, personal computers 120, mobile computing devices, or other devices. The network 116 may also enable the computing system 100 to connect to another network by way of a router 122 or other device 122. Such a router 122 may allow the computing system 100 to communicate with servers, workstations, personal computers, or other devices located on different networks.
Referring to
In certain embodiments, a customer order may include one or more of the following: order quantity, order type, order configuration, order destination, and ship date. In certain cases, a manufacturing site may be unable to fulfill a customer order due to raw material shortage, capacity limitation, time limitations, and/or customer requirements. When a raw material shortage arises, a site 200 may obtain parts from a sister site 200 or an external supplier. When other issues (i.e., capacity, time, customer requirements, etc.) arise, a site 200 may offload an order to a sister site 200 that has the ability to fulfill the order, as shown by the dashed line extending between block 200a and block 202b.
Referring to
In complex build-to-order manufacturing environments, orders may be treated differently since some orders may be more important than others. Thus, the framework 300 may prioritize 316 orders before assigning 318 parts. An order with higher priority may be allocated parts 318 first in cases where there are a limited number of parts compared to orders. A cheapest shipping option for parts may then be selected 320 by comparing available time for shipping to transportation time for the shipping option. Shipping costs may be calculated 322 based on the chosen shipping option.
The cost to ship parts between sites may then be compared 324 to a cost to ship an order directly to a customer from another site 200. If the cost to ship parts between sites 200 is greater than the cost to ship an order directly to a customer from another site 200, a decision may be made to offload 336 the order, change the due date 328, or ship the parts 342, depending on the outcome of decision steps 326, 330. A transportation delay risk may also be taken 332 into consideration. If the delay risk is high, a higher priority shipping option may be selected 334 to reduce the delay risk. If extra time is available at step 338, the shipment may also be postponed 340 to reduce shipping costs.
Referring to
Referring again to
Available Time=[(Ship Date−Today's Date(Excluding Weekends))±Time Difference]−[Cycle Time]
where the Time Difference refers to a time difference between geographical locations of manufacturing sites (also considering daylight savings time) and the Cycle Time is calculated based on order type and order configuration.
A shipping option for parts may be determined at step 320 by comparing the Available Time to a Transportation Time of the shipping option according to the following equation:
C>Available Time≧Transportation Time(Excluding Weekends)
where Available Time and Transportation Time are in days and C represents a transportation time for the next shipping option.
An example of shipping options for two different countries are shown in Table 1 below (in the table, SLX, SL1, SL2, and SL3 are different shipping options, with SLX being the fastest, most expensive shipping option, and SL3 being the slowest, least expensive shipping option):
To determine when parts should be shipped between sites 200, the following equation may be used:
When-to-Ship=[Available Time]−[Transportation Time(Excluding Weekends)]+Today's Date
where [Available Time]−[Transportation Time(Excluding Weekends)]>1. Shipping restrictions may need to be taken into consideration when selecting a shipping option. Some shipping options such as express options that use passenger flights have restrictions with regard to chemicals and shipment height.
Referring to
The framework 500 then assigns 514 cargo to the shipping box and calculates 516 the actual and dimensional weight of the cargo. If, at step 518, the dimensional weight is less than the actual weight, the framework 500 considers 522 the actual weight when calculating 524 total shipping costs. If, however, the dimensional weight is greater than the actual weight, the framework 500 considers 520 the dimensional weight when calculating 524 total shipping costs. Once the total shipping cost is calculated 524, the framework 500 may break down 526 the total shipping cost to determine 526 a cost per order.
Referring to
In certain embodiments, inputs 602 to the interplant transshipment tool 600 are divided into two types: (1) one-time inputs 602a which may include, for example, shipping option costs and times, new parts data, and cycle times for different product types; and (2) shipment request inputs 602b such as order numbers and requested part numbers and quantities.
Outputs 604 from the interplant transshipment tool 600 may include the following: order priority, shipping options, shipping costs, available time, part ship dates, and comments.
Referring to
If a shipment includes multiple orders, the transportation risk for each order may be simultaneously displayed in the matrix 900, as shown in
In certain embodiments, the matrix may be color coded (or shaded as shown in
The block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer-usable storage media according to various embodiments of the present invention. In this regard, each block in the block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions discussed in association with a block may occur in a different order than discussed. For example, two functions occurring in succession may, in fact, be implemented in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams, and combinations of blocks in the block diagrams, may be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
