Source: https://patents.google.com/patent/US20070219656A1/en
Timestamp: 2019-12-11 00:55:37
Document Index: 618412162

Matched Legal Cases: ['art 900', 'art 900', 'art 900', 'art 900', 'art 900', 'art 900', 'art 900']

US20070219656A1 - Modeling manufacturing processes to include defined markers - Google Patents
Modeling manufacturing processes to include defined markers Download PDF
US20070219656A1
US20070219656A1 US11/375,633 US37563306A US2007219656A1 US 20070219656 A1 US20070219656 A1 US 20070219656A1 US 37563306 A US37563306 A US 37563306A US 2007219656 A1 US2007219656 A1 US 2007219656A1
US11/375,633
US7412295B2 (en
Mario Rothenburg
2006-03-14 Application filed by SAP SE filed Critical SAP SE
2006-03-14 Priority to US11/375,633 priority Critical patent/US7412295B2/en
2006-04-19 Assigned to SAP AG reassignment SAP AG ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ROTHENBURG, MARIO
2007-09-20 Publication of US20070219656A1 publication Critical patent/US20070219656A1/en
2008-08-12 Publication of US7412295B2 publication Critical patent/US7412295B2/en
238000000034 methods Methods 0 claims description title 124
239000003550 marker Substances 0 abstract claims description 89
238000004519 manufacturing process Methods 0 abstract claims description 79
238000005365 production Methods 0 claims description 114
230000000694 effects Effects 0 description 52
238000000227 grinding Methods 0 description 11
This invention relates to modeling manufacturing processes for manufacturing and execution computing systems.
This document describes a computer-implemented method of defining and using marker points within a modeled manufacturing process routing that includes multiple sequenced operations. The method includes receiving user input that defines one or more marker points within the modeled manufacturing process routing and between sequential ones of the operations. The one or more marker points each define a user-defined point within a manufacturing process and include one of multiple defined types that each define a different use to be made by the marker point. The method also includes detecting if any marker points of a specified one of the defined types have been defined in the manufacturing process routing while operating a computing process that uses the modeled manufacturing process routing and that is configured to detect and use marker points of the specified one of the defined types. If a marker point having the specified one of the defined types is detected, a predefined computing function is executed that uses the detected marker point.
The manufacturing planning and execution computing system 102 has a supply planning component 108 and a manufacturing execution component 118. The supply planning component 108, which also may be referred to as a manufacturing planning component, is a tool that a user may employ to plan how the manufacturing environment 104 can be operated to achieve a supply of end products that meets a specified demand. The planning component 108 receives, as shown in FIG. 1A, demand information 105, which may, for example, be in the form of a customer order that the manufacturing entity 100 supply a specified number of product within a specified timeframe, or the demand information be internally generated by the supplier, or manufacturer based on a forecast. The planning component 108 produces planning production orders 116, which may be used in the generation of an execution order 120, which is used by the execution component 118 in executing the manufacturing process to meet the demand input. A user station 113 is shown in FIG. 1A to illustrate that a planning user may interact with the manufacturing computing system 102 to perform supply planning functions, described in more detail later.
The manufacturing execution component 118 is the “execution” portion of the manufacturing planning and execution system 102. The execution component 118 operates to control and track the execution of the manufacturing process carried out by the manufacturing environment 104 in accordance with execution orders 120. As such, FIG. 1A shows that there is an interface 119 between the manufacturing execution module 118 and the manufacturing environment 104, which interface 119 serves to integrate. the computing system 102 with the manufacturing environment 104, or shop floor. For example, the interface 119 allows the computing system 102 to provide instructions that control when and where materials and resources will be used in the manufacturing environment 104, as well as the ability of the computing system 102 to receive input from the manufacturing environment 104, for example, confirming that a certain manufacturing operation has been completed.
The manufacturing planning and execution computing system 102 includes predefined manufacturing process master data, including routing definitions, shown in FIG. 1A as stored in repository 110. In particular, there are two levels of defined master data stored in master data repository, execution-level (or “execution view”) master data 112 and planning-level (or “planning view” master data 114. The execution-level manufacturing process master data are, in a typical case, defined by a process designer or engineer. The execution-level master data typically define each of the operations of the manufacturing process in detail, and how each of the operations relates to other operations. The execution-level manufacturing master data and are generally defined up front, before the manufacturing process is ever run, and are generally not changed very frequently. In some cases, however, the master data may be changed more frequently, and even daily.
Generally, many manufacturing operations for execution are defined in the execution-level master data to make up the overall manufacturing process. The planning component 108, instead of using the planning view master data that includes all of the defined execution operations, use the planning-level master data during the planning process. For example, a manufacturing process of twenty defined execution operations may be aggregated into three planning, or “rough-cut,” operations of, for example, six execution operations for a first planning operation, eight execution operations for a second planning operation, and six execution operations for a third and final planning operation. By using this aggregation functionality to create separate planning-level master data to use in the planning process, constraints arising from any of the execution operations may be accounted for in the planning process (or ignored if the details are not needed), but the level of granularity will be appropriate.
In addition, the manufacturing computing system 102 may also allow a user to select the level of granularity desired in the planning process by selecting which of the execution operations will be aggregated into a planning, or rough-cut, operation. The user may do this by putting “markers” in the overall process flow of execution operations, and the markers will serve, in addition to the beginning and end points of the overall process flow, as beginning and end points of the execution operations that will be aggregated into a single planning, or rough-cut, operation. For example, for a routing that has 20 execution operations, setting a marker between execution operations six and seven and another marker between execution operations fourteen and fifteen will yield three planning operations of, respectively, six, eight, and six execution operations. In one implementation, a user may set the markers, and hence define the groupings of execution operations, once, and then the planning master data 114 will be created based on these groupings and stored in the master data repository 110. Then, the planning master data 114 created using those groupings will be used in the planning process for a particular demand input 105, and will have the level of granularity defined by the groupings. If more granularity is desired, the markers may be redefined to have more planning operations, and new planning master data may be created with the newly defined groupings. In addition, several groupings may be defined and master data generated for using in planning, and in addition, it may be possible in some implementations to change the grouping definitions during the planning process.
In addition, a user may select to filter selected materials and resources out of the planning process, leaving flexibility for the executors to assign these materials and resources during execution. This may be done for materials and resources that are known to not be “critical path” components and need not be considered during planning. In a further example, a user may select the accuracy for the capacity planning so that the constraints for the capacity supply and capacity requirements in planning may be relaxed based on the selection. This will be described in more detail later in the context of performing rough-cut planning.
Referring now to FIG. 1C, another depiction of the system 102 shown in FIGS. 1A and 1B is shown to illustrate another point. In particular, FIG. 1C illustrates that the aggregation engine 106 is used both in generating planning-level master data 114 from execution-level master data 112 (that is, a master data layer), and in generating planning production orders 116 (that is, at a transactional data layer), for example from execution production orders 120 if an execution production order 126 has already been generated (which is not the case in many scenarios, and so instead the planning production order 116 would simply be generated as described previously).
Referring to FIG. 3, there is another conceptual depiction of a routing 300 that illustrates the difference between the detailed execution-level operations of the execution view of the routing, and the less granular planning-level operations of the planning view of the routing. In addition, FIG. 3 shows the use of markers, and specifically two different types of markers, that define different groupings. One set of markers are “planning operation” (PO) markers, and these define the groupings for the planning-level, or rough-cut operations used for planning purposes. The other set of markers are “production step” (PStep) markers, and these define groupings that are used in functions that are unrelated to planning, such as in execution to define the points in time where confirmations are made as to when a confirmation if completion is made at an intermediate point in the execution of an execution production order.
Next, the method proceeds to step 454 where a planning process on the lot is performed. The details of step 454 are shown in FIG. 4E. For present purposes as shown in FIG. 4D, the planning process 454 includes a step 456 of generating a planning order for the lot using the rough-cut planning model. Then at step 458 the planning order is scheduled. At some point after the planning process is complete, the scheduled planning order is released for execution in step 460. After the scheduled planning order is released, an execution production order is generated at step 462. This may be done, in one implementation, by using the execution-level master data, and performing scheduling of execution operations and resource and material requirements that are consistent with the scheduling contained in the planning order. In addition, an inverse of the rough-cut process model may be used in the process of translating the scheduling parameters of the planning order to the scheduling for the execution order.
A RCCR, as is the case with RCCR1 528, generally may have a time duration associated with it that is shorter than a time period imposed by the rough-cut operation and any offsets. This provides some level of flexibility in scheduling the resources. In some cases, the constraints imposed by the offsets may be tightened or relaxed, dependent on how little time or how much extra time a planner may want to provide to ensure that execution is performed within time frames that are planned.n planning and execution.
The rough-cut operation 502. includes RCCRs 604, 606 and 608. The RCCRs 604, 606, 608 may only include the capacity requirement of planning-relevant operations. For example, the RCCR 604 may be modeled in a single requirement that may only include the planning relevant requirements in a setup requirement, a produce requirement, and a teardown requirement of the operation 512. In the depicted embodiment, the RCCRs 604, 606 and 608 are not related to each other. Therefore, there is no time relationship that links the RCCRs 604, 606, 608 together to establish an exact sequence of operations. A rough sequential relationship may be established by the aid of offsets.
Referring now to FIG. 9, an exemplary Gantt chart 900 may be generated to provide visual presentation of the production process schedule on planning boards. Many different types of such planning boards may be used, and it will be appreciated that such boards may be used to present rough-cut operations as described in this document. A user may visualize the timing of occurrences for material and resource requirements in the Gantt chart 900. In the depicted embodiment, the Gantt chart 900 shows the timing of the material or resource requirement within the rough-cut determined timing. The Gantt chart 900 includes Rows 902 to represent the materials needed to fulfill the production order. The Gantt chart 900 also includes a product column 903 and a description column 904. The product column 903 includes reference numbers of the material in the production order and the description column 904 includes brief descriptions of the material. For example, the row 906 may be for “insulation,” which has a product identification of R-0006. The Gantt chart 900 also includes date columns 908 along the top. A scheduled time for each of the included material requirements (indicated by the rows 902) may be represented by an activity bar, which has a left end that marks the expected start date of the planning operation and a right end that marks the expected completion date of the operation where the material is needed. In some embodiments, the header activity duration 602 (FIG. 6) may directly correspond to the length of the activity bars. As an example, material C-0001 may be used in an operation with a header activity duration of four days. In the Gantt chart 900, an activity bar 912 may indicate that the “control and regulation” material may be expected to be needed during a period from March 4th to March 8th.
The rough-cut operation area 108 includes a table 1020. The table 1020 may include some or all of the rough-cut operations in the production order 1000. In this example, the table 1020 includes two rough-cut operations, an assembling operation 1022 and a packing operation 1024. The table 1020 includes information, such as resources required, scheduled start and end time, operation duration, buffer time, and lot size of the rough-cut operations 1022, 1024. These information may be obtained from the rough-cut operation planning. For example, the buffer time may be obtained from the user during the generation procedure of the production order 1000. The materials area 1010 may include a table 1026 that shows information on materials used in the production order 1000. In this example, the table 1026 includes information such as require date, quantity required, and procurement of each of the required materials. The material requirements may be computed separately from the computation of the lead time requirement.
As an example, the process engineer 1130 may configure a routing scenario for producing bowling balls, where the planning activities may include a forklift that brings stock to a drilling machine, a grinding process that shapes the balls, and a drilling process that drills holes in the balls. Additionally, the scenario may include subsequent production activities such as packaging the finished product in a box filled with protective material. In this example, the process engineer 1130 may be fully aware of each of these steps, and may include in the master data describing the overall production of bowling balls, the maximum amount of stock the forklift can bring to the grinder in one trip, the amount of time it takes to grind the balls, the efficiency of the drilling process, and the resources it may take to package the product. This example illustrates four “procedures” for describing the overall routing process of producing bowling balls: transport of stock, grinding, drilling, and packaging.
Markers may also be defined in the master data. Markers are master data database objects that may be used, in one example, in such a way that they may be incorporated into a routing scheme so as to “group” similar procedures within a defined routing sequence into a singular representation of the group activities. Continuing with the above example, markers (M) may be defined between the operations of transport of stock and grinding, and between drilling and packaging (transportation of stock→M→grinding→drilling→M→packaging); in this case, the grinding and drilling production processes may be represented as one production process whose aggregated attributes combine to form a single production activity. In reality, producing bowling balls may involve hundreds of planning and production steps, and grouping similar steps together using marker master data may allow increased efficiency in many regards of a manufacturing environment.
It is also possible that no markers will be set in the master data for the modeled manufacturing process. In such a case, the entire manufacturing process routing may be defined as a production step and also as a planning operation. As discussed previously, markers are points where planning activities, production step borders and operations meet each other. As an illustration of different types of markers, FIG. 3, discussed previously, shows, for example, a “Mark2” 318 defined within the modeled manufacturing process. The “Mark2” 318 is a marker object that has a defined role, or type, of a production step and also for planning. In other words, in an implementation where the marker is a database object with roles, the marker object “Mark2” has multiple defined roles. As is also shown in FIG. 3, production step markers may define an execution user interface view that may be displayed during execution of the manufacturing process, and planning markers may define a planning user interface view that may be displayed during a planning function.
FIGS. 13-15 show a graphical representation for each of the individual steps of the method shown in FIG. 12. First, FIG. 13 shows the definition of important markers for a manufacturing process being modeled in master data (step 1220 of FIG. 12). This figure depicts a “rough to fine” approach to modeling where planning markers are defined for the manufacturing process before the operations and routing information between the defined markers are entered. FIG. 13 represents an exemplary manufacturing environment process 1300, which overall depicts the synthesis of product from beginning to end, which starts with mechanical production, then assembly, and finally packing (as shown on the users production structure 1310 shown in FIG. 13). FIG. 13 shows the definition of two planning markers, called “planning operation,” or “PO,” markers 1334 and 1336. A start marker 1332 at the beginning of the modeled process and an end marker 1338 may be defined by default.
The definition of the two planning markers 1334 and 1336 as shown in FIG. 13 defines three planning operations that will appear on a planning view 1340 during a run-time planning process during which the master data defining the manufacturing process gets used. The planning operations are, respectively from a beginning of the manufacturing process to an end of the manufacturing process, a mechanical production planning operation 1342, an assembly planning operation 1344, and a packing planning operation 1346. It deserves noting that no intermediate “production step,” or “PStep,” markers have been defined yet for the master data, and as such, at this time and with no further PStep markers being defined, there will only be one production step presented on an execution user interface view 1320 during a run-time execution process.
Next, FIG. 14 shows a definition of execution objects (step 1230 of FIG. 14) in yet the next step of a “rough to fine” modeling approach that began with FIG. 13. Here, execution operations are defined between the previously defined markers shown along line 1410. For example, between start marker 1332 and M1 marker 1334, three execution operations and their routings have been defined. The three operations are shown as operations 01, 02 and 03 in depiction 1420. In the blow-out depiction 1430 and 1440 of the operations shown at 1420, it is shown that operation 01 is a drilling operation 1402, operation 02 is a grinding operation 1404, and operation 03 is an assembly operation 1406. Under the operations shown at 1430, there are defined activities for the defined operations. The drilling operation 1402 has two defined activities, for example, activity A 1408 and activity B 1412. Given that multiple execution operations are defined between planning markers, a planning user interface view that makes use of the planning markers will have a level of granularity corresponding with the number of planning markers that are set, and there may be an aggregation capacity planning information for the operations between two planning markers.
FIG. 16 is a schematic diagram of a generic computer system 1600. The system 1600 can be used for the operations described in association with any of the computer-implemented methods described previously. The system 1600 includes a processor 1610, a memory 1620, a storage device 1630, and an input/output device 1640. Each of the components 1610, 1620, 1630, and 1640 are interconnected using a system bus 1650. The processor 1610 is capable of processing instructions for execution within the system 1600. In one implementation, the processor 1610 is a single-threaded processor. In another implementation, the processor 1610 is a multi-threaded processor. The processor 1610 is capable of processing instructions stored in the memory 1620 or on the storage device 1630 to display graphical information for a user interface on the input/output device 1640.
receiving user input that defines one or more marker points within the modeled manufacturing process routing and between sequential ones of the operations, the one or more marker points each defining a user-defined point within a manufacturing process and including one of multiple defined types that each define a different use to be made by the marker point; and
detecting if any marker points of a specified one of the defined types have been defined in the manufacturing process routing while operating a computing process that uses the modeled manufacturing process routing and that is configured to detect and use marker points of the specified one of the defined types, and if a marker point having the specified one of the defined types is detected, executing a predefined computing function that uses the detected marker point.
2. The computer-implemented method of claim 1, wherein one of the multiple defined types is a planning type.
3. The computer-implemented method of claim 2, wherein the computing process detects marker points have the planning type, and uses the detected marker points as boundary points for defined groups of the multiple sequenced operations.
4. The computer-implemented method of claim 3, wherein the computing process aggregates the multiple sequenced operations included in a defined group into a single operation to be used in a rough-cut manufacturing planning process.
5. The computer-implemented method of claim 4, further comprising performing a manufacturing planning process that performs a manufacturing planning function using the aggregated operations.
6. The computer-implemented method of claim 1, wherein one of the multiple defined types is an execution type for use in connection with executing the manufacturing process.
7. The computer-implemented method of claim 6, wherein the computing process detects marker points that have the execution type, and uses the detected marker points as boundary points for defined groups of the multiple sequenced operations.
8. The computer-implemented method of claim 7, wherein the computing process aggregates the multiple sequenced operations included in a defined group into a single operation that corresponds with a defined organization that is responsible for executing the manufacturing operations of the defined group.
9. The computer-implemented method of claim 7, wherein the computing process performs a reporting function when execution of a manufacturing order reaches a milestone corresponding to a point in the manufacturing process corresponding to the location of the marker point.
10. The computer-implemented method of claim 9, wherein the reporting function comprises creating an electronic report of actual production quantities at the point in the manufacturing process that corresponds with the detected marking point.
11. A computer program product tangibly embodied in an information carrier and comprising instructions that when executed by a processor perform a method of defining and using marker points within a modeled manufacturing process routing that comprises multiple sequenced operations, the method comprising:
12. The computer program product of claim 11, wherein one of the multiple defined types is a planning type.
13. The computer program product of claim 12, wherein the computing process detects marker points have the planning type, and uses the detected marker points as boundary points for defined groups of the multiple sequenced operations.
14. The computer program product of claim 13, wherein the computing process aggregates the multiple sequenced operations included in a defined group into a single operation to be used in a rough-cut manufacturing planning process.
15. The computer program product of claim 14, further comprising performing a manufacturing planning process that performs a manufacturing planning function using the aggregated operations.
16. The computer program product of claim 11, wherein one of the multiple defined types is an execution type for use in connection with executing the manufacturing process.
17. The computer program product of claim 16, wherein the computing process detects marker points that have the execution type, and uses the detected marker points as boundary points for defined groups of the multiple sequenced operations.
18. The computer program product of claim 17, wherein the computing process aggregates the multiple sequenced operations included in a defined group into a single operation that corresponds with a defined organization that is responsible for executing the manufacturing operations of the defined group.
19. The computer program product of claim 17, wherein the computing process performs a reporting function during execution of a manufacturing order reaches a milestone corresponding to a point in the manufacturing process corresponding to the location of the marker point.
20. The computer-implemented method of claim 19, wherein the reporting function comprises creating an electronic report of actual production quantities at the point in the manufacturing process that corresponds with the detected marking point.
US11/375,633 2006-03-14 2006-03-14 Modeling manufacturing processes to include defined markers Active 2026-09-26 US7412295B2 (en)
US11/375,633 US7412295B2 (en) 2006-03-14 2006-03-14 Modeling manufacturing processes to include defined markers
US12/188,905 US8175733B2 (en) 2006-03-14 2008-08-08 Modeling manufacturing processes to include defined markers
US12/188,905 Continuation US8175733B2 (en) 2006-03-14 2008-08-08 Modeling manufacturing processes to include defined markers
US20070219656A1 true US20070219656A1 (en) 2007-09-20
US7412295B2 US7412295B2 (en) 2008-08-12
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US11/375,633 Active 2026-09-26 US7412295B2 (en) 2006-03-14 2006-03-14 Modeling manufacturing processes to include defined markers
US12/188,905 Active 2026-11-16 US8175733B2 (en) 2006-03-14 2008-08-08 Modeling manufacturing processes to include defined markers
US (2) US7412295B2 (en)
US20160140470A1 (en) * 2014-11-17 2016-05-19 Caterpillar Inc. Systems and methods for determining lead-time offset values
AU7594101A (en) * 2000-08-07 2002-02-18 Honda America Mfg Supplier synchronization system and method
US7451011B2 (en) * 2004-08-27 2008-11-11 Tokyo Electron Limited Process control using physical modules and virtual modules
US7809457B2 (en) * 2007-10-30 2010-10-05 Gm Global Technology Operations, Inc. Framework for automatic generation of sequence of operations
2006-03-14 US US11/375,633 patent/US7412295B2/en active Active
2008-08-08 US US12/188,905 patent/US8175733B2/en active Active
US20090099676A1 (en) 2009-04-16
US7412295B2 (en) 2008-08-12
US8175733B2 (en) 2012-05-08
JP4587246B2 (en) 2010-11-24 Computerized supply chain planning methodology
JP2007048291A (en) 2007-02-22 Automated batch manufacturing
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