GB2248704A  Production order determining method  Google Patents
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 GB2248704A GB2248704A GB9117410A GB9117410A GB2248704A GB 2248704 A GB2248704 A GB 2248704A GB 9117410 A GB9117410 A GB 9117410A GB 9117410 A GB9117410 A GB 9117410A GB 2248704 A GB2248704 A GB 2248704A
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 G—PHYSICS
 G06—COMPUTING; CALCULATING; COUNTING
 G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
 G06Q10/00—Administration; Management
 G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models

 Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSSSECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSSREFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
 Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
 Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
 Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
 Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
 Y02P90/04—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS] characterised by the assembly processes
Abstract
Description
PRODUCTION ORDER DETERMINING METHOD The present invention relates to a production order determining method for determining a production order of a plurality of production types of products in a production line where a production information is given in the form of specified periods of time of production with respect to production types of products.
Japanese Patent Publication SHO 63265791 discloses a method for determining a production order of different models or production types of engines, in an engine assembly line, which are to be supplied to different car assembly lines. In the prior art method, the production order of the different production types of engines at the engine assembly line is determined based on input requirements from the respective car assembly lines, which are given in the form of numbers of each production type of engine to be supplied per successive fixed production periods (e.g., per shift or per day) to each of the car assembly lines. More particularly, a production period portion P. for an engine of each production type i is calculated from the input requirements.After a fixed value of P. has been calculated for an engine of each production type i, a production expectation value <RTI>Xii</RTI> for each production order j of each engine type i is calculated by the following equations: <RTI> Xi1 = Pi ~~~~~~~~~ ( 1 ) Xij = Xij1 + Pi  Dij1 (2)</RTI> where, <RTI>Dij</RTI> is a variable having the value 1 in a case where an engine of production type i is produced at production order j and taking the value 0 in other cases. In the prior art, a production order j is determined so as to produce an engine of the production type i having the highest value of Xij.
For example, in an engine assembly line which receives requests from an A car assembly line to supply two atype engines a day, from a B car assembly factory to supply one btype engine a day, and a C car assembly factory to supply one ctype engine, a production order of the a, b, and ctype engines is determined in the following way.
At first, a production period portion <RTI>PA</RTI> for the atype engine is calculated by dividing the required number of atype engines per production period (2 per day) by the sum of all a, b, and ctype engines required per production period: 2 / (2 <RTI>+</RTI> 1 + 1). The resulting value of PA is 0.5.
Similarly, a production rate <RTI>PB</RTI> of the btype engine is 0.25, and a production rate PC of the ctype engine is 0.25.
Therefore, from equation (1), Xa1 is 0.5, <RTI>Xbl</RTI> is 0.25, and <RTI>Xcl is 0.25. Because the highest of these values is X it </RTI> is determined that the first type of engine to be produced each day is the atype engine.
Then, <RTI>Xa2,</RTI> Xb2, and Xc2 are calculated in the following manner: Xa2 <RTI>Xal</RTI> + 0.5  1 = 0 <RTI>Xb2</RTI> <RTI>Xb1</RTI> + 0.25  0 = 0.5 <RTI> Xc2 X Xci + 0.25  0 = 0.5</RTI> Because the highest of these values is Xb2 or <RTI>Xc2,</RTI> either <RTI>or or X , for example, Xb2, is chosen and the second c2 c2</RTI> engine to be produced each day is the btype engine.
Similarly, Xa3 = Xa2 + 0.5  0 = 0.5 Xb3 = Xb2 + 0.25  1 = 0.25 Xc3 <RTI>=</RTI> Xc2 + 0.25  0 = 0.75 Because the highest of these values is <RTI>Xc3,</RTI> the third engine to be produced each day is the ctype engine.
Similarly, Xa4 <RTI>= Xa3</RTI> + 0.5  0 = 1 Xb4 = Xb3 + 0.25  0 = 0 Xc4 = Xc3 + 0.25  1 = 0 Because the highest of these values is <RTI>Xa4,</RTI> the fourth engine to be produced each day is another atype engine.
Therefore, the engine production order for producing four engines a day is determined to be an order of a, b, c, and a.
With respect to the second day, <RTI> Xa5 = Xa4 + 0.5  1 = 0.5</RTI> <RTI>X</RTI> = Xb4 + 0.25  0 = 0.25 Xc5 = Xc4 + 0.25  0 = 0.25 Because these values are equal to the values of <RTI>Xa1,</RTI> <RTI>Xb1,</RTI> and <RTI>Xcl,</RTI> respectively, the same order of engine production as that of the first day should be executed in the second day.
The reason why the abovedescribed determination of a production order is possible is that P. can be calculated for the first day, and the same P. can be used for the second day, the third day, ... , and the nth day without varying the P. value. More particularly, the above described determination of a production order is possible or effective only for a production line where input information is provided in the form of a number of products to be produced per fixed production period (e.g., each day) with respect to each production type, because the production period portion P. used in equations (1) and (2) is fixed.
However, in a production line, such as a complete knock down line (a packing line where parts are packed in a domestic country and are shipped to foreign countries), where input information for a production order schedule is given in the form of usually different specified periods of time of production (in the case of a packing line, specified periods of time of packing, that is, information about how many of what type of boxes should be packed within what periods of time), the prior art production order determining method cannot be used, because fixed values of <RTI>Pi</RTI> cannot be used in the above equations (1) and (2).
An object of the invention is to provide a method for determining a production order of production of different product types which is effective even in a production line where production inputs are given in the form of specified production time periods with respect to production of each production type, with the production time periods having different possible values, both for products of the same type and for products of different types.
The abovedescribed object is attained by a method for determining a production order in accordance with the present invention. The method comprises steps of providing production information in the form of a specified production time period and a number of products to be produced in the specified period with respect to production of each of a plurality of product types; calculating a production expectation value for each specified production time period, the production expectation value being defined as a number of products to be produced a day with respect to each of the product types, by dividing the number of products to be produced in each specified production time period by the number of days included in each specified production time period; summing the production expectation values for all specified production time periods for all the production types with respect to each day to calculate a total number of products to be produced with respect to each day; then integerprocessing the total number of products to be produced with respect to each day; providing a table having a number of columns for each day equal to the integerprocessed number of products to be produced that day; and then average processing to determine what product type should be inserted in each of the columns, and thereby to determine a production order for all the product types.
In the abovedescribed method, since a production expectation value for each day (which corresponds to the number of products to be produced for each day) is calculated by summing the production expectation values for all specified production time periods for all the product types with respect to each day and then integerprocessing the total number of products to be produced with respect to each day, it is possible to determine a production order.
In this instance, the averaging process is necessary because the production period portions <RTI>Pij</RTI> change with respect to the production days, while the production period portions P.
in the prior art method have constant values because they are not functions of the production order j.
The above and other objects, features, and advantages of the present invention will become more apparent and will be more readily appreciated from the following detailed description of the preferred embodiment of the invention taken in conjunction with the accompanying drawings, in which: FIG. 1 is a diagram of a system for executing a production order determining method in accordance with one embodiment of the present invention; FIG. 2 is a table illustrating input information fed to a production schedule input file of the system of FIG. 1; FIG. 3 is a table illustrating production expectation values for respective specified periods of time of production calculated from the input information shown in the table of FIG. 2;; FIG. 4 is a table illustrating summed numbers of products to be produced each day calculated from the production expectation values shown in the table of FIG. 3 and the integerprocessed values of the summed numbers of products to be produced each day; and FIG. 5 is a table illustrating the results of average processing based on the data shown in the tables of FIGS. 3 and 4 and a production order determined by the averaging process.
A preferred embodiment of the present invention will now be explained with reference to the drawings.
As illustrated in FIG. 1, a production order determing method of the present invention includes step 11 of feeding production information into a production schedule input file, step 12 of calculating a production expectation value for each specified production time period, step 13 of summing the production expectation values and integerprocessing the summedup values, step 14 of applying an averaging process to determine a production order, and step 15 storing the determined production order in a production order output file.
More particularly, the input information is fed to the production schedule input file 11 from outside, either manually by an operator or via a communication network, and is stored in the production schedule input file 11.
As illustrated in FIG. 2, the input information is given in the form of a specified production time period, for example, a specified packing time period in a case where the production line is a packing line. Hereinafter, such packing line will be taken for an example; therefore, "production" may be replaced by "packing". FIG. 2 illustrates an example where three boxes of products of an A type (e.g., products to be shipped to a country A) are to be packed. The first box is to be packed in two days (the first and second days of a fiveday period), the second box in four days (the first through fourth days of the same period), and the third box in two days (the fourth and fifth days of the period).Also, one box of products of a B product type (products to be shipped to a country B) is to be packed in five days (the first through fifth days of the same fiveday period), and two boxes of products of a C product type (products to be shipped to a country C) are to be packed, the first Ctype box in four days (the first through fourth days of the same period), and the second Ctype box also in four days (the second through fifth days of the period).
At step 12 of FIG. 1, a production (packing) expectation value for each specified production (packing) time period is calculated. The production expectation value is defined as a number of product portions to be produced (packed) aday with respect to each of a plurality of product (packing) types. This value is calculated by dividing the number of products to be produced (packed) in each specified production (packing) time period by the number of days in each specified production (packing) time period.
For example, as illustrated in FIG. 3, the requirement of one Atype box to be produced (packed) in the first and second days is divided into 0.5 box for the first day and 0.5 box for the second day; so that the production (packing) expectation value on the first day for this Atype box is 0.5, and the production (packing) expectation value for first box on the second day is 0.5. The requirement of a second Atype box for the first through fourth days is divided into 0.25 box for the first day, 0.25 box for the second day, 0.25 box for the third day, and 0.25 box for the fourth day; so that the production (packing) expectation value on each day of the first through fourth days for this second Atype box is 0.25.The requirement of a third Atype box for the fourth and fifth days is divided into 0.5 box for the fourth day and 0.5 box for the fifth day; so that the production (packing) expectation value for this third Atype box on each of the fourth and fifth days is 0.5. Similarly, the same calculation is applied to the single box of products of the B type; so that the production (packing) expectation value for the one Btype box on each of the first through fifth days is 0.2. Finally, the same calculation is applied to the two boxes of products of the C type; so that the production (packing) expectation value for the first Ctype box on each of the first through fourth days is 0.25, and the production (packing) expectation value for the second Ctype box on each of the second through fifth days is 0.25.
Then, at step 13 of FIG. 1, and as illustrated in FIG. 4, the production expectation values for specified production (packing) time periods are summed for all the product types with respect to each day to obtain a total number of product portions to be produced (partial boxes to be packed) on each day of the fiveday period. For example, in the first column, all of the production (packing) expectation values 0.5, 0.25, 0.2, and 0.25 are summed to obtain the total number 1.2 of product portions to be produced in the first day. Similarly, the totaled numbers of 1.45 for the second day, 0.95 for the third day, 1.45 for the fourth day, and 0.95 for the fifth day are obtained.
Then, at step 13 of FIG. 1, and as illustrated in FIG. 4, integerprocessing is applied to each total number of product portions to be produced on each day. The integerprocessing is executed by selecting the closest integer to the sum of the totaled number for the instant day and a remainder from the previous day. For example, because the total number 1.2 of the first day is closer to integer 1 than to integer 2, integer 1 is selected for the first day; that is, one box is produced (packed) on the first day. A difference of +0.2 between the total number 1.2 and the selected integer 1 is carried over as a remainder for the next day. With respect to the second day, the total number 1.45 of the instant day (the second day) and the remainder +0.2 from the previous day (the first day) are summed to obtain a number 1.65.Because the number 1.65 is closer to integer 2 than to integer 1, the integer 2 is selected for the second day; that is, two boxes are produced (packed) on the second day. The difference of 0.35 between the total number 1.65 and the selected integer 2 is carried over to the next day. With respect to the third day, the total of 0.95 for the third day and the remainder 0.35 from the second day are summed to obtain a number 0.6. Because the number 0.6 is closest to integer 1, the integer 1 is selected for the third day; so that one box is produced (packed) on the third day. The difference of 0.4 (= 0.6 1) is carried over to the next day. With respect to the fourth day, the total of 1.45 for the fourth day and the remainder 0.4 from the third day are summed to obtain a number 1.05.Because the number 1.05 is closest to integer 1, the integer 1 is selected for the fourth day; so that one box is produced for the fourth day. The difference of 0.05 (= 1.05  1) is carried over to the next day. Similarly, with respect to the fifth day, the total number 0.95 for the fifth day and the remainder +0.05 from the fourth day are summed to obtain a number of 1.00, so that integer 1 is selected for the fifth day and one box is produced on the fifth day. In this way, the integerprocessed numbers of products to be produced (packed) in the first, second, third, fourth, and fifth days are determined to be 1, 2, 1, 1, and 1, respectively.
Then, at step 14 of FIG. 1, and as illustrated in FIG. 5, an average <RTI>process' (a</RTI> process for making production intervals even) is applied to the integerprocessed numbers of products so that a production order of a plurality of product types is determined.
More particularly, FIG. 5 is a table having as many vacant columns as all of the integerprocessed number of products to be produced (packed) in first through fifth days, with each column representing a production order.
Thus, one column is allotted to each of the first day, the third day, the fourth day, and the fifth day, and two columns are allotted to the second day. The six columns are given production order numbers one through six. The first column number means the order of production (packing) of products to be produced (packed) in the first day.
Similarly, the second column number and the third column number mean the order of production of products to be produced in the second day. The fourth column number means the order of production of products to be produced in the third day, the fifth column number means the order of production of products to be produced in the fourth day, and the sixth column number means the order of production of products to be produced in the fifth day. The production (packing) expectation values of the A, B, and Cproduct (packing) types are inserted below the six column numbers.
Thus, in the example, the numbers 0.75, <RTI>0.2,</RTI> and 0.25 below column number 1 are the respective production (packing) expectation values of the A, B, and Ctypes of boxes for the first day.
These production (packing) expectation values are obtained using the following equations: <RTI>Xi1</RTI> = Pi1 <RTI></RTI> (3) <RTI>Xij = Xij1 + Pij  Dij1  (4)</RTI> where, <RTI>Xij</RTI> is a production (packing) expectation value for production of product (packing) type i and production (packing) order j, Pij is the sum of all production (packing) expectation values for each specified production time period with respect to production (packing) of product type i in a day on which product (packing) type i is to be produced in production (packing) order j, and <RTI>Dij</RTI> is a variable that is equal to the total number of all product portions to be produced on the day that contains the production (packing) order j and the production (packing) of type i products, and that is equal to 0 when there is no production (packing) of itype product.
For example, in accordance with equation (3) and as illustrated in FIG. 5, the production (packing) expectation values XA1, <RTI>XB1,</RTI> and <RTI>Xcl</RTI> in the case where the production (packing) order j is 1 are equal to <RTI>PA1,</RTI> <RTI>PB1,</RTI> and <RTI>PCl.</RTI> In this instance, PA1 is calculated to be 0.75, which is a summation of the production (packing) expectation values 0.5 and 0.25 (see FIG. 3) of the first day with respect to the production (packing) of the Atype of product.Similarly, PB1 is calculated to be 0.2, which is the production expectation value 0.2 of the first day with respect to production (packing) of the Btype of product, and <RTI>PCl</RTI> is calculated to be 0.25, which is the production expectation value 0.25 of the first day with respect to the Ctype of product. Then, since the largest of these production (packing) expectation values is 0.75, it is determined that the Atype of product should be produced (packed) in the order j=l.
Similarly, with respect to the order j=2, <RTI>A2</RTI> = XAl + 0.75  1.2 = 0.3 XB2 = XB1 + 0.2  0 = 0.4 XC2 = XCl + 0.5  0 = 0.75 Since the largest value is 0.75, it is determined that the Ctype of product should be produced (packed) in the order J=2. In this instance, the 0.75 in the equation for <RTI>XA2</RTI> is a summation of the production expectation values 0.5 and 0.25 (See FIG. 3) of the Atype of product with respect to the second day, and the 1.2 in the equation for XA2 is the total number of products to be produced on the first day (see FIG. 4) and has to be subtracted in the equation for XA2 because Atype product was produced (packed) in the first day. Similarly, in the equation for <RTI>XB2,</RTI> the 0.2 is the production expectation value of the Btype of product with respect to the second day (see FIG. 3), and the 0 means that <RTI>Dij</RTI> is zero. In the equation for <RTI>Xc2,</RTI> the 0.5 is a summation of the 0.25 and 0.25 of production expectation values of the Cproduct type (see FIG. 3), and the 0 means that <RTI>D.</RTI> is zero.
Similarly, with respect to the order j=3, XA3 = XA2 + 0.75  0 = 1.05 XB3 = XB2 + 0.2  0 = 0.6 XC3 = XC2 + 0.5  1.45 = 0.2 Since the largest of these expectation values is <RTI>XA3,</RTI> the Atype of product is produced (packed) in the order j=3.
Similarly, with respect to the order j=4, XA4 = XA3 + 0.25  1.45 = <RTI>0.15</RTI> XB4 = XB3 + 0.2  0 = 0.8 XC4 XC3 + 0.5  0 = 0.3 Since the largest of these expectation values is <RTI>XB4,</RTI> the Bproduct type is produced (packed) in the order j=4.
Similarly, with respect to the order j=5, <RTI>XAS</RTI> XA4 + 0.75  0 = 0.6 XBS <RTI>= XB4</RTI> + 0.2  0.95 = 0.05 <RTI>XCS</RTI> XC4 + 0.5  0 = 0.8 Since the largest of these expectation values is <RTI>XC5,</RTI> the Ctype of product is produced (packed) in the order j=5.
Finally, with respect to the order j=6, <RTI>A6</RTI> = <RTI>XAS</RTI> + 0.5  0 = 1.1 XB6 = XB5 + 0.2  0 = 0.25 XC6 = XC5 + 0.25  1.45 = 0.4 Since the largest of these expectation values is XA6, the Aproduct type is produced (packed) in the order j=6.
In this way, a production (packing) order is determined so that the Atype product is produced (packed) in the first day (j = 1), the Ctype product and then the Atype product are produced in the second day (j = 2, 3), the Btype product is produced in the third day (j = 4), the Ctype product is produced in the fourth day (j = 5), and the Atype product is produced in the fifth day (j = 6).
The abovedescribed process for making production intervals as even as possible is called an averaging process.
In this averaging process, it is possible to <RTI>calculate Pij because it is determined as a summation of </RTI> production expectation values of the day that contains the order j. In this instance, <RTI>Pij</RTI> varies in accordance with the order j, while P. of the described prior art method is constant (i.e., is independent of the order j).
In accordance with the present invention, the following advantages are obtained.
First, a production order determining method which can satisfy both (a) production of products within a production time limit and (b) average processing (making production intervals as even as possible) is obtained, though the two production conditions are not compatible in the prior art.
Second, due to the abovedescribed production condition (a), a required stock of products at a given production (packing) line is greatly decreased and a shutdown of a subsequent assembly line due to lack of supply of products is effectively prevented.
Third, due to the abovedescribed production condition (b), a required stock of parts at a previous line is greatly decreased and a shutdown of the instant line due to lack of supply of parts is effectively prevented.
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Cited By (2)
Publication number  Priority date  Publication date  Assignee  Title 

GB2289963A (en) *  19940525  19951206  Matsushita Electric Ind Co Ltd  Production plan generating program. 
US5841659A (en) *  19940526  19981124  Matsushita Electric Industrial Co., Ltd.  Production plan generating method and apparatus 
Families Citing this family (1)
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JP6339935B2 (en) *  20141229  20180606  株式会社 日立産業制御ソリューションズ  Work order planning system, work order planning methods and work order schedule program 
Citations (1)
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US4802094A (en) *  19850710  19890131  Hitachi, Ltd.  Process monitoring apparatus for process management in production and assembly lines 
Patent Citations (1)
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US4802094A (en) *  19850710  19890131  Hitachi, Ltd.  Process monitoring apparatus for process management in production and assembly lines 
Cited By (3)
Publication number  Priority date  Publication date  Assignee  Title 

GB2289963A (en) *  19940525  19951206  Matsushita Electric Ind Co Ltd  Production plan generating program. 
GB2289963B (en) *  19940525  19990512  Matsushita Electric Ind Co Ltd  Production line controller operated in accordance with generated production plans 
US5841659A (en) *  19940526  19981124  Matsushita Electric Industrial Co., Ltd.  Production plan generating method and apparatus 
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