Patent Publication Number: US-9851713-B2

Title: Operation-time calculation device and method for calculating operation time

Description:
TECHNICAL FIELD 
     The present invention relates to techniques regarding an operation time calculation device and a method for calculating operation time using operation result information from a manufacturing floor. 
     BACKGROUND ART 
     In order to implement production planning and manufacturing cost management with precision, it is necessary to accurately estimate input data composed of the operation time information about each manufacturing process of each product. The methods for estimating operation time include: (1) a method of dividing the operation into elementary operations (to move, to turn a screw, etc.), before aggregating predefined elementary operation times based on product specifications to calculate the operation time; and (2) a method of calculating the time actually required to perform the operation (actual operation time) from operation result information, and categorizing the results of the calculation by product specification and by manufacturing condition. The method (1) above has the problem of requiring a large amount of man-hours in measuring the elementary operation times and dividing the operation into the elementary operations, as well as the problem of the aggregated elementary operation times resulting in a divergence from the actual operation time. Thus the method (2) above is generally employed. 
     In the past, an example of calculating operation time using operation result information such as the method (2) above has been disclosed by PTL 1, the disclosure being the method of calculating individual operation times based on the operation start date and time and on the operation end date and time from operation result information, the results of the calculation being categorized by product specification and subjected to statistical processing, thereby calculating the operation time per product specification. PTL 2 discloses a method of calculating individual operation times in a manner similar to that of PTL 1, the disclosed method categorizing the calculated individual operation times by event (equipment failure, change of job count within a lot, etc.) that occurred on the manufacturing floor while the operation was being implemented, whereby the operation time is calculated from the currently occurring event. 
     CITATION LIST 
     Patent Literature 
     
         
         PTL 1: Japanese Patent Application Laid-Open No. 2006-127012 
         PTL 2: Japanese Patent Application Laid-Open No. 2009-9380 
       
    
     SUMMARY OF INVENTION 
     Technical Problem 
     The existing methods for calculating operation time such as those disclosed by PTL 1 and 2 presuppose that individual operation times can each be calculated from the operation start date and time and operation end date and time. For example, the operation time is calculated by subtracting the operation start date and time from the operation end date and time. However, on the actual manufacturing floor, particularly on a manufacturing floor where operation result information is recorded manually, there may well be cases in which losses occur in operation result information due to omissions and delays so that the operation start dates and times and operation end dates and times may not be obtained of the entire operation. There may even be cases in which only operation end dates and times are recorded, with no operation start dates and times recorded in the first place. In such cases, individual operation times cannot be calculated through the process of subtracting the operation start date and time from the operation end date and time. The existing methods for calculating operation time are thus not practicable. 
     Solution to Problem 
     In solving the above problems and according to the present invention, there is provided an operation time calculation device using operation result information from a manufacturing floor, the operation time calculation device including a storage unit, an input unit, a control unit, and a display unit. The storage unit stores operation result information including at least operation process information, start date and time information, and end date and time information about each operation implemented; work time information including at least an assigned process, a date, and a work time per piece of equipment and per worker; and operation time information including at least a product type, an operation process, an initially set operation time, and an operation time conversion coefficient. The input unit accepts input, from a user, of parameters regarding at least an aggregation target process, an aggregation start date and time, an aggregation end date and time, and an aggregation unit period. The control unit performs a process in which an aggregation period is set based on the input aggregation start date and time, aggregation end date and time, and aggregation unit period; a process in which a total work time of the aggregation target process in each aggregation period is calculated by a search through the work time information, and a total operation time of the aggregation target process in each aggregation period is calculated by a search through the operation result information and the operation time information and by converting the corresponding operation time using the operation time conversion coefficient; a process in which an error is calculated between the total work time and the total operation time in each aggregation period; and a process in which the operation time conversion coefficient is changed so as to minimize the error. The display unit displays the operation time conversion coefficient, a graph comparing the total work time with the total operation time in each aggregation period before and after the operation time conversion, and the errors involved, all being obtained in the processes performed by the control unit. 
     In solving the above problems and also according to the present invention, there is provided an operation time calculation method using operation result information from a manufacturing floor, the operation time calculation method including causing a computer equipped with a storage unit, an input unit, a control unit, and a display unit to function so that the storage unit stores operation result information including at least operation process information, start date and time information, and end date and time information about each operation implemented; work time information including at least an assigned process, a date, and a work time per piece of equipment and per worker; and operation time information including at least a product type, an operation process, an initially set operation time, and an operation time conversion coefficient; that the input unit accepts input, from a user, of parameters regarding at least an aggregation target process, an aggregation start date and time, an aggregation end date and time, and an aggregation unit period; that the control unit performs a process in which an aggregation period is set based on the input aggregation start date and time, aggregation end date and time, and aggregation unit period; a process in which a total work time of the aggregation target process in each aggregation period is calculated by a search through the work time information, and a total operation time of the aggregation target process in each aggregation period is calculated by a search through the operation result information and the operation time information and by converting the corresponding operation time using the operation time conversion coefficient; a process in which an error is calculated between the total work time and the total operation time in each aggregation period; and a process in which the operation time conversion coefficient is changed so as to minimize the error; and that the display unit displays the operation time conversion coefficient, a graph comparing the total work time with the total operation time in each aggregation period before and after the operation time conversion, and the errors involved, all being obtained in the processes performed by the control unit. 
     Advantageous Effects of Invention 
     According to the present invention, the user of this device can calculate operation times even if operation start dates and times or operation end dates and times are missing from work result information. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a functional block diagram of an operation time calculation device. 
         FIG. 2  is a schematic view of the operation time calculation device. 
         FIG. 3  is a schematic view of a typical operation process on a manufacturing floor. 
         FIG. 4  is a schematic view of an operation result information table. 
         FIG. 5  is a schematic view of a work time information table. 
         FIG. 6  is a schematic view of an operation time information table. 
         FIG. 7  is a schematic view of a parameter information table. 
         FIG. 8  is a schematic view of an aggregation result information table. 
         FIG. 9  is a schematic view of an average error information table. 
         FIG. 10  is a schematic view of a computer. 
         FIG. 11  is a flowchart showing an operation time calculation process. 
         FIG. 12  is a flowchart showing an aggregation period setting process. 
         FIG. 13  is a flowchart showing a per-period work time calculation process. 
         FIG. 14  is a flowchart showing an operation implementation period estimation process. 
         FIG. 15  is a flowchart showing an operation implementation period start date and time estimation process. 
         FIG. 16  is a flowchart showing an operation implementation period end date and time estimation process. 
         FIG. 17  is a flowchart showing a per-period operation time calculation process. 
         FIG. 18  is a flowchart showing an error estimation and coefficient calculation process. 
         FIG. 19  is a schematic view showing the operation time calculation process. 
         FIG. 20  is a schematic view showing the aggregation period setting process. 
         FIG. 21  is a schematic view showing the operation implementation period estimation process. 
         FIG. 22  is another schematic view showing the operation implementation period estimation process. 
         FIG. 23  is another schematic view showing the operation implementation period estimation process. 
         FIG. 24  is a schematic view showing a per-period operation time aggregation process. 
         FIG. 25  is a schematic view showing a typical input screen. 
         FIG. 26  is a schematic view showing a typical output screen. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     The present invention is aimed at calculating operation times using operation result information from the manufacturing floor.  FIG. 3  shows an example of the operation process flow on a manufacturing floor. What follows is a detailed explanation of the present invention that uses this example as the target. 
     As shown in  FIG. 3 , the target operation process flow on the manufacturing floor includes such operation processes as a sizing lathe process and an outside diameter lathe process, and a plurality of product types are manufactured thereby. The operation time of each operation process varies from one product type to another. The operation time calculation device of the present invention may calculate the operation time of each operation process of each product type from operation result information, for example, and offers the results of the calculation to the user. 
       FIG. 1  is a functional block diagram of the operation time calculation device. As illustrated, the operation time calculation device includes a storage unit  110 , a control unit  120 , an input unit  130 , a display unit  140 , and a communication unit  150 . 
     The storage unit  110  includes an operation result information storage region  111 , a work time information storage region  112 , an operation time information storage region  113 , a parameter information storage region  114 , an aggregation result information storage region  115 , and an average error information storage region  116 . 
     Regarding the operation actually implemented on the manufacturing floor, the operation result information storage region  111  stores operation result information identifying component numbers, product types of the components, operation process numbers of the components, operation processes for the components, and the operation start dates and times and operation end dates and times of the operation processes for the components. For example, this embodiment stores an operation result information table such as one shown in  FIG. 4 . As illustrated, the operation result information table has a component number column  111   a , a product type column  111   b , an operation process number column  111   c , an operation process column  111   d , an operation start date and time column  111   e , and an operation end date and time column  111   f . The component number column  111   a  stores information identifying the components involved. The product type column  111   b  stores information identifying the types of the products identified in the component number column  111   a . The operation process number column  111   c  stores information identifying the serial numbers of the operation processes for the components identified in the component number column  111   a . The operation process column  111   d  stores information identifying the operation processes corresponding to the operation process numbers identified in the operation process number column  111   c  regarding the components identified in the component number column  111   a . The operation start date and time column  111   e  and the operation end date and time column  111   f  store information identifying the operation start dates and times and the operation end dates and times, respectively, of the operation process numbers identified in the operation process number column  111   c  regarding the components identified in the component number column  111   a . The data records in the operation result information table are sorted in ascending order of the component number and of the operation process when stored in the operation result information storage region  111 . Here, there may occur losses of the data of operation start dates and times or operation end dates and times due to omissions and delays in recording the operation results from the manufacturing floor. 
     Returning to  FIG. 1 , the work time information storage region  112  stores the work time information about equipment and workers. For example, with the present embodiment, a work time information table such as one shown in  FIG. 5  is stored. As illustrated, the work time information table has a date column  112   a , an equipment/worker number column  112   b , an assigned process column  112   c , and a work time column  112   d . The date column  112   a  stores information identifying the dates involved. The equipment/worker number column  112   b  stores information identifying the equipment and/or workers involved. The assigned process column  112   c  stores information identifying the processes assigned to the equipment and/or workers identified in the equipment/worker number column  112   b  on the dates identified in the date column  112   a . The work time column  112   d  stores information identifying the times worked during the processes identified in the assigned process column  112   c  by the equipment and/or worker identified in the equipment/worker number column  112   b  on the dates identified in the date column  112   a.    
     Returning to  FIG. 1 , the operation time information storage region  113  stores operation time information identifying the product types involved, operation process numbers of the product types, operation processes for the product types, operation times of the operation processes for the product types, and an operation time conversion coefficient for the operation process for each of the product types. With this embodiment, for example, an operation time information table such as one shown in  FIG. 6  is stored. As illustrated, the operation time information table has a product type column  113   a , an operation process number column  113   b , an operation process column  113   c , an initially set operation time column  113   d , and an operation time conversion coefficient column  113   e . The product type column  113   a  stores information identifying the product types involved. The operation process number column  113   b  stores information identifying the serial numbers of the operation processes for the product types identified in the product type column  113   a . The operation process column  113   c  stores information identifying the operation processes corresponding to the operation process numbers identified in the operation process number column  113   b  regarding the product types identified in the product type column  113   a . The initially set operation time column  113   d  stores information identifying the operation times of the processes corresponding to the operation process numbers identified in the operation process number column  113   b  regarding the product types identified in the product type column  113   a . Here, the initially set operation time is the initial value used by a per-period operation time conversion unit  124 , to be discussed later, in converting operation times. Whereas there are methods for theoretically or empirically setting the initially set operation time based on the specification information about the product type of interest, for example, the present invention is not limited to any of these methods. The operation time conversion coefficient column  113   e  stores information identifying the operation time conversion coefficients for the operations corresponding to the operation process numbers identified in the operation process number column  113   b  regarding the product types identified in the product type column  113   a . Here, the initial value of the operation time conversion coefficient is 1, which may be changed in a process performed by the operation time conversion unit, to be discussed later. With regard to this example, it is assumed that one operation time conversion coefficient corresponds to one operation process of one product type and that the operation time after conversion is calculated by multiplying the operation time conversion coefficient by the initially set operation time. However, the number of operation time conversion coefficients and the method of conversion are not limitative of the present invention. For example, there may be two conversion coefficients (e.g., “a” and “b”), and the operation time after conversion may be calculated by multiplying “a” by the initially set operation time, plus “b.” 
     Returning to  FIG. 1 , the parameter information storage region  114  stores parameter information identifying the execution conditions for an operation time calculation process. With this embodiment, for example, a parameter information table such as one shown in  FIG. 7  is stored. As illustrated, the parameter information table has an item column  114   a  and a value column  114   b . The item column  114   a  stores information identifying parameter items. What is stored here is an “aggregation target process,” an “aggregation start date and time,” an “aggregation end date and time,” an “aggregation unit period,” and a “conversion iteration count upper limit” as the information identifying the items. The value column  114   b  stores information identifying the values regarding the items identified in the item column  114   a.    
     Returning to  FIG. 1 , the aggregation result information storage region  115  stores aggregation result information identifying aggregation period start dates and times, aggregation period end dates and times, total work times of the aggregation periods involved, total operation times before conversion, and total operation times after conversion. With this embodiment, for example, an aggregation result information table such as one shown in  FIG. 8  is stored. As illustrated, the aggregation result information table has an aggregation period start date and time column  115   a , an aggregation period end date and time column  115   b , a total work time column  115   c , a before-conversion total operation time column  115   d , and an after-conversion total operation time column  115   e . The aggregation period start date and time column  115   a  stores information identifying the start date and time of each of the aggregation periods. The aggregation period end date and time column  115   b  stores information identifying the end date and time of each aggregation period. The total work time column  115   c  stores information identifying the total work time of the aggregation period in question as the result of processing by a per-period work time calculation unit  112 , to be discussed later. The before-conversion total operation time column  115   d  stores information identifying the total work time of the aggregation period in question before operation time conversion as the result of processing by a per-period operation time calculation unit  124 , to be discussed later. The after-conversion total operation time column  115   e  stores information identifying the total work time of the aggregation period in question after operation time conversion as the result of processing by the per-period operation time calculation unit  124 , to be discussed later. 
     Returning to  FIG. 1 , the average error information storage region  116  stores information identifying the errors between per-period work times and per-period operation times as the result of processing by an error evaluation and coefficient calculation unit  125 , to be discussed later. With this embodiment, for example, an average error information table such as one shown in  FIG. 9  is stored. As illustrated, the average error information table has an item column  116   a  and a value column  116   b . The item column  116   a  stores information identifying the items involved. What is stored here is an “error before conversion” and an “error after conversion” as the information identifying the items. The value column  116   b  stores information identifying the values corresponding to the items identified in the item column  116   a.    
     Returning to  FIG. 1 , the control unit  120  includes an aggregation period setting unit  121 , a per-period work time calculation unit  122 , an operation implementation period estimation unit  123 , a per-period operation time calculation unit  124 , and an error evaluation and coefficient calculation unit  125 . 
     The aggregation period setting unit  121  acquires aggregation start dates and times, aggregation end dates and times, and aggregation unit periods based on the parameter information, and performs the process of setting the start date and time and the end date and time of each aggregation period. 
     Based on the results of the processing by the aggregation period setting unit  121  and on the work time information, the per-period work time calculation unit  122  performs the process of calculating the total work time of each aggregation period and the process of storing the results of the calculation into the aggregation result information storage region  115 . 
     The operation implementation period estimation unit  123  performs the process of estimating the operation implementation period of each operation process for each component based on the operation result information. 
     Based on the results of the processing by the aggregation period setting unit  121 , on the operation result information and on the operation time information, the per-period operation time calculation unit  124  performs the process of calculating the total operation time of each aggregation period and the process of storing the results of the calculation into the aggregation result information storage region  115 . 
     Based on the results of the processing by the per-period work time calculation unit  122  and by the per-period operation time calculation unit  124 , the error evaluation and coefficient calculation unit  125  performs the process of calculating an average error between the total work time and the total operation time in each aggregation period, the process of calculating the operation time coefficient in a manner minimizing the error, and the process of storing the results of the calculation into the average error information storage region  116 . 
     Returning to  FIG. 1 , the input unit  130  accepts input of the information to be set in the parameter information storage region  114  from the user of the operation time calculation device. 
     The display unit  140  outputs the information from the storage unit  110 . For example, the display unit  140  performs the process of displaying the information from the aggregation result information storage region  115  and average error information storage region  116  in the storage unit  110 . 
     The communication unit  150  transmits and receives information via a network. 
       FIG. 2  is a schematic view of an operation time calculation device  200  as one embodiment of the present invention. As illustrated, the operation time calculation device  200  includes an operation time calculation device  210 , a work result management device  220 , a process management device  230 , and an operation result management device  240 . These devices can transmit and receive information therebetween via a network  250 . 
     The work result management device  220  accepts input of the work result information about equipment and workers from the user of the device  220  and, at a predetermined point in time or in response to a request from the operation time calculation device  210 , transmits the accepted work result information to the operation time calculation device  210 . 
     The process management device  230  accepts input of process management information such as the product types of components, operation process numbers, operation processes, and operation time information from the user of the device  230  and, at a predetermined point in time or in response to a request from the operation time calculation device  210 , transmits the accepted process management information to the operation time calculation device  210 . 
     The operation result management device  240  accepts input of operation result information from the equipment and workers deployed on the manufacturing floor and, at a predetermined point in time or in response to a request from the operation time calculation device  210 , transmits the accepted operation result information to the operation time calculation device  210 . 
     The operation time calculation device  210  described above can be implemented in the form of a general-purpose computer that includes a CPU (Central Processing Unit)  151 , a memory  152 , an external storage device  153  such as HDD (Hard Disk Drive), a read/write device  157  that reads and writes information from and to a portable storage medium  158  such as CD (Compact Disk) or DVD (Digital Versatile Disk), an input device  156  such as a keyboard and a mouse, an output device  155  such as a display, and a communication device  154  such as NIC (Network Interface Card) for connecting to a communication network  159 . 
     For example, the storage unit  110  can be implemented by the CPU  151  using the memory  152  or external storage device  153 . The control unit  120  can be implemented when relevant programs stored in the external storage device  153  are loaded into the memory  152  and executed by the CPU  151 . The input unit  130  can be implemented by the CPU  151  using the input device  156 . The display unit  140  can be implemented by the CPU  151  using the output device  155 . The communication unit  150  can be implemented by the CPU  151  using the communication device  154 . 
     The relevant programs may be written from the storage device  158  to the external device  153  via the read/write device  157  or downloaded thereto from the network via the communication device  154 . From the external storage device  153 , the programs may be loaded into the memory  152  and executed by the CPU  151 . Alternatively, the programs may be loaded directly into the memory  152  from the storage medium  158  via the read/write device  157  or from the network  159  via the communication device  154 , and executed by the CPU  151 . 
     The operation time calculation device  210  described above performs an operation time calculation process, to be discussed below, in which the operation time is calculated in a manner minimizing the error between the work time and the operation time in each aggregation period.  FIGS. 11 through 18  are flowcharts showing the operation time calculation process, and  FIGS. 19 through 24  are schematic views of this process. The embodiment of the present invention is explained below in detail with reference to  FIGS. 11 through 24 . 
       FIG. 19  is a schematic view showing the operation time calculation process. In this process, the operation time is calculated in a manner minimizing the error between the total work time and the total operation time in the aggregation period of interest. First, on the basis of a predetermined aggregation unit period, aggregation periods (indicated by 1, 2, 3 on the horizontal axis of the drawing) are established, and the total work time and total operation time of each aggregation period are calculated. Here, the total operation time is calculated by totaling the initially set operation time for the operation implemented in the aggregation periods involved. The upper illustration in  FIG. 19  is a schematic diagram showing the results of calculating the total work time and the total operation time of each aggregation period. Next, an error is calculated between the total work time and the total operation time of each aggregation period, and the operation time is converted in a manner minimizing the sum of the errors from all aggregation periods. The lower illustration in  FIG. 19  is a schematic diagram showing the results of calculating the total operation time of each aggregation period using the operation time after conversion. 
       FIG. 11  is a flowchart showing the operation time calculation process performed by the control unit  120  mentioned above. 
     In step S 100 , the aggregation target process is acquired from the parameter information table stored in the parameter information storage region  114 , and the value involved is substituted into an operation process Proc. Here, multiple operation processes may be set in Proc. 
     In step S 200 , an aggregation period setting process is performed. Details of the process will be discussed later. 
     In step S 300 , a per-period work time calculation process is performed. Details of the process will be discussed later. 
     In step S 400 , an operation implementation period estimation process is performed. Details of the process will be discussed later. 
     In step S 500 , a per-period operation time calculation process is performed. Details of the process will be discussed later. 
     In step S 600 , an error estimation and coefficient calculation process is performed. Details of the process will be discussed later. 
     The aggregation period setting process of step  200  in  FIG. 11  is explained below in detail. In this process, the start dates and times and the end dates and times of the aggregation periods involved are established based on the aggregation start dates and times, aggregation end dates and times, and aggregation unit period in the parameter information. 
       FIG. 20  is a schematic view showing the aggregation period setting process of step  200 . In  FIG. 20 , reference characters T start  and T End  stand for the aggregation start date and time and the aggregation end date and time of the aggregation unit, respectively, and ΔT denotes the aggregation unit period. Starting from T start , aggregation periods R 1 , R 2 , R 3 , etc., are established at intervals of ΔT, and the process is terminated when the aggregation end date and time T End  is exceeded by the end date and time T End,k  of an aggregation period R k . Here, the aggregation period R j  is assumed to have, as its attribute values, a start date and time T start,j , an end date and time T End,j , a total work time totAT j , and a total operation time totST j . 
       FIG. 12  is a flowchart detailing the aggregation period setting process of step  200 . 
     In step S 201 , an aggregation start date and time, an aggregation end date and time, and an aggregation unit period are acquired from the parameter information table stored in the parameter information storage region  114 , and the acquired values are substituted into T start , T End , and ΔT, respectively. 
     In step S 202 , T start  is substituted into the date and time T, and “1” is substituted into a counter “j.” 
     In step S 203 , T is substituted into the start date and time T start,j  of the aggregation period R j , and T+ΔT into the end date and time T End,j  of the aggregation period R j . 
     In step S 204 , T+ΔT is substituted into the date and time T, and j+1 into the counter “j.” 
     In step S 205 , it is determined whether the date and time T is larger than the aggregation end date and time T End . Specifically, if T is determined to be larger than or equal to T End , the process is terminated; if T is determined to be smaller than T End , then step S 203  is reached. 
     In step S 206 , the start dates and times and the end dates and times of the aggregation periods involved are stored into the aggregation period start date and time column  115   a  and the aggregation period end date and time column  115   b , respectively, in the aggregation result information table of  FIG. 8 . 
     The per-period work time calculation process of step S 300  in  FIG. 11  is explained below in detail. In this process, the total work times of the aggregation periods involved are calculated based on the results of the aggregation period setting process mentioned above and on the work time information stored in the work time information storage region  112 . 
       FIG. 13  is a flowchart detailing the per-period work time calculation process of step S 300 . 
     In step S 301 , the total work time of each aggregation period is initialized. Specifically, “0” is substituted into the total work time totAT j  of the aggregation period R j , and this step is performed on all aggregation periods. 
     In step S 302 , the number of records in the work time information table is acquired and substituted into N. 
     Steps S 303  through S 308  are repeated from 1 to N on a counter “i.” 
     In step S 304 , the operation process of a record “i” in the work time information table (i-th record from the top of the table) is acquired. It is then determined whether the acquired operation process matches the aggregation target process Proc. If the acquired operation process is determined to match the aggregation target process Proc, step S 305  is reached. In the event of a mismatch, the acquired operation process is not considered the target, and step S 308  is reached. 
     In step S 305 , the date of the record “i” in the work time information table is acquired and substituted into the date t i  to acquire the work time. The acquired work time is substituted into a work time AT i . 
     In step S 306 , out of all aggregation periods, the aggregation period Rj is acquired in which the aggregation period start date and time T Start,j ≦date t i &lt;aggregation period end date and time T End,j . 
     In step S 307 , the work time AT j  is accumulated into the total work time totAT j  of the aggregation period R j . 
     In step S 309 , the total work times of the aggregation periods are stored into the total work time column  115   c  in the above-mentioned aggregation result information table of  FIG. 8 . 
     The operation implementation period estimation process of step S 400  in  FIG. 11  is explained below in detail. This process involves estimating the start date and time and the end date and time of the operation implementation period for the operation corresponding to each record of the operation result information stored in the operation result information storage region  111 . 
       FIGS. 21 through 23  are schematic views of the operation implementation period estimation process in step S 400 . 
       FIG. 21  shows the case where there are no omissions of the operation start date and time or the operation end date and time in a given record “i” of the operation result information. In this case, the start date and time t Start,i  of the operation implementation period in the record “i” is the date and time at which the outside diameter lathe process is started, and the end date and time t End,i  of the operation implementation period in the record “i” is the date and time at which the outside diameter lathe process is completed. 
       FIG. 22  shows the case where there is an omission of the operation start date and time in the record “i.” In this case, the start date and time t Start,i  of the operation implementation period in the record “i” is estimated from the operation end date and time of the sizing lathe process preceding the outside diameter lathe process. If the operation end date and time of the sizing lathe process is also found omitted, the estimation is based on the operation start date and time of the sizing lathe process. In this manner, the start date and time t Start,i  of the operation implementation period is estimated using the operation start date and time or the operation end date and time of the preceding operation. 
       FIG. 23  shows the case where there is an omission of the operation end date and time in the record “i.” In this case, the end date and time t End,i  of the operation implementation period in the record “i” is estimated from the operation start date and time of the machining process subsequent to the outside diameter lathe process. If the start date and time of the machining process is also found omitted, the estimation is based on the operation end date and time of the machining process. In this manner, the end is estimated using the operation start date and time or the operation end date and time of the subsequent operation. 
       FIG. 14  is a flowchart detailing the operation implementation period estimation process in step S 400 . 
     In step S 401 , the number of records in the operation result information table is acquired and substituted into N. 
     Steps S 402  through S 406  are repeated from 1 to N on the counter “i.” 
     In step S 403 , the operation process of the record “i” in the operation result information table (i-th record from the top of the table) is acquired. It is then determined whether the acquired operation process matches the aggregation target process Proc. If the acquired operation process is determined to match the aggregation target process Proc, step S 404  is reached. In the event of a mismatch, step S 406  is reached. 
     In step S 404 , the start date and time of the operation implementation period in the record “i” is estimated. Details of this step will be discussed later. 
     In step S 405 , the end date and time of the operation implementation period in the record “i” is estimated. Details of this step will be discussed later. 
       FIG. 15  is a flowchart detailing the operation implementation period start date and time estimation process in step S 404  of  FIG. 14 . In this process, the operation implementation period start date and time is estimated where the operation start date and time is found omitted, as shown in  FIG. 22 . 
     In step S 404   a , it is determined whether there is data in the operation start date and time in the record “i.” If data is determined to exist in the operation start date and time in the record “i,” step S 404   b  is reached. If there is no data in the operation start date and time, step S 404   c  is reached. 
     In step S 404   b , the operation start date and time in the record “i” is acquired and substituted into the start date and time t Start,i  of the operation implementation period in the record “i.” 
     In step S 404   c , i−1 is substituted into the counter “j.” 
     In step S 404   d , it is determined whether the component number of the record “i” matches that of the record “j.” If the component number of the record “i” is determined to match that of the record “j,” step S 404   e  is reached. In the event of a mismatch, step S 404   f  is reached. 
     In step S 404   e , it is determined whether the operation end date and time column in the record “j” is blank. If the operation end date and time column in the record “j” is not found blank, step S 404   g  is reached. If the column is found blank, step S 404   h  is reached. 
     In step S 404   f , the aggregation start date and time in the parameter information table is acquired and substituted into the start date and time t Start,i  of the operation implementation period in the record “i.” 
     In step S 404   g , the operation end date and time in the record “j” is acquired and substituted into the start date and time t Start,i  of the operation implementation period in the record “i.” 
     In step S 404   h , it is determined whether the operation start date and time column in the record “j” is blank. If the operation start date and time column in the record “j” is not found blank, step S 404   i  is reached. If the column is found blank, step S 404   j  is reached. 
     In step S 404   i , the operation start date and time in the record “j” is acquired and substituted into the start date and time t Start,i  of the operation implementation period in the record “i.” 
     In step S 404   j , j−1 is substituted into the counter “j.” 
       FIG. 16  is a flowchart detailing the operation implementation period end date and time estimation process in step S 405  of  FIG. 14 . In this process, the operation implementation period end date and time is estimated where there is an omission of the operation end date and time, as shown in  FIG. 23 . 
     In step S 405   a , it is determined whether the operation end date and time column in the record “i” is blank. If the operation end date and time column in the record “i” is not found blank, step S 405   b  is reached. If the column is found blank, step S 405   c  is reached. 
     In step S 405   b , the operation end date and time in the record “i” is acquired and substituted into the end date and time t End,i  of the operation implementation period in the record “i.” 
     In step S 405   c , i+1 is substituted into the counter “j.” 
     In step S 405   d , it is determined whether the component number of the record “i” matches that of the record “j.” If the component number of the record “i” is determined to match that of the record “j,” step S 405   e  is reached. In the event of a mismatch, step S 405   f  is reached. 
     In step S 405   e , it is determined whether the operation start date and time column in the record “j” is blank. If the operation start date and time column in the record “j” is not found blank, step S 405   g  is reached. If the column is found blank, step S 405   h  is reached. 
     In step S 405   f , the aggregation end date and time in the parameter information table is acquired and substituted into the end date and time t End,i  of the operation implementation period in the record “i.” 
     In step S 405   g , the operation start date and time in the record “j” is acquired and substituted into the end date and time t End,i  of the operation implementation period in the record “i.” 
     In step S 405   h , it is determined whether the operation start date and time column in the record “j” is blank. If the operation start date and time column in the record “j” is not found blank, step S 405   i  is reached. If the column is found blank, step S 405   j  is reached. 
     In step S 405   i , the operation start date and time in the record “j” is acquired and substituted into the end date and time t End,i  of the operation implementation period in the record “i.” 
     In step S 405   j , j+1 is substituted into the counter “j.” 
     The per-period operation time calculation process of step S 500  in  FIG. 11  is explained below in detail. In this process, the total operation times of the aggregation periods are calculated based on the results of the aggregation period setting process described above and on the results of the operation implementation period estimation process above. 
       FIG. 24  is a schematic view of the per-period operation time calculation process in step S 500 . As illustrated, where the range of the operation implementation period t Start,i  through t End,i  of a given record “i” in the operation result information overlaps with the aggregation periods R j , R j+1 , . . . R k , the operation time ST i  in the record “i” is read from the initially set operation time  113   d  of the record in question in the operation time information storage region  113 , and is distributed to the total operation times totST j , totST j+1 , . . . , totST k  of the aggregation periods R j , R j+1 , . . . , R k . Specifically, out of the operation implementation period t Start,i  through t End,i , a period segment overlapping with the aggregation period R j  is given as ΔT j , and ST j ×ΔT j /(t End,i −t Start,i ) is accumulated into totST j . 
       FIG. 17  is a flowchart detailing the per-period operation time calculation process of step S 500  in  FIG. 11 . 
     In step S 501 , the total operation time of each aggregation period is initialized. Specifically, “0” is substituted into the total operation time totST j  of the aggregation period R j , and this step is performed on all aggregation periods. 
     In step S 502 , the number of records in the operation result information table is acquired and substituted into N. 
     Steps S 503  through S 511  are repeated from 1 to N on the counter “i.” 
     In step S 504 , the operation process in the record “i” in the operation result information table (i-th record from the top of the table) is acquired. It is then determined whether the acquired operation process matches the aggregation target process Proc. If the acquired operation process is determined to match the aggregation target process Proc, step S 505  is reached. In the event of a mismatch, step S 511  is reached. 
     In step S 505 , the start date and time and the end date and time in the record “i” in the operation result information table are acquired, and substituted into t Start,i  and t End,i , respectively. 
     In step S 506 , based on the product type and operation process number in the record “i,” the initially set operation time and the operation time conversion coefficient corresponding to the operation process number of the product type in question are acquired from the operation time information table, and are substituted into ST i  and Coef i , respectively. 
     In step S 507 , out of all aggregation periods, the aggregation period R j  is acquired in which the aggregation period start date and time T Start,j &lt;operation implementation period start date and time t Start,i &lt;aggregation period end date and time T End,j . 
     In step S 508 , out of all aggregation periods, the aggregation period R k  is acquired in which the aggregation period start date and time T Start,k ≦operation implementation period end date and time t End,k &lt;aggregation period end date and time T End,k . 
     In step S 509 , within each aggregation period R x  between the aggregation period R j  and the aggregation period R k , a period ΔT x  overlapping with t Start,i  through t End,i  is calculated. On the basis of the following expression, an operation time distribution rate α x  is calculated: α x =(period overlapping with R x  between t Start,i  and t End,i )/(period between t Start,i  and t End,i ). 
     In step S 510 , for each aggregation period R x  between the aggregation period R j  and the aggregation period R k , the value of Coef i ×ST i ×ΔT x /(t End,i −t Start,i ) is accumulated into the total operation time totST x . 
     In step S 512 , the total operation times of the aggregation periods are stored into the before-conversion total operation time column  115   d  in the aggregation result information storage region  115  of  FIG. 8 . However, if this process is invoked during a per-period operation time aggregation process of step S 608  in the error estimation and coefficient calculation process of step S 600 , to be discussed later, the values are stored into the after-conversion total operation time column  115   e  in the aggregation result information table of  FIG. 8 . 
       FIG. 18  is a flowchart detailing the error estimation and coefficient calculation process of step S 600  in  FIG. 11 . In this process, based on the results of the per-period work time calculation process described above and on the results of the per-period operation time calculation process above, an average error is calculated between the work time and the operation time of each of the aggregation periods, and the operation time conversion coefficient is calculated in such a manner that its value minimizes the average error. Here, there are various methods for calculating the operation time conversion coefficient, including the method of repeatedly changing the operation time conversion coefficient and evaluating the resulting error to find an operation time conversion coefficient that minimizes the error, and the method involving multivariate analysis technique such as least-square approach for calculating an operation time conversion coefficient that minimizes the error. The present invention is not limited to any of these methods. 
     In step S 601 , an average error E Initial  between the operation time and the work time of each aggregation period before operation time conversion is calculated by Σ((totAT j −totST j )/totAT j )/number of aggregation periods. 
     In step S 602 , the value of E Initial  is stored into the error before conversion in the average error information table. 
     In step S 603 , the value of E Initial  is substituted into a minimum error E min . 
     In step S 604 , the conversion iteration count upper limit M is acquired from the parameter information table. 
     Steps S 605  through S 613  are repeated from 1 to M on the counter “i.” 
     In step S 606 , the operation time conversion coefficient in the operation time information table is temporarily saved into a matrix Coefs. 
     In step S 607 , the operation time conversion coefficient is changed, and the changed operation time conversion coefficient is stored into the operation time conversion coefficient table. For example, if the average error is larger than “0,” the operation time conversion coefficient is incremented by a unit quantity; if the average error is smaller than “0,” then the operation time conversion coefficient is decremented by a unit quantity. With this method, a different variation of the operation time conversion coefficient may be used for each of the product types, and the operation time conversion coefficient may be calculated in a manner minimizing the average error per product type. 
     In step S 608 , the per-period operation time aggregation process described above is performed. In this process, the total operation time of each aggregation period is calculated after the operation time conversion coefficient is changed. This embodiment uses the method of incrementing or decrementing the operation time conversion coefficient by a unit quantity when the average error is either positive or negative, with an upper limit placed on the iteration count as the condition for terminating the change of the operation time conversion coefficient. However, this or any other method is not limitative of the present invention. 
     In step S 609 , an average error E tmp  between the operation time and the work time of each aggregation period after operation time conversion is calculated by Σ((totAT j −totST j )/totAT j )/number of aggregation periods. 
     In step S 610 , it is determined whether E tmp  is smaller than E Min . If E tmp  is determined to be smaller than E min , step S 611  is reached; if E tmp  is found larger than E Min , step S 612  is reached. 
     In step S 611 , the value of E tmp  is substituted into E Min . 
     In step S 612 , the values of the elements in Coef in which the operation time conversion coefficient was temporarily saved are stored into the operation time conversion coefficient column in the operation time information table. 
     In step S 614 , the value of EMin is stored into the error after conversion in the average error information table. 
       FIG. 25  is a schematic view showing a typical input screen.  FIG. 25  gives an example of the input screen for setting parameter information. This input screen includes, for example, an aggregation target process input region  131   a , an aggregation start date and time input region  131   b , an aggregation end date and time input region  131   c , an aggregation unit period input region  131   d , and a conversion iteration count upper limit input region  131   e . The information input through this input screen is stored into the parameter information storage region  114  of the storage unit  110  mentioned above. 
       FIG. 26  is a schematic view showing a typical display screen.  FIG. 26  shows the display screen for displaying the information from the aggregation result information storage region  115 , operation time information storage region  113 , and average error information storage region  116  of the storage unit  110  mentioned above. The display screen includes, for example, a before-conversion average error display region  141   a , an after-conversion average error display region  141   b , a before-conversion aggregation result display region  141   c , an after-conversion aggregation result display region  141   d , and a product-type-wise conversion coefficient display region  141   e . This display screen allows the user of the operation time calculation device to verify the values of the operation time conversion coefficients and a conversion-induced change in the average error. Also, this display screen may be arranged to further include, for example, an aggregation target process display/selection region  141   f  and an aggregation unit period display/input region  141   g  allowing the aggregation target process and the aggregation unit period to be changed and the changed aggregation target process and aggregation unit period to be displayed. 
     REFERENCE SIGNS LIST 
     
         
         
           
               110  . . . Storage unit 
               111  . . . Operation result information storage region 
               111   a  . . . Component number column 
               111   b  . . . Product type column 
               111   c  . . . Operation process number column 
               111   d  . . . Operation process column 
               111   e  . . . Operation start date and time column 
               111   f  . . . Operation end date and time column 
               112  . . . Work time information storage region 
               112   a  . . . Date column 
               112   b  . . . Equipment/worker number column 
               112   c  . . . Assigned process column 
               112   d  . . . Work time column 
               113  . . . Operation time information storage region 
               113   a  . . . Product type column 
               113   b  . . . Operation process number column 
               113   c  . . . Operation process column 
               113   d  . . . Initially set operation time column 
               113   e  . . . Operation time conversion coefficient column 
               114  . . . Parameter information storage region 
               114   a  . . . Item column 
               114   b  . . . Value column 
               115  . . . Aggregation result information storage region 
               115   a  . . . Aggregation period start date and time column 
               115   b  . . . Aggregation period end date and time column 
               115   c  . . . Total work time column 
               115   d  . . . Before-conversion total operation time column 
               115   e  . . . After-conversion total operation time column 
               116  . . . Average error information storage region 
               116   a  . . . Item column 
               116   b  . . . Value column 
               120  . . . Control unit 
               121  . . . Aggregation period setting unit 
               122  . . . Per-period work time calculation unit 
               123  . . . Operation implementation period estimation unit 
               124  . . . Per-period operation time calculation unit 
               125  . . . Error evaluation and coefficient calculation unit 
               130  . . . Input unit 
               131   a  . . . Aggregation target process input region 
               131   b  . . . Aggregation start date and time input region 
               131   c  . . . Aggregation end date and time input region 
               131   d  . . . Aggregation unit period input region 
               131   e  . . . Conversion iteration count upper limit input region 
               131   f  . . . Input enter key 
               140  . . . Display unit 
               141   a  . . . Before-conversion average error display region 
               141   b  . . . After-conversion average error display region 
               141   c  . . . Before-conversion aggregation result display region 
               141   d  . . . After-conversion aggregation result display region 
               141   e  . . . Product-type-wise conversion coefficient display region 
               141   f  . . . Aggregation target process display/selection region 
               141   g  . . . Aggregation unit period display/input region 
               150  . . . Communication unit 
               151  . . . CPU (Central Processing Unit) 
               152  . . . Memory 
               153  . . . External storage device 
               154  . . . Communication device 
               155  . . . Output device 
               156  . . . Input device 
               157  . . . Read/write device 
               158  . . . Storage medium 
               159  . . . Communication network 
               200  . . . Operation time calculation system 
               210  . . . Operation time calculation device 
               220  . . . Work result management device 
               230  . . . Process management device 
               240  . . . Operation result management device 
               250  . . . Network