JP7779104B2 - Operational status management system, operational status management device, program, and operational status management method - Google Patents

Description

This disclosure relates to an operation status management system, an operation status management device, a program, and an operation status management method.

Traditionally, various products are produced (manufactured) on various production lines installed within a factory. Production lines combine production equipment that performs a variety of processes. In order to efficiently produce products using such production lines, technologies for managing their operations have been developed (see, for example, Patent Document 1).

Patent No. 4846412

In production equipment that performs high-speed production, such as PET bottle aseptic filling lines, equipment stoppages result in significant production losses. Such production lines consist of multiple processes, and if a problem occurs during production, each process issues an alert and stops the production. Because production lines are large and complex, it is difficult to grasp the impact on production progress when multiple alerts are issued.

The present disclosure aims to provide an operation status management system, operation status management device, program, and operation status management method that can grasp the impact on production progress when multiple alerts are issued on a production line.

In order to solve the above problems, the present disclosure provides:
An operation status management system including a production device that produces a product, an operation status management device that acquires data from the production device, and a display device that displays information acquired from the operation status management device,
The operation status management device
a reduction coefficient storage means for storing a relationship between an alert for each alert type and a reduction coefficient that affects a reduction in production efficiency;
a predicted operational efficiency calculation means for calculating a predicted operational efficiency based on alert occurrence information for each alert type received from the production device and the degradation coefficient for each alert type,
The display device provides an operational status management system that displays predicted information based on the predicted operational efficiency.

In addition, in the operation status management system of the present disclosure,
The operation status management device
a production schedule storage means for storing production schedule information including the planned production quantity and production equipment capacity;
The system further comprises a scheduled end time calculation means for calculating a scheduled end time using the predicted operating efficiency calculated by the predicted operating efficiency calculation means, the scheduled production quantity, and the production equipment capacity,
The display device may display the estimated end time as the prediction information.

In addition, the operation status management system of the present disclosure includes:
an operation record storage means for storing operation record information in which the occurrence result of an alert for each alert type and the operating efficiency of the production device are recorded in association with a manufacturing lot of the production target;
The system may further include a reduction coefficient calculation means for calculating a reduction coefficient for an alert for each alert type by performing a simple regression analysis with reference to the operational performance information, using the operational efficiency as a response variable and the alert occurrence result as an explanatory variable.

In addition, in the operation status management system of the present disclosure,
The reduction coefficient calculation means may calculate the reduction coefficient in association with one or more of the product type, liquid content, bottle shape, bottle capacity, cap type, and label material.

In addition, in this disclosure,
An operation status management system including a production device that produces a product, an operation status management device that acquires data from the production device, and a display device that displays information acquired from the operation status management device,
An operation status management device that acquires production information from a production device that produces a product and manages the operation status,
a reduction coefficient storage means for storing the relationship between an alert for each alert type and a reduction coefficient that affects a reduction in production efficiency;
An operation status management device is provided, which has a predicted operation efficiency calculation means that calculates a predicted operation efficiency based on alert occurrence information for each alert type received from the production device and the degradation coefficient for each alert type.

In addition, in this disclosure,
Computer,
a reduction coefficient storage means for storing a relationship between an alert for each alert type and a reduction coefficient that affects a reduction in production efficiency;
a predicted operational efficiency calculation means for calculating a predicted operational efficiency based on alert occurrence information for each alert type received from the production equipment and the degradation coefficient for each alert type;
We provide a program to function as a

In addition, in this disclosure,
An operation status management method in which an operation status management device including a production schedule storage means for storing production schedule information and a reduction coefficient storage means for storing the relationship between alerts for each alert type and a reduction coefficient that affects a reduction in production efficiency manages operation status,
calculating a predicted operating efficiency based on alert occurrence information for each alert type received from the production device and the degradation coefficient for each alert type;
Calculating an estimated end time using the predicted operation efficiency;
The present invention provides an operational status management method having the above-mentioned steps.

This disclosure makes it possible to understand the extent to which an alert issued on a production line will affect production efficiency.

FIG. 1 is a configuration diagram illustrating an operational status management system according to an embodiment of the present disclosure. FIG. 1 is a diagram illustrating an operating status management device 110 according to an embodiment of the present disclosure. FIG. 4 is a diagram showing an example of operation performance information stored in an operation performance storage means. FIG. 10 is a diagram illustrating an example of a reduction coefficient that is not based on product information. FIG. 10 is a diagram illustrating an example of a reduction coefficient for each product type. FIG. 10 is a diagram showing an example of a reduction coefficient for each bottle shape. FIG. 10 is a diagram showing an example of a reduction coefficient for each bottle capacity. FIG. 4 is a diagram showing an example of production schedule information stored in a production schedule storage means. FIG. 10 is a diagram showing product information including product types. FIG. 2 is a diagram illustrating a hardware configuration of a display device 120. 10 is a flowchart showing the processing operation of the operational status management system. FIG. 10 is a diagram showing a display image on a display device 120. FIG. 10 is a diagram showing an example of an alert in an aseptic filling line for PET bottles.

Preferred embodiments of the present disclosure will be described in detail below with reference to the drawings.
<System Configuration>
FIG. 1 is a diagram illustrating an operation status management system using an operation status management device according to an embodiment of the present disclosure. In FIG. 1, reference numeral 100 denotes the operation status management system, 110 denotes the operation status management device, 120 denotes a display device, 130 denotes a production device, 140 denotes a gateway device, and 150 denotes a network. The operation status management device 110, the display device 120, and the gateway device 140 are connected to a network 150 such as the Internet and are capable of data communication with each other. The production device 130 is connected to the gateway device 140 so as to be capable of data communication. The gateway device 140 transmits data such as production information received from the production device 130 to the operation status management device 110 via the network 150. The display device 120 accesses the operation status management device 110 via the network 150, receives data from the operation status management device 110, and displays the data.

For ease of explanation, the example in Figure 1 shows only one display device 120. However, in reality, the operational status management device 110 is accessible from many display devices 120 via the network 150. Also, for ease of explanation, the example in Figure 1 shows three production devices 130. However, in reality, many more production devices 130 are typically installed at a production site. The operational status management system 100 according to this embodiment is particularly useful when a production line comprises a large number of production devices and the entire production line has a complex configuration.

Figure 2 shows details of the operational status management device 110. Figure 2(a) is a hardware configuration diagram of the operational status management device 110. The operational status management device 110 can be implemented as a general-purpose server computer. Specifically, as shown in Figure 2, the hardware configuration of the operational status management device 110 includes a CPU (Central Processing Unit) 110a, a RAM (Random Access Memory) 110b, which is the computer's main memory, a large-capacity storage device 110c (e.g., a hard disk, flash memory, etc.) for storing programs and data executed by the CPU, an input I/F (interface) 110d for accepting input from input devices such as a keyboard and mouse, a data input/output I/F (interface) 110e for data communication with external devices (e.g., data storage media), a display output I/F (interface) 110f for sending information to a display device (e.g., liquid crystal display), and a communication unit 110g for network communication with other devices such as the display device 120 and gateway device 140 via the network 150. These elements are connected to each other via a bus.

Figure 2(b) is a functional block diagram of the operational status management device 110. In the hardware configuration shown in Figure 2(a), the CPU 110a loads a program stored in the storage device 110c into the RAM 110b and executes it, thereby enabling the operational status management device 110 to function as each of the means shown in Figure 2(b). As shown in Figure 2(b), the operational status management device 110 has an operational performance storage means 111, a reduction coefficient storage means 112, a production schedule storage means 113, a reduction coefficient calculation means 114, a predicted operating efficiency calculation means 115, and a scheduled end time calculation means 116.

The operation performance storage means 111 is a storage means that stores operation performance information. Operation performance information is information that compiles the operation performance of each production device 130 by product production lot. Therefore, operation performance information is recorded in association with the production lot of the production target. Figure 3 is a diagram showing an example of operation performance information stored in the operation performance storage means 111. As shown in Figure 3, the operation performance storage means 111 stores the production start time, production end time, production time, product type, production device capacity (denoted as "device capacity" in the figure), production quantity, operating efficiency (operation performance), and the number of alerts issued for each alert type as operation performance information.

Operation performance information is managed by production lot for each product that has already been produced. Furthermore, the operation performance information is managed in chronological order, with the production lots sorted in order from the earliest production start date. In the example of Figure 3, the same product type, product c, is produced in a different production lot. Figure 3 shows an example in which products a, b, and d are each produced once, and product c is produced twice in different production lots. A production device 130 corresponds to each product type. Production device capacity is the number of units that can be produced per unit time. In Figure 3, production device capacity indicates the number of units that each production device 130 can produce of the corresponding product type. Here, production device capacity is shown as the number of units that can be produced of the corresponding product type per minute. For example, in the example of Figure 3, the production device 130 corresponding to product type a has the capacity to produce a maximum of 606 units of product type a per minute.

In Figure 3, the production start time and production end time indicate the production start time and production end time for the corresponding manufacturing lot. The production time is the time during which production took place, and indicates the elapsed time from the production start time to the production end time. The production quantity is the number of products actually produced during that production time. Operating efficiency is the ratio of the production quantity to the number that would be produced if production were made using the maximum capacity of the production equipment.

In the example of Figure 3, the number of occurrences (occurrence count) of each of four alerts, Alert A to Alert D, is displayed as the number of occurrences for each alert type. Note that while the number of alert occurrences is used here as an example of alert occurrence information indicating the severity of the alert, alert occurrence information such as the alert occurrence time or alert occurrence rate may also be used. Alert occurrence time is the total amount of time an alert has occurred. Alert occurrence rate is the number of times an alert has occurred per unit time.

Using the top row in Figure 3 as an example, this shows that the production capacity of production equipment 130 producing product type a is 606 units per minute. It also shows that production took place over 24.48 hours, from the production start time of "2020/12/1 18:12" to the production end time of "2020/12/2 18:29," and that 837,114 units of product type a were produced. It also shows that between the production start time of "2020/12/1 18:12" and the production end time of "2020/12/2 18:29," alert A occurred 10 times, alert B 20 times, alert C 14 times, and alert D 1 time. It also shows that the operating efficiency was 94.8%.

The reduction coefficient storage means 112 is a storage means that stores reduction coefficient information. The reduction coefficient information is a coefficient that indicates the degree to which each alert reduces production efficiency. Naturally, the impact on production efficiency varies depending on the malfunction that the alert is directed at. Therefore, the reduction coefficient also varies depending on the alert type. Figure 4 is a diagram showing an example of a reduction coefficient that is not based on product information. As shown in Figure 4, the reduction coefficient storage means 112 stores a reduction coefficient associated with each alert type. The reduction coefficient is not particularly limited as long as it is a numerical value that indicates the degree of reduction, and various values can be used. In this embodiment, the reduction coefficient is a reduction rate that indicates the rate of reduction in operating efficiency. In this embodiment, the reduction rate is a negative value.

The reduction coefficients shown in Figure 4 are not dependent on product information, but reduction coefficients managed by product information may also be used. For example, reduction coefficients for each product information item, such as variety, bottle shape, and bottle capacity, may be used. Figures 5, 6, and 7 are diagrams showing reduction coefficients for each product type, bottle shape, and bottle capacity, respectively. As shown in Figures 5, 6, and 7, even for alerts of the same type, the reduction coefficients differ depending on the product type, bottle shape, bottle capacity, etc. produced.

The production schedule storage means 113 is a storage means that stores production schedule information including planned production quantities and production equipment capacity. Figure 8 is a diagram showing an example of production schedule information stored in the production schedule storage means 113. As shown in Figure 8, the production schedule information includes the product number, the type of product to be produced, the production equipment capacity (denoted as "equipment capacity" in the figure), and the planned production quantity. For example, the first line in Figure 8 indicates that "100,000 units" of type a are planned to be produced by production equipment 130 with a production equipment capacity of "606 (units/minute)."

The "product type" used in the production schedule information in Figure 8 can be accompanied by product information such as bottle shape, labeler type, bottle capacity, whether acidic or neutral, liquid contents, cap type, and label material. Figure 9 is a diagram showing an example of product information. In the example of Figure 9, product information such as bottle shape, labeler type, bottle capacity, whether acidic or neutral, liquid contents, cap type, and label material are recorded as product type information. This type of product information can be stored in a specified storage area within storage device 110c. Product information may also have attributes other than those shown in Figure 9.

The reduction coefficient calculation means 114 is a means for calculating a reduction coefficient for each alert by referencing the operation performance information stored in the operation performance storage means 111. Specifically, a simple regression analysis is performed on each objective variable, with the operating efficiency as the objective variable and the alerts of each alert type as the explanatory variables. The simple regression analysis can be performed using, for example, the least squares method. This simple regression analysis calculates the p-value (reliability) and slope for each alert. This slope is then used as the reduction coefficient. In this way, the reduction coefficient calculation means 114 calculates the reduction coefficient for each alert.

The predicted operational efficiency calculation means 115 calculates the predicted operational efficiency based on the reduction coefficient calculated by the reduction coefficient calculation means 114. Specifically, the predicted operational efficiency calculation means 115 calculates the predicted operational efficiency by performing processing in accordance with the following [Equation 1].

[Formula 1]
Predicted operational efficiency = 1 + (number of occurrences of alert A × α) + (number of occurrences of alert B × β) + (number of occurrences of alert C × γ) + ... + (number of occurrences of alert Z × ζ)

In [Formula 1], α, β, γ, and ζ are reduction coefficients corresponding to each alert. In the above [Formula 1], the reduction coefficients α, β, γ, and ζ indicate the reduction coefficients for alerts A, B, C, and Z, respectively. In this embodiment, the reduction coefficients are calculated as the rate at which driving efficiency decreases. Therefore, the reduction coefficients take negative values. Therefore, the more times each alert occurs, the more the predicted driving efficiency decreases. In the above [Formula 1], when no alerts have occurred, the predicted driving efficiency is at its maximum, that is, 1.

The estimated end time calculation means 116 calculates the predicted operation efficiency using the predicted operation efficiency calculated by the predicted operation efficiency calculation means 115. Specifically, the estimated end time calculation means 116 calculates the estimated end time by performing processing in accordance with the following [Equation 2].

[Formula 2]
Estimated end time:
Current time + (Planned production volume - Current production volume) / (Production equipment capacity x Predicted operating efficiency)

In [Formula 2], the planned production quantity is the planned production quantity of the product currently being produced. The current production quantity is the quantity produced up to that point. The equipment capacity is the equipment capacity of the production equipment currently in production. As shown in [Formula 2], the planned completion time is calculated by subtracting the current production quantity from the planned production quantity, dividing the result by the equipment capacity multiplied by the predicted operating efficiency, and adding the result to the current time.

The operating status management device 110 also performs various processes not included in the above-mentioned means by having the CPU 110a load programs stored in the storage device 110c into the RAM 110b and execute them. The operating status management device 110 may be physically implemented as a single computer or multiple computers. It may also be implemented as a cloud system distributed across multiple computers on the network 150.

The display device 120 is a terminal device that displays information stored and managed by the operational status management device 110. Figure 10 is a hardware configuration diagram of the display device 120. The display device 120 is realized, for example, by a general-purpose computer equipped with browser software.

As shown in FIG. 10, the display device 120 comprises a CPU (Central Processing Unit) 120a, RAM (Random Access Memory) 120b as main memory, a non-volatile storage device 120c (e.g., flash memory) for storing programs and data executed by the CPU 120a, an instruction input unit 120d such as a keyboard or touch panel, a data input/output I/F (interface) 120e for data communication with external devices (data storage media, etc.), a display unit (liquid crystal display, etc.) 120f, and a communication unit 120g for network communication with other computers such as the operating status management device 110 via a network 150, all of which are connected to each other via a bus.

The display device 120 may be any device equipped with a CPU processing unit and equipped with display, information processing, and network communication functions, and may be a general-purpose device such as a laptop PC, tablet, or smartphone. In this embodiment, the display device 120 is equipped with a web browser and uses the web browser to access the operational status management device 110, which functions as a web server. This allows the display device 120 to obtain and display information managed by the operational status management device 110.

The production devices 130 are facilities for producing a specified variety of products. Each production device 130 is equipped with a PLC (programmable logic controller), various sensors, and a communication device, and acquires production information and transmits it to the gateway device 140.

The gateway device 140 aggregates production information obtained from multiple production devices 130. The aggregated production information is then transmitted to the operation status management device 110 via the network 150. The production information may be transmitted to the operation status management device 110 periodically (for example, every 5 minutes), or may be transmitted in real time upon receipt from each production device 130. Note that the production devices 130 may be directly connected to the network 150 and transmit production information directly to the operation status management device 110 without going through the gateway device 140.

<Collecting operational performance information>
Next, the collection of operation information in the operation status management system shown in Fig. 1 will be described. As shown in Fig. 1, the production device 130 is capable of transmitting data to the operation status management device 110 via the gateway device 140 and the network 150. Therefore, in the production device 130, the production information detected by an attached sensor or the like is transmitted to the operation status management device 110 by the attached PLC. The operation status management device 110 stores the collected production information in operation record storage means 111.

Regarding the production start time and production end time, the production device 130 transmits information indicating the start and end of production and the time, and the operation status management device 110 stores the acquired time information as the production start time and production end time.

For product types, information on the product type obtained from the production equipment 130 is stored. For production equipment capacity, a table is provided in which values calculated from past performance are recorded for each product type, and when a product type is identified, this is automatically stored as part of the operational performance information. For production quantities, a detection sensor installed on the production equipment 130 detects the produced products and sends this information to the operational status management device 110. The operational status management device 110 then counts the obtained information and sets it as the production quantity. The value counted up to the end of production becomes the actual production quantity. The operational status management device 110 stores the actual production quantity in association with the corresponding product type.

Regarding alerts, each time an alert is generated by each alert generation means, the PLC installed on the production equipment 130 transmits the alert type and the fact that an alert has been generated to the operation status management device 110 via the gateway device 140. The operation status management device 110 then counts the acquired alert generation information for each alert type. Then, at the end of production, it stores the number of alerts generated up to that point for each alert type, associating them with the corresponding product type.

In this way, various information from the production start time to the production end time is sent from each production device 130 to the operation status management device 110, and the operation performance information is accumulated in the operation performance storage means 111. Once production ends and the production end time is determined, the operation status management device 110 calculates the production time from the difference between the production start time and the production end time. Furthermore, the operation status management device 110 calculates the operation efficiency (operation performance) by dividing the number of productions by the value obtained by multiplying the production time by the operation status management device capacity. In the example of Figure 3, the operation efficiency is converted to a percentage and recorded in % units.

<Calculation of the reduction coefficient>
When production for a certain production lot is completed, the reduction coefficient calculation means 114 in the operation status management device 110 calculates the reduction coefficient of each alert for each alert type. The reduction coefficient is a coefficient that indicates the degree to which each alert reduces production efficiency. The reduction coefficient takes a negative value. Specifically, the reduction coefficient calculation means 114 performs a simple regression analysis using the operating efficiency and the number of alerts for each alert from the operation performance information such as that shown in FIG. 3, and calculates the p-value and slope for each alert.

The calculated p-value represents the reliability of the numerical value. If this p-value is not sufficiently small, the reliability of the data is low. Therefore, a predetermined threshold is set, and data with a p-value greater than this threshold is excluded from the adopted data. Therefore, if the p-value is greater than the threshold, the reduction coefficient is not calculated and the reduction coefficient becomes 0. In this way, each calculated reduction coefficient is stored in the reduction coefficient storage means 112 as reduction coefficient information. As shown in FIG. 4, the reduction coefficient calculation means 114 can calculate a reduction coefficient independent of product information. However, as shown in FIGS. 5, 6, and 7, it may also calculate a reduction coefficient for each type, bottle shape, and bottle capacity. It may also calculate a reduction coefficient for other attributes, which are attribute information shown in the product information of FIG. 9. For example, the reduction coefficient calculation means 114 may calculate a reduction coefficient by associating the information on the labeler type, acidic/neutral, liquid contents, cap type, and label material with one or more of the bottle shape, labeler type, bottle capacity, acidic/neutral, liquid contents, cap type, and label material.

<Calculating the estimated end time>
As described above, the reduction coefficient is calculated using the latest operational performance information, and the reduction coefficient for each alert stored in the reduction coefficient storage means 112 is always updated to the latest value. In the operational status management system according to this embodiment, the predicted operational efficiency and estimated completion time are calculated as prediction information during the production of a product. The operational status is managed by obtaining the prediction information in this manner. For this purpose, production schedule information for the product to be produced is prepared in the production schedule storage means 113. As described above, the production schedule information is as shown in FIG. 8.

Figure 11 is a flowchart showing the operation status management method according to this embodiment. When production begins using the production device 130 with the reduction coefficient information and production schedule information prepared, the production device 130 transmits production information to the operation status management device 110, as in the case described above. The operation status management device 110 then acquires production information from the production device 130, as in the case described above (step S1). The received production information is accumulated in the operation record storage means 111. The production volume is received at any time, so it increases over time. Furthermore, the number of alerts is received each time one is generated, so the number of alerts stored in the operation record storage means 111 also increases.

The predicted operating efficiency calculation means 115 calculates the predicted operating efficiency at a predetermined timing while the production equipment 130 is in operation (step S2). The predetermined timing can be set to various timings, such as when a predetermined unit of time has elapsed or when an alert is received. When the predetermined timing arrives, the predicted operating efficiency calculation means 115 calculates the predicted operating efficiency. Specifically, the predicted operating efficiency calculation means 115 executes processing in accordance with the following [Equation 1] to calculate the predicted operating efficiency.

[Formula 1]
Predicted operational efficiency = 1 + (number of occurrences of alert A × α) + (number of occurrences of alert B × β) + (number of occurrences of alert C × γ) + ... + (number of occurrences of alert Z × ζ)

The predicted operating efficiency calculation means 115 obtains the number of occurrences of each alert from the start of production to the present in order to perform processing in accordance with the above [Formula 1]. The predicted operating efficiency calculation means 115 also obtains the reduction coefficient for each alert type from the reduction coefficient storage means 112. Then, using the number of occurrences and reduction coefficient for each alert, it performs processing in accordance with the above [Formula 1] to calculate the predicted operating efficiency.

Once the predicted operating efficiency has been calculated, the scheduled end time calculation means 116 uses the predicted operating efficiency to calculate the scheduled end time (step S3). Specifically, the scheduled end time calculation means 116 calculates the scheduled end time by performing processing in accordance with the following [Equation 2].

[Formula 2]
Estimated end time:
Current time + (Planned production volume - Current production volume) / (Production equipment capacity x Predicted operating efficiency)

The estimated end time calculation means 116 acquires information on the current time, planned production quantity, current production quantity, production equipment capacity, and predicted operating efficiency to execute processing according to [Equation 2] above. The current time is acquired from the internal clock of the computer that implements the operation status management device 110. The planned production quantity is acquired from the production plan information. The current production quantity is the production quantity received from the production equipment 130 and updated as needed. The production equipment capacity can be acquired and used from the production equipment capacity recorded in the operation information. The predicted operating efficiency is the current predicted operating efficiency calculated by the predicted operating efficiency calculation means 115. The acquired information is then used to execute processing according to [Equation 2] above to calculate the estimated end time.

The operational status management device 110 calculates the predicted operating efficiency and scheduled end time as forecast information whenever the production equipment 130 is in operation. The calculated values are stored along with the calculation time, and are transmitted in response to a request from the display device 120. The display device 120 then displays the acquired forecast information (step S4). Figure 12 shows an example of the display on the display device 120.

On the left side of Figure 12, an arrow pointing from top to bottom is shown. This arrow indicates the progression of time, with the further down the arrow goes, the more time has advanced. In the example of Figure 12, alert A occurs at a certain time after production starts, followed by alerts D and H. On the right side of Figure 12, three screens G1 to G3 are shown. Screens G1 to G3 correspond to the progression of time on the left side of Figure 12. As shown on screens G1 to G3 in Figure 12, during production, the display device 120 displays four items: scheduled finish time, operating results, predicted operating efficiency, and alerts.

The estimated end time is the estimated end time calculated by the estimated end time calculation means 116. The operating performance is displayed as the details of the operating efficiency from the start of the current production to the present time. The predicted operating efficiency is displayed as the current predicted operating efficiency calculated by the predicted operating efficiency calculation means 115. All alerts that have occurred up to that point that have caused a decrease in the predicted operating efficiency are displayed with the most recent alert at the top. The most recent alert is then displayed at the top. The estimated end time and predicted operating efficiency are both predicted information based on the predicted operating efficiency. The estimated end time does not necessarily need to be displayed; it is also possible to display only the predicted operating efficiency as predicted information based on the predicted operating efficiency.

After production has started, but before alert A is issued, the display device 120 displays the content shown in screen G1 in Figure 12. At the time screen G1 is displayed, no alerts have been issued since production began. Therefore, the predicted operating efficiency calculated using the processing in accordance with [Formula 1] above is 1. When converted to a percentage, the predicted operating efficiency is "100%." Using this predicted operating efficiency of "100%," the current time, the planned production quantity, the current production quantity, and the production equipment capacity in the operation information, the estimated end time calculation means 116 executes processing in accordance with [Formula 2] above. In this way, the estimated end time calculation means 116 calculates the estimated end time. Screen G1 shows an example in which 17:00 is calculated as the estimated end time.

After alert A has occurred 10 times, the content shown in screen G2 in Figure 12 is displayed. Because alert A has occurred 10 times at the time screen G2 is displayed, the predicted operating efficiency calculated using the processing in accordance with [Formula 1] above is a value less than 1. Screen G2 in Figure 12 converts this to a percentage and shows a predicted operating efficiency of "97%." Using this predicted operating efficiency of "97%," the current time, the planned production quantity, the current production quantity, and the production equipment capacity in the operation information, the estimated end time calculation means 116 executes processing in accordance with [Formula 2] above. In this way, the estimated end time calculation means 116 calculates the estimated end time.

Screen G2 in Figure 12 displays the calculated scheduled end time of 17:05. As the predicted operational efficiency decreases, the value of the predicted end time calculated using Formula 2 above increases. In other words, the predicted end time is delayed. In screen G1 in Figure 12, the predicted operational efficiency was 100%, so the scheduled end time was 17:00. However, in screen G2 in Figure 12, the predicted operational efficiency is 97%, so the scheduled end time is 17:05, which is 5 minutes late. This means that alert A has occurred 10 times, and the operational status management device 110 has estimated (calculated) a new scheduled end time.

After alert D has occurred 20 times and alert H 8 times, the content shown in screen G3 in Figure 12 is displayed. After screen G2 is displayed, alert D has occurred 20 times and alert H has occurred 8 times at the time screen G3 is displayed. As described above, the most recent alert is displayed at the top of the display device 120 screen. In this example, alert A has occurred 10 times, alert D 20 times, and alert H 8 times. Therefore, screen G3 displays, from top to bottom, alert H 8 times, alert D 20 times, and alert A 10 times. At this point, the predicted operating efficiency calculation means 115 calculates a new predicted operating efficiency by performing processing according to the above [Equation 1] using alerts A, D, and H that have occurred so far and the number of occurrences of each. Suppose the new predicted operating efficiency calculated by performing processing according to the above [Equation 1] is 0.8. In this case, screen G2 in Figure 12 converts this to a percentage and displays a predicted operating efficiency of "80%." Using this predicted operating efficiency of 80% (0.8), the current time, the planned production quantity, the current production quantity, and the production equipment capacity in the operation information, the estimated end time calculation means 116 executes processing according to the above [Equation 2]. In this way, the estimated end time calculation means 116 calculates the estimated end time.

Screen G3 in Figure 12 displays the calculated scheduled end time of 17:30. In screen G2 in Figure 12, the predicted operational efficiency was 97%, so the scheduled end time was 17:05. However, in screen G3 in Figure 12, the predicted operational efficiency is 80%, so the scheduled end time is 17:30, which is a further 25 minutes later. This means that the operational status management device 110 has estimated (calculated) a new scheduled end time due to the occurrence of 20 new alerts D and 8 new alerts H.

As described above, the operational status management system 100 according to this embodiment comprises a production device 130 that produces products, an operational status management device 110 that acquires data from the production device 130, and a display device that displays information acquired from the operational status management device. The operational status management device 110 comprises a reduction coefficient storage means 112 that stores the relationship between alerts for each alert type and reduction coefficients that affect reductions in production efficiency, and a predicted operational efficiency calculation means 115 that calculates predicted operational efficiency based on alert occurrence information for each alert type received from the production device 130 and the reduction coefficient for each alert type. The display device 120 displays prediction information based on the predicted operational efficiency, making it possible to understand the extent to which an alert generated on a production line will affect production efficiency.

In addition, in the operation status management system 100 according to this embodiment, the operation status management device 110 further includes a production schedule storage means 113 that stores production schedule information including the planned production quantity and production equipment capacity, and a planned completion time calculation means that calculates the planned completion time using the predicted operating efficiency calculated by the predicted operating efficiency calculation means 115, the planned production quantity, and the production equipment capacity, and the display device 120 displays the planned completion time as predicted information. Therefore, if an alert occurs and the initial completion schedule is delayed, it is possible to know the planned completion time, making it easier to adjust the schedule for subsequent processes.

The operational status management system according to this embodiment also includes an operational performance storage means 111 that stores operational performance information that records the alert occurrence results for each alert type and the operational efficiency of production equipment in association with the production lot of the production target, and a reduction coefficient calculation means 114 that references the operational performance information, performs a simple regression analysis with operational efficiency as the objective variable and the alert occurrence results as the explanatory variable, and calculates a reduction coefficient for the alert for each alert type. This allows the relationship between the alert type of the alert that occurs and production delays to be kept up to date, which is useful for calculating accurate predicted operational efficiency and estimated completion times. The reduction coefficient calculation means 114 may calculate a reduction coefficient in association with one or more of the product variety, liquid contents, bottle shape, bottle capacity, cap type, and label material of the production target. In this case, using a reduction coefficient specialized for each attribute allows for more accurate calculation of predicted operational efficiency and estimated completion times.

The operational status management system disclosed herein can be applied to any production equipment in the production process that is equipped with a means for detecting the status of the production equipment and issuing an alert. Therefore, it can be applied to a variety of products and production equipment, regardless of the type of product or the type of production equipment that produces the product.

For example, the operational status management system disclosed herein can be applied to an aseptic filling line for PET (polyethylene terephthalate) bottles. When applied to an aseptic filling line for PET bottles, the production equipment used includes equipment for the blending and liquid processing process, the filling and molding process, and the packaging process. These pieces of equipment are equipped with PLCs, and information detected during the production process is sent to the predicted operating efficiency calculation device via a gateway device.

Figure 13 is a diagram showing an example of an alert on a PET bottle aseptic filling line. Because alerts for the entire production line are aggregated, there are a variety of alerts, as shown in Figure 13. The urgency of each alert varies depending on the alert type (alert name). In Figure 13, the urgency is expressed in order of increasing urgency with ◎, ○, and △. This urgency is determined by the worker's perception and does not necessarily correspond to the degree of production delay. In the operational status management system according to this embodiment, the alert reduction coefficient is accurately set based on actual results, making it possible to calculate predicted operational efficiency and estimated completion times that cannot be fully grasped by the worker's perception.

The above describes a preferred embodiment of the present disclosure, but the present disclosure is not limited to the above embodiment and various modifications are possible. For example, in the above embodiment, the predicted driving efficiency and scheduled end time are received from the predicted driving efficiency calculation device via a network and displayed on a display device, but they may also be displayed on a display device directly connected to the display output I/F of the predicted driving efficiency calculation device.

In addition, in the above embodiment, the predicted driving efficiency calculation device calculates the predicted driving efficiency and scheduled end time, and the display device displays them. However, it is also possible to calculate and display only the predicted driving efficiency without calculating and displaying the scheduled end time. This is because even if the scheduled end time is not known, knowing the predicted driving efficiency makes it possible to estimate a certain amount of time delay.

100: Operational status management system 110: Operational status management device 110a: CPU (Central Processing Unit)
110b...RAM (Random Access Memory)
110c: Storage device 110d: Input I/F
110e...Data input/output I/F
110f...display output I/F
DESCRIPTION OF THE SYMBOLS 110g: Communication unit 111: Operation performance storage means 112: Reduction coefficient storage means 113: Production schedule storage means 114: Reduction coefficient calculation means 115: Predicted operation efficiency calculation means 116: Estimated end time calculation means 120: Display device 130: Production device 140: Gateway device 150: Network

Claims (6)

An operation status management system including a production device that produces a product, an operation status management device that acquires data from the production device, and a display device that displays information acquired from the operation status management device,
The operation status management device
a reduction coefficient storage means for storing a relationship between an alert for each alert type and a reduction coefficient that affects a reduction in production efficiency;
a predicted operational efficiency calculation means for calculating a predicted operational efficiency based on alert occurrence information for each alert type received from the production device and the degradation coefficient for each alert type,
the display device displays prediction information based on the predicted driving efficiency,
an operation record storage means for storing operation record information in which the occurrence result of an alert for each alert type and the operating efficiency of the production device are recorded in association with a manufacturing lot of the production target;
a reduction coefficient calculation means for calculating a reduction coefficient for an alert of each alert type by referring to the operation performance information and performing a simple regression analysis using the operation efficiency as a response variable and the alert occurrence result as an explanatory variable;
An operation status management system further comprising : The operation status management device
a production schedule storage means for storing production schedule information including the planned production quantity and production equipment capacity;
The system further comprises a scheduled end time calculation means for calculating a scheduled end time using the predicted operating efficiency calculated by the predicted operating efficiency calculation means, the scheduled production quantity, and the production equipment capacity,
The operating status management system according to claim 1 , wherein the display device displays the scheduled end time as the predicted information. 3. The operating status management system according to claim 1, wherein the reduction coefficient calculation means calculates the reduction coefficient in association with one or more of the product type, liquid contents, bottle shape, bottle capacity, cap type, and label material. An operation status management device that acquires production information from a production device that produces a product and manages the operation status,
a reduction coefficient storage means for storing a relationship between an alert for each alert type and a reduction coefficient that affects a reduction in production efficiency;
a predicted operational efficiency calculation means for calculating a predicted operational efficiency based on alert occurrence information for each alert type received from the production device and the degradation coefficient for each alert type;
an operation record storage means for storing operation record information in which the occurrence result of an alert for each alert type and the operating efficiency of the production device are recorded in association with a manufacturing lot of the production target;
an operational status management device having a reduction coefficient calculation means for calculating a reduction coefficient for an alert for each alert type by referring to the operational performance information and performing a simple regression analysis using the operational efficiency as a target variable and the alert occurrence result as an explanatory variable . Computer,
a reduction coefficient storage means for storing a relationship between an alert for each alert type and a reduction coefficient that affects a reduction in production efficiency;
a predicted operational efficiency calculation means for calculating a predicted operational efficiency based on alert occurrence information for each alert type received from the production equipment and the degradation coefficient for each alert type;
an operation record storage means for storing operation record information in which the occurrence result of an alert for each alert type and the operating efficiency of the production equipment are recorded in association with the manufacturing lot of the production target;
a reduction coefficient calculation means for calculating a reduction coefficient for an alert of each alert type by performing a simple regression analysis with the operational efficiency as a response variable and the alert occurrence result as an explanatory variable, with reference to the operational performance information;
A program to function as a An operation status management method in which an operation status management device including a production schedule storage means for storing production schedule information and a reduction coefficient storage means for storing the relationship between alerts for each alert type and a reduction coefficient that affects a reduction in production efficiency manages operation status,
calculating a predicted operating efficiency based on alert occurrence information for each alert type received from the production device and the degradation coefficient for each alert type;
and calculating an estimated end time using the predicted operation efficiency ,
storing operation performance information in which the alert occurrence results for each alert type and the operating efficiency of the production equipment are recorded in association with the manufacturing lot of the production target;
a step of referring to the operation performance information, performing a simple regression analysis using the operation efficiency as a response variable and the occurrence result of the alert as an explanatory variable, and calculating a reduction coefficient of an alert for each alert type;
The operating status management method further comprises: