JP5683223B2 - Cargo work vehicle management device - Google Patents

Description

  The present invention relates to a management apparatus for a cargo handling work vehicle that provides an index for determining the skill of a driver of the cargo handling work vehicle.

  A management device for grasping the driving state of a cargo handling work vehicle has been proposed. For example, an operation variable having a large influence on the total work amount per unit consumption of fuel is extracted from operation variables such as a rapid acceleration level, a maximum speed, and the number of brakes. Based on the extraction result, an instruction for improving the total work amount per unit consumption of fuel is output.

JP 2009-256081 A

  It is difficult to determine the quality of work efficiency by simply comparing operating variables when the work environment is different, such as outdoors where there is a large free space, or in a warehouse where a lot of luggage is involved.

  An object of the present invention is to provide a cargo handling work management device that provides an index that can appropriately determine the skill of a driver even when the work environment is different.

According to one aspect of the invention,
Based on the driving information acquired from the cargo handling work vehicle that lifts the load and travels, an energy consumption amount and an operation state variable depending on the work environment are calculated, and according to the size of the calculated operation state variable, Having a processor that normalizes energy consumption and calculates normalized energy consumption;
The processing apparatus is provided with a management apparatus for a cargo handling work vehicle that classifies the normalized energy consumption into a plurality of categories based on a correlation between the normalized energy consumption and the operating state variable.

By classifying the normalized energy consumption into a plurality of categories based on the correlation between the normalized energy consumption and the operating status variable, it is possible to appropriately determine the skill of the driver even when the work environment is different. Possible indicators can be provided.

It is a side view of a cargo handling work vehicle. It is a block diagram of a vehicle-mounted management apparatus and a cargo handling work management apparatus. It is a graph which shows the total table of the driving information created with the vehicle-mounted management apparatus of Example 1. It is a chart which shows the driving information created with the cargo handling management device of Example 1. It is a graph displayed on the display apparatus of a cargo handling management apparatus. It is a graph which shows the total table of the driving information created with the vehicle-mounted management apparatus of Example 2. It is a graph which shows the driving information created with the cargo handling management apparatus of Example 2. It is a graph which shows the total table of the driving information created with the vehicle-mounted management apparatus of Example 3.

[Example 1]
FIG. 1 is a side view of a cargo handling work vehicle that is a management target of the cargo handling work management apparatus according to the first embodiment. The cargo handling work vehicle 10 includes a fork 11, wheels 12, an instrument panel 13, a handle 14, a lever 15, and a seat 16. FIG. 1 shows a forklift as an example of a cargo handling work vehicle. However, the management object of the cargo handling work management apparatus according to the embodiment is other vehicles that travel with lifting parts, products, etc. on the premises such as factories and warehouses. It may be.

  The cargo handling work vehicle 10 may be a so-called engine vehicle whose driving source is an internal combustion engine such as a gasoline engine, and a so-called battery having an electric motor driven by electric energy supplied from a power storage device such as a battery as a driving source. It may be a car. In the following description, it is assumed that the cargo handling work vehicle 10 is a battery car.

  The driver gets on the seat 16 and operates the handle 14, the plurality of levers 15, the accelerator pedal, the brake pedal, and other various switches. By these operations, operations such as raising and lowering of the fork 11, forward and backward movement of the cargo handling work vehicle 10, right turn and left turn are performed. By combining these operations, it is possible to load and unload packages and carry them.

  In FIG. 2, the block diagram of the vehicle-mounted management apparatus 20 and the cargo handling work management apparatus 50 which are mounted in the cargo handling work vehicle 10 is shown. The in-vehicle management device 20 includes a control device 21, a real time clock (RTC) 22, a memory 23, a display device 24, an input device 25, a communication circuit 26, and an interface 27.

  The control device 21 includes a calculation device such as a CPU and an MPU, and a storage device such as a semiconductor memory. The RTC 22 measures the current time and transmits the current time information to the control device 21. The memory 23 includes a temporary storage unit 23a and an information storage unit 23b. The temporary storage unit 23a temporarily stores various data. The information storage unit 23b stores vehicle information. The display device 24 is mounted on the instrument panel 13 (FIG. 1) and is configured by a CRT, a liquid crystal display panel, an LED display panel, or the like. The input device 25 has a connection function with an input key and an external input device. Input key information and various initial setting information are input to the control device 21 through the input device 25.

  The communication circuit 26 communicates with the cargo handling work management device 50 via the network 40. The interface 27 receives the measurement results measured by the load measurement device 31, the vehicle speed measurement device 32, the cargo handling lever operation measurement device 33, and the lift measurement device 34, and inputs them to the control device 21.

  The load measuring device 31 measures the load (the weight of the load) received by the fork 11 (FIG. 1). The vehicle speed measuring device 32 measures the traveling speed of the cargo handling work vehicle. The cargo handling lever operation measuring device 33 measures the operation amount of the cargo handling lever of the lever 15 (FIG. 1). The lift height measuring device 34 measures the height of the fork 11 from the reference position.

  As the network 40, various networks capable of performing data communication can be applied. For example, a wired or wireless public communication network, a dedicated communication network, the Internet, a mobile phone network, an intranet, or a communication network that combines these can be used.

  A cargo handling work management device 50 is connected to the network 40. The cargo handling work management device 50 includes a processing device 51 and a display device 52. The display device 52 displays an image under the control of the processing device 51.

  Before describing the operations of the in-vehicle management device 20 and the cargo handling work management device 50, terms are defined.

  “Load state” means a state in which the load measured by the load measuring device 31 exceeds a specified value. That is, it means a state where the fork 11 (FIG. 1) holds the load (for example, a state where the pallet is lifted away from the ground).

  The “number of times of cargo handling” means the number of times the cargo is conveyed, and the number of times of cargo handling increases by one every time one load state is completed. After placing the pallet, it is determined that one load state is completed by moving backward. As an example, after determining that there is no load based on the measurement value of the load measuring device 31, it is determined that one load state is completed by performing a backward movement operation. Here, when the baggage is temporarily grounded and then lifted again to travel, the number of cargo handling does not increase. That is, no matter how many times the same luggage is lifted, the number of times of cargo handling is one.

  “Load travel distance” means the distance traveled by the cargo handling work vehicle in a loaded state. The load travel distance can be calculated by subtracting the value of the cumulative distance meter at the start of the load state from the value of the cumulative distance meter at the end of the load state.

  “Power storage device discharge amount” means a value obtained by integrating the discharge current from the power storage device over time. When the product of the voltage of the power storage device and the discharge current is integrated over time, the consumed energy is obtained. When the voltage of the power storage device is substantially constant, the discharge amount of the power storage device can be handled as a physical quantity equivalent to the energy consumption amount. In the case of an engine vehicle, fuel consumption corresponds to energy consumption.

  Next, the operation of the in-vehicle management device 20 will be described. The in-vehicle management device 20 acquires driving information of the cargo handling work vehicle 10 and stores the acquired information in the temporary storage unit 23a. For example, each time the load state ends, the weight (load) of the load transported in the load state is stored in the temporary storage unit 23a.

  When one counting period ends, the travel distance traveled within the counting period is calculated. The one aggregation period is, for example, 15 minutes. This travel distance can be calculated by subtracting the value of the cumulative distance meter at the start of the total period from the value of the cumulative distance meter at the end of the total period. Further, the amount of discharge from the power storage device during the counting period is calculated. The discharge amount can be calculated, for example, by measuring the discharge current at regular sampling times and integrating the measurement results over time. The travel distance, the discharge amount, and the number of cargo handling operations within the counting period are stored in the temporary storage unit 23a. Since it can be considered that the discharge amount represents the energy consumption amount, the “discharge amount” may be hereinafter referred to as “energy consumption amount”.

  FIG. 3 shows an example of data stored in the temporary storage unit 23a. For each counting period, the number of cargo handling operations, the load corresponding to the number of cargo handling operations, the travel distance, and the energy consumption amount are stored. The load L (i, j) indicates the load in the jth load state (loading) performed within the ith total period. The travel distance D (i) indicates the distance traveled during the i-th counting period. The energy consumption amount E (i) indicates the energy consumption amount released from the power storage device during the i-th counting period.

  The in-vehicle management device 20 transmits the operation information such as the number of times of cargo handling, the load, the travel distance, and the energy consumption shown in FIG. 3 to the cargo handling work management device 50 at regular intervals, for example, every day.

  The processing device 51 of the cargo handling work management device 50 has a travel distance per unit cargo handling (hereinafter referred to as “cargo handling distance”) DU (k) and a load LU (k) per unit cargo handling for each evaluation unit period. Then, the total weight WU (k) per unit cargo handling frequency and the energy consumption EU (k) per unit cargo handling frequency are calculated. The “evaluation unit period” is, for example, one day. Here, k is a serial number assigned to the evaluation unit period in order to identify the evaluation unit period.

  FIG. 4 shows an example of data calculated by the cargo handling work management device 40. Assuming that the number of unit handling operations is one, the traveling distance DU (k) per unit handling number is the sum of the traveling distances D (i) of a plurality of total periods belonging to the kth evaluation unit period. Calculated by dividing by value. The load per unit handling number is calculated by dividing the total value of loads L (i, j) of a plurality of total periods belonging to the kth evaluation unit period by the total number of handling times. That is, it means the average load of the load.

  The total weight WU (k) per unit handling frequency is calculated by the following formula.

WU (k) = WV + LU (k) × (Tl (k) / Tm (k))
Here, WV is the vehicle weight, Tl (k) is the time during which the load is in the evaluation unit period, and Tm (k) is the time during which the vehicle is in operation within the evaluation unit period. Here, the “operating state” refers to a state in which any operation is performed on the vehicle, such as forward, backward, fork up / down, forward / backward tilting of the mast supporting the fork, reach in, reach out, etc. This means that the vehicle is in operation.

  The energy consumption amount EU (k) per unit handling frequency is calculated by dividing the total value of the energy consumption amounts E (i) of a plurality of aggregation periods belonging to the kth evaluation unit period by the total number of cargo handling times. Is done. The calculated data is stored in the storage unit of the processing device 51.

  For each evaluation unit period, the cargo handling travel distance DU, the load LU per unit cargo handling frequency, and the energy consumption EU are stored.

The processing device 51 calculates the normalized energy consumption amount NEU by normalizing the energy consumption amount EU per unit cargo handling frequency based on the total weight WU per unit cargo handling frequency and the cargo handling distance DU. Specifically, the normalized energy consumption NEU is
NEU (k) = EU (k) / (WU (k) × DU (k))
It can be expressed as.

In addition, when the work is always performed only on the same cargo, since the change in the total weight WU (k) per unit cargo handling is small, the energy consumption EU per unit cargo handling is expressed as the cargo handling distance. You may normalize based only on DU. In this case, the normalized energy consumption NEU is
NEU (k) = EU (k) / DU (k)
It can be expressed as.

  The processing device 51 displays the cargo handling travel distance DU (k) and the normalized energy consumption NEU (k) on the display device 52 in association with each other.

  FIG. 5 shows an example of the displayed image. The displayed image is a graph in which calculated values for each evaluation unit period are plotted with the horizontal axis as the cargo handling distance DU and the vertical axis as the normalized energy consumption NEU. From the graph shown in FIG. 5, it can be seen that the cargo handling travel distance DU and the normalized energy consumption NEU have a correlation such that the normalized energy consumption NEU decreases as the cargo handling travel distance DU increases.

  When carrying out the cargo handling operation, it is preferable to keep in mind that the normalized energy consumption NEU is as small as possible. However, since the normalized energy consumption NEU has a correlation with the cargo handling mileage DU, the quality of driving is determined only based on the magnitude relationship of the normalized energy consumption NEU without considering the cargo handling mileage DU. It is not preferable to determine this.

For example, in FIG. 5, an operation corresponding to a point P where the handling distance is DU ₁ and the normalized energy consumption is NEU ₁ and a handling distance corresponding to a point Q where the handling distance is DU ₂ and the normalized energy consumption is NEU ₂ Compare with driving. The normalized energy consumption NEU ₂ for the operation corresponding to the point Q is smaller than the normalized energy consumption NEU ₁ for the operation corresponding to the point P. However, the distribution of the normalized energy consumption NEU in the vicinity of DU ₁ with the cargo handling mileage is more biased toward the higher energy consumption than the distribution of the normalized energy consumption NEU in the vicinity of DU _{2 with the} cargo handling mileage.

  It is preferable to determine whether the operation is good or bad in consideration of the uneven distribution of the normalized energy consumption NEU. Then, in terms of energy consumption, it is determined that the operation corresponding to the point P where the normalized energy consumption is large is preferable to the operation corresponding to the point Q where the normalized energy consumption is small. Thus, by determining the quality of driving in consideration of the cargo handling travel distance DU, it is possible to eliminate the influence of the work environment such as the size of the work premises and more appropriately determine the quality of driving.

The processing device 51 classifies the calculated values for each evaluation unit period into a plurality of categories based on the correlation between the normalized energy consumption amount NEU and the cargo handling travel distance DU. In FIG. 5, each calculated value is classified into three categories A ₁ , A ₂ , and A ₃ . For example, as shown in FIG. 5, when the normalized energy consumption NEU and the cargo handling mileage DU have a downward-sloping correlation, the boundary line of each segment is changed to a downward-sloping curve. do it.

Hereinafter, an example of a method for classifying into three categories will be described. The standard deviation σ of the distribution of normalized energy consumption at all points where the loading distance is between DU and DU + ΔDU is obtained. The range from −3σ to + 3σ of the normalized energy consumption NEU is divided into three equal parts. The three ranges divided into three equal parts are defined as sections A ₁ , A ₂ , A _{3 in} order from the smallest normalized energy consumption NEU. Sections A ₁ , A ₂ , and A ₃ are defined in the same manner over the entire range of the cargo handling distance DU. In addition, the range outside the standard deviation from −3σ to 3σ is included in the sections A ₁ or A ₃ at both ends.

The processing device 51 displays on the display device 52 in such a manner that it can be visually recognized which category the calculated value of the normalized energy consumption NEU belongs to. In FIG. 5, the points belonging to the sections A ₁ , A ₂ , and A ₃ are indicated by white circles, white triangles, and cross symbols, respectively. In addition, you may display according to color instead of the shape of a symbol. For example, the points belonging to the sections A ₁ , A ₂ and A ₃ may be displayed in blue, green and red, respectively.

  By displaying in a state where the measurement points belong to each section in a visible state, the manager can easily determine the quality of driving corresponding to each measurement point.

  In the first embodiment, the loading / unloading travel distance DU is adopted as the horizontal axis in FIG. 5, but other variables depending on the work environment may be adopted as the horizontal axis among the variables calculated based on the driving information. . Thus, the variable calculated based on the driving information is referred to as an “operation status variable”. For example, when a cargo is transported, the cargo handling work vehicle travels on almost the same route, but in a work environment where the variation in the weight of the cargo to be transported is large, the cargo handling distance DU is taken as the horizontal axis in FIG. The variation in the horizontal direction of the plot becomes small.

In this case, the load LU per unit handling frequency may be adopted as the horizontal axis in FIG. In addition, since it is considered that the cargo handling distance DU is substantially constant, the energy consumption amount EU per unit cargo handling may be normalized based only on the total weight WU per unit cargo handling. In this case, the normalized energy consumption NEU is
NEU (k) = EU (k) / WU (k)
It can be expressed as.

  Moreover, you may employ | adopt the load time per unit cargo handling frequency, load operation time, operation time, or key-on time as a horizontal axis of FIG. Here, the “load time” means a time during which the load state is maintained. The “load time” includes the time when the fork is stationary with the load lifted and the vehicle is not operating. “Operating time” means the operating time. The time during which the vehicle is operating in a state where the fork does not hold the pallet (no load state) is also included in the “operation time”. The “load operating time” means a time during which the load is in an operating state. “Key ON time” means the time when the start key is ON.

  In the first embodiment, the normalized energy consumption amount NEU, which is the vertical axis in FIG. 5, is calculated by normalizing the energy consumption amount EU per unit handling frequency, but the energy consumption amount per unit operating time, unit The energy consumption per load time, the energy consumption per unit load operating time, and the energy consumption per unit key ON time may be normalized.

[Example 2]
Next, Example 2 will be described. In Example 1, the evaluation unit period (for example, 1 day) was used as the identification target item, and the energy consumption amount representing the driving information was calculated for each evaluation unit period. When the cargo handling operation is performed without changing the driver of the cargo handling work vehicle in one evaluation unit period (one day), one measurement point shown in FIG. 5 indicates the driving skill of one driver. It can be thought of as representing.

  When a plurality of cargo handling work vehicles are driven on the same premises, the driving information shown in FIG. 4 is generated for each cargo handling work vehicle. In this case, the cargo handling work vehicle and the evaluation unit period are selected as a unit (identification target item) for calculating the normalized energy consumption. That is, the normalized energy consumption NEU is calculated for each cargo handling work vehicle and for each evaluation unit period.

  When the driver of the cargo handling work vehicle is switched during one evaluation unit period (one day), it is preferable to calculate the normalized energy consumption for each driver in addition to the “target driver” in addition to the identification target item. Hereinafter, a calculation method for each driver will be described.

  A driver identification number is assigned in advance to each driver. A driver identification number input device is installed on the instrument panel 13 of the cargo handling work vehicle 10 shown in FIG. The driver identification number input device is, for example, a numeric keypad or a touch panel for inputting numbers. When the driver drives the cargo handling work vehicle, his / her identification number is input from the driver identification number input device. The input identification number is transmitted to the control device 21 shown in FIG. 2 and stored in the temporary storage unit 23a.

  FIG. 6 shows an example of operation information totaled for each total period. Hereinafter, differences from the driving information shown in FIG. 3 will be described. In the example shown in FIG. 6, a driver identification number is stored for each counting period. When the driver with identification number ID1 is switched to the driver with identification number ID2 during the second counting period shown in FIG. 3, the second counting period in FIG. Separated into two tabulation periods, the third and the third. The number of times of handling, the load, the travel distance, and the energy consumption amount are aggregated for each of the separated aggregation periods. The third to fifth aggregation periods shown in FIG. 3 are shifted one by one and become the fourth to sixth aggregation periods, respectively. When the length of one aggregation period is set to 15 minutes, the lengths of the second and third aggregation periods are shorter than 15 minutes.

  FIG. 7 shows an example of operation information calculated by the cargo handling work management device 40. Hereinafter, differences from the driving information shown in FIG. 4 will be described. In the example shown in FIG. 4, the length of the evaluation unit period is one day, and the normalized energy consumption and the like are calculated for each evaluation unit period based on the operation information of the aggregation period included in the evaluation unit period. . In the example shown in FIG. 7, when a plurality of drivers are driving within one evaluation unit period, normalized energy consumption and the like are calculated for each driver.

  For example, when the driver with the identification number ID1 and the driver with the identification number ID2 are driving in the third evaluation unit period, the driver identification number ID1 is in the third evaluation unit period. The driving information of driving is set as one identification item No. 3 and the driving information of driving with the driver identification number ID2 within the third evaluation unit period is represented by one identification target item No. As 4, the two are distinguished.

  Thus, by calculating the normalized energy consumption NEU for each driver, it is possible to prevent the driving information of a highly skilled driver and a less skilled driver from being mixed and averaged.

[Example 3]
Next, Example 3 will be described. In Example 1, as shown in FIG. 3, the load was memorize | stored for every package conveyed within the totaling period. In the third embodiment, the load is converted into frequency data.

  FIG. 8 shows a summary table of driving information created in the third embodiment. Hereinafter, differences from the tabulation table of FIG. 3 will be described. The load of the load is divided into three stages of less than L1 (kg), L1 (kg) or more and less than L2 (kg), and L2 (kg) or more. For each load category, the number of packages transported during the counting period is stored.

  As in the first embodiment, in order to store the load for each package, it is necessary to secure a storage area for the maximum number of packages transported within one counting period. Even if the storage area is dynamically allocated, the size of the storage area to be allocated increases as the number of delivered packages increases. In the third embodiment, since the load is converted into frequency data, the required size of the storage area does not change even if the number of packages to be conveyed increases.

  When calculating the load per unit handling shown in FIG. 4, it can be considered that, for each of the load categories, the load of the representative load of the category is conveyed by the frequency of the category. As the representative load, for example, the center value of the load range can be adopted. It should be noted that the representative load can be determined in the classification at both ends in consideration of variations in the load of the load to be transported.

[Example 4]
Next, Example 4 will be described. In Example 1, the discharge current from the power storage device was measured in order to calculate the energy consumption. In Example 4, the discharge current is not measured directly. Information that greatly affects energy consumption is extracted as basic items from various operation information other than the discharge current. Extraction of basic items and determination of energy consumption estimation model are based on multivariate analysis method and data mining method (multiple regression analysis method using stepwise method, neural network model). This can be done by applying

  When the estimation model is determined, the energy consumption amount can be calculated by the estimation calculation from the measured value of the driving information extracted as the basic item. Hereinafter, an example of the estimation model will be described.

  The energy consumption Et is estimated by the following equation.

Et = a ₁ × (Ec + Er) (1)
Here, Ec is the energy consumed in order to perform the lifting of the load (cargo handling energy), Er is the energy consumed for the vehicle running (running energy), a ₁ is luggage lift and It is a constant for counting energy consumed in operations other than vehicle travel. “Energy consumed by operations other than lifting and lowering of luggage and traveling of the vehicle” includes, for example, energy consumed by power steering operation, energy consumed by various control devices, and the like. Since these energy consumptions are sufficiently smaller than the total consumption, they are calculated by multiplying the sum of the cargo handling energy Ec and the traveling energy Er by a certain coefficient instead of measuring individually. The constant a ₁ is about 1.03.

  The cargo handling energy Ec is estimated by the following equation.

Ec = Tc × {a ₂ + a ₃ × (Mm + LU)} (2)
Here, Tc is the total cargo handling time performed within the unit period, Mm is the weight of the lifting / lowering part (mast) when lifting / lowering without loading, and LU is shown in FIG. This is the load per unit handling shown. a ₂ and a ₃ are constants. “Handling time” means the time during which the mast is lifted and lowered.

  The travel energy Er is estimated by the following equation.

Er = Tr × {a ₄ + a ₅ × (Mf + a ₆ × Ra)} (3)
Mf = Mf ₀ + LU × (Trc / Tr) (4)
Here, Tr is the time (traveling time) during which the vehicle has traveled within the unit period, Mf ₀ is the weight of the vehicle when the baggage is not held, and Trc is the baggage held within the unit period. And Ra is an acceleration excess rate. The acceleration excess rate Ra is a ratio of time traveled exceeding a specified acceleration to the total travel time. The prescribed acceleration is determined in advance. a ₄ , a ₅ , and a ₆ are constants.

  The estimation model including the estimation expressions (1) to (4) is stored in the processing device 51 of the cargo handling work management device 50. The mast weight Mm is measured in advance. The cargo handling time Tc, the travel time Tr, and the load travel time Trc are measured during driving. As described with reference to FIG. 4, the load LU per unit number of times of handling can be calculated from the load of the load and the number of times of handling. The processing device 51 obtains an energy consumption amount EU per unit cargo operation by estimation calculation based on the operation information.

  The difference between the amount of discharge of the power storage device estimated using the above estimation model and the amount of discharge obtained by actually measuring the discharge current is ± 10% or less of the amount of discharge obtained by actually measuring the discharge current It was confirmed that

  In Example 4, energy consumption can be calculated | required, without arrange | positioning an ammeter in a cargo handling work vehicle.

  In the first to fourth embodiments, the cargo handling work management device 50 (FIG. 2) and the cargo handling work vehicle 10 are connected via the network 40, but the cargo handling work management device 50 may be mounted on the cargo handling work vehicle 10. Good.

  Although the present invention has been described with reference to the embodiments, the present invention is not limited thereto. It will be apparent to those skilled in the art that various modifications, improvements, combinations, and the like can be made.

DESCRIPTION OF SYMBOLS 10 Cargo work vehicle 11 Fork 12 Wheel 13 Instrument panel 14 Handle 15 Lever 16 Seat 20 Car-mounted management apparatus 21 Control apparatus 22 Real-time clock 23 Memory 23a Temporary storage part 23b Information storage part 24 Display apparatus 25 Input apparatus 26 Communication circuit 31 Load measurement Device 32 Vehicle speed measuring device 33 Cargo handling lever operation measuring device 34 Lifting height measuring device 40 Network 50 Cargo handling operation management device 51 Processing device 52 Display device

Claims (7)

Based on the driving information acquired from the cargo handling work vehicle that lifts the load and travels, an energy consumption amount and an operation state variable depending on the work environment are calculated, and according to the size of the calculated operation state variable, Having a processor that normalizes energy consumption and calculates normalized energy consumption;
The processing apparatus is a management apparatus for a cargo handling work vehicle that classifies the normalized energy consumption into a plurality of categories based on a correlation between the normalized energy consumption and the operation status variable. Based on the driving information acquired from the cargo handling work vehicle that lifts the load and travels, an energy consumption amount and an operation state variable depending on the work environment are calculated, and according to the size of the calculated operation state variable, Having a processor that normalizes energy consumption and calculates normalized energy consumption;
The processing device calculates the operating status variable and the normalized energy consumption for each item to be identified, and sets one axis as a travel distance per unit handling frequency and the other axis as the normalized energy consumption. A cargo handling work vehicle management apparatus that displays a graph in which a calculated value is plotted for each identification target item on a display device. The identification target item is at least one selected from the group consisting of evaluation unit periods when a certain period is divided into a plurality of evaluation unit periods, a cargo handling work vehicle, and a driver driving the cargo handling work vehicle. 2. The cargo handling work vehicle management device according to 2. The management apparatus for a cargo handling work vehicle according to any one of claims 1 to 3 , wherein the energy consumption is a discharge amount of a power storage device or a fuel consumption amount. The processor is
The weight of the lifting part of the cargo handling work vehicle, the weight of the load, the weight of the vehicle when not holding the load,
Estimate the relationship between the energy consumption and the value of multiple basic items selected from the group consisting of total travel time, travel time with luggage held, and travel time with acceleration exceeding the specified value I remember it as a model,
Obtain the value of the basic item,
The management apparatus for a cargo handling work vehicle according to any one of claims 1 to 3 , wherein the energy consumption is calculated based on the acquired value of the basic item and the estimated model. The operational status variables, the management device materials handling vehicle according to claim 1 or 2 which is traveling distance per unit handling times. 7. The normalized energy consumption amount according to any one of claims 1 to 6 , wherein the energy consumption amount per unit cargo handling is normalized based on a weight of a load and a travel distance per unit cargo handling. The cargo handling work vehicle management device described.

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