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Example of “HAKO-FLO” solution to reduce manual labor

Tokyo Electron Device America, Inc.

Introducing some examples of how the logistics management solution “HAKO-FLO” is used to streamline manual tasks such as “inbound/outbound management,” “inventory management,” “stocktaking management,” and “documentation,” including cargo damage reports.


As logistics volume increases along with the recent surge in the size of the Internet shopping market, there is a need to reduce manual work and shift to more effective operations without incurring the cost of modifying existing warehouse management systems. In some distribution warehouses, many tasks related to receiving, storing, and shipping cargo are managed by manual operations. In such warehouses, there is a risk of incurring return costs due to misplaced or misdirected shipments.
The current situation is that there are many issues that need to be resolved, such as incurring costs for returned goods due to misdelivery, accurate grasp of inventory quantities, effective utilization of empty space on shelves and in the warehouse, elimination of delivery delays due to insufficient staff, and control of labor costs.

The warehouse floor management solution “HAKO-FLO” developed by TOKYO ELECTRON DEVICE AMERICA manages and streamlines the “receiving management” such as “measurement” and “inspection” at the time of receiving and shipping that occur in existing systems, as well as “inventory management,” “shipping management,” “inventory control,” “damage to outer boxes,” and “documentation” such as reporting. It is a service that supports efficiency improvement in conjunction with users’ existing systems by managing and streamlining manual tasks such as “documentation” and “report creation” with dedicated software provided in the cloud or on-premise.

The HAKO-FLO service consists of five services: RFID, which quickly retrieves information on the box; LIDAR, which automatically measures the box size; EZ-Report, which takes AR (Augmented Reality) measurements of the box and generates a report; Tracking, which tracks the box; and Cloud, which stores and visualizes the data. HAKO-FLO can be used for a part of the service separately. HAKO-FLO can be used for specific tasks independently, and can be combined to best suit the user’s warehouse operations. (HAKO-FLO can be combined with other services to best suit the user’s warehouse operations (Figure 1).

Figure 1 – HAKO-LO Implementation Image


TOKYO ELECTRON DEVICE AMERICA integrated its multiple departments in the U.S. about three years ago, creating a structure that allows the company to develop its own products and services while conducting research on cutting-edge technologies and startups in Silicon Valley. While exploring new business opportunities in the U.S., the company investigated various issues related to logistics from users in the manufacturing and distribution industries with whom it has business relationships in the trading company business, and thought it might be able to help improve these issues by utilizing digital technology. We visited the users’ warehouses, analyzed their work processes in detail, repeatedly discussed where the real issues were and how they could be improved, and developed a problem-solving application service. In this article, we will introduce a case study in which “EZ-Report” and “RFID Query” were used to improve operational efficiency without incurring the cost of modifying the existing system.

Improvement of business efficiency by AR measurement using LiDAR

1) Challenges due to manual operations
Users who own and operate distribution warehouses throughout the U.S. conduct damage checks of outer boxes upon cargo arrival and measurements of outer boxes during shipment. In some cases, dozens of damage checks are conducted per day. When damage occurs, the user visually checks for damage, takes pictures with a digital camera or cell phone, imports the pictures into a PC, compiles them into a damage report, and sends the report to the user. Each time this occurs, the people in the office rushes to the warehouse site to respond, which takes more than 30 minutes per case. In addition, measurements for shipments are taken manually using a tape measure, which imposes a heavy workload when taking measurements for large packages, and it is difficult to compile a database of measurement information.

2) How to resolve issues
“HAKO-FLO EZ-Report” enables users to complete a series of tasks from AR (Augmented Reality) measurement, photo shooting, text input, and report creation on a tablet device with our application installed on an iPad Pro equipped with a LiDAR sensor. This allows the work to be completed using only a tablet device, instead of the previously dispersed work using individual tools, thereby improving work efficiency and reducing work time. In our experience, it has reduced work time by more than 80%. Also, even for large cargoes over 1 meter in length, the AR measurement allows for easy and quick measurement. (Figure 2)
We are currently developing an automatic measurement application that utilizes the ToF camera, and plan to add a service that allows measurements to be taken more easily, quickly, and accurately with a fixed camera.

Figure 2 – AR measurement using LiDAR technology

3) Integrating with the Cloud
Exterior box damage reports created with tablet terminals and measurement data obtained can be easily uploaded to “HAKO-FLO CLOUD” to create a database. Furthermore, information can be shared with back offices and other locations. Data in the cloud can be analyzed and utilized to improve transportation quality. (Figure 3) In addition, since no paper is used at all, it is possible to promote a paperless environment.

Figure 3 – EZ Report integration with the Cloud

Next, we will introduce our efforts to utilize RFID.

Improving operational efficiency with RFID

A user’s warehouse, which operates a logistics business on the West Coast of the U.S., is entrusted with the storage and shipping of sake and ships 2,000 to 3,000 boxes of sake bottles each month, but many issues existed in the work process.

1) Issues in warehouse operations
It was found that there were a wide range of challenges due to manual operations, market conditions, and regional backgrounds.

  • Workload is heavy due to visual inspection of each shipment
  • Workers are unable to read the Japanese on packages, resulting in shipping inspection errors
  • Long hours in the refrigerated warehouse are a heavy workload
  • Many hours are spent traveling back and forth between the office and the warehouse
  • Inventory is time-consuming
  • Time-consuming to search for mislocated items
  • High turnover of workers, and inconsistent work levels among workers
  • Soaring labor costs

To address these various issues, we aimed to improve operational efficiency by utilizing RFID Query, an application with a collation function.

2) Preparation
In order to utilize RFID, it is necessary to attach an RFID tag to the target cargo and verify the accuracy of reading the tag in advance. Since there are various types of RFID tags, it is necessary to select the most appropriate tag based on an understanding of the work environment at the site and the target cargo. (Figure 4)
In addition, the process of attaching RFID tags occurs in the work process, and it is important to devise a method that does not significantly affect the existing work process and prevents tag mis-attachment.
Once the RFID tag to be used is determined, the necessary information is printed and encoded on the tag using a dedicated RFID printer, and the tag is attached to the target cargo.

Figure 4 – RFIF tag types

3) Operation
After attaching tags to the target cargo, the RFID reader terminal equipped with the “RFID Query” application is used to perform the actual work. The system can be used for a wide range of general work processes, from receiving and receiving inspection to shipping inspection. In this article, we will introduce picking and shipping inspections, as well as inventory control scenarios. (Figure 5)

Figure 5 – Warehouse operation flow

3-1) Picking and shipping inspection
The shipping list (CSV file) output from the WMS (Warehouse Management System) is imported into the RFID reader terminal, and the picking target is selected on the reader terminal. After picking the cargo to be shipped from the shelves, the reader scans the picking target, and the results are instantly displayed on the screen to verify that the picking target is correct and that the required number of items have been scanned. By referring to the verification results, workers can confirm that they have not picked the wrong cargo, or picked more or less than the required quantity, without having to visually check each shipment one by one. As a result, it is possible to prevent erroneous shipments and reduce work time. (Figure 6)

3-2) Inventory Management
The inventory list (CSV file) output from the WMS is imported into the RFID reader terminal, and the area (shelf) to be inventoried (Cycle Count) is selected on the reader terminal. When the reader terminal scans the inventory on the target shelf, the results of verification are instantly displayed to confirm that the inventory target cargo in the selected area (shelf) exists on the list. The results are instantly displayed, allowing the user to check whether the inventory list and the quantity of the cargo actually on the shelves match, without having to check each item one by one. This can lead to a significant reduction in work time, increase the number of inventory counts, and help improve the accuracy of inventory quantity control. In addition, the use of long-range RFID reader terminals makes it possible to check cargo from ground level without having to climb to a high shelf, such as 10 meters (30 feet) above the ground, thus contributing to worker safety.

3-3) Cargo Search
The RFID Query application has a cargo search mode that uses the strength of radio reception from RFID tags. This allows the user to search for cargo that is not in the location specified by the WMS (Figure 6). Compared to the conventional method, which relies on intuition and experience to search for cargo, this system can significantly shorten the search time.

Figure 6 – RFID Query

By utilizing “RFID Query” with these features, the above-mentioned issues were resolved as follows.

Issue 1: Workload is heavy because each item is visually inspected and matched one by one
→ Batch matching by RFID shortens the inspection time and reduces the workload of workers.
Issue 2: Japanese on packages is unreadable by local employees, resulting in shipping inspection errors
→ The data matching function prevents inspection errors even if the text is unreadable.
Issue 3 Long hours of visual inspection work in refrigerated warehouses is burdensome
→ Batch collation using RFID shortens work hours and reduces workload.
Issue 4: A lot of time is spent going back and forth between the office and the warehouse
→ The same work can be performed by anyone, so work can be completed at the warehouse site.
Issue 5: Workers are frequently replaced, and the work level is not stable among workers
→ The same work can be performed by anyone, so the work quality level is stable.
Issue 6: Soaring labor costs
→ Curbing labor costs and overtime expenses by improving efficiency through shortened work hours.
Issue 7: It takes time to search for misplaced items
→ Search time is reduced by the search mode function.

4) Integrating with the Cloud
By uploading cargo data acquired by RFID reader terminals to the cloud to accumulate and visualize data, the following applications can be expected.

  • Utilized as asset management data to show which boxes are where and how many (MAP display available: Figure 7)
  • Utilized for demand forecasting as statistical data of increase/decrease of physical quantity
  • Utilized as evidence data to show the condition of goods at the time of shipment to users
  • Utilized for inventory management as inventory data that shows how much inventory has remained in the warehouse since it was received
  • Comparison of the original data in the cloud and the data actually read to prevent errors at the warehouse site
  • Real-time monitoring of warehouse operations from remote locations, including multiple warehouses, and use as a risk countermeasure when problems occur
Figure 7 – Mapping the location

By combining data obtained from RFID with visualization and analysis functions provided by the cloud, the potential for more multifaceted data use will expand. Based on user feedback and market trends, we will continue to develop cloud services that can be used in more situations.


In this paper, I introduce how to improve the efficiency of logistics warehouse floor operations by utilizing RFID, LiDAR, and cloud computing without modifying the existing system and in conjunction with the existing system, with case studies.
We try to implement our services in a short period of time to meet the user’s schedule, as little as three months, but we also take the time to clarify the user’s issues through consultation at the initial stage. (Figure 8) We share with the user what kind of operation they want to achieve in the end in the process from receiving to shipping, including not only issues that have already been clarified, but also issues that have not yet been clarified, and make various proposals for pain points that the existing WMS cannot provide. We will provide support and services that will ensure that improvements can be achieved in terms of actual operations.

Figure 8 – Implementation Steps

In addition to the usual one-time sales, subscription plans are available for all services to meet the needs of customers who want to start with a small investment. For example, the “RFID Query” service can be introduced at a monthly fee of $270/RFID Reader (for a contract of 5 RFID Readers).

Our slogan is “Committed to solving logistics crises.” We understand the importance of logistics, are attentive to the issues faced by logistics sites, and will contribute to improving the corporate value of our users with optimal technological solutions.