Vol. 79, No. 3, May 2024

Special Reports

Logistics Automation Solutions for Evolution of Entire Supply Chain



Lately, Japanese industries in the logistics sector  face various issues including compliance with regulations to shorten the long working hours of truck drivers, labor shortages accompanying a declining birthrate and an aging population, and the increasing volume of goods in small lots driven by e-commerce transactions, notwithstanding their role in maintaining a stable supply chain through transportation. This situation underscores the growing need to ensure sufficient labor to handle such heavy workloads.

The Toshiba Group has taken the initiative in constructing cyber-physical systems (CPS), including automated equipment capable of replacing or supporting personnel in physical distribution warehouses, and a warehouse execution system (WES) enabling personnel to collaborate with machines such as robots, under the banner of “best matching between personnel and machines.” We are currently making efforts to promote further automation of physical distribution operations and to create and provide new value to customers and society.


With the increasing burden on workers in physical distribution warehouses, there is a strong need to introduce automated processes for picking a high volume of goods from shelves and for streamlining work. 

To maximize physical distribution warehouse operational throughput where automated guided vehicles (AGVs) are being used, Toshiba Corporation has developed two optimization technologies for pod transport robot systems capable of automatically transporting dedicated shelves, known as pods, to each work station: (1) pod processing order technology, and (2) AGV plan optimization technology. We have constructed a new pod transport robot system incorporating prototype engines using these technologies at a customer site and have confirmed their effectiveness via actual operations, showing that they can improve shelf picking efficiency by 10%, and can reduce waiting time at shelves by 19% compared with the conventional system.

IWASAKI Toshio / WADA Yusuke / KONDA Kazunobu

In recent years, it has become increasingly important to reduce the burden on workers in the physical distribution domain due to ever more complex business operations accompanying the expansion of e-commerce and workforce shortages. As it is difficult to fully automate picking tasks to handle various types of goods in terms of recognizing and grasping, there is growing demand for labor-saving solutions through the collaboration of robots and workers.

Toshiba Infrastructure Systems & Solutions Corporation has developed an intelligent picking robot system that delivers portability and availability, and is capable of operating in cooperation with workers in response to continuously changing worker allocation in a physical distribution warehouse. Regarding portability, the use of a collaborative robot arm and safety laser sensors eliminate the need for safety fences, reducing the footprint by 92% compared to conventional systems. Regarding availability, the introduction of a recovery processing function, etc. is expected to achieve a business continuity rate of 99.999% in the event of picking work failure. We are now conducting verification tests using a prototype system.

FUJIOKA Kentaro / IWABUCHI Yuta / YOSHIDA Takufumi

Following enforcement of regulations limiting overtime work for truck drivers, Japanese industries in the logistics sector face critical issues, including transportation disruption and labor shortages. To transport the increasing volume of goods swiftly and efficiently, it is necessary to decrease truck wait times at berths through operational collaboration at physical distribution warehouses.

The Toshiba Group has developed technology that makes it possible to allocate the optimal loading berth from among multiple berths and optimize truck loading timing in consideration of warehouse operations. This technology can also optimize complicated situations based on whether there is a need to load goods at multiple buildings, etc. Comprehensive evaluations show that it can decrease wait times between one-fourth and one-eighth of the benchmarking technology. The technology is now available as a function in the LADOCsuite/WES warehouse operation optimization service.

MATSUMURA Atsushi / MATSUO Takuya / WANG Yacheng

With logistics industries facing a critical labor shortage in recent years, the pace of introducing automated equipment in various operation processes at physical distribution warehouses has been accelerating. To improve the efficiency of such processes, it is essential to coordinate automated equipment operations in each process to avoid delays in work schedules, which can lead to interruption of operations, as well as to assigning difficult tasks, which are not suitable for automated equipment, to workers as needed. 

The Toshiba Group has developed a warehouse execution system (WES) to enhance the operational efficiency of automated equipment while balancing tasks by workers via the following: (1) an integrated progress management function for both automated equipment and workers, and (2) a function to optimize task assignments. We have conducted evaluation experiments using actual operational data obtained at physical distribution warehouses and confirmed that the above functions can enhance the delivery throughput.

Feature Articles

ONO Soichiro / FUU Shimou / FURUHATA Akio

Various businesses use optical character recognition (OCR) systems, and improving accuracy of extracting information from various business forms, such as semi-structured forms, is increasingly required to deal with labor shortages and to streamline work. The trend of applying the latest artificial intelligence (AI) technologies in OCR systems has accelerated recently, however, the higher development costs for finetuning processes of AI models are serious issues.

Toshiba Digital Solutions Corporation is developing a technology to recognize semi-structured forms by adopting AI language models to its existing AI-OCR service. Our experiments on entity extraction of substrings from the results of recognized strings have confirmed that it achieves extraction accuracy comparable to that of existing methods while saving on advance preparations. In the future, we will consider applying generative AI to allow users to easily customize this technology.


Cables installed in an electrical product play a key role in the transmission of electrical signals and electricity between product constituent components. If a cable connected to moving mechanical parts of the component deteriorates due to repeated bending, it could result in cable disconnection. Because long-term testing is required, it is difficult to confirm whether disconnection occurs during the operating lifetime via prototype testing , so selection of both durable wire material and appropriate cable routing at the cable design phase is essential to improve product development efficiency.

With this in mind, Toshiba Tec Corporation has developed technology capable of predicting the number of bending cycles leading to fracture and/or disconnection of cables in products through the application of a numerical analysis method that takes into consideration cable bending operation stopping time. This technology has been applied to actual product development and is significantly contributing to improving bending durability.

YAMADA Keiju / HOMMA Toru / SHIBUYA Takashi

Bluetooth® Low Energy modules can be used in a wide variety of applications including wireless communication functions for Internet of Things (IoT) devices. Antenna-integrated wireless modules certified by radio laws in various countries can be easily introduced in many different devices without the need for expertise in wireless technologies. The footprint of devices incorporating these modules, however, tends to increase due to a larger printed circuit board (PCB) to suppress electromagnetic interference between the antenna and surrounding wiring patterns on the PCB, resulting in larger end products.

Toshiba Corporation has found a solution by developing a proprietary slot antenna on shielded package technology, called SASP. and has provided samples of compact Bluetooth® Low Energy modules with SASP (hereafter referred to as “SASP module”) since 2021. Furthermore, we developed a new SASP module that achieves the world’s smallest board footprint of 35 mm2 with an improved antenna design in 2023. This module is suitable for wearable devices, human interface devices, industrial sensor devices, etc. due to narrow wiring-prohibited areas as well as a highly flexible wiring route and component layout. It can also provide users with open software development environments to enable efficient design of various devices.


The Toshiba Group has developed a Simulated Bifurcation Machine (SBM) equipped with a proprietary algorithm acquired through development of quantum computers. The SBM makes it possible to quickly solve combinatorial optimization problems which frequently arise in social and industrial settings.

Since 2019, we have promoted the expanding SBM application in the financial field to implement trading and investment strategies by solving complex and sophisticated combination optimization problems that were considered difficult to solve within a realistic time frame. We have developed a method to optimize stock portfolio investment strategies as an SBM application to financial products. We have also conducted simulation tests using actual historic market data and confirmed the effectiveness of this method, showing that the computation speed is 6 230 times faster than a conventional solver while achieving over 95% accuracy. 


To enhance wind farm power generation efficiency, the layout of each wind farm turbine must be adjusted to increase the total annual energy production (AEP) while taking into consideration the constraints on distances among multiple wind turbines. Installations in mountainous areas with complex terrain necessitate time-consuming wind condition analyses in order to calculate design parameters such as total AEP, making it difficult to find an appropriate layout via manual adjustments through trial and error in a limited period of time.

To rectify this situation, the Toshiba Group has developed a new design method using machine learning to optimize wind farm turbine layout by estimating wind condition analysis results. We have conducted simulation experiments using actual data and confirmed that this method can automatically find a layout with a maximum total AEP that is about 33% higher than that of the conventional manual method whereas the conventional method could not satisfy the constraints even in three hours.


The trend toward application of collagen materials in areas of advanced medicine, including regenerative medicine and precision medicine, has accelerated recently with the goal of practical application.

Toshiba Corporation has developed the following two types of collagen nanofiber sheets fabricated using an electrospinning (ES) technique: (1) a transplantation sheet that replicates three-dimensionally oriented structure of living tissues while achieving excellent handleability and biocompatibility through proprietary fiber adhesion treatment, and (2) a sheet for early-stage cancer diagnosis, which cultures cancer cells and visualizes the gene activities in living cells. Experiments on prototype samples have verified that the former type of sheet transplanted into mice is effective in suppressing skin flap necrosis and the latter type of sheet thinly formed on the surface of an image sensor can observe living breast cancer cells with high engraftment rate. We are now actively promoting the practical application of these collagen nanofiber sheets.

Frontiers of Research & Development

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*Company, product, and service names appearing in each paper include those that are trademarks or registered trademarks of their respective companies.