Notice of our van master exhibition at 【MFLP ICT LABO 2.0】.

Improvement of loading for parts transportation using the TP box loading improvement system.

The TP Box Loading Improvement System is a system (algorithm) designed to maximize the loading efficiency of pallet transportation for products utilizing TP boxes. The TP boxes have standardized blocks of the same size on their bottom surface, and by combining the interlocking parts of these blocks, different sizes of TP boxes can be loaded onto a pallet. However, combining TP boxes of different sizes to increase the loading efficiency on a pallet has been very challenging and could only be handled by skilled workers. The newly developed TP Box Loading Improvement System allows for multi-layer stacking of pallets by ensuring that the top layer is flat, and enhances work efficiency by consolidating containers of the same size, enabling even those with less experience to achieve a high level of loading efficiency.

• Scientific Calculation and Simulation Software
• Other Software

Automatically create loading plans that minimize dead space. Presentation of materials introducing features and improvement examples. Trial version available.

"Banning Master" is a system that visualizes cargo based on size information and creates loading plans considering weight balance, constraints, and workability. It optimizes loading efficiency for containers, trucks, pallets, etc., and can flexibly respond to additions or cancellations of cargo. It can also be used to identify bottlenecks and continuously improve loading efficiency. We offer a "software version" that can be tailored to your business needs and a "cloud version" that requires no installation. 【Features】 ■ Automatically calculates and visualizes highly efficient loading plans ■ Properly calculates the center of gravity, preventing cargo shifts and contributing to improved transport quality ■ Many successful implementations in automotive parts, electronics, food, and building materials manufacturers ■ Capable of providing algorithms that consider loading rules ★ We are currently offering materials that include examples of improvements in import and export of goods. You can view them immediately via "PDF Download." * A trial version of the cloud version (10 days) is also available. Please contact us for more details.

• Other Software
• Logistics and warehouse management systems

Visualization of logistics sites" "Reduction of working hours at logistics sites

The loading software has many implementation cases from logistics companies to manufacturers, and the effects of its introduction are significant. ● The reasons are... - Shipment size, weight, and quantity are managed in-house. - With the cooperation of the information systems department (IT), data can be linked with the loading software, allowing for calculations to be made repeatedly. - It is possible to determine increases or decreases in shipment volume based on remaining space [important]. - Time can be saved compared to inquiries to freight forwarders. ■ Current Implementation Site A logistics company of a certain food manufacturer group. ■ On-site Challenges - Want to immediately answer questions like "How many containers?", "What types of containers?", and "What is the remaining space?" - Want to maximize loading during imports from China and provide loading instructions to the Chinese side. - The loading rules for products (packaging) are either unknown or have become unclear due to being overly reliant on specific individuals. ■ Operations/Requirements - Which products and how many will be loaded into the remaining space? - Heavy items should be loaded on the bottom tier.

• Other Software

It is possible to develop special loading conditions as a dedicated algorithm.

In building material manufacturers, heavy building materials are loaded onto trucks after creating a load plan, taking safety and workability into consideration. Before the introduction of the Vanning Master, multiple office employees planned using Excel (including the creation of work diagrams) while considering constraints related to safety, workability, and unloading. By developing a unique algorithm that takes into account constraints related to loading, we have successfully significantly reduced these administrative tasks. The optimization of space utilization through the algorithm generally aims to increase the loading (filling) rate as the primary objective. Prioritizing workability made it very challenging to develop, as the evaluation metrics for the results of the algorithm became ambiguous. The development of the algorithm for building material manufacturers was made possible by our consultants, who understood the field and conducted detailed interviews to clarify the operational rules and metrics involved in the work.

• Other Software

Determination of packaging box dimensions for new products" "Pattern development for pallet stacking

"Palette Master" is a system that proposes the most efficient way to stack on a pallet. It is a convenient optimization tool useful for single-item loading, such as "I want to switch to T11 type pallets," "Determining the dimensions of new product packaging boxes," and "Warehouse transfer." "Palette Master" is dedicated stacking software for pallets. It is not a plugin for Vanning Master. Since customization is necessary to match the logistics site conditions, we will submit a quotation after hearing about the situation. ■ Implementation Effects 1) Instantly simulates based on pallet size and product size, displaying multiple optimal loading patterns. You can choose a loading pattern suitable for storage or transportation purposes. 2) With Palette Master, centralized management of information regarding loading across various departments from the development of new containers is possible. - It allows consideration of optimal loading during the container development stage. - Centralizing the database makes information sharing easier. - Authority management is realized by dividing general users, administrators, and viewers.

• Other Software

Fare reduction, automatic selection of packaging boxes, work efficiency improvement.

■Do you have any of these concerns? 1) The variety of outer box types makes selecting the appropriate box a challenge directly linked to shipping costs. 2) There is a discrepancy in box selection accuracy between experienced and new employees, causing shipping personnel to struggle with box selection and feel stressed. 3) It is impossible to know the number of boxes needed until packing is attempted, making it difficult to prepare boxes and shipping labels in advance. These concerns can be resolved with the introduction of the Vanning Master Box Packing BOX Engine. ■Benefits of Implementation 1) Automatically suggests the smallest cardboard box that fits the three dimensions of the shipping item, aiming to reduce shipping costs. 2) By linking with the inventory management system and printing box information on shipping instructions such as picking lists, the worries about box selection are eliminated. 3) Knowing the number of boxes needed at the shipping planning stage allows for box preparation, packing details, shipping labels, and delivery slips to be issued at the order stage. 4) Shipping cost calculations can be done at the order stage. 5) It becomes easier to consider reducing or introducing new types of cardboard boxes.

• Other Software

White Logistics," "Reduction of Overtime Hours," "Improvement of Services to Shippers

■Objective As part of business improvement, create a vanning plan using a loading simulation tool to reduce work time. ■Challenges 1) Data Input - Support for converting shipping request forms (PDF) from shippers into Excel data. - Provided an Excel macro to reduce data entry workload. 2) Loading Diagram - Standard features are provided, but we also respond to requests for modifications. 3) Manual Placement Operations - Does not match the expertise of seasoned professionals. ⇒ Addressed with the manual placement modification feature of the standard package. 4) Manual Placement Operations - Seasoned professionals are not skilled with mouse operations. ⇒ An assistant creates the loading diagram under the guidance of seasoned professionals, enabling the transfer of expertise.

• Other Software

From personalization to standardization! Reducing work time!

■Objective To reduce the workload of the planning staff and shorten the time required for creating loading diagrams ■Operation/Requirements ・Maximize loading volume within the constraint of a maximum load weight of 5 tons ・Develop a weekly shipping plan *Loading for one day can be advanced by day of the week ・Automate the creation of loading diagrams ■Implementation Effects ・Tasks that were previously dependent on individuals can now be handed over to multiple people ・Reduction in the time required for planning and creating loading diagrams, from a total of 4 hours over several days to just 30 minutes

• Other Software

We are pleased to announce the archive distribution of our seminar titled "New Plan 'Mojitori Plus' Debuts! From Paper to Data! The First Step Towards In-House DX with Mojitori." 'Mojitori' allows you to convert text from photos, images, PDF files, and more into data, automatically inputting it into various fields in kintone. In this seminar, we will clearly explain the basic functions and usage of Mojitori. Additionally, we will provide detailed explanations about the Plus plan and the document-focused Mojitori, which were added in the major update in November. 【Recommended for】 - Those who are struggling with frequent transcription errors due to manual data entry. - Those who wish to digitize items currently stored on paper. 【Timetable】 - Overview of Mojitori's functions - Overview of Mojitori Plus's functions - Details and pricing of each plan - Q&A session We look forward to your registration.

Is the performance report you are currently creating, which takes a tremendous amount of time and effort, appreciated by the management? Are you facing complaints from management such as: - The reports are coming out late (results from the previous month are reported around the 20th of the current month) - The reports are difficult to understand and hard to read - There is missing necessary information In this seminar, we will introduce a new system for managing performance information that addresses these issues, along with specific methods. The cost is free. We encourage you to participate. □ Seminar Content 1. What is performance improvement? 2. What information is useful for performance improvement? 3. How to view performance information 4. A system for automatically generating performance information and accessing necessary information when needed (Using our company's developed performance information management tool as a model)

Holding a management strategy seminar to "embed" generative AI and connect it to organizational outcomes! Are you facing challenges such as "not knowing how to use it," "lack of progress in utilization," or "not being embedded due to organizational rules and management" while advancing AI implementation? In this seminar, we will thoroughly explain the secrets to realizing an organization where AI operates autonomously, drawing from the generative AI training of Panhouse Co., Ltd. and the management methods of Shikigaku Co., Ltd. In particular, we will share specific case studies of the "Agent Model AI," which is gaining attention as a next-generation AI application, along with organizational design know-how for integrating generative AI into business, management pitfalls that hinder embedding, and their solutions, all accompanied by concrete examples. What you can learn in this seminar: - Experiences and case studies of Agent Model AI (exabase generative AI demo) - Initial preparations and design know-how to accelerate AI utilization - Key management points to break down organizational barriers that hinder AI embedding If you are in management or responsible for ensuring that generative AI becomes a "truly usable" system rather than just "trying it out," we encourage you to participate in this opportunity.

We are pleased to announce that Pan House Co., Ltd. will be participating in the online marketing conference "Data Driven Marketing 2026," which will be held from January 14 (Wednesday) to 16 (Friday), 2026. At this event, where professionals achieving results at the forefront will gather, our Chief Integration Officer, Tsubasa Kimura, will explain the new organizational approaches utilizing AI. Organizational Theory for "Maximum Effect with Minimal Effort" in the AI Era As AI technology rapidly evolves and the marketing environment changes significantly due to cookie regulations, relying on "past success experiences" and "intuition and experience" is reaching its limits. In this session, we will focus on how to utilize AI not just as a tool, but as a strategic infrastructure to build competitive advantages for organizations. We will discuss specific examples and methods on how to maximize the efficiency of marketing operations and establish an organizational structure that leads to results with minimal effort.

"Where should we start with AI implementation, and how can we expand it company-wide?" The reason for the slow progress in AI implementation is not the tools themselves. The key lies in project design that encompasses everything from creating guidelines to establishing a promotion system and turning success stories into models. In this webinar, we will systematically explain the types of AI implementation projects that successful companies practice to overcome the "zero-to-one barrier" and the "utilization promotion barrier." Both companies that have not yet implemented AI and those that are stagnating in their utilization will gain clarity on their respective starting points and take home actionable "answers at the action level" that can be executed starting tomorrow in just 60 minutes. Recommended for those facing the following challenges: This webinar is ideal for individuals in departments at the level of section chief or higher who want to promote AI implementation as a project. Companies that do not know how to "start" AI implementation (zero-to-one stage) Companies that have implemented generative AI but are experiencing stagnation in its utilization Companies lacking a driving force or where the initiative is not moving forward, struggling with individualization and the lack of established training Companies that are looking to expand company-wide but are unclear on how to horizontally deploy Companies considering the introduction of AI training (especially in the pre-approval stage)