LIGHTz Product Lineup

For Boilers: The General Knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger members and those from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortened lead time for trouble response.

• others

For heat exchangers: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a "knowledge infrastructure" for companies. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing searches and references not only for "what was judged" but also for "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early risk detection. - Shortening of lead time for troubleshooting responses.

• others

For piping equipment: General-purpose AI accumulates the tacit knowledge of experts naturally from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger staff and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to troubles based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searching but also understanding "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For compressors: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] - Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allow younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Respond quickly to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of previously personalized judgment criteria. - Utilization of knowledge that not only allows for search but also understanding of "why." - Reduction of rework through early detection of risks. - Shortened lead time for troubleshooting responses.

• others

For valve applications: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing for searches and references not only on "what was judged" but also on "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger members or those from other departments to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to troubles based on similar cases and countermeasures 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For pumps: The general knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time for trouble response.

• others

For Motors: The General Knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger members or those from other departments to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response during trouble occurrences based on similar cases and countermeasure proposals 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For power supply devices: The general-purpose AI for manufacturing is a specialized organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, allowing it to be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, enabling searches and references not only for "what was judged" but also for "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Quickly responding to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times for trouble response.

• others

Analysis Machine Target: Generalized AI is a manufacturing industry-specific organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, enabling it to be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during trouble response. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allowing younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Rapid response during trouble occurrences based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For optical equipment: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time in troubleshooting responses.

• others

For medical device components: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during troubleshooting. 【Usage Scenarios】 - Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allow younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Respond quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 - Visualization and inheritance of previously personalized judgment criteria. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortened lead time for troubleshooting responses.

• others

For sensor manufacturers: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For industrial sensors: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Responding quickly during trouble occurrences based on similar cases and countermeasure proposals. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times for trouble response.

• others

For solar cells: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for companies. It is a specialized organizational knowledge AI platform for the manufacturing industry. By structuring the experiences and judgment criteria of veterans from internal documents and conversation records, it allows users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before veterans retire or transfer. - Allowing younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when troubles arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that were previously personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times for trouble response.

• others

For power equipment: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and the presentation of similar cases during trouble response. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when troubles occur. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searching but also understanding "why." - Reduction of rework through early detection of risks. - Shortening of lead times for trouble response.

• others

For gas equipment: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It includes AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger members or those from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to troubles based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead times for trouble response.

• others

For petrochemicals: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allow younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Respond quickly to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that were previously personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time in trouble response.

• others

For electronic materials: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a "knowledge infrastructure" for companies. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when troubles occur. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time for trouble response.

• others

For semiconductor materials: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing for searches and references not only on "what was judged" but also on "why it was judged that way." It is equipped with AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Utilization Scenarios] - Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allow younger or members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Quickly respond to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time for trouble response.

• others

For battery materials: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time in trouble response.

• others

For paint: The general knowledge AI for manufacturing is a specialized organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, allowing it to be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, enabling searches and references not only for "what was judged" but also for "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during trouble response. [Usage Scenarios] ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to issues based on similar cases and countermeasures when problems arise [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For rubber products: The general-purpose AI for knowledge management naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during troubleshooting. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times for troubleshooting responses.

• others

For cement: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as the company's "knowledge infrastructure." It structures and stores the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortened lead time for trouble response.

• others

For pulp: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing for searches and references not only on "what was judged" but also on "why that judgment was made." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during troubleshooting. [Usage Scenarios] ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response during trouble occurrences based on similar cases and countermeasures [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized ■ Knowledge utilization that not only allows for searches but also understanding of "why" ■ Reduction of rework through early risk detection ■ Shortening of lead time in trouble response

• others

For the paper industry: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for manufacturing that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allow younger members or those from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Respond quickly to troubles based on similar cases and countermeasures. [Implementation Effects] - Visualization and inheritance of previously personalized judgment criteria. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time in trouble response.

• others

For marine equipment: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during troubleshooting. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 - Visualization and inheritance of previously personalized judgment criteria. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times for troubleshooting responses.

• others

For shipbuilding machinery: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was decided" but also "why that decision was made." It includes AI agent functions that address various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past decision-making bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasure proposals. 【Implementation Effects】 ■ Visualization and inheritance of previously personalized judgment criteria. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For railway vehicles: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during troubleshooting. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For aircraft: The general-purpose AI for manufacturing is an organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, enabling it to be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when troubles arise. 【Implementation Effects】 - Visualization and inheritance of judgment criteria that were previously personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead time for trouble response.

• others

For precision machining: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to troubles based on similar cases and countermeasures [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For AI machines: The General Knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Identify risks early from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time in trouble response.

• others

For Robotics: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For Autonomous Driving: The General Knowledge AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For EV components: The general-purpose AI accumulates the tacit knowledge of experts naturally from daily operations and conversations, and serves as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger or other department members to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that were previously personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For environmental devices: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly to issues based on similar cases and countermeasures when problems arise. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searching but also understanding "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for troubleshooting responses.

• others

For inspection devices: Generalized AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of business, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Quickly responding to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilizing knowledge that not only allows for searches but also explains "why." - Reducing rework through early detection of risks. - Shortening lead times for troubleshooting responses.

• others

For electronic equipment assembly: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and the presentation of similar cases during troubleshooting. [Usage Scenarios] ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searching but also understanding "why." ■ Reduction of rework through early risk detection. ■ Shortening of lead time for trouble response.

• others

For resin molding: The general-purpose AI for knowledge management naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a "knowledge infrastructure" for companies through a manufacturing industry-specific organizational knowledge AI platform. It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger employees and members from other departments to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to issues based on similar cases and countermeasures when problems arise [Implementation Effects] ■ Visualization and inheritance of judgment criteria that were previously personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for troubleshooting responses

• others

For sheet metal processing: The general-purpose AI for knowledge accumulation naturally gathers the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a "knowledge infrastructure" for companies. It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. 【Usage Scenarios】 ■ Preserving judgment criteria and experiential knowledge before the retirement or transfer of veterans ■ Allowing younger employees and members from other departments to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to issues based on similar cases and countermeasures when problems arise 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for troubleshooting responses

• others

Welding-oriented: The general knowledge AI for manufacturing is a specialized organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, enabling it to be utilized as the company's "knowledge infrastructure." It structures and accumulates the experiences and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] ■ Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Rapid response to issues based on similar cases and countermeasures when problems arise [Implementation Effects] ■ Visualization and inheritance of previously personalized judgment criteria ■ Utilization of knowledge that not only allows for search but also understanding of "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time for trouble response

• others

For forging: The general knowledge AI for manufacturing is a specialized organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, enabling it to be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before veterans retire or transfer. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to troubles based on similar cases and countermeasures. [Implementation Effects] - Visualization and inheritance of judgment criteria that were previously personalized. - Utilization of knowledge that not only allows for searches but also explains "why." - Reduction of rework through early detection of risks. - Shortening of lead times in trouble response.

• others

For casting: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a manufacturing industry-specific organizational knowledge AI platform that can be utilized as a company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions that address various aspects of operations, such as risk detection in project documents, linked searches between 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger employees and members from other departments to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Rapid response to issues based on similar cases and countermeasures when troubles arise. [Implementation Effects] - Visualization and inheritance of judgment criteria that had become personalized. - Utilization of knowledge that not only allows for searching but also understanding "why." - Reduction of rework through early risk detection. - Shortening of lead time for trouble response.

• others

For molds: General-purpose AI accumulates the tacit knowledge of experts naturally from daily operations and conversations, serving as a "knowledge infrastructure" for companies through a manufacturing-focused organizational knowledge AI platform. It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why that judgment was made." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches between 3D drawings and knowledge, and presenting similar cases during trouble response. 【Usage Scenarios】 ■ Preserve judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. ■ Allow younger employees and members from other departments to independently search and reference past judgment bases. ■ Early identification of risks from project documents during the design and production preparation stages. ■ Respond quickly during trouble occurrences based on similar cases and countermeasures. 【Implementation Effects】 ■ Visualization and inheritance of judgment criteria that had become personalized. ■ Utilization of knowledge that not only allows for searches but also explains "why." ■ Reduction of rework through early detection of risks. ■ Shortening of lead time for trouble response.

• others

For FA machines: General-purpose AI is a manufacturing industry-specific organizational knowledge AI platform that naturally accumulates the tacit knowledge of experts from daily operations and conversations, enabling it to be utilized as the company's "knowledge infrastructure." It structures and accumulates the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during trouble response. [Usage Scenarios] ■ Preserving judgment criteria and experiential knowledge before the retirement or transfer of veterans ■ Allowing younger or other department members to independently search and reference past judgment bases ■ Early identification of risks from project documents during the design and production preparation stages ■ Quickly responding to issues based on similar cases and countermeasures when problems arise [Implementation Effects] ■ Visualization and inheritance of judgment criteria that had become personalized ■ Utilization of knowledge that not only allows for searches but also explains "why" ■ Reduction of rework through early detection of risks ■ Shortening of lead time in trouble response

• others

For industrial robots: General-purpose AI naturally accumulates the tacit knowledge of experts from daily operations and conversations, serving as a specialized organizational knowledge AI platform for the manufacturing industry that can be utilized as a company's "knowledge infrastructure." It structures and stores the experience and judgment criteria of veterans from internal documents and conversation records, allowing users to search and reference not only "what was judged" but also "why it was judged that way." It features AI agent functions tailored to various aspects of operations, such as risk detection in project documents, integrated searches of 3D drawings and knowledge, and presenting similar cases during troubleshooting. [Usage Scenarios] - Preserving judgment criteria and experiential knowledge as knowledge before the retirement or transfer of veterans. - Allowing younger or other department members to independently search and reference past judgment bases. - Early identification of risks from project documents during the design and production preparation stages. - Quickly responding to issues based on similar cases and countermeasures when problems arise. [Implementation Effects] - Visualization and inheritance of previously personalized judgment criteria. - Utilizing knowledge that not only allows for searches but also explains "why." - Reducing rework through early detection of risks. - Shortening lead times for troubleshooting responses.

• others