Smart Cognitive HMI With Automated Knowledge Extraction for Machine Tool - Jongsu Park; Jinho Son; Seongwoo Cho; Jumyung Um (IEEE Access)
In the field of machine tools, it is general to use facilities from various vendors with different interfaces. However, manuals that vary from machine to machine and are less portable and usable, are adding the burden. In this case, the digital intelligent assistant can be used as an easy and unified interface to communicate with users and increase work efficiency. However, applying a digital assistant requires a large amount of dataset and effort separately, and there is a limitation that it only plays a role in a specific situation designed. In this paper, we propose a smart and cognitive chatbot with a dataset-constructing pipeline to solve the problems. The proposed pipeline aims to build a dataset and update source data for the chatbot automatically. It provides relevant manual context, machine status, current operation, and operation sequence, depending on the users’ intention. It utilizes various AI technologies including optical character recognition, reinforcement learning, and natural language preprocessing technologies to minimize human intervention in the dataset construction. Also, it can be applied to various heterogeneous facilities with different interfaces. Thanks to the proposed data extraction pipeline, the proposed chatbot interacts with users intuitively using conversational language, replacing cumbersome manipulation and unusable documentation. In the paper, one of the equipment, commonly used in the real world, is chosen to be applied the proposed system to the chosen facility, dealing with possible problems during the operation.