Citation: Trappey, A.J.C.; Trappey,
C.V.; Chao, M.-H.; Hong, N.-J.; Wu,
C.-T. A VR-Enabled Chatbot
Supporting Design and
Manufacturing of Large and
Complex Power Transformers.
Electronics 2022, 11, 87.
https://doi.org/10.3390/
electronics11010087
Academic Editors: Răzvan
Gabriel Boboc, Radu Godina,
Albert Smalcerz and
Dimitris Mourtzis
Received: 14 December 2021
Accepted: 24 December 2021
Published: 28 December 2021
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electronics
Article
A VR-Enabled Chatbot Supporting Design and Manufacturing
of Large and Complex Power Transformers
Amy J. C. Trappey
1,
*, Charles V. Trappey
2
, Min-Hua Chao
1
, Nan-Jun Hong
1
and Chun-Ting Wu
1
1
Department of Industrial Engineering and Engineering Management, National Tsing Hua University,
Hsinchu 300, Taiwan; s106034803@m106.nthu.edu.tw (M.-H.C.); s107034531@m107.nthu.edu.tw (N.-J.H.);
s108034530@m108.nthu.edu.tw (C.-T.W.)
2
Department of Management Science, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan;
trappey@nycu.edu.tw
* Correspondence: trappey@ie.nthu.eu.tw; Tel.: +886-3572-7686
Abstract: Virtual reality (VR) immersive technology allows users to experience enhanced reality
using human–computer interfaces (HCI). Many systems have implemented VR with improved HCI
to provide strategic market advantages for industry and engineering applications. An intelligent
chatbot is a conversational system capable of natural language communication allowing users to
ask questions and receive answers online to enhance customer services. This research develops
and implements a system framework for a VR-enabled large industrial power transformer mass-
customization chatbot. The research collected 1272 frequently asked questions (FAQs) from a power
transformer manufacturers’ knowledge base that is used for question matching and answer retrieval.
More than 1.2 million Wikipedia engineering pages were used to train a word-embedding model for
natural language understanding of question intent. The complex engineering questions and answers
are integrated with an immersive VR computer human interface. The system enables users to ask
questions and receive explicit and detailed answers combined with 3D immersive images of industrial
sized power transformer assemblies. The user interfaces can be projected into the VR headwear or
computer screen and manipulated with a controller. The unique immersive VR consultation chatbot
system is to support real-time design consultation for the design and manufacturing of complex
power transformers.
Keywords: intelligent chatbot; virtual reality; smart manufacturing; power transformer
1. Introduction
Large-size industrial power transformers are complex static engineering systems used
for electrical power distribution to step-up voltages for transmission from power plants or
distribution centers and step-down voltage levels for receiving power at end user factories,
manufacturing centers, or large building complexes. A high degree of customization is
required for complex industrial-grade machinery design and manufacturing of transform-
ers due to their extensive use in all aspects of construction including large ships, wind
farms, factories, large medical centers, and even shopping malls. In order to provide remote
customers with highly customized machinery designs and quotations, engineering consul-
tation services during the processes of procurement are critically important. This research
develops a generic methodology and system framework for building a Virtual Reality
(VR) enabled intelligent engineering consultation Chatbot system. The customer-driven
transformer consultation Chatbot prototype with VR as an improved Human Computer
Interface (HCI) is demonstrated using a case example in Section 4.
Request for Quotation (RFQ) is a process where an enterprise or public entity releases
purchase specifications for the manufacturing, design, and services for a product or service
to a qualified vendor. Vendors then tender bids in response to the request, which often
requires interaction and negotiations over key components, customization, services, and
Electronics 2022, 11, 87. https://doi.org/10.3390/electronics11010087 https://www.mdpi.com/journal/electronics