Crop Price and Yield Prediction Model by Functional Principal Component Analysis (2013.1 ~ 2013.12)
Funded by 2013 Technology Project of Ministry of Economic – Digital Convergence Service Platform R&D project(4/4), PI
This project aims at developing a crop price and yield prediction model to provide a more adaptive crop planning for Taiwan local framer. In this project, two kinds of datasets will be collected: 1) the market price and yield of crop in Taiwan, 2) relevant climate information. By utilizing the statistical methods and machine learning techniques on analyzing the collected data, a mathematical model will be built to predict crop price and yield. The data analysis tool, functional principal component analysis (FPCA), will be developed to search the representative independent factors for the prediction model. The production result will be used to search price and yield patterns which can form the complementary crop group for the more flexible cultivation planning.
A Study of Using Big Data Analytic Tools for Improving the Operating Performance in Manufacturing/Retailing (2013.4~2013.12)
Funded by 2013 Technology Project of Ministry of Economic – III Innovative Advanced Technology Project (1/1) , Co-PI（PI is Dr. James Chen, Industrial Engineering and Management, NTHU）
Manufacturing industry sector is one of major Big Data owners because great volumes of data such as product R&D documents, drawings, equipment status, production dispatching, shop floor data collection, labor management, Work-In-Process status, quality management, performance analysis, product tracking, and finance information are generated rapidly during the product development and production process. How to extract the knowledge from the collected Big Data during manufacturing process to improve the productivity is an important research topic. Furthermore, due to the nature of manufacturing industry, how to reveal the value of utilizing the Big Data by analytical models to enhance the operating performance toward the better intelligent business is also the major concern of applying Big Data analytic in manufacturing. In this research, through literature review, academic-industry interaction and data collection, we plan to investigate the needs of implementing Big Data analytics tools in manufacturing. The appraisal of the existing analysis tools will be conducted to find the appropriate analystics methods especially for analyzing the manufacturing Big Data. By collaborating with the industrial alliance, the implementation domain will be determined to demonstrate the preliminary study of applying the Big Data analytics tool in manufacturing.
A Study of Open Innovation Technology (2014.4~2014.12)
Funded by 2013 Technology Project of Ministry of Economic – Big SMART Service System and Open Innovative Project(1/4) ，PI（Co-PI is Dr. Cheng-Jhe Robert Chen, Industrial Management, NTUST）
Cultural and Creative Park is a recreational campus which usually consists of exhibition, gallery, show room, movie theater, and multi-function facility to provide the cultural activities. Besides, in the Cultural and Creative Park, restaurants, coffee shops, bookstores, gift shops, and other business units are nearby. How to improve the customer experience in the Cultural and Creative Park is an important research question for the managerial division to promote culture industries. In this research, we plan to apply Persuasive Technology integrated with Recommendation system to design a tour-guide model to provide the better guidance for exploring the Cultural and Creative Park. The first stage of this research will focus on data collection by delivering questionnaires, and time study on the field to understand the customers’ behavioral patterns. Based on the data analysis results, we will apply persuasive technology to develop a guideline for visiting Cultural and Creative Park. The second stage of this research will focus on developing the recommendation module which can be implemented on the digital signage or smartphone App softare that can be downloaded in advance before customer visit the park. The recommendation module will be utilized in the electronic device to deliver the persuasive information for customers to obtain higher the service satisfaction.
Investigation of Users’ Needs and Future Service in 3D Printing (2014.5~2014.11)
Funded by 2013 Technology Project of Ministry of Economic – III Innovative Advanced Technology Project，Co-PI（PI is Dr. Cheng-Jhe Robert Chen, Industrial Management, NTUST）
The introduction of 3D printing technology has become quick and innovative manufacturing options for its provision of material- and time-saving process. However, existing service gaps hinders its popularity to spread among general public including individual and family users. The lack of knowledge in this gap needs an investigation for both makers (experienced users) and novice users to construct complete behavioral models so that the service gap can be eliminated by comparing the two behavioral models and providing solutions for difference in motivation, knowledge and skills. This projects aims to utilize contextual interview, field observation, think aloud and questionnaires to extract makers and novice users’ behavioral models in six categories: (1) Creative Thinking; (2) 3D Modeling; (3) 3D Printing; (4) Product consummation; (5) Problem Diagnosis, and (6) User Experience. The results are expected to help (1) current manufacturers who desire to transform into small-quantity-large-variation providers; (2) makers or hackers who wants to perfect their expertise, and (3) students who are eager to become future makers or hackers enter this market with products of high added-value through a quick and painless process.
The Empirical Research of Integrating Internet of Thing and Network Service (2015.1~2015.12)
Funded by 2015 Technology Project of Ministry of Economic ，PI（coPI is Dr. Cheng-Jhe Robert Chen, Industrial Management, NTUST）
This Empirical research aims to develop a service design course for Internet of Things (IoT) device and service providers to create and evaluate their products. The outcomes of this research are 1) course material, 2) evaluation method and tools for IoT user experience, and 3) learning map for cross-disciplinary participants. Though the empirical study and learning, the outcomes of this research will be used to cultivate the design projects and train the participants to transform manufacturing mindset to the service design thinking. By collaborating with the existing service design courses, this project will provide the guidance of IoT service development and utilize the real-world design case study to motivate the participants to join the crowdfunding and realize their developing project.
