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Advanced Manufacturing and Service Management Research Center, National Tsing Hua University
Advanced Manufacturing and Service Management Research Center, National Tsing Hua University
Home > Research areas III
Research areas III

★ Research project of 3rd Stage


 ◇ Strategy Management  ◇ Innovation & Design ◇ Manufacturing Management 

◇ Green Supply Chain Management ◇ Service Management


◇ Strategy ManagementStrategic and Institutional Mechanisms for New Industry Creation – Towards the FAB Framework


 The global industrial landscape has changed dramatically over the past 20 years. Along with a quantitative shift in value added, a qualitative shift also appears in how value is to be proposed, created and captured. This qualitative shift can also be described as the fourth industrial revolution, or Industry 4.0, emphasizing the idea of consistent digitization and linking of all productive units in an economy, including "Internet of things", "maker movement" or "factory 4.0". Such new idea has a huge impact on established companies, attacking not only how they organize their capabilities, processes and activities, but also how they compete with each other, and above all, how they identify and realize new business opportunities emerging out of this new trend. To address both the challenge and opportunity associated with this new trend, it is therefore important to explore how the rules of the game are changing, and how new industries are to be created in this new context. Here we propose a framework for new industry creation –framing, aggregating and bridging - which addresses three types of mechanisms critical for new industry creation. We use this framework to investigate three types of new industries in China – mobile phone, ecommerce and venture capital - to explore the strategic and institutional mechanisms for new industry creation. These three industries play an important role in Industry 4.0, particularly in the Greater China Circle region.


◇ Innovation & DesignErgonomics and system Innovation in Smart Manufacturing Enviroment 


 The flexibility and cost-leadership was the core competitiveness in Taiwan’s industry. The recent fast development of globalization and raising wage in mainland caused dramatic changes and challenges in the global business environment. In order to revitalize manufacturing and enhance competitions, the U.S. government proposes ''Advance Manufacturing Partnership (AMP)'' program and the German government promotes the high-tech development strategy being recognized as ''Industry 4.0''. The goal is to construct the smart manufacturing environment which is characterized by agility, human centric, automation, smart grid, sustainability as well as the integration of the value chain processes. The technological bases include cyber-physical systems, ergonomics, cloud computing and the Internet of Things. Thus, it offers a critical opportunity to enhance Taiwan’s global competitiveness.

 This study aims to develop a Smart Manufacturing system with smart monitoring, smart error prevention, smart assembly simulation and internet of things fields. Subproject 1~4 proposes the development of automated collection and monitoring of the operators’ physiological and psychological responses including EEG, heart rate variability (HRV), eye movement and eye-hand coordination skills, body motion analysis etc. Combining with the cloud computing technology, supervisors can receive real time information regarding the safety and health status of the staffs. Subproject 5 will focus on the prevention and reduction of human errors in manufacturing and service environment. Subproject 6 will develop a novel method for assembly simulation of virtual models and real objects. This work will open up new applications of depth sensors in product design and manufacturing from their traditional use in motion capturing. Subproject 7 will develop a smart and integrate Internet of Things for link operator and process data, creating intelligent networks along the value chain and production system. Eventually, the overall effectiveness and competitiveness can be enhanced.


◇ Manufacturing ManagementResearch and Development of Foundation Technologies in Internet of Things for Smart Manufacturing


 In recent years, with the rapid development of Internet and mobile communications technology, internet of things (IOT) has become a popular field and governments and companies invest more resources to develop foundation technologies and applications. In particular, IOT for manufacturing can help manufacturing companies make revolution to reduce production cost and enhance yields and thus maintain their competitive advantage. This project aims to develop foundation technologies of smart manufacturing as the basis of the infrastructure for Taiwan man structuring companies. This integration project contains six sub-projects. Each of them addresses critical issues in smart manufacturing as follows: (1) smart production and scheduling, (2) reliability analysis and calculations of internet of things, (3) decision-based analytic model for smart manufacturing, (4) smart acceptance sampling plans development, (5) smart lean production, (6) smart quality index prediction based on big data.


◇ Green Supply Chain ManagementA Smart System for Supporting Green Energy Value Chain Management with Technology Development 


 Recently, both the worldwide and our government are aware of sever climate changes caused by rapid technology development and excessive resources usage. From the previous study on the management and control of an uncertain green value chain management, we have realized that the most critical factors which cause high risk of resource supply is the environment variation which affects both the fluctuation of oil cost and electricity price. Since it has been a worldwide polity to promote green energy technology development and supply, Taiwan government provides Feed-in-Tariff schemes for the private enterprises to invest green power installation. Due to the intermittency of weather condition and cloud technology development, investment and generation of renewable energies such as wind or solar powers require real-time data process including weather and demand. Therefore, this aggregated project intends to develop a smart recommender system to support in-time decisions, so that the sustainable development from the balance of economy, environment and society can be achieved.

 To cope with the issues above, the system will include 3 modules of big data prediction module, data-driven investment and generation solution module and user-friendly interface. The in-time response solution will be provided by 5 sub-projects as below:

  1. A Smart Recommender System for Sustainable Green Energy Value Chain Management
  2. Patent-evolution Based Technology Innovation Analysis
  3. Visualized Augmented Reality for Social Networks
  4. Building Smart Decision Support System for Green Energy Storage Systems
  5. An Intelligent Decision Support System for Energy Scheduling and Logistics Planning


◇ Service ManagementService Design for Smarter Service Through Analytics


 With the advent and growth of the Internet, more and more data are captured digitally, enterprises of various sizes are having the luxury of owning a tremendous amount of data in their hands. This opportunities also pose a challenge for companies to better use the data in order to gain meaningful insights that can eventually create value and enhance competitiveness for the organizations. However, for most Small and Medium Enterprises (SME) and institutions alike, they need to address the issue of data integrity, version control, and dispersion of data repository before they can embark on doing analytics on the data. Moreover, with limited data set and restricted capabilities, SMEs are less likely to take full advantage of modern analytics practices and technologies. This project will focus on leveraging third party platforms to help realize the benefits of smart services by doing analytics for the three stakeholders, namely, service offering organizations benefitting from analytics services, consumers of the service organizations, and the platform providers who add value to all the users of the platform.
 The first subproject will use data from EZTable, a service platform for offering reservation service to small and medium sized restaurants. The service platform provide analytics to restaurants using reservation system provided by the platform. The analytics can help SME generate insights which each individual SME cannot obtain by doing analytics themselves when they only have access to their own limited data set. This subproject will perform data mining, machine learning, statistics
modeling, and data visualization to find the best use of the reservation data.
 The second subproject will use data from the library of National Tsing Hua University to address the issue of increasing cost in knowledge creation. As knowledge diffusion now heavily relies on the spread of digital contents for professional communities, keeping abreast of the current status of a field has become a daunting task of information overloading. We find that the keyword-based search functions appear to be inadequate when interdisciplinary study increasingly become the norm for knowledge creation. To address the issue, we identify key activities for knowledge creation process and apply service design approach to create smart services for people who usually rely on keyword-based search when interacting with the knowledge repository. We expect to identify the gaps which lead to the problem of increasing cost in the knowledge creation process. In the first year, we will identify the needs of researchers and define the value propositions for users. Interviews and workshops will be conducted to create personas of various knowledge creation processes. In the second year, we plan to create smart service in the library by incorporating new sources of knowledge. This can be done by adopting text/data mining techniques and social network analysis to help connect the knowledge sources and interesting knowledge seekers.
 This project will help SMEs and individual knowledge creators to benefit from the state-of-the-art analytics and to embed insights to drive actions and deliver value. In doing so, SME will be able to enhance competitiveness and sense of engagement by applying smarter analytics. Individual knowledge creators will leverage IT power to focus more on things they can do best.