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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
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Home > Research areas I
Research areas I

★ Research project of 1st Stage

 

 ◇ Strategy Management  ◇ Innovation & Design ◇ Manufacturing & Quality Management 

◇ Green Supply Chain Management ◇ Service Management

 

◇ Strategy Management:Strategizing in Industrial Clusters and Innovation

  Systems

 

The majority of industrial clusters in the world tends to focus on technology innovation in manufacturing while the significant impact of services on increasing industrial productivity has been widely recognized due to market diversification, localized 'collective learning' processes, and increasing globalization in clustering. The previous literature used to separate the discussions for technology and service innovations, arguing that the innovation patterns prevailing in services and in manufacturing are different. However,the clustering itself engenders significant competitive advantages for and attracts constituent firms because of the ease with which new professional, technical and market-relevant knowledge can be accessed and shared via personal and business networks, local flows of highly-qualified staff, and proximity to and collaboration with other consultancies and service providers. The results indicate that cluster firms recognize and value their ability to tap into a collective learning capacity provided by the whole cluster’s firms, including both knowledge-intensive technology and service sectors.

 

This study will focus on the interface between producers and users and how such networks actively contribute to industrial development and innovation. Thus, this study aims to investigate the industrial clusters (particularly the green energy industrial clusters) in Hsinchu (Taiwan), Tenjing (China), and Silicon Valley (the US) to examine two questions under three different sub-projects: (1) how the interdependence of technology (producer) and service (user) innovations shaping the economic value in the three industrial clusters? and (2) how the local linkages, regional linkage, and global linkages in the three industrial clusters (especially the green energy industrial clusters) affect advancement in technology (producer) and service (user) innovations?

 

◇ Innovation & Design:The ergonomics and green design in green photonics

  industry

 

As the green photonics industry is fast growing, the safety and comfort for the workers in the clean room is becoming more and more important. Prolonged walking and standing in the clean room workplace tend to cause musculoskeletal disorders of the lower extremity. The study aims to collect foot anthropometric data of young Taiwanese people using 3D scanner. The foot dimensions are then used to classify foot shapes and to design an innovative insoles being used in the clean room environment. In addition to clean room boot, clean room suit also affects workers’ comfort. The main function of a clean room suit is to protect the product manufacturing process from particles and so to increase quality. This study aims to investigate the influence of the double-layer clothing on the physiological responses comfort in clean room environment. The findings can be used to propose a best combination between clean room suit and inner clothing. Moreover, respiratory mask is an important gadget protecting manufacturing personnel in the shop floor. Single mask design based on standard facial geometry or masks of fixed sizes, as previous studies proposed, fail to provide sufficient wearing comfort. Their segregation function is also not satisfactory. Therefore, this research will develop a novel design method for mass customization of semi-face mask. Various technologies will be integrated in this method, including non-contact 3D metrology, machine learning, free form deformation of mesh, and parametric design. The goal is to provide an automatic economic approach for respiratory mask design driven by individual human facial data. Finally this study will also investigate all the risks and the abnormal events exist inside the facility supplying system of solar cell factory by PHA and abnormal analysis. Thus, the safety and health of the workers and the environment friendliness can be assured and the total competitiveness of the green photonics industry can be enhanced.

 

◇ Manufacturing & Quality Management

 

Ⅰ、Advanced Quality Technology with Solar Cell Application

 

Manufacturing of products, such as solar cell and LED, in the green-value chain has already enjoyed a prosperous start-up. Its continued profitable development is critical to maintaining Taiwan’s role in the global supply chain. One of the main challenges of this industry is how to produce high quality/reliable products with low cost. Enabling advanced quality management technology has proven to be an effective solution. Advanced quality management must consider design, control and service in an integrated manner. Based on the research works of our team members in statistical methodology, control theory and computer simulations, this project attempts to integrate process simulation, run-to-run control, statistical process control, and reliability analysis into an advanced quality management toolset. It is also our goal to proliferate such ideas and technology to the green energy product manufacturing industry to improve their competitiveness.

 

Ⅱ、Research and Development for Manufacturing Strategy and Advanced  

  Manufacturing Systems

 

This project team aims to develop integrated solution for manufacturing strategy and advanced manufacturing system to support green energy industries such solar cell and LED to manufacture low cost, high quality and highly reliable products. In particular, under different conditions of market demands, available resources, and customer valuations, and different decision making times, Project I aims to develop revenue management approaches to maximize corporate profit. With the rapid development of CPU technology and affordable computation cost, the fourth sub-project models future demands as stochastic processes and develops dynamic decision methods by consider latest information on customer demands and available resources. Project II aims to extract domain knowledge of production planners in various layers of the supply chains to develop a rule-based solution for production planning that cab be employed to deal with large scale problems in real settings. Project III aims to develop a customer-focused process optimization design system; next, a high-performance parameter design method is developed using the statistical and computational intelligence approaches. Project III then applies the proposed methods in improving the fracture resistance of TFT-LCD of a display panel manufacturing company. Project IV aims to develop a solution based on a novel soft computing algorithm utilizing a modified “Simple Swarm Optimization” (SSO) for the optimal disassembly sequence involved in the “End-of-life Disassembly Sequencing Problem”. Project V aims to develop a decision support to integrate the developed solutions by this project team to support corporate operation strategic decisions. In particular, solar cell and LED industries are facing similar problems in which the output products have the performance distributions in terms of binning due to the variation of process and input materials. We will develop a multi-objective model to find the optimal solution that consider the wafer purchase and inputs, inventory management, and output bins to meet various customer demands. This integrated project team will conduct industrial collaborative project as a platform to validate each of the developed solutions and integrate them through implementation to support green industries in Taiwan.

 

◇ Green Supply Chain Management:A Decision Support System to  

  Facilitate Green Technology R&D and Green Supply Chain Operations

 

Development and applications of the green technologies have drawn much attention from the triple helix of government-university-industry in Taiwan in order to facilitate development of the green industry and green supply chain. In the step toward greening the enterprises, most practitioners (including the green technology providers and users) face a problem of lacking sufficient knowledge about the greening policies, R&D directions of green technologies, and utilization strategies of green resources. The aim of this project is to establish a decision support model and system to aid industries on green technology R&D and green supply chain operations. The main issues concerned in the proposed decision support system are as follows:

 

  • Exploration of a framework for sustainable development of the green industry and a plan for energy saving and carbon reduction of the supply chain

  • Assessment and strategy planning of the intellectual properties of green technologies

  • Discovery of cost-benefit knowledge of the green technologies

  • Optimal allocation of the green technologies and resources in green supply chain

  • Relationship analysis of the green resources in green supply chain

 

In this integrated project, five subprojects are formed in order to develop the decision support models with respect to the above issues. As a whole, the attempt of this project is to facilitate development of the green industry and green supply chain in Taiwan.
 

 

◇ Service Management:Open Service Innovation for Sustainability

 

The service value created usually takes joint efforts from collaborative business entities with integrative processes to perform in a coherent rhythm to create value-added experiences for service providers and customers. It is an open innovation in essence. The sustainability of service innovation is the upmost goal for new service development projects; however, not predictably attained in practice. Thus, this integrative project is proposed to investigate the sustainability of open service innovation based on the open service innovation matrix and SAT new service development cycle. We divide the efforts into the three subjects. The first subproject aims to investigate service innovation readiness in various industries in Taiwan to identify key determinants of service innovation capability and benchmark service innovation networks. The second subproject investigates the healthcare eco-systems of experimental capitation payment systems in Taiwan to develop the model of sustainability of open service innovation. The third subproject aims to study social collaboration networks for service innovation suing online community coordination and IC design platform as two target domains. The general objective of this integrative project is to validate the open service innovation methods in order to shape up the effectiveness of service innovation for service science discipline, and in turn, contribute to the academic communities and industries.