Academic Research

Introduction

Detailed planning for the research projects of AIM-HI in the next 5 years are:
  1. Green manufacturing systems
  2. Real-time multi-core intelligent control
  3. Intelligent sensing systems
  4. Intelligent industrial applications and management

  AIM-HI will conduct extensive academic research into all aspects of advanced manufacturing systems. Over the next 5 years or so, the major research direction in the advanced manufacturing systems field is expected to be that of intelligent green manufacturing technologies. The realization of next-generation manufacturing technologies which are environment friendly, energy saving and intelligent requires the use of micro/nano techniques to develop energy-efficient materials that are lightweight, structurally strong, with good heat dissipation properties. To be intelligent, manufacturing systems must mimic human beings. Smart human beings make use of their sensing mechanisms, i.e., eyes, ears, nose, tongue and fingers, to acquire information about the world around them. This information is then processed and manipulated by the brain in order to arrive at rational decisions and intelligent actions. Therefore, intelligent manufacturing systems should ideally incorporate multiple embedded wireless sensors and utilize information and communication technologies to process the information received from these sensors in order to make intelligent machining decisions. Consequently, three key engineering technologies are required to support the realization of future AIM-HI applications, namely green manufacturing systems, real-time multi-core intelligent control systems, and intelligent wireless sensing systems. Specifically, AIM-HI will aim to develop several key components of next generation manufacturing systems such as controllers, precision mechanics, and advanced metallic materials, and to expand its expertise in two critical technologies, namely, machine design and development with submicron precision and ultrahigh precision motion control. Figures 1 and 2 present a technology roadmap and a technology fishbone diagram for AIM-HI, respectively. Using the intelligence of a single machine as a basis, the AIM-HI research center at CCU will examine the intelligence of individual product lines and the overall factory, and will develop intelligent industrial applications and management strategies. To achieve this, the following four subprojects are proposed. For details, please click on the title of each subproject.

1. Green manufacturing systems:The green systems subproject will be led by Zhang-Hua Fong (Deputy Director of AIM-HI and Dean of the College of Engineering, CCU) and co-led by Chih-Chun Cheng (Chairperson of the ME department, CCU). The members of the subproject will be drawn mainly from AMTC, with a lesser number drawn from LEPROF. The primary objective of the subproject will be to develop green precision mechanisms and advanced metallic materials with energy-efficient properties. Energy conservation studies show that only 25% of the energy consumption is used in actual machining. With 75% of the energy wasted in non-machining motion, machine idling, friction, and heat dissipation, there is plenty of opportunity for energy conservation. As a result, two research directions are planned in this subproject, namely, (1) improving efficiency of motion with reduced non-machining motion and idling time and (2) innovative mechanisms and materials with green characteristics such as light weight, structural strength and better heat dissipation. An example of a green material is porous metal foam composites. The structural/mechanical research will focus on an energy efficient intelligent feed drive system and design of machine tools, for example, a minimal-chatter feed drive system and “thermally friendly” structure. Meanwhile, investigation into the physical principles underlying energy consumption patterns and health status (like tool breakdown) of the whole manufacturing system will be conducted in support of the other two subprojects, the “intelligent control” and “intelligent sensor”.

2. Real-time multi-core intelligent control:The intelligent control subproject will be led by Jinn-Shyan Wang (a professor in the EE department, CCU and current program coordinator of the Microelectronics Engineering Program of the Taiwan NSC) and co-led by Jiun-In Guo (Chairperson of the CSIE department, CCU). The team members will be drawn mostly from SoC, but with additional support provided by AMTC, EPARC and CTR. The main objective of the subproject will be to develop the controllers required to realize intelligent multi-axis motion systems by taking advantage of the multi-processor technique. It is anticipated that these controllers will utilize the ICT (information and communication technology) to process the signals received from embedded wireless sensors within the manufacturing system and will then provide the system with various intelligent functions for machining and health monitoring. In implementing such controllers, the subproject will devise effective schemes which enable the controller to maintain a real-time capability despite the need to process huge volumes of information received from all the sensors in the various motion axes simultaneously. Specifically, the research issues include source-level analysis at the upper level, software support at the middle level, and operating systems at the lower level, including synchronization and communication, computation migration, code scheduling and parallelism exploration, middleware design, library support, and real-time operating systems.

3. Intelligent sensing systems:The intelligent sensing subproject will be led by Kuang-Chao Fan (Deputy Coordinator of AIM-HI and a professor in the ME department, NTU) and co-led by Shyh-Leh Chen (Director of AMTC, CCU). The members of the subproject will be drawn mostly from AMTC, but with a few members drawn from CTR. The main objective of the subproject will be to develop advanced embedded wireless sensors like a high resolution accelerometer, concentricity sensor for axial alignment, temperature sensor, etc., for in-line intelligent status monitoring, diagnosis, and control. One major challenge of this subproject is how to develop sensors with robust wireless communication in the harsh machining environment of high temperature and vibration. In practice, high-speed motor rotation and metal cutting will generate enormous low frequency (< 30 MHz) EMI noise, seriously interfering with wireless communication. Moreover, in the confined operating conditions of machine tools, slow signal fading due to reflection by chamber walls and fast signal fading due to serial reflection and deflection by fast-rotating parts pose other serious wireless communication issues. Furthermore, machine vibration will cause an internal sensing noise (so-called microphonic noise) in the electronic phase-locked loop, which will in turn create unwanted variation in the carrier frequency. This will give rise to a higher bit transmission error rate that will require resending of the signal; excessive increase of transmission latency due to frequent signal re-transmission will eventually violate the real-time transmission requirement of the sensor information. Thus, one key issue in embedded wireless sensors for machine tools is robust real-time wireless communication. In this subproject, both broad spectrum (including direct sequence broad spectrum and rapid carrier frequency hopping methods) and error coding techniques will be exploited to achieve real-time wireless communication in the harsh machining environment.

4. Intelligent industrial applications and management:The industrial applications subproject will be led by Shi-Ming Huang (Dean of the College of Management, CCU) and co-led by Houn-Gee Chen (a professor in the Department of Business Administration, NTU). Most of the project members will be drawn from CMCA. However, a small number of individuals will also be drawn from CRCS and RCPM. This subproject represents a unique feature of AIM-HI. It starts with an innovative application of cognitive psychology to identifying characteristics of intelligent machines and consequently developing an effective human machine interface (HMI). With the development of intelligent machines, the subproject will take on its second focus – development of intelligent production lines and promotion of intelligent industrial applications and management. For a HMI to be intelligent and effective, the design of the HMI must possess the desirable qualities of being (a) intuitive in operation, (b) flexible in organization, and (c) adaptive in modification and re-organization. Many areas of basic research in cognitive science can be used to help design and assess the extent to which an HMI is truly intelligent in creating a user-friendly operation environment. In particular, rigorous behavioral methods of experimentation in usability testing can provide sound evidence-based, rather than designer-hunch-based, assessment and enhancement of HMI efficiency. Furthermore, in the face of customer-oriented service economy and globalization and cooperative-competitive relationships among industrial value-added chains, our research on intelligent industrial management aims at creation of customer-service precision manufacturing and novel applications of emerging technologies to seamless integration of engineering and management. Specifically, an effective information service platform based on cloud computing will be developed. This “cloud-based” service platform can then be employed to construct an integrated e-supply chain to assist part suppliers to develop high-level parts that meet the needs of the machine developer, and be adopted to promote strategic alliance and collaborative commerce among participating companies. At the same time, emerging technologies like RFID-equipped intelligent sensing devices will be used for network communication among various pieces of equipment to achieve intelligent monitoring and diagnosis of production lines or across the whole factory floor.

  The research outcomes will be published in high impact journals in manufacturing discipline. Because the broad technology coverage of manufacturing systems, we define these high impact journals as the manufacture-related transactions published by authoritative academic societies like ASME, IEEE, and ACM. Further description of the research planning is available on the web page of AIM-HI, http://www.ccu.edu.tw/ATU.htm.

  At the 30th meeting of the Science and Technology Advisory Group of the Executive Yuan in December last year, it was pointed out in its “Strategy for Solidly Cultivating Fundamental Industry Technologies (深耕工業基礎技術發展策略)” that in order to have a robust industrial base, the society must (1) conduct challenging R&D projects, (2) start from the ground floor, not relying on foreign technology, and (3) be patient, not look for quick returns. This strategy exactly matches the research philosophy of AIM-HI.

  First, with a confident attitude, we are taking on challenging research projects which have traditionally been conducted in Europe and Japan – in particular, green manufacturing, real-time multi-tasking intelligent control, and smart wireless sensing. Based on the solid research foundation of AIM-HI, we believe that we can help domestic industry to develop core technologies and key components of high-end intelligent machine tools (e.g., high performance controllers, intelligent spindles, intelligent health monitoring, etc.). Furthermore, our research team has long held the belief that advanced manufacturing plays a crucial role in the industrial capability of a nation and is fully devoted to basic research on manufacturing, with an attitude of patience and perseverance. Although the electronics and related industries have created an economic miracle in Taiwan, the industries are faced with a serious problem of exponentially increasing capital costs for imported high-end fabrication equipment, adversely affecting their international competitiveness. Moreover, precision machines have found high value applications in bio-medicine recently, a notable example being the DaVinci machine for surgical application. This is the motivation for the “Strategy for Solidly Cultivating Fundamental Industry Technologies” as well as the driving force behind our long-term research on manufacturing. We are pleased to learn that the industrial development policy of the government shares the same philosophy. The support of this project will give AIM-HI a big boost in its effort to become a pivotal force in development at many levels, from our own students to local industry, to the national economy, to first-class international technology.

Figure 1. Technology Roadmap for AIM-HI

Figure 1. Technology Roadmap for AIM-HI

Figure 2. Technology Fishbone Diagram for AIM-HI

Figure 2. Technology Fishbone Diagram for AIM-HI

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