Innovative Design and Integrated Manufacturing Laboratory
創新設計與集成製造實驗室
Location E11-1058
Academic Staff in charge Prof. Zhixin YANG
Technician Song On SHUM; Hoi Sun CHIO
Telephone (853) 8822-4288

Objective | Research Projects | Lab Facilities | Experiments | Courses supported

 

Objective

The Innovative Design & Integrated Manufacturing Laboratory lab aims to support teaching and research in the areas of design innovation and intelligent manufacturing. It provides advanced design and manufacturing theory and practice environment which fit modern industry requirements. It utilizes computer as assistance in carrying out innovative design, 3D product geometric design, process planning, and CNC programming by means of prevailing tools, such as Catia, Creo (Pro/E), Acis, 3D scanner, etc. Advanced manufacturing equipment, including CNC Turning, CNC Milling, Rapid Prototyping machine and 3D Printer, are provided for practice. The students could be impressed with the amazing integration of computer with design and manufacturing. The lab objectives include:

  1. To support teaching and research in the areas of computer-aided innovative design, customized design, design reuse, geometric deformation, shape similarity evaluation.
  2. To support teaching and research in integrated manufacturing in terms of process planning, intelligent manufacturing, rapid prototyping, etc.
  3. To provide prevailing facilities for design, including Catia, Creo (Pro/Engineer), Acis, 3D scanner, etc. for innovative product design; and advanced manufacturing equipment, including CNC Turning, CNC Milling and Rapid Prototyping machine, for manufacturing practice.
  4. To provide facilities for undergraduate final year projects and graduate research projects.

Research Projects

1. Fault diagnosis of rotating machinery using intelligent neuro networksBrief Introduction

The rotating machinery is the one of significant equipment in modern industrial applications, such as power plants, vehicle, aircraft, and so on. Any abnormal situations of the rotating machinery may interrupt normal machine operation as well as hazard to personnel to cause enormous economic loss.

The traditional manual inspection on the rotating machinery faces two main chanlleges. One of challenges in rotating machinery diagnosis is that the existence of simultaneous-faults, that is, multiple single-faults appeared concurrently. Another challenge is a typical multi-signal fusion problem; it involves the use of multi-signal such as vibration and sound to simultaneously detect and identify faults. To solve these challenges, development of a reliable and accurate intelligent system for fault diagnosis of rotating machinery is therefore a promising research topic.

2. Innovation design 

With the development of modern industrial manufacturing and the demand of reducing product development life-cycle, reverse engineering becomes to play an important role in product design and industrial manufacturing. Reverse engineering refers to the process of obtaining the engineering design data from existing parts. Recently, 3D scanning technologies and devices have been widely applied in product redesign by scanning existing parts to acquire 3D point cloud and obtaining the 3D models by some subsequent procedures which are criterion to design new products. The process of innovation design is first scanning the real part in the world to generate a 3D point cloud set (PCD), then the preprocess of de-noising and data reduction is performed to optimize the PCD; secondly the PCD is deformed under boundary constraint with an innovative algorithm to generate some new models to help increase the speed of product design; thirdly the procedure of similarity estimation is performed to choose the suitable elements to design a new product.
The following works are in progress:

  1. Extensions to K-Means Algorithm based on Random Sampling and Similarity Measure of Area Density for 3D Point Cloud Massive Data
  2. A Novel Point Cloud Data Reduction and Regularity Framework for Design Reuse
  3. Constraint-based Adaptive Shape Deformation Technology for Customised Product Development
  4. An Investigation on 3D Shape Similarity Assessment for Design Re-usage
3. Machine Learning and Its Applications 

Machine learning is a subfield of computer science and statistics that deals with the construction and study of systems that can learn from data. Besides CS and Statistics, it has strong ties to artificial intelligence and optimization, which deliver both methods and theory to the field.

As a popular machine learning method, an artificial neural network (ANN) learning algorithm, usually called "neural network" (NN), is a learning algorithm that is inspired by the structure and functional aspects of biological neural networks. Computations are structured in terms of an interconnected group of artificial neurons, processing information using a connectionist approach to computation. They are usually used to model complex relationships between inputs and outputs, to find patterns in data, or to capture the statistical structure in an unknown joint probability distribution between observed variables.

4. RFID Enabled Indoor Positioning for Real-time Manufacturing Execution System based on OS-ELM 


Manufacturing Execution System (MES) is recently been introduced to leverage the competitive edge of manufacturing enterprises where the shop-floors are under dynamic and mixed-product assembly environment. However, current MES practices for wireless manufacturing still suffer from two kinds of difficulties: (1) inefficient information acquisition technique; (2) lack of reliable and fast signal-positioning conversion method for real-time monitoring of manufacturing objects. Traditional indoor positioning algorithms cannot process massive signal data and predicate the positions of manufacturing objects in accurate and efficient manner. This research proposes to handle the first challenge by adopting the RFID technology which could constantly capture the dynamic wireless signals sent from the tags mounted on manufacturing objects. The second difficulty could be solved by applying online sequential extreme learning machine (OS-ELM), which inherits the elegant properties of ELM (extremely fast learning speed and high generalization performance) and could avoid retraining for new arrived objects and disturbance existed in dynamic shop-floor environment. With the novel RFID enabled framework based on OS-ELM, the proposed method upgrades the manufacturing objects as smart manufacturing objects (SMOs) for real-time signal processing and intelligently tracing of MES. The experimental results verify that the proposed RFID enabled indoor positioning method based on OS-ELM outperforms than other prevailing approaches in terms of accuracy, efficiency and robustness.

5. Project task flow optimization using design structure matrix and an improved genetic algorithm in addition with wireless manufacturing 

Unnecessary rework in engineering projects could result in huge project time consuming and cost lost. This paper is objective to establish the best project task flow by using design structure matrix (DSM) and an improved genetic algorithm (GA) method together, also realize wireless manufacturing (WM). DSM is used to show the project task structure and identify relationships among the project tasks. Improvement is made in the simplification of DSM by valuing the coupling strength among tasks from 0 to 1. Those with values below 0.5 will be deleted to simplify the DSM to only retain the necessary task relations. GA is used to optimize the project task structure according to task time, task cost and their coupling strength. Digital code presentation of chromosomes is used instead of binary one.  The theory of the improved GA is to cross the chromosomes which have better fitness function value with the one which has the best fitness function value instead of randomly crossing during the reproduction process. The aim is to keep some good gene fragments (task sequences) in every crossing process to speed up the optimization process. This paper also provides network environment to store and update all the project information, it can help managers and engineers in their work.

Lab Facilities

1. CAD and Innovative Design Facilities

Pro/EngineerTM (CreoTM) & CATIATM (3D Modeling Drawing Software)
Students can learn fundamental and advanced product modeling technique, including 3D feature based solid modeling, surface analysis, assembly etc., by practicing on these software.

2. Intelligent Manufacturing Facilities



Machining Center
It is a 3-axis computer numerical controlled (CNC) milling machine, which equipped with tool magazine for 16 tools and an automatic tool changer device. It can fabricate work-piece with sculptured surfaces. Machining center has been integrated with design facilities. The NG code of a part, generated by manufacturing software, could be transmitted to the machining center directly.
CNC Lathe
A CNC lathe machine could machine part in rotating shape.  The tool magazine could accommodate and automatically change 8 cutting tools. It has also been connected into the computer integrated environment.


Rapid Prototyping Machine
Prototyping is a process of building pre-production models of a product to test various aspects of its design.
Laminated Object Manufacturing (LOM) builds up a 3D part by adding each layer of material (paper) to a stack, by controlling laser cutting away the unused portions.

3. Collaborative Design Innovation

3D Scanner
The 3D scanner could can convert a physical  model into point cloud, which is in digital form. It could facilitate downstream design reuse,  revision, and innovation.
3D Printer
3D printing fuels limitless creativity when designer, architects, and students get to see, hold and test their ideas in real space. 3D platform enables you to manufacture on demand and makes true-to-life objects quickly and easily.
Our lab offers professional 3-D graphics software (Pro/E) and 3-D Printing equipment (MakerBot) to help students bring great ideas into reality.
SMARTEAM A PDM (Product Data Management) software that provides information platform to manage and develop product solution. The product development process could also be managed. It could support to build design collaboration environment.
Hoops A versatile visualization tool that enable view 3D model across internet among multiple team members.
ACIS Robust geometric kernel that provides fundamental packages for customized  geometric programming applications for  design innovation.

Experiments

  1. Product design in 2D and 3D modeling
  2. Convert physical model into digital model for reverse engineering applications
  3. Surface model deformation and similarity comparison
  4. Work-piece machining using CNC machine
  5. Numerical Control programming simulation
  6. Rapid prototyping
  7. 3D model printing
  8. Condition monitoring and failure diagnosis using intelligent machine learning method
  9. Applcation of Radio Frequency Identification (RFID)

Courses supported

EMEB221 Computer-aided Design
EMEB310 Production Management
EMEB350 Advanced Manufacturing
EMEB361 Industrial Data Management
EMEB373 Production System, Planning & Control
IMEM005 Computer-Aided Geometry Design
IMEM006 Computer-Integrated Design and Manufacturing