Computer-Aided Engineering and Mechatronics in the Design of Apparel Equipment

Transcription

1 F98-S4, Page 1 Computer-Aided Engineering and Mechatronics in the Design of Apparel Equipment FACULTY ADVISORS: RESEARCH ASSISTANTS: Timothy G. Clapp (Textile Eng.) and Jeffrey W. Eischen (Mechanical Eng.) - North Carolina State University, Frank W. Paul Christopher D. Rahn(Mechanical Eng.)- Clemson University. Roberto Bigliani (Visiting Scholar from Polytecnico di Torino, Italy), Shrinivas Lankalapalli (PhD)- Mechanical Engineering NCSU, Clayton Kopp (MS), Sandeep Shenoy(MS), Markus Loffler (PhD), Yugang Li (PhD), Elango Sundaram(MS) -Mechanical Engineering Clemson. TEAM LEADER: J. W. Eischen ( , eischen@eos.ncsu.edu) ANNUAL REPORT: May April ABSTRACT: This research project combines computer-aided-engineering methods with practical control strategies to develop precise fabric part handling capabilities. The primary goal is to develop mechatronic design concepts for assembly processes such as: folding, joining, placing, and locating that take into account variability in fabric material properties such as weight and stiffness. Three-dimensional modeling of fabric drape and manipulation using both a finite element method and a particle method has been simplified for the design of fabric handling control systems. The machine implementation aspect of this years research focuses on real-time position control for draping fabric that is sliding on a high friction surface. Although fabrics are usually positioned on smooth surfaces with fixed fabric guides to simplify automated handling, a high friction work surface holds the fabric in place after positioning, allowing accurate assembly of multiple fabric parts without specialized jigs or fixtures. A neural adaptive controller with feed-forward friction compensation provides asymptotic tracking for a spring mass model with friction. A test stand and an optical sensor are designed to facilitate real time position measurement and control. The neural adaptive controller demonstrates good position tracking and robustness to fabric property variations relative to open loop or PID control. I. PROJECT GOALS AND RELEVANCE TO NTC GOALS The key question and challenge for this research project is: Can computer-aided-engineering techniques commonly used in the automotive and aerospace industries be applied to the design and development of fabric handling equipment? And, can the machinery be designed to accommodate multiple part configurations (shape, thickness, etc.) and material properties (weight,

2 F98-S4, Page 2 stiffness, etc.)? The major objective of this research project is then to combine computer-aidedengineering methods with practical control strategies to develop precise fabric handling capabilities. The primary goal is to develop mechatronic design concepts for assembly processes such as: folding, joining, placing, and locating that take into account variability in fabric material properties such as weight and stiffness. Advanced three-dimensional modeling of fabric drape and manipulation using the finite element method will be simplified for the design of fabric handling control systems. Controls that stabilize the fabric motion and allow accurate handling with minimum wrinkling will be investigated. Proof of concept demonstrations have been constructed to show techniques for systematically adjusting for material property variation. Other potential applications for this technology in future years would include 3D fabric processes such as shape pressing and sewing. Computer-aided-engineering is prevalent in many high technology industries in the US, including automotive and aerospace. Computer simulation of manufacturing processes during the equipment design phase is an accepted procedure. This same approach must be implemented in the design of fabric handling equipment. Machinery must be engineered in advance to accommodate multiple part configurations and material properties. Competitive advantage from Demand Activated Manufacturing will require this level of knowledge. II. TECHNICAL APPROACH AND PROGRESS Flexible automation allows apparel manufacturers to respond quickly to rapidly changing market conditions while minimizing skilled labor. Successful automation in the apparel industry has primarily been limited to fixed automation using special purpose, mass production machines. Flexible automation using general purpose machines is difficult because the limp nature of the fabric complicates actuation and sensing, thus adding cost and complexity. A wide variety of materials need to be handled with diverse bending stiffness, weights, and frictional characteristics. Additionally, these characteristics vary from part to part and with temperature and humidity. Dependable flexible automation requires feedback to adapt to these variations. A number of researchers focused on automating entire apparel manufacturing lines. The Charles Stark Draper Laboratory and Textile/Clothing Technology Corporation [1.] applied large scale automation to the men's clothing industry. MITI [2.] implemented similar apparel automation systems. Taylor and Taylor [3.] developed an automated line for the assembly of men's underwear. Other researchers concentrated on fabric handling. Gunner [4.] investigated the laying of fabric strips on moving conveyor belts. Brown et. al. [5.] used Konopasek's [6.] equations to derive trajectories for fabric standing. Eischen and Kim [7.] used a nonlinear technique to solve for fabric standing up, laying down, and folding trajectories. During past years (see Refs. [8-10]) we focused on iterative position control for folding on a friction-less (slippery) work surface, a fundamental fabric handling operation. A fast, memorized folding trajectory was implemented using an industrial robot. A vision system measured the fabric position error after each fold. If the error was too large, the trajectory was modified on-line and the fabric was then refolded. This process repeats until small errors are achieved. This past year,

3 F98-S4, Page 3 with NTC funding, we have focused on real-time position control for draping fabrics sliding on high friction (rough) surfaces. Last year s report (Ref. [10]) focused on the control and hardware implementation aspects of our project, at the expense of the computer simulation results. Therefore, this report will focus on the simulation results. COMPUTER SIMULATION A computer simulation tool has been developed that allows modeling of various fabric manipulation processes that occur during manufacturing. Fabric parts are modeled as very flexible elastic beams that can accommodate stretching and bending in a single plane. The governing equilibrium equations are solved using the finite element method. The nonlinear moment curvature response is measured directly with the Kawabata Test System, or with a simpler drape test. Realistic manipulation processes involve interaction of fabric parts with other objects such as: work surfaces, robot manipulators, other fabrics. Therefore, the ability to model contact has been implemented. A Visiting Scholar from Italy with expertise in 3D fabric drape (clothing on mannequins) and computer graphics has recently joined the NCSU team. A computer simulation tool has been developed that allows modeling of various fabric manipulation processes that occur during manufacturing. Fabric parts are modeled as very flexible elastic surfaces that can accommodate stretching, bending, and shear. The governing equilibrium equations are solved using either the finite element method or a particle system approach, see Refs. [11-12]. The nonlinear moment curvature response is measured directly with the Kawabata Test System, or with a simpler drape test. Realistic manipulation processes involve interaction of fabric parts with other objects such as: work surfaces, robot manipulators, other fabrics. Therefore, the ability to model contact has been implemented. Several representative simulation results are shown next. Airbag: Fig. 1 shows several steps of a simulation where an airbag is being picked up vertically. The final picture in the sequence shows the airbag as transparent, whereby the internal diaphragm can be seen. Fig. 2 shows several steps of a simulation where the airbag is being inflated.

4 F98-S4, Page 4 Fig. 1- Airbag Pickup Simulation

5 F98-S4, Page 5 Fig. 2- Airbag Inflation Simulation Ribbon: Fig. 3 shows several frames of a simulation where a vertical strip of fabric falls on a horizontal table. One end of the strip is fixed to the horizontal surface and two vertical feeder guides constrain the strip movement. The first picture shows the initial imperfection at the bottom of the strip which is necessary for initiating out of plane buckling.

6 F98-S4, Page 6 Fig.3- Ribbon Simulation

7 F98-S4, Page 7 Horizontal Strip: Fig. 4 shows several simulation steps for an horizontal strip which lies on a flat surface. One end of the strip is fixed to the table while a tangential displacement is imposed on the other end. Strip Fig. 4- Horizontal Strip Simulation displacement [mm] 55 Series1 Series2 Fig. 5 shows a graph which compares experimental results (Series 1) with simulated results (Series 2) for the horizontal strip. A displacement between 5 and 60 mm is imposed at the end of the strip: the graph shows the maximum height that the material reaches related to the imposed displacement. Fig. 5- Horizontal Strip: Comparing Results

8 F98-S4, Page 8 Clothing: Fig. 6 shows several frames of a simulation where a wheel skirt is draped on the body of a mannequin. A collision algorithm is performed every simulation step for handling the interaction between the fabric and the surface of the mannequin. A self-collision algorithm is also necessary for avoiding fabric to fabric penetration. Fig. 6- Wheel Skirt Simulation

9 F98-S4, Page 9 CONCLUSIONS Three-dimensional modeling of fabric drape and manipulation using the finite element method and particle method has been simplified for the design of fabric handling control systems. The machine implementation aspect of this year s research focuses on real-time position control for draping fabric that is sliding on a high friction surface. A neural adaptive controller with feed-forward friction compensation provides asymptotic tracking for a spring mass model with friction. A test stand and an optical sensor are designed to facilitate real time position measurement and control. The neural adaptive controller demonstrates good position tracking and robustness to fabric property variations relative to open loop or PID control. IV. INDUSTRY COLLABORATION Leonard Brewington at Milliken arranged for us to visit the American Bag Corporation airbag manufacturing plant during the fall of We have characterized airbag materials at NCSU in order to simulate manufacturing processes on the computer. We have also built a CAD database with detail dimensions. Clemson is currently investigating mechatronic issues such as gripper technology and handling strategies for arbitrary shaped fabric parts such as airbag components. Future automation of airbag assembly could potentially benefit from our research findings. We are also working with TC 2 in the area of experimental validation of fabric drape on 3D objects (mannequins). It is our intention to tailor our experimental investigation towards fabric handling problems that are relevant to industry problems. V. PUBLICATIONS 1. Rahn, C.D., Iterative Techniques for Fabric Position Control During Folding, submitted to International Journal of Clothing Science and Technology, June Eischen, J. W., Finite-Element Modeling and Control of Flexible Fabric Parts, IEEE Computer Graphics and Applications, Special Issue on Computer Graphics in Textiles and Apparel, Volume 16, Number 5, pp , (Invited Paper) 3. Eischen, J. W., Optimum Manipulation Strategies for Limp Fabric Materials, with W. Clifton, Proceedings of the Fifth Pan American Congress of Applied Mechanics Conference, San Juan, Puerto Rico, Jan Clifton, W., Optimum Fabric Trajectories for Edge Position and Control, MS Thesis, North Carolina State University, Mast, S., Iterative Techniques for Control of Fabric Manipulations, MS Thesis, Clemson University, Shenoy, S., Neural Adaptive Position Control of Fabric on a Frictional Surface, MS Thesis, Clemson University, VI. REFERENCES 1. Charles Stark Draper Lab, Inc., Report on the Fourth-Year Research and Development Program for the Tailored Clothing Technology Corporation, June 28, 1985.

10 F98-S4, Page Jones, S.H., MITI: Progress Report, Apparel Ind., Feb. 1985, pp Taylor, P.M., and Taylor, G. E., Progress Toward Automated Garment Manufacture, Sensory Robotics For the Handling of Limp Materials, ed. Paul M. Taylor, Gunner, M.B., Taylor, P. M., and Wilkinson, A. J., Placing Fabric onto Moving Surfaces, International Journal of Clothing Science and Technology, Vol. 2 No. 3/4, 1990, pp Brown, P.R. III, Buchanan, D. R., and Clapp, T. G., Large-deflection Bending of Woven Fabric for Automated Material-Handling, Textile Research Journal, Vol. 81 No. 1, 1990, pp Konopasek, M., and Hearle, J. W. S., Computational Theory for Bending Curves. Part I: The Initial Value Problem for the Three-Dimensional Elastic Bending Curve, Fibre Science and Technology, Vol. 5, 1972, pp Eischen J.W., and Kim, Y. G., Optimization of Fabric Manipulation during Pick/Place Operations, International Journal of Clothing Science and Technology, Vol. 5 No. 3/4, 1993, pp National Textile Center 1995 Annual Report, pp National Textile Center 1996 Annual Report, pp National Textile Center 1997 Annual Report, pp Eischen, J. W., Finite-Element Modeling and Control of Flexible Fabric Parts, IEEE Computer Graphics and Applications, Special Issue on Computer Graphics in Textiles and Apparel, Volume 16, Number 5, pp Eischen, J. W., Technical Issues, Approaches, and Challenges, Course 31 on Cloth and Clothing in Computer Graphics, 25 th International Conference on Computer Graphics and Interactive Techniques-SIGGRAPH 98, Orlando, FL, July 1998.