4 DOF SCARA機器人結構設計【說明書+CAD+UG】,說明書+CAD+UG,DOF,SCARA機器人結構設計【說明書+CAD+UG】,scara,機器人,結構設計,說明書,仿單,cad,ug This paper to be published in the Proceedings of the 1996 IEEE International Conference on Robotics and Automation For more information, contact: Roger Quinn, Associate Professor - Mechanical Engineering Case Western Reserve University, 216-368-3222 Design of an Agile Manufacturing Workcell for Light Mechanical Applications Roger D. Quinn, Greg C. Causey Department of Mechanical and Aerospace Engineering Frank L. Merat, David M. Sargent, Nicholas A. Barendt Wyatt S. Newman, Virgilio B. Velasco Jr. Department of Electrical Engineering and Applied Physics Andy Podgurski, Ju-yeon Jo Leon S. Sterling, Yoohwan Kim Department of Computer Engineering and Science Case Western Reserve University (CWRU) Cleveland Ohio, 44106 Abstract This paper introduces a design for agile manufacturing workcells intended for light mechanical assembly of products made from similar components (i.e. parts families). We define agile manufacturing as the ability to accomplish rapid changeover from the assembly of one product to the assembly of another product. Rapid hardware changeover is made possible through the use of robots, flexible part feeders, modular grippers and modular assembly hardware. The flexible feeders rely on belt feeding and binary computer vision for pose estimation. This has a distinct advantage over non- flexible feeding schemes such as bowl feeders which require considerable adjustment to changeover from one part to another. Rapid software changeover is being facilitated by the use of a real-time, object-oriented software environment, modular software, graphical simulations for off-line software development, and an innovative dual VMEbus controller architecture. These agile features permit new products to be introduced with minimal downtime and system reconfiguration. 1. Introduction 1.1 What is Agile Manufacturing ? Agile manufacturing is a term that has seen increased use in industry over the past several years. The definition of “agile”, however, is not clear, nor is it consistent: “Agility: The measure of a manufacturers ability to react to sudden, unpredictable change in customer demand for its products and services and make a profit” 1 . “Today factories are coming on line that are agile at tailoring goods to a customers requirements, without halting production.” 2 . “Agile manufacturing assimilates the full range of flexible production technologies, along with the lessons learned from total quality management, just-in-time production and lean production” 3 . The only common thread among the various definitions is the ability to manufacture a variety of similar products based on what may be rapidly changing customer needs. In the past, production was geared toward high-volume production of a single product. In todays market, however, the emphasis is moving toward small lot sizes from an ever-changing, customer-driven product line. Figure 1: Agile Workcell A definition of “agile” manufacturing has been adopted which applies to light mechanical assembly of products: Agile manufacturing is the ability to accomplish rapid changeover between the manufacture of different assemblies utilizing essentially the same workcell. Rapid changeover (measured in hours), further, is defined as the ability to move from the assembly of one product to the This paper to be published in the Proceedings of the 1996 IEEE International Conference on Robotics and Automation For more information, contact: Roger Quinn, Associate Professor - Mechanical Engineering Case Western Reserve University, 216-368-3222 assembly of another product with a minimum of change in tooling and software. Rapid changeover enables the production of small lot sizes, allowing for just-in-time production. A central theme of our definition of “agile” manufacturing is the ability to rapidly introduce (measured in weeks) new assemblies and components into the system. In this system, rapid changeover is accomplished through the use of reusable software, quick change grippers for the robotic manipulators, modular work tables, and parts feeders which are flexible enough to handle several types of parts without needing mechanical adjustment. These feeders use vision, in place of hard fixturing, to determine the position and orientation of parts. Generic, reusable vision routines permit new parts to be added to the system with a minimum of effort. A testbed implementation of an agile manufacturing workcell has been developed (Figure 1). This includes mechanical manipulators, flexible part feeders, a vision system (cameras, frame grabber, and a library of image processing routines), as well as a limited number of dedicated sensors and actuators needed to complete a given assembly. The central feature of such a workcell is a controller capable of controlling each of the aforementioned components. 1.2 Relevance of CWRU Work Several companies have implemented what may be considered “agile” manufacturing. Motorola has developed an automated factory with the ability to produce physically different pagers on the same production line 4 . At Panasonic, a combination of flexible manufacturing and just-in-time processing is being used to manufacture bicycles from combinations of a group of core parts 5 . Against the backdrop of such work, the CWRU workcell is innovative in several ways. The use of vision- guided, flexible parts feeders is one example. Another is the development of software design patterns for agile manufacturing. The over-arching design philosophy of quick-changeover, however, is what makes this workcell particularly novel. The CWRU workcell has been designed to be a versatile production facility, amenable to a wide range of applications and an enabling technology for factory wide agile manufacturing. 2. Workcell Hardware The agile workcell developed at CWRU consists of a Bosch flexible automation system, multiple Adept SCARA robots, as many as four flexible parts feeders per robot, and an Adept MV controller. An important feature of the workcell is the central conveyor system, which was implemented using standard Bosch hardware. It is responsible for transferring partially completed assemblies between the robots and for carrying finished units to an unloading robot The robots are mounted on pedestals near the conveyor system. Pallets with specialized parts fixtures are used to carry assemblies throughout the system, after which the finished assemblies are removed from the pallet by the unloading robot. Finally, a safety cage encloses the entire workcell, serving to protect the operator as well as providing a structure for mounting overhead cameras. 2.1 Conveyor System The conveyor system used in the CWRU workcell is a model T2 manufactured by Bosch. Pallets are circulated on two main conveyor lines. These lines are parallel to each other and operate in opposite directions. Pallets are transferred between these two sections by means of Lift Transfer Units (LTUs). These allow for the circulation of pallets around the conveyor system and the capability to re-order the pallets. Each of the pallets in the system is given a unique identification number, allowing the system to track and direct its progress. Stops are mounted at critical points on the conveyor to control the flow of the pallets. An innovative use of this conveyor system is the use of short “spur lines”. A spur (Figure 2) is simply an extension of the conveyor, perpendicular to the main line (analogous to a railroad spur). This allows the flow of the main conveyor line to be maintained while a robot performs an assembly at the spur. Pallets entering a spur are registered in the robots world coordinate frame by an arm-mounted camera, allowing the robot to place or remove parts on the pallet and avoiding the expense of mechanical registration. 2.2 Assembly Stations Several assembly station layouts were analyzed in choosing the final layout. After evaluating several features of each layout, including: placement of the robots relative to the conveyor, impact of feeder placement relative to the robot work envelope, and the robot motions necessary for a generic assembly, it was determined that the layout in Figure 2 would best suit the needs of the workcell. Each assembly robot is surrounded by two modular, removable work tables and two fixed feeding tables (Figure 2). The modular tables are easily exchangeable, allowing for specialized assembly hardware to be placed within the robots work envelope. The modular tables contain pneumatic actuators and This paper to be published in the Proceedings of the 1996 IEEE International Conference on Robotics and Automation For more information, contact: Roger Quinn, Associate Professor - Mechanical Engineering Case Western Reserve University, 216-368-3222 electrical sensors which can be connected quickly, allowing the rapid change of any specialized tooling required for a given assembly. By designing these tables to be modular and easily exchanged, different assembly hardware can be quickly accommodated. To achieve rapid changeover, the modular work tables are registered in the robots world coordinate system in the same manner as the pallets (i.e. using an arm-mounted camera). The feeding tables are fixed, and the horizontal, parts- feeding conveyors are mounted to them. Figure 2: Workstation Layout One drawback of the conveyor/spur system, as outlined above, is the time required to exchange a full pallet for an empty one. During this time (approximately 15 seconds) the robot would conceivably be inactive. A simple solution to this problem is a mini-warehouse: a fixture is located on the exchangeable portion of the work table to hold a few completed assemblies. During a pallet swap, the robot can continue the assembly operation working while the incoming pallet arrives, placing the completed assemblies in the mini-warehouse. After the incoming pallet is transferred to the spur, the vision system registers the pallet. The robot places the current assembly (still in its gripper) on the pallet and then proceeds to move the completed assemblies from the mini-warehouse to the pallet. 2.3 Flexible Parts Feeders Each feeder consists of three conveyors (Figure 3). The first conveyor is inclined and lifts parts from a bulk hopper. The second conveyor is horizontal, with a translucent belt. It transports the parts to the robot, presenting them at an underlit section near the robot. The third conveyor returns unused or unfavorably oriented parts to the bulk hopper. Proper functioning of the feeders depends on the parts being lifted from the bulk hopper in a quasi- singulated manner. Many factors influence the effectiveness of the inclined conveyor: the angle of the conveyor with respect to the horizontal, the belt properties (e.g. coefficient of friction), the type of belt (cleated, magnetic, vacuum), and the linear speed of the belt, for example. Figure 3: Flexible Feeding System Schematic When different parts are to be fed, the bulk hopper is emptied and filled with the new parts. If the parts are of a similar geometry, no changes to the feeding system are typically needed. Some parts, such as circular or cylindrical ones (i.e. ones that would roll back down the incline) may need a different belt surface, such as a cleated one, or a different angle of inclination. Overhead cameras are used to locate parts on the horizontal conveyors. An array of compact fluorescent lights is installed within each of the horizontal conveyors. These lights together with a translucent conveyor belt provide an underlit area in which parts can be presented to the vision system. Using binary vision tools (currently provided by an Adept vision system) parts on the feeder belts are examined. First, the vision system looks to see if a part is graspable (i.e. the part is in a recognized, stable pose (position and orientation) and enough clearance exists between the part and its neighbors to grasp it with a gripper). Second, the pose of the part in the robots world coordinates is determined. This pose, and the motions associated with acquiring the part, are checked to make sure that they are within the work envelope of the robot. 2.4 Vision System One essential function of the vision system is to determine the pose of components for flexible parts feeding. Pose estimation is performed using built-in functions of the AdeptVision software, and must be fast enough not to interfere with the assembly cycle-time. A secondary function of the vision system is to register pallets and modular work tables to a robots world coordinate system, avoiding the need for alignment hardware. Still another use may be error recovery, This paper to be published in the Proceedings of the 1996 IEEE International Conference on Robotics and Automation For more information, contact: Roger Quinn, Associate Professor - Mechanical Engineering Case Western Reserve University, 216-368-3222 wherein the cameras can be used to inspect critical points in the system, or in-process assemblies. The vision system uses a number of standard CCD cameras, mounted either above the flexible parts feeders or on the robot arms. Since the number of camera inputs to the AdeptVision system is limited to four, a low- cost, custom video multiplexer was developed, utilizing a monolithic video-switcher integrated circuit. This allows up to four cameras to be attached to each video input on the video hardware. In keeping with the quick-changeover philosophy, the vision routines are designed to be reusable; that is a given routine may be used to locate several different but similar parts (i.e. similar asymmetries, topology, etc.). This approach has many advantages, including minimizing the number of software routines. In addition, this reusability allows for software modularity and “agility 6 .” For example, by parameterizing the characteristics that a routine searches for, it can be applied to parts that have a similar profile but are of a different size. This means that parts with similar geometries to those in the parts library can be added to the system by simply modifying the inspection procedures that call these lower-level, reusable routines. 2.5 Introduction of New Parts Adding a new part to the system involves a few well defined tasks. A vision routine which determines the pose of the part is developed, utilizing the library of reusable vision routines. If the new part has characteristics that appear nowhere else in the parts library, new routines may need to be added to the software library. Also, if the part has not been designed for use on the generic parts feeders (e.g. it has no stable poses, like a cylinder), the feeders may require a belt change or a change in the angle of inclination. A gripper must also be designed to manipulate the new part. In order to minimize the specialized hardware and avoid tool changes during assembly, the gripper design should be performed concurrently with the gripper designs for other parts to be assembled at a given robot. For instance, if a given operation requires both an A widget and a B widget to be assembled at the first robot, the gripper designer should take this into account. In general, it is best to design the parts and the associated hardware concurrently. This will allow maximum reuse of software, minimal change to the flexible feeding setup and the design of a robust assembly sequence which will enhance unattended operation. This approach is known as Design for Manufacturing and Assembly 7 , or simply DFMA. 3. Computer Hardware/Controller Design The current software has been developed entirely in the V+ 8 programming language and operating system, on Adepts MV controller. For most industrial applications, this programming environment would be sufficient; however, it lacks the power and flexibility needed to support rapid software development and changeover. This is largely because V+ lacks features which are standard in other languages and operating systems, such as user-defined functions, standard data structures and shell script execution. To circumvent these limitations, a more extensive controller interface design is under development. It will allow the system to support C and C+, and provide a friendlier and more flexible user interface. In addition, it will allow the use of a real-time operating system, thus simplifying software development and improving performance. I/O Reflective Memory Network Ethernet Adept MV Controller Agile Workcell Non-Adept VME Cage Workstation Figure 4: System Architecture In this design, the systems capabilities are expanded by using a second VMEbus in addition to the MV controller VMEbus (Figure 4). This second VMEbus houses I/O boards and dedicated single-board computers (SBCs), on which a real-time operating system executes. C and C+ programs running on the SBCs are responsible for all high-level control and robot motions (e.g. conveyor control, pneumatic operations, specifying robot destinations), while the MV controller is used exclusively for low-level robot motions (e.g. servo control and trajectory generation) and some machine vision routines. In later implementations, a vision processing board can also be used on the second VMEbus, thereby augmenting the AdeptVision system. The two buses are connected by a reflective memory network. This consists of two memory cards, one on each bus, which can be connected by either a cable or a fiber optic link. Changes made to memory on This paper to be published in the Proceedings of the 1996 IEEE International Conference on Robotics and Automation For more information, contact: Roger Quinn, Associate Professor - Mechanical Engineering Case Western Reserve University, 216-368-3222 one board are automatically reflected on the other, thus allowing commands and data to be transmitted between the two buses 9 . The SBCs can thus place robot and vision commands on the reflective memory network. These are read by a set of command servers running on the MV controller. The servers execute the commands and, where applicable, return the results via the same network. 4. Workcell Software Software is another key to the flexibility of an agile manufacturing workcell; however, this flexibility does not come without careful design. Although software is inherently easier to change than hardware, the structure of a software system can degrade after repeated modification, leading to poor reliability and increased maintenance costs. In designing the workcell control software, we have employed software engineering methods and tools that support the principle of design for change. In particular, our latest design is object-oriented (OO), that is, it is based upon identifying the objects of the system, which are those entities having a state and a behavior. Physical devices, abstract data structures, and entire subsystems are modeled as objects that provide a well-defined set of services whose implementation is encapsulated and hidden. Emphasis on OO software design reduces the amount of effort required to introduce new products into the workcell through reusable code. The ability to rapidly introduce new products into the workcell is crucial to an agile system. Object types or classes are defined using the C+ class construct, wherein services correspond to member- function calls. New classes are derived from existing ones by adding services or by overriding the implementations of existing services. Object orientation facilitates maintenance because the implementation of a class can be changed without affecting client code, which uses the classs services, and because a derived class can be used wherever its parent class can be. In addition to satisfying the requirements of our particular manufacturing application, we wish to specify software design components that might prove useful in a variety of agile manufacturing applications. Hence, we have sought to identify design patterns for agile manufacturing. A design pattern is a group of communicating objec