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The tangible and intangible benefits of robotic simulation for manufacturing development are rapidly becoming evident in industry. The use of such systems requires an understanding of the appropriate components that synthesise and compose a simulation model. The principle objective of this chapter is to provide a comprehensive overview of these simulation components. Particular attention is made to the history of computer simulation, the fundamentals of robotics, the ABB IRB400_10 robot and the simulation-robot relationship. The robotic simulation package Workspace 5 is introduced along with its key navigation suggestions. Finally, the structure of this dissertation is defined.
.1 The History of Simulation
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Simulation involves the imitation of conditions of situations for the purpose of training or predicting outcomes.
The earliest documented use of simulation by man for training dates back to military training by the Roman Empire. Soldiers utilised a tree trunk to practice sword strokes on foot. Apparatus that replicated environmental conditions were developed allowing training to progress to practicing sword strokes in a boat and on horseback along with developing a six-foot wooden figure of an enemy soldier armed with a shield and sword. Simulation for military training has developed through the ages and continues to be a key technique for training and predicting outcomes today.
The methodology is applied to the definition of simulation in the 1st century. That is, simulation is a technique for imitating some behaviour of some situation of a process by means of a suitable analogous situation or apparatus. Modern simulators have been developed to acquire the skill necessary to control movement and processes. Such examples include the motion of an aircraft, automobile and ships or the processes of air traffic control and atomic power.
Early simulation schemes have branched off into many areas, the most prominent use has been in the field of medicine. However, in manufacturing, simulation is increasingly being used as a tool to increase production capacity, and workplace safety. Visualization and graphics have undoubtedly made a huge impact on all simulation companies. Easy-to-use modelling has resulted in low-priced packages that would have been unthinkable a few years ago. Simulation is no longer just the domain of academics.
The history of computer simulation dates back to World War II when two mathematicians, Jon Von Neumann and Stanislaw Ulam, were required to investigate the baffling problem of neutron behaviour. Trial and error experiments were costly and the problem was too complicated for analysis. Hence, the Roulette wheel technique was suggested by the mathematicians [online]. The basic data regarding the occurrence of events were known, into which the probabilities of separate events were emerged in a systematic analysis to predict the outcome of the whole sequence of events [online]. With the remarkable success of the technique, its emerging popularity found many applications in business and industry.
In post-war times, new technologies that were developed for military purposes during the war began to emerge as problem-solving tools in the business world. In the late 140s and 50s analogue and digital commercially designed computers started to appear in a number of organizations. Computer simulation was not a useful tool in the 50s as simulation exploited great lengths of time to get results and required many skilled people. The result was a considerable cost in both personnel and computer time but most discouraging was that results were often ambiguous.
In October 161, IBM presented the Gordon Simulator to a system design company called Norden, which allowed for the distribution of weather information to general aviation. IBM provided the software and hardware and a team was able to construct a model, simulate a problem and obtain answers in only six weeks. A new tool had become available for system designers. With the success of the Gordon Simulator, models began to be produced for groups outside Norden and hence, computer simulation activity was established. Early simulation groups were established at Boeing, Martin Marietta, Air Force Logistics Command, General Dynamics, Hughes Aircraft, Raytheon, Celanese, Exxon, Southern Railway and the computer manufacturers were IBM, Control Data, National Cash Register and UNIVAC [online]. As computer technology developed through the 60s and 70s, several simulation languages were developed with few efforts to coordinate and compare the different approaches.
In the 70s, simulation became a topic taught to Industrial Engineers in school but rarely applied as long hours spent at the computer terminal and seemingly, endless runs were required to find an obscure bug in a language. The popularity of simulation as a powerful tool only increased with the increasing number of conferences and sessions being held on the topic in the United States at the time. Such conferences included a panel discussion at Miami (USA) in 178 on the Failures of Simulation focussing on what can and does go wrong and a paper on Managing Simulation Projects. The number of sessions held on simulation doubled by 171 and continued to rise to about forty sessions in 177 and sixty sessions in 18 compared to twelve in 167 [online].
The commercial availability of a large number of computerised manufacturing systems was complemented by the emergence of an extensive array of available computer software and hardware, particularly from 180 on. At the same time, the attractive computer price relative to performance was fuelling a similar explosion of computing applications in engineering design and plant automation. However, two common fears of simulation in the early 80s were
1) Simulation is extremely complicated. Therefore, only experts can use it.
) Simulation is extremely time consuming because of programming and debugging.
Pritsker and associates developed SLAMII in 18 highlighting simulation software as a powerful tool. It was popularly used on IBM PC and provided three different modelling approaches Network, Discrete Event and Continuous. It also provided the flexibility to use any combination of them in a single simulation model. At release, it costed $75. In 184, the first simulation language specifically designed for modelling manufacturing systems was developed and in the late 80s, SIMANIV and CINEMAIV were developed using animation software. Models of complex systems could be developed entirely with easy-to-use menu driven frameworks, increasing software interactive capabilities. Other capabilities included expanded drawing features, real time plots and frequency graphs [online]. Management was now able to assess the cost-benefit alternatives, maintenance strategies, converting equipment repairs and capital replacements and so forth.
The power of simulation as a tool became evident in the mid 0s as the challenge of manufacturing product and process improvement increased. One such example was that of a modern electronic assembly companies called Universal Data Systems. Their test was to convert the entire plant to a hybrid flow-shop where an individual unit would be sent to the next operation as soon as it was completed at the current operation. One serious reservation for the change was the impact on finished goods inventory. Experiments were carried out using the simulation program written in GPPS/PC (a succession of the Gordon Simulator) using an IBM PC/AT. The entire program took 0 days to simulate and results were positive with the eventual conversion of the entire plant, a flow-shop environment as compared to the original batch environment [online].
Models were increasingly used to design new plants and to plan the flow of work in these facilities before physical implementation. The rapid development of computer graphics largely influenced the visual and user-friendly capabilities of simulation software. Technology had moved so far that simulation became quicker, cheaper, and more responsive. In 18, software providing automatic data collection, optimisation and a new Windows interface, such as Micro Saint version .0, began to stand out. In addition, it did not require the ability to write in any programming language.
Today, simulation has advanced to such a stage that the software enables the user to model, execute and animate any manufacturing system in any level of detail in a very short amount of time. The products, equipment and information are represented by a single entity associated with four dimensions (x, y, z and time) and a definition of its behaviours.
Advanced versions of simulation software today support the following features
· Uniquely structured environment allows the user to quickly enter the geometry and production requirements of a model.
· Expert system technology generates details automatically while windows and pop-up menus guide the user through the modelling process.
· Changes can be made quickly and easily with far less chance of errors.
· Built in material-handling templates make the user more productive. Eliminating time wasting programming.
· The user can verify and test designs, answer what-if questions, explore more alternatives and catch system glitches using D animation, all before implementation.
· D graphics are automatically created as the user enters data.
· Results can be communicated in real time automation.
Simulation has developed in leaps and bounds since the 0s and the future of simulation may involve the integration with other techniques and software applications.
. Fundamentals of Robotics
The configuration of a robot can vary greatly depending on the operation it is required to perform. The robot industry uses degrees of freedom to describe the operational characteristics of a robot. The way a robot moves and the assembly structure of a robot defines the robot configuration. Figure 1 shows an articulated robot with six degrees of freedom. These are arm sweep, shoulder swivel, elbow extension, wrist pitch, wrist yaw and wrist roll. The first three degrees of freedom move the robot limb in space, while the last three degrees of freedom orientate the tool or gripper in position for the operation at hand. A robot joint is a mechanism that permits relative movement between parts of a robot arm.
Figure 1 - Six Degrees of Freedom Robot
Robots are classified based on their physical configurations and/or the control systems adopted. Commercially available industrial robots are classified into four basic configurations. These are Cartesian configuration, cylindrical configuration, polar configuration and jointed-arm configuration. A thorough explanation of each configuration is beyond the scope of this text.
..1 End Effector
The end effector is commonly known as the robot hand. It is mounted on the wrist and enables the robot to perform specified tasks. Two major types of end effectors are grippers and tools.
Grippers are generally used to grasp and hold an object and place it in a desired position. Grippers can be further classified as mechanical, vacuum, magnetic and so forth. A tool is used to perform an operation on a work part and can be mounted directly on the robot end effector. Examples of tools are spot/arc-welding tools; spray painting nozzles and rotating spindles for drilling and grinding.
.. Robot Movement and Precision
Speed of response and stability are two important characteristics of robot movement. Speed defines how quickly the robot arm moves from one point to another. Stability refers to robot motion with the least amount of oscillation. Speed and stability are often conflicting goals. The precision of robot movement is defined by three basic features Spatial Resolution, Accuracy and Repeatability.
The spatial resolution of a robot is the smallest increment of movement into which the robot can divide its work volume; it is dependant on the robot systems control resolution and the robots mechanical inaccuracies. For a particular axis, the number of separate increments is given by
Number of increments = n
Where n is the number of bits in the control memory.
Equation 1 - Calculating Spatial Resolution
Spatial resolution can be improved by enhancing the control bit capacity. Other factors leading to robot inaccuracies can include elastic deformation in the links due to gravity, speed with which the arm is moving and the condition of the robot. The accuracy of the robot is the ability to position its wrist end at a desired target point within its reach and repeatability is the robots ability to position its end effector at a point previously been taught to the robot.
.. Robot Reach
The robot reach is known as the robot work envelope or work volume and is the area of all the points in the surrounding space that can be reached by the robot arm. The area reachable by the end effector itself is not considered part of the work envelope.
..4 Robot Programming
The objective of robot programming is to make the robot understand its work cycle. The program teaches the robot the path it should take, the points it should reach precisely, how to interpret sensor data, how and when to actuate the end effector, how to move parts from one location to another and so on.
Programming a robot can be achieved in two distinct forms teach-by-showing and textual language programming. In teach-by-showing programming, the programmer is required to move the robot arm through the desired motion path, which is stored in the robot memory by the controller. The motion of the robot may be achieved via a teach pendant (powered leadthrough), which is small handled control box equipped with buttons and dials used to control the robots movements, or a manual leadthrough where the programmer physically moves the robot through the required motion cycle. Textual language programming is a method whereby an English-like language is used to establish the logical sequence of a work cycle. Off-line programming is used when a textual language program is entered defining the work cycle without the use of the teach pendant.
..5 Robotic Application
The scope of robotic application is continuously growing. In the manufacturing environment robots are used to carry out continuous work associated with the production line. Robots have been employed in flexible automation such as cellular and flexible manufacturing whereby two or three NC machines are served by a robot performing loading and unloading operations. Welding is a popular application for robots as is eliminates the need for human beings in a tedious, repetitive, hot and cramped environment. Furthermore, productivity of robots in such an application is high as can be seen in automobile assembly lines. Along with welding, spray painting has proven to be suitable for the application of robotic technology. Apart from the removal of health risks to humans (as with the welding application) robots have the potential to achieve a higher level of consistency thus increasing quality. Other robotic applications include assembly lines, part assembly stations, pick-and-place (material handling) operations, gluing, inspection and so on.
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