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Proceedings of the 2014 American Society for Engineering Education Zone IV Conference Copyright © 2014, American Society for Engineering Education

Machine Vision, PLCs and Motion Control for Manufacturing Engineering Undergraduate Students

Dr. Jose A. Macedo, Nick Sweeney Industrial and Manufacturing Engineering

California Polytechnic State University, San Luis Obispo Abstract A sequence of two 10-week courses on advanced industrial automation were designed and implemented in 2013 with support from various industry partners. The courses, including laboratory, were designed for upper division undergraduate engineering students, and were offered for the first time in Spring and Fall 2013. The objective was to provide engineering students with theoretical and hands-on practical experience with automation technologies that are of prime importance in industry: machine vision, programmable logic controllers based on the IEC-61131 standard, motion control and the integration of these technologies. Developing applications and integration of state of the art industrial automation technology (hardware and software) has become fairly easy compared to only a few years ago. Manufacturing engineering students, as well as all other engineering students who will work on design and improvement of automated processes should be exposed to these advanced automation technologies. This paper describes the methodologies and relevant concepts covered in class, laboratory equipment, and lab activities developed for this course, as well as examples of student projects from Fall 2013. The course and laboratory materials were evaluated for learning effectiveness and technical content, which are included in this paper. Introduction During the past ten years, manufacturing automation has changed dramatically. Developments in software and new standards allow rapid development and integration of sophisticated automation applications. It is possible now to develop applications that require integration of machine vision, programmable logic controllers, control of multi-axis servomotors, and robot manipulators from multiple vendors in a fairly short amount of time. It has become an accepted technology with many successful industrial applications. These changes have occurred due to several factors: the growth in computing processor power and speed, growth in memory capacity, significant cost reduction of computer and machine vision technologies, the availability of powerful and easy-to-use PLC, machine vision and motion control software tools, and the development of industry standards such as the IEC 61131. There is much interest in industry to recruit talented engineers with knowledge of automation of products and processes. It is important to distinguish the difference between engineers who may work in automation of products, known as mechatronics or embedded computers, and engineers who may work on automation of processes, known as factory automation. There are similarities in the body of knowledge for both of these automation engineers, and both are very much in demand. The difference between engineers who work in automation of products (mechatronics) and automation of processes, becomes evident when we look into the development cost, number

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http://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=1050&context=ime_fac


of copies into which the automation will be implemented and cost per unit. When developing an automated product, for example a refrigerator that is “internet ready”, the cost of development and cost of hardware will be prorated among many thousand copies of the product, so the cost per unit will be small enough to be attractive to consumers and competitive. When developing an automated process or production line, it is likely that there will be one or very few productions lines, but what is important is that the development of the automated system is completed in a short time, is robust, reliable, safe, easy to integrate to existing networks, easy to repair, and easy to modify. This paper is concerned with developing a sequence of two courses and laboratory experiences to prepare engineering students for the automation of processes and production lines. Details of the Courses These two courses are IME 356 Manufacturing Automation, and IME 416 Automation of Industrial Systems. Both courses include three-hours of lecture per week and a three-hour laboratory experience per week. These courses cover use of computers in factory automation, basic control theory including feedback, programming and use of programmable logic controllers (PLC), human-machine interface (HMI), number systems, digital inputs/outputs, analog inputs/outputs, A/D and D/A conversion, sensors, actuators, IEC 61131 standard, ladder logic, Boolean algebra, state transition diagrams, timers, counters, math instructions, logic functions, sequencer instructions, automation safety, fail safe concept, pneumatic actuators, solenoid valves, motion control, stepper motors, servo motors, encoders, machine vision, CNC motion control, robotics, automation networks, and integration of systems. The emphasis on the second course is on machine vision, two-axis servomotor control, and integration of systems. The cumulative objectives for these two courses are that by the end of this sequence, students should be able to: • Be able to identify relevant variables in the design of automated systems • Be able to describe the components of an automated system, their functions, and the various

technological options available for them. • Be able to select the components suitable for an automation application • Be able to design and integrate automation into a manufacturing system • Be familiar with programming a PLC using ladder logic or other IEC 61131 languages. • Be able to identify situations or systems which could be improved by the application of automation. • Be able to identify and select the automation components that are suitable for an intended

application. • Be able to design or integrate automation into a manufacturing system. • Be familiar with automation safety terminology, technology, and its application. • Be able to do an economic justification for an automated system. • Be able to describe the components of a machine vision systems, their functions, and the

various technological options available for them. • Be familiar with the most common image processing algorithms used in industrial applications. • Be able to identify situations or systems that could be improved by the application of machine

vision.


• Be able to identify and select the machine vision components suitable for an intended application.

• Be able to design or integrate machine vision into a manufacturing automation system. • Be able to describe the components of servomotor systems, their functions, and the various

technological options available for them, including multi-axis servos, stepper motors. • Be familiar with servomotor functions and algorithms used in industrial applications, such as:

electronic gearing, camming, and servo-tunning. • Be able to identify situations or systems that could be improved by the application of servo-

motors, and identify situations in when stepper motor control is adequate. • Be able to identify and select the motion control components suitable for an intended

application. • Be able to design or integrate stepper motors and servo motors into a manufacturing automation

system. These courses are offered within a quarter systems. Therefore, each course includes 10-weeks of lecture and laboratory. During the first six weeks of the session, students learn how to use the equipment in the laboratory, following prescribed lab activities which include challenge exercises. During the last four weeks of the session, students work on projects, to be described later in this paper. Details of the Laboratory There are 12 workstations in the laboratory, which can accommodate up to 24 students working in teams of two students per workstation. We have at least twelve copies of all the equipment available in the laboratory. Figures 1 and 2 show views of the automation laboratory.

Figure 1. Gene Haas Laboratory for Robotics and Automation The equipment available in the laboratory includes twelve setups of the following:


(1) Rockwell Automation, CompactLogix 5000 PLC, RSLogix 5000 Software, add-on modules for A/D, D/A, high-speed counter, and one-axis stepper motor controller, Kinetics 350 one-axis servomotor controller, FactoryTalk View software for HMI. See Figures 2 and 4.

(2) Yaskawa America, MPiec two-axis servomotor controller, drivers, and two Sigma-5 servomotors, MotionWorks IEC software, and I/O trainer built at Cal Poly. See Figure 3.

Figure 2. Rockwell Automation (Allen Bradley) CompactLogix PLC Trainer

Figure 3. Yaskawa 2-Axis Servo-Motor Control Trainer


(3) Keyence, XG-7000 Machine Vision Systems and color cameras. See Figures 4 and 5. (4) AMCI 3401 Stepper Motor Controller. See Figure 4.

Figure 4. Keyence Machine Vision Controller and CompactLogix PLC

Figure 5. Keyence Cameras for Machine Vision System


(5) Pneumatic Cylinder Trainer, Built at Cal Poly with SMC components. See Figure 6. (6) Linear Slides with Servomotor Control, Built at Cal Poly using Anaheim Automation

components and Allen-Bradley Kinetix, built at Cal Poly. See Figure 7.

Figure 6. Pneumatic Cylinder Control Trainer Setup

Figure 7. Linear Slide with Rockwell Automation Kinetix Servo-Motor


Student Projects Students were asked to develop a project in which they were expected to apply concepts learned in this class. All projects were self-selected. Students were encouraged to generate their own ideas for a project and to discuss these ideas with the instructors. There are some benefits as well as potential difficulties of this approach which instructors should be aware. The biggest benefit of self-selected projects is the high level of enthusiasm and motivation of the students once they start working on their project ideas. Students want to make their project idea work and will come to the lab more frequently to ensure the success of their project, very much like graduate students. A potential difficulty is that students unfamiliar with the technology may find it difficult to select a project idea. If the indecision is carried too far into the term, there may not be adequate time to develop or complete a quality project. Providing examples of project ideas, especially past projects for the same class, allows students to more easily move forward. Students were asked make a brief informal presentation in class at the end of the quarter and to prepare a video about their project. The presentations were useful to all students as examples of other applications, methods used, problems encountered, lessons learned, and to discuss possible future enhancements of the projects. The videos have been useful to show past projects to the next cohort of students, as well as to visitors in general. The next few pages describe briefly the project topics developed by students in the last two offerings. A cumulative 32 students developed 16 projects. All the projects were successful in meeting their initial objectives, and in many cases, the projects were enhanced with additional features. Summaries of the student projects follow.

Figure 8. Student Project - Inspection of sliced apples to detect if they have seeds


Figure 8 shows a project developed to inspect sliced apples to detect if they have seeds or not. The machine vision system was programmed to analyze the image and determine if the appled had seeds or not. If the apples had seeds, they would be moved by the servo motor and slide mechanism in front of a pneumatic cylinder to be rejected. Figures 9 and 10 show a project developed to copy any image presented to the camera on the vision system. The image was “sliced” into eight increments, and their boundaries of each segment were found, and their coordinates were sent to an X-Y table controlled by the two-axis servomotor system. The motion of the X-Y table was synchronized with a pneumatic cylinder which would lift and drop a pen to trace and replicate the drawing of the image.

Figure 9. Student Project – Copy machine to reproduce an image

Figure 10. Student Project – Copy machine to reproduce an image


Figures 11 and 12 show a student project to detect five fingers in a human hand using machine vision, and when all five fingers are detected, it directs a servomotor to move a cardboard hand to give a “high five”.

Figure 11. Student Project – High Five Machine

Figure 12. Student Project – High Five Machine


All of these projects required students to develop programs for the PLC, the machine vision controller, and the servomotor controller, and integrate these programs into one functional system. What is remarkable about all of these projects is that they were all developed during the last 3 to 4 weeks of the quarter, which is the way this classes and labs are designed. Evaluation of Learning Objectives Both courses offered in this laboratory were well received by students. We are in the process of developing instruments to assess the effectiveness of this lab in meeting the learning objectives. We are also working on improvements to the lab modules and instructions to students with the idea of developing a laboratory manual. Some of the anonymous comments made by students in IME 416 in Fall 2013 were: “Great class”, “Very interesting class pertaining to automation technology used in industry”, “I am very glad that Dr. Macedo was flexible enough to open the lab for us and help us at all times”, “The documents and tutorial videos were great”, and “I was able to learn on the latest automation equipment”. Conclusions Developing and integrating industrial automation applications has become fairly easy due to availability of new industry standards and software tools. Manufacturing engineering students, as well as all other engineering students who will work on design and improvement of automated processes should be exposed to advanced automation technologies. This paper describes effective methodologies, laboratory equipment, and lab activities developed for a two-course sequence on manufacturing automation at Cal Poly, as well as examples of student projects from Fall 2013. Acknowledgements The development of the Gene Haas Laboratory for Robotics and Automation was made possible by generous grants and equipment donations from: The Gene Haas Foundation, Rockwell Automation, Yaskawa America, and Keyence. Bibliography 1. Ferrater-Simón, Coia, et al, “A Remote Laboratory Platform for Electrical Drive Control Using Programmable

Logic Controllers”, IEEE TRANSACTIONS ON EDUCATION, VOL. 52, NO. 3, AUGUST 2009, p.425. 2. Ljungkrantz, Oscar, et al, “Formal Specification and Verification of Industrial Control Logic Components”,

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, VOL. 7, NO. 3, JULY 2010, p. 538.

3. Macedo,, Jose, et al, “Machine Vision Course for Manufacturing Engineering Undergraduate Students”, JOURNAL OF MANUFACTURING SYSTEMS, SME, VOL. 24, NO. 3, 2005, p.256

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