
- •1. INTEGRATED AND AUTOMATED MANUFACTURING
- •1.1 INTRODUCTION
- •1.1.1 Why Integrate?
- •1.1.2 Why Automate?
- •1.2 THE BIG PICTURE
- •1.2.2 The Architecture of Integration
- •1.2.3 General Concepts
- •1.3 PRACTICE PROBLEMS
- •2. AN INTRODUCTION TO LINUX/UNIX
- •2.1 OVERVIEW
- •2.1.1 What is it?
- •2.1.2 A (Brief) History
- •2.1.3 Hardware required and supported
- •2.1.4 Applications and uses
- •2.1.5 Advantages and Disadvantages
- •2.1.6 Getting It
- •2.1.7 Distributions
- •2.1.8 Installing
- •2.2 USING LINUX
- •2.2.1 Some Terminology
- •2.2.2 File and directories
- •2.2.3 User accounts and root
- •2.2.4 Processes
- •2.3 NETWORKING
- •2.3.1 Security
- •2.4 INTERMEDIATE CONCEPTS
- •2.4.1 Shells
- •2.4.2 X-Windows
- •2.4.3 Configuring
- •2.4.4 Desktop Tools
- •2.5 LABORATORY - A LINUX SERVER
- •2.6 TUTORIAL - INSTALLING LINUX
- •2.7 TUTORIAL - USING LINUX
- •2.8 REFERENCES
- •3. AN INTRODUCTION TO C/C++ PROGRAMMING
- •3.1 INTRODUCTION
- •3.2 PROGRAM PARTS
- •3.3 CLASSES AND OVERLOADING
- •3.4 HOW A ‘C’ COMPILER WORKS
- •3.5 STRUCTURED ‘C’ CODE
- •3.6 COMPILING C PROGRAMS IN LINUX
- •3.6.1 Makefiles
- •3.7 ARCHITECTURE OF ‘C’ PROGRAMS (TOP-DOWN)
- •3.8 CREATING TOP DOWN PROGRAMS
- •3.9 CASE STUDY - THE BEAMCAD PROGRAM
- •3.9.1 Objectives:
- •3.9.2 Problem Definition:
- •3.9.3 User Interface:
- •3.9.3.1 - Screen Layout (also see figure):
- •3.9.3.2 - Input:
- •3.9.3.3 - Output:
- •3.9.3.4 - Help:
- •3.9.3.5 - Error Checking:
- •3.9.3.6 - Miscellaneous:
- •3.9.4 Flow Program:
- •3.9.5 Expand Program:
- •3.9.6 Testing and Debugging:
- •3.9.7 Documentation
- •3.9.7.1 - Users Manual:
- •3.9.7.2 - Programmers Manual:
- •3.9.8 Listing of BeamCAD Program.
- •3.10 PRACTICE PROBLEMS
- •3.11 LABORATORY - C PROGRAMMING
- •4. NETWORK COMMUNICATION
- •4.1 INTRODUCTION
- •4.2 NETWORKS
- •4.2.1 Topology
- •4.2.2 OSI Network Model
- •4.2.3 Networking Hardware
- •4.2.4 Control Network Issues
- •4.2.5 Ethernet
- •4.2.6 SLIP and PPP
- •4.3 INTERNET
- •4.3.1 Computer Addresses
- •4.3.2 Computer Ports
- •4.3.2.1 - Mail Transfer Protocols
- •4.3.2.2 - FTP - File Transfer Protocol
- •4.3.2.3 - HTTP - Hypertext Transfer Protocol
- •4.3.3 Security
- •4.3.3.1 - Firewalls and IP Masquerading
- •4.4 FORMATS
- •4.4.1 HTML
- •4.4.2 URLs
- •4.4.3 Encryption
- •4.4.4 Clients and Servers
- •4.4.5 Java
- •4.4.6 Javascript
- •4.5 NETWORKING IN LINUX
- •4.5.1 Network Programming in Linux
- •4.6 DESIGN CASES
- •4.7 SUMMARY
- •4.8 PRACTICE PROBLEMS
- •4.9 LABORATORY - NETWORKING
- •4.9.1 Prelab
- •4.9.2 Laboratory
- •5. DATABASES
- •5.1 SQL AND RELATIONAL DATABASES
- •5.2 DATABASE ISSUES
- •5.3 LABORATORY - SQL FOR DATABASE INTEGRATION
- •5.4 LABORATORY - USING C FOR DATABASE CALLS
- •6. COMMUNICATIONS
- •6.1 SERIAL COMMUNICATIONS
- •6.2 SERIAL COMMUNICATIONS UNDER LINUX
- •6.3 PARALLEL COMMUNICATIONS
- •6.4 LABORATORY - SERIAL INTERFACING AND PROGRAMMING
- •6.5 LABORATORY - STEPPER MOTOR CONTROLLER
- •7. PROGRAMMABLE LOGIC CONTROLLERS (PLCs)
- •7.1 BASIC LADDER LOGIC
- •7.2 WHAT DOES LADDER LOGIC DO?
- •7.2.1 Connecting A PLC To A Process
- •7.2.2 PLC Operation
- •7.3 LADDER LOGIC
- •7.3.1 Relay Terminology
- •7.3.2 Ladder Logic Inputs
- •7.3.3 Ladder Logic Outputs
- •7.4 LADDER DIAGRAMS
- •7.4.1 Ladder Logic Design
- •7.4.2 A More Complicated Example of Design
- •7.5 TIMERS/COUNTERS/LATCHES
- •7.6 LATCHES
- •7.7 TIMERS
- •7.8 COUNTERS
- •7.9 DESIGN AND SAFETY
- •7.9.1 FLOW CHARTS
- •7.10 SAFETY
- •7.10.1 Grounding
- •7.10.2 Programming/Wiring
- •7.10.3 PLC Safety Rules
- •7.10.4 Troubleshooting
- •7.11 DESIGN CASES
- •7.11.1 DEADMAN SWITCH
- •7.11.2 CONVEYOR
- •7.11.3 ACCEPT/REJECT SORTING
- •7.11.4 SHEAR PRESS
- •7.12 ADDRESSING
- •7.12.1 Data Files
- •7.12.1.1 - Inputs and Outputs
- •7.12.1.2 - User Numerical Memory
- •7.12.1.3 - Timer Counter Memory
- •7.12.1.4 - PLC Status Bits (for PLC-5s)
- •7.12.1.5 - User Function Memory
- •7.13 INSTRUCTION TYPES
- •7.13.1 Program Control Structures
- •7.13.2 Branching and Looping
- •7.13.2.1 - Immediate I/O Instructions
- •7.13.2.2 - Fault Detection and Interrupts
- •7.13.3 Basic Data Handling
- •7.13.3.1 - Move Functions
- •7.14 MATH FUNCTIONS
- •7.15 LOGICAL FUNCTIONS
- •7.15.1 Comparison of Values
- •7.16 BINARY FUNCTIONS
- •7.17 ADVANCED DATA HANDLING
- •7.17.1 Multiple Data Value Functions
- •7.17.2 Block Transfer Functions
- •7.18 COMPLEX FUNCTIONS
- •7.18.1 Shift Registers
- •7.18.2 Stacks
- •7.18.3 Sequencers
- •7.19 ASCII FUNCTIONS
- •7.20 DESIGN TECHNIQUES
- •7.20.1 State Diagrams
- •7.21 DESIGN CASES
- •7.21.1 If-Then
- •7.21.2 For-Next
- •7.21.3 Conveyor
- •7.22 IMPLEMENTATION
- •7.23 PLC WIRING
- •7.23.1 SWITCHED INPUTS AND OUTPUTS
- •7.23.1.1 - Input Modules
- •7.23.1.2 - Actuators
- •7.23.1.3 - Output Modules
- •7.24 THE PLC ENVIRONMENT
- •7.24.1 Electrical Wiring Diagrams
- •7.24.2 Wiring
- •7.24.3 Shielding and Grounding
- •7.24.4 PLC Environment
- •7.24.5 SPECIAL I/O MODULES
- •7.25 PRACTICE PROBLEMS
- •7.26 REFERENCES
- •7.27 LABORATORY - SERIAL INTERFACING TO A PLC
- •8. PLCS AND NETWORKING
- •8.1 OPEN NETWORK TYPES
- •8.1.1 Devicenet
- •8.1.2 CANbus
- •8.1.3 Controlnet
- •8.1.4 Profibus
- •8.2 PROPRIETARY NETWORKS
- •8.2.0.1 - Data Highway
- •8.3 PRACTICE PROBLEMS
- •8.4 LABORATORY - DEVICENET
- •8.5 TUTORIAL - SOFTPLC AND DEVICENET
- •9. INDUSTRIAL ROBOTICS
- •9.1 INTRODUCTION
- •9.1.1 Basic Terms
- •9.1.2 Positioning Concepts
- •9.1.2.1 - Accuracy and Repeatability
- •9.1.2.2 - Control Resolution
- •9.1.2.3 - Payload
- •9.2 ROBOT TYPES
- •9.2.1 Basic Robotic Systems
- •9.2.2 Types of Robots
- •9.2.2.1 - Robotic Arms
- •9.2.2.2 - Autonomous/Mobile Robots
- •9.2.2.2.1 - Automatic Guided Vehicles (AGVs)
- •9.3 MECHANISMS
- •9.4 ACTUATORS
- •9.5 A COMMERCIAL ROBOT
- •9.5.1 Mitsubishi RV-M1 Manipulator
- •9.5.2 Movemaster Programs
- •9.5.2.0.1 - Language Examples
- •9.5.3 Command Summary
- •9.6 PRACTICE PROBLEMS
- •9.7 LABORATORY - MITSUBISHI RV-M1 ROBOT
- •9.8 TUTORIAL - MITSUBISHI RV-M1
- •10. OTHER INDUSTRIAL ROBOTS
- •10.1 SEIKO RT 3000 MANIPULATOR
- •10.1.1 DARL Programs
- •10.1.1.1 - Language Examples
- •10.1.1.2 - Commands Summary
- •10.2 IBM 7535 MANIPULATOR
- •10.2.1 AML Programs
- •10.3 ASEA IRB-1000
- •10.4 UNIMATION PUMA (360, 550, 560 SERIES)
- •10.5 PRACTICE PROBLEMS
- •10.6 LABORATORY - SEIKO RT-3000 ROBOT
- •10.7 TUTORIAL - SEIKO RT-3000 ROBOT
- •10.8 LABORATORY - ASEA IRB-1000 ROBOT
- •10.9 TUTORIAL - ASEA IRB-1000 ROBOT
- •11. ROBOT APPLICATIONS
- •11.0.1 Overview
- •11.0.2 Spray Painting and Finishing
- •11.0.3 Welding
- •11.0.4 Assembly
- •11.0.5 Belt Based Material Transfer
- •11.1 END OF ARM TOOLING (EOAT)
- •11.1.1 EOAT Design
- •11.1.2 Gripper Mechanisms
- •11.1.2.1 - Vacuum grippers
- •11.1.3 Magnetic Grippers
- •11.1.3.1 - Adhesive Grippers
- •11.1.4 Expanding Grippers
- •11.1.5 Other Types Of Grippers
- •11.2 ADVANCED TOPICS
- •11.2.1 Simulation/Off-line Programming
- •11.3 INTERFACING
- •11.4 PRACTICE PROBLEMS
- •11.5 LABORATORY - ROBOT INTERFACING
- •11.6 LABORATORY - ROBOT WORKCELL INTEGRATION
- •12. SPATIAL KINEMATICS
- •12.1 BASICS
- •12.1.1 Degrees of Freedom
- •12.2 HOMOGENEOUS MATRICES
- •12.2.1 Denavit-Hartenberg Transformation (D-H)
- •12.2.2 Orientation
- •12.2.3 Inverse Kinematics
- •12.2.4 The Jacobian
- •12.3 SPATIAL DYNAMICS
- •12.3.1 Moments of Inertia About Arbitrary Axes
- •12.3.2 Euler’s Equations of Motion
- •12.3.3 Impulses and Momentum
- •12.3.3.1 - Linear Momentum
- •12.3.3.2 - Angular Momentum
- •12.4 DYNAMICS FOR KINEMATICS CHAINS
- •12.4.1 Euler-Lagrange
- •12.4.2 Newton-Euler
- •12.5 REFERENCES
- •12.6 PRACTICE PROBLEMS
- •13. MOTION CONTROL
- •13.1 KINEMATICS
- •13.1.1 Basic Terms
- •13.1.2 Kinematics
- •13.1.2.1 - Geometry Methods for Forward Kinematics
- •13.1.2.2 - Geometry Methods for Inverse Kinematics
- •13.1.3 Modeling the Robot
- •13.2 PATH PLANNING
- •13.2.1 Slew Motion
- •13.2.1.1 - Joint Interpolated Motion
- •13.2.1.2 - Straight-line motion
- •13.2.2 Computer Control of Robot Paths (Incremental Interpolation)
- •13.3 PRACTICE PROBLEMS
- •13.4 LABORATORY - AXIS AND MOTION CONTROL
- •14. CNC MACHINES
- •14.1 MACHINE AXES
- •14.2 NUMERICAL CONTROL (NC)
- •14.2.1 NC Tapes
- •14.2.2 Computer Numerical Control (CNC)
- •14.2.3 Direct/Distributed Numerical Control (DNC)
- •14.3 EXAMPLES OF EQUIPMENT
- •14.3.1 EMCO PC Turn 50
- •14.3.2 Light Machines Corp. proLIGHT Mill
- •14.4 PRACTICE PROBLEMS
- •14.5 TUTORIAL - EMCO MAIER PCTURN 50 LATHE (OLD)
- •14.6.1 LABORATORY - CNC MACHINING
- •15. CNC PROGRAMMING
- •15.1 G-CODES
- •15.3 PROPRIETARY NC CODES
- •15.4 GRAPHICAL PART PROGRAMMING
- •15.5 NC CUTTER PATHS
- •15.6 NC CONTROLLERS
- •15.7 PRACTICE PROBLEMS
- •15.8 LABORATORY - CNC INTEGRATION
- •16. DATA AQUISITION
- •16.1 INTRODUCTION
- •16.2 ANALOG INPUTS
- •16.3 ANALOG OUTPUTS
- •16.4 REAL-TIME PROCESSING
- •16.5 DISCRETE IO
- •16.6 COUNTERS AND TIMERS
- •16.7 ACCESSING DAQ CARDS FROM LINUX
- •16.8 SUMMARY
- •16.9 PRACTICE PROBLEMS
- •16.10 LABORATORY - INTERFACING TO A DAQ CARD
- •17. VISIONS SYSTEMS
- •17.1 OVERVIEW
- •17.2 APPLICATIONS
- •17.3 LIGHTING AND SCENE
- •17.4 CAMERAS
- •17.5 FRAME GRABBER
- •17.6 IMAGE PREPROCESSING
- •17.7 FILTERING
- •17.7.1 Thresholding
- •17.8 EDGE DETECTION
- •17.9 SEGMENTATION
- •17.9.1 Segment Mass Properties
- •17.10 RECOGNITION
- •17.10.1 Form Fitting
- •17.10.2 Decision Trees
- •17.11 PRACTICE PROBLEMS
- •17.12 TUTORIAL - LABVIEW BASED IMAQ VISION
- •17.13 LABORATORY - VISION SYSTEMS FOR INSPECTION
- •18. INTEGRATION ISSUES
- •18.1 CORPORATE STRUCTURES
- •18.2 CORPORATE COMMUNICATIONS
- •18.3 COMPUTER CONTROLLED BATCH PROCESSES
- •18.4 PRACTICE PROBLEMS
- •18.5 LABORATORY - WORKCELL INTEGRATION
- •19. MATERIAL HANDLING
- •19.1 INTRODUCTION
- •19.2 VIBRATORY FEEDERS
- •19.3 PRACTICE QUESTIONS
- •19.4 LABORATORY - MATERIAL HANDLING SYSTEM
- •19.4.1 System Assembly and Simple Controls
- •19.5 AN EXAMPLE OF AN FMS CELL
- •19.5.1 Overview
- •19.5.2 Workcell Specifications
- •19.5.3 Operation of The Cell
- •19.6 THE NEED FOR CONCURRENT PROCESSING
- •19.7 PRACTICE PROBLEMS
- •20. PETRI NETS
- •20.1 INTRODUCTION
- •20.2 A BRIEF OUTLINE OF PETRI NET THEORY
- •20.3 MORE REVIEW
- •20.4 USING THE SUBROUTINES
- •20.4.1 Basic Petri Net Simulation
- •20.4.2 Transitions With Inhibiting Inputs
- •20.4.3 An Exclusive OR Transition:
- •20.4.4 Colored Tokens
- •20.4.5 RELATIONAL NETS
- •20.5 C++ SOFTWARE
- •20.6 IMPLEMENTATION FOR A PLC
- •20.7 PRACTICE PROBLEMS
- •20.8 REFERENCES
- •21. PRODUCTION PLANNING AND CONTROL
- •21.1 OVERVIEW
- •21.2 SCHEDULING
- •21.2.1 Material Requirements Planning (MRP)
- •21.2.2 Capacity Planning
- •21.3 SHOP FLOOR CONTROL
- •21.3.1 Shop Floor Scheduling - Priority Scheduling
- •21.3.2 Shop Floor Monitoring
- •22. SIMULATION
- •22.1 MODEL BUILDING
- •22.2 ANALYSIS
- •22.3 DESIGN OF EXPERIMENTS
- •22.4 RUNNING THE SIMULATION
- •22.5 DECISION MAKING STRATEGY
- •23. PLANNING AND ANALYSIS
- •23.1 FACTORS TO CONSIDER
- •23.2 PROJECT COST ACCOUNTING
- •24. REFERENCES
- •25. APPENDIX A - PROJECTS
- •25.1 TOPIC SELECTION
- •25.1.1 Previous Project Topics
- •25.2 CURRENT PROJECT DESCRIPTIONS
- •26. APPENDIX B - COMMON REFERENCES
- •26.1 JIC ELECTRICAL SYMBOLS
- •26.2 NEMA ENCLOSURES

page 448
16. DATA AQUISITION
16.1 INTRODUCTION
An analog value is continuous, not discrete, as shown in figure 17.1. In the previous chapters, techniques were discussed for designing logical control systems that had inputs and outputs that could only be on or off. These systems are less common than the logical control systems, but they are very important. In this chapter we will examine analog inputs and outputs so that we may design continuous control systems in a later chapter.
Voltage |
logical |
continuous |
t |
Figure 17.1 - Logical and Continuous Values
Typical analog inputs and outputs for PLCs are listed below. Actuators and sensors that can be used with analog inputs and outputs will be discussed in later chapters.
Inputs:
•oven temperature
•fluid pressure
•fluid flow rate
Outputs:
•fluid valve position
•motor position
•motor velocity
This chapter will focus on the general principles behind digital-to-analog (D/A) and analog- to-digital (A/D) conversion. The chapter will show how to output and input analog values with a PLC.

page 449
16.2 ANALOG INPUTS
To input an analog voltage (into a PLC or any other computer) the continuous voltage value must be ’sampled’ and then converted to a numerical value by an A/D converter. Figure 17.2 shows a continuous voltage changing over time. There are three samples shown on the figure. The process of sampling the data is not instantaneous, so each sample has a start and stop time. The time required to acquire the sample is called the ’sampling time’. A/D converters can only acquire a limited number of samples per second. The time between samples is called the sampling period ’T’, and the inverse of the sampling period is the sampling frequency (also called sampling rate). The sampling time is often much smaller than the sampling period. The sampling frequency is specified when buying hardware, but for a PLC a maximum sampling rate might be 20Hz.
Voltage is sampled during these time periods
voltage |
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time |
T = (Sampling Frequency)-1 |
Sampling time |
Figure 17.2 - Sampling an Analog Voltage
A more realistic drawing of sampled data is shown in Figure 17.3. This data is noisier, and even between the start and end of the data sample there is a significant change in the voltage value. The data value sampled will be somewhere between the voltage at the start and end of the sample. The maximum (Vmax) and minimum (Vmin) voltages are a function of the control hard-

page 450
ware. These are often specified when purchasing hardware, but reasonable ranges are;
0V to 5V
0V to 10V -5V to 5V -10V to 10V
The number of bits of the A/D converter is the number of bits in the result word. If the A/D converter is ’8 bit’ then the result can read up to 256 different voltage levels. Most A/D converters have 12 bits, 16 bit converters are used for precision measurements.
V( t) |
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Vmax |
V( t2) |
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V( t1) |
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Vmin |
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t |
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τ |
t1 |
t2 |
where, |
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V( t) |
= the actual voltage over time |
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= |
sample interval for A/D converter |
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t |
= time |
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t1, t2 |
= time at start,end of sample |
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V( t1) , V( t2) |
= |
voltage at start, end of sample |
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Vmin, Vmax |
= |
input voltage range of A/D converter |
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N = |
number of bits in the A/D converter |
Figure 17.3 - Parameters for an A/D Conversion
The parameters defined in Figure 17.3 can be used to calculate values for A/D converters.
page 451
These equations are summarized in Figure 17.4. Equation 17.1 relates the number of bits of an A/ D converter to the resolution. Equation 17.2 gives the error that can be expected with an A/D converter given the range between the minimum and maximum voltages, and the resolution (this is commonly called the quantization error). Equation 17.3 relates the voltage range and resolution to the voltage input to estimate the integer that the A/D converter will record. Finally, equation 17.4 allows a conversion between the integer value from the A/D converter, and a voltage in the computer.
R = 2 |
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VERROR = |
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– V |
min |
(17.2) |
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– Vmin |
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– V |
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max |
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VC |
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(17.4) |
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---- |
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R |
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where, |
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R = |
resolution of A/D converter |
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the integer value representing the input voltage |
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VC = |
the voltage calculated from the integer value |
VERROR = the maximum quantization error
Figure 17.4 - A/D Converter Equations
Consider a simple example, a 10 bit A/D converter can read voltages between -10V and 10V. This gives a resolution of 1024, where 0 is -10V and 1023 is +10V. Because there are only 1024 steps there is a maximum error of ±9.8mV. If a voltage of 4.564V is input into the PLC, the A/D converter converts the voltage to an integer value of 746. When we convert this back to a voltage the result is 4.570V. The resulting quantization error is 4.570V-4.564V=+0.006V. This error can be reduced by selecting an A/D converter with more bits. Each bit halves the quantization error.
page 452
Given,
N = 10
Vmax = 10V
Vmin = –10V
Vin = 4.564V
Calculate,
R = 2N = 1024
VERROR = |
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– Vmin |
= |
0.0098V |
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2R |
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Vin – Vmin |
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= 746 |
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INT |
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R |
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V |
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– V |
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max |
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+ V |
= 4.570V |
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Figure 17.5 - Sample Calculation of A/D Values
If the voltage being sampled is changing too fast we may get false readings, as shown in Figure 17.6. In the upper graph the waveform completes seven cycles, and 9 samples are taken. The bottom graph plots out the values read. The sampling frequency was too low, so the signal read appears to be different that it actually is, this is called aliasing.

page 453
Figure 17.6 - Low Sampling Frequencies Cause Aliasing
The Nyquist criterion specifies that sampling frequencies should be at least twice the frequency of the signal being measured, otherwise aliasing will occur. The example in Figure 17.6 violated this principle, so the signal was aliased. If this happens in real applications the process will appear to operate erratically. In practice the sample frequency should be 4 or more times faster than the system frequency.
fAD > 2fsignal |
where, |
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fAD = |
sampling frequency |
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fsignal |
= maximum frequency of the input |
There are other practical details that should be considered when designing applications with analog inputs;
•Noise - Since the sampling window for a signal is short, noise will have added effect on the signal read. For example, a momentary voltage spike might result in a higher than normal reading. Shielded data cables are commonly used to reduce the noise levels.
•Delay - When the sample is requested, a short period of time passes before the final sample value is obtained.
•Multiplexing - Most analog input cards allow multiple inputs. These may share the A/D converter using a technique called multiplexing. If there are 4 channels using an A/
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D converter with a maximum sampling rate of 100Hz, the maximum sampling rate per channel is 25Hz.
•Signal Conditioners - Signal conditioners are used to amplify, or filter signals coming from transducers, before they are read by the A/D converter.
•Resistance - A/D converters normally have high input impedance (resistance), so they affect circuits they are measuring.
•Single Ended Inputs - Voltage inputs to a PLC can use a single common for multiple inputs, these types of inputs are called ’single’ ended inputs. These tend to be more prone to noise.
•Double Ended Inputs - Each double ended input has its own common. This reduces problems with electrical noise, but also tends to reduce the number of inputs by half.