Ch 5 Industrial Control Systems 2023 PDF

Ch 5 Industrial Control Systems Outlines: 1. Architecture of Industrial Automation Systems 2. Industrial Automation vs. Industrial Information Technology...

Ch 5 Industrial Control Systems Outlines: 1. Architecture of Industrial Automation Systems 2. Industrial Automation vs. Industrial Information Technology 3. Process Industries vs. Discrete Manufacturing Industries 4. Classification of Control System 5. Continuous vs. Discrete Control 6. Computer Process Control ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Architecture of Industrial Automation Systems ❑ Industrial automation systems as a whole are quite complex entities. Industrial automation systems are very complex having large number of devices with confluence of technologies working in synchronization. ❑ In order to know the performance of the system we need to understand the various parts of the system. ❑ Industrial automation Various components in an industrial automation system can be explained using the automation pyramid systems are organized as shown above. Here, various layers represent the hierarchically as shown in the wideness ( in the sense of no. of devices ), and following figure. fastness of components on the time-scale.  Architecture of Industrial Automation Systems The spatial scale increases as the level is increased e.g. at lowest level a sensor works in a single loop, but there exists many sensors in an automation system which will be visible as the level is increased. The lowest level is faster in the time scale and the higher levels are slower. The aggregation of information over some time interval is taken at higher For example the sensors and actuators may be connected to the automatic controllers using a levels. point-to-point digital communication, while All the above layers are connected the automatic controllers themselves may be by various types of communication connected with the supervisory and production systems. control systems using computer networks. Some of these networks may be proprietary.  Example: Production Management System ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Architecture of Industrial Automation Systems Enterprise control layer: This deals less technical and more commercial activities like supply, demand, cash flow, product marketing etc. This is called as the ‘level 4’ layer. Production Control Layer: This solves the decision problems like production targets, resource allocation, task allocation to machines, maintenance management etc. This is called ‘level 3’ layer. Supervisory Control Layer: This layer drives the automatic control system by setting target/goal to the controller. Supervisory Control looks after the equipment, which may consists of several control loops. This is called as ‘level 2’ layer. : Automatic Control Layer: This layer consists of automatic control and monitoring systems, which drive the actuators using the process information given by sensors. This is called as ‘level 1’ layer. Sensors and Actuators Layer: This layer is closest to the processes and machines, used to translate signals so that signals can be derived from processes for analysis and decisions and hence control signals can be applied to the processes. This forms the base layer of the pyramid also called ‘level 0’ layer.  Architecture of Industrial Automation Systems Table 5.2 Levels of Automation in the Process Industries and Discrete Manufacturing Industries ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Architecture of Industrial Automation Systems ▪ Significant differences are seen in the low and intermediate levels. ▪ Device level: There are differences in the types of actuators and sensors used. Process Industries: the devices are used mostly for the control loops in chemical, thermal, or similar processing operations. Discrete Manufacturing: the devices control the mechanical actions of machines. ▪ At level 2: the difference is that unit operations are controlled in the process industries, and machines are controlled in discrete manufacturing operations. ▪ At level 3: the difference is between control of interconnected unit processing operations and interconnected machines. ▪ At the upper levels (plant and enterprise): the control issues are similar, allowing for the fact that the products and processes are different. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book  Industrial Automation vs. Industrial Information Technology ▪ Industrial Automation makes extensive use of Information Technology. Some of the major IT areas that are used in the context of Industrial Automation are: 1. Control and Signal Processing 2. Simulation, Design, Analysis, Optimization 3. Communication and Networking 4. Real-time Computing 5. Database ▪ However, Industrial Automation is distinct from IT in the following senses: Industrial Automation also involves significant amount of hardware technologies, related to Instrumentation and Sensing, Actuation and Drives, Electronics for Signal Conditioning, Communication and Display, Embedded as well as Stand-alone Computing Systems etc. As Industrial Automation systems grow more sophisticated in terms of the knowledge and algorithms they use, as they encompass larger areas of operation comprising several units or the whole of a factory, or even several of them, and as they integrate manufacturing with other areas of business, such as, sales and customer care, finance and the entire supply chain of the business, the usage of IT increases dramatically.  Features of IT However, the lower level Automation Systems that only deal with individual or , at best, a group of machines, make less use of IT and more of hardware, electronics and embedded computing.. ▪ Industrial information systems are generally: I. Reactive in the sense that they receive stimuli and in turn produce responses. Naturally, a crucial component of an industrial information system is its interface. II. Have to be real-time, by that we mean that the computation not only has to be correct, but also must be produced in time. An accurate result, which is not timely may be less preferable than a less accurate result produced in time. Therefore systems have to be designed with clear considerations of meeting computing time deadlines. III. Considered mission-critical, in the sense that the malfunctioning can bring about catastrophic consequences in terms of loss of human life or property. Therefore extraordinary care must be exercised during their design to make them flawless. In spite of that, elaborate mechanisms are often deployed to ensure that any unforeseen circumstances can also be handled in a predictable manner. Fault-tolerance to emergencies due to hardware and software faults must often be built in.  Process Industries vs. Discrete Manufacturing Industries ▪ Process industries Production operations are performed on amounts of materials: liquids, gases, powders, etc. ▪ Discrete manufacturing industries Production operations are performed on quantities of materials: Parts, product units ▪ The kinds of unit operations performed on the materials are different in the two industry categories. Figure 5.1 ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Process Industries and Discrete Manufacturing Industries ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover. 11  Process Industries Versus Discrete Manufacturing Industries ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Definitions: Variable and Parameters ❑ Variables - outputs of the process ❑ Parameters - inputs to the process ❑ Continuous variables and parameters: they are uninterrupted as time proceeds (e.g. flow rate, force , temperature, pressure & velocity) are continuous over time during the process. ▪ Also considered to be analog - can take on any of an infinite number of possible values within a certain practical range. ▪ They are not restricted to a discrete set of values ❑ Discrete variables and parameters - can take on only certain values within a given range. The most common types of discrete variable and parameters are: 1) Binary, i.e., ON/OFF, open/closed, and so on, i.e., limit switch open/closed, motor on/off, work part present/not present. 7/98  Definitions: Variable and Parameters 2) Discrete, are variables that can take on more than two possible values but less than an infinite number. Examples include daily piece counts in a production operation and the display of a digital tachometer. 3) Pulse data, which consist of a series of pulses called a pulse train. As a process variable, it might be used to indicate piece counts, i.e.; parts passing on a conveyor activate a photocell to produce a pulse for each part detected. As a process parameter, a pulse train might be used to drive a stepper motor. 7/98  Continuous and Discrete Variables and Parameters ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Automation Systems vs. Industrial Control Systems ▪ It is important at this stage to understand some of the differences in the senses that these two terms are generally interpreted in technical contexts and specifically in this course. These are given below. 1. Industrial Control Systems: the main function of control systems is to ensure that outputs follow the set points. 2. Automation Systems: may have much more functionality, such as computing set points for control systems, monitoring system performance, plant startup or shutdown, job and equipment scheduling, ….etc. Automation Systems are essential for most modern industries. ▪ Automation Systems may include Control Systems but the reverse is not true. Control Systems may be parts of Automation Systems.  Structure Elements of Industrial Control System ▪ The control system is one of the three basic components of an automated system (Module 1-Lecture1). This Module focuses on industrial control systems, in particular how digital computers are used to implement the control function in production. ▪ By industrial control systems, we denote the sensors systems, actuator systems as a controller. Controllers are essentially (predominantly electronic, at times pneumatic/hydraulic) elements that accept command signals from human operators or supervisory Systems, as well as feedback from the process sensors and produce or compute signals that are fed to the actuators. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Structure of Industrial Control ❑ Below, we classify the major functional elements typically found in IA systems and also describe the nature of technologies that are employed to realize the functions. Industrial Sensors and Instrument Systems: Modern sensors often have the additional capability of digital communication using serial, parallel or network communication protocols. Such sensors are called “smart” and contain embedded digital electronic processing systems. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Structure of Industrial Control ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Structure of Industrial Control ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Structure of Industrial Control ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Structure of Industrial Control ▪ Industrial Actuator Systems: convert the input signals computed by the control systems into forms that can be applied to the actual process and would produce the desired variations in the process physical variables. ▪ In the same way as in sensors but in a reverse sense, these systems convert the controller output, which is essentially information without the power, and in the form of electrical voltages (or at times pneumatic pressure) in two ways. Firstly it converts the form of the variable into the appropriate physical variable, such as torque, heat or flow. Secondly it amplifies the energy level of the signal manifold to be able to causes changes in the process variables. Thus, while both sensors and actuators cause variable conversions, actuators are highEducation, ©2008 Pearson power devices Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book while sensors are not. Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Structure of Industrial Control 1. The electronic signal-processing element accepts the command from the control system in electrical form. The command is processed in various ways. For example it may be filtered to avoid applying input signals of certain frequencies that may cause resonance. Many actuators are themselves closed feedback controlled units for precision of the actuation operation. Therefore the electronic signal-processing unit often contains the control system for the actuator itself. 2. The electronic power amplification element sometimes contains linear power amplification stages called servo-amplifiers. In other cases, it may comprise power electronic drive circuits such as for motor driven actuators. 3. The variable conversion element serves the function of altering the nature of the signal generated by the electronic power amplification element from electrical form to non-electrical form, generally in the form of motion. Examples include electrohydraulic servo valve, stepper/servo motors, current to pneumatic pressure converters etc.  Structure of Industrial Control 4. The non-electrical power conversion elements are used to amplify power further, if necessary, typically using hydraulic or pneumatic mechanisms. 5. The non-electrical variable conversion elements may be used further to transform the actuated variable in desired forms, often in several stages. Typical examples include motion-to-flow rate conversion in flow-valves, rotary to linear motion converters using mechanisms, flow-rate to heat conversion using steam or other hot fluids etc. 6. Other Miscellaneous Elements such as auxiliaries for lubrication/cooling/filtering, reservoirs, prime movers etc., sensors for feedback, components for display, remote operations, as well as safety mechanisms since the power handling level is significantly high. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Types of Industrial Control Systems ▪ Here the controller objective is to provide such inputs to the plant such that the output y(t) follows the input r(t) as closely as possible, in value and over time. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Types of Industrial Control Systems ▪ Just as there are two basic types of variables and parameters in processes, there are also two corresponding types of Control Systems: 1. Continuous control - variables and parameters are continuous and analog. This is also often termed as Automatic Control, Process Control, Feedback Control etc. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Types of Industrial Control Systems 2. Discrete control or Sequence / Logic Control - Many control applications do not involve analog process variables, that is, the ones which can assume a continuous range of values, but instead variables and parameters are discrete, variables that are set valued, that is they only assume values belonging to a finite set, mostly binary discrete. The simplest examples of such variables are binary variables, that can have either of two possible values, (such as 1 or 0, on or off, open or closed etc.). These control systems operate by turning on and off switches, motors, valves, and other devices in response to operating conditions and as a function of time. Such systems are referred to as sequence/logic control systems. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Types of Industrial Control Systems For example, in the operation of transfer lines and automated assembly machines, sequence control is used to coordinate the various actions of the production system (e.g., transfer of parts, changing of the tool, feeding of the metal cutting tool, etc.). A modern controller device used extensively for sequence control today in transfer lines, robotics, process control, and many other automated systems is the Programmable Logic Controller (PLC). In essence, a PLC is a special purpose industrial microprocessor based real-time computing system, ❑ Production operations in both the process industries and discrete parts manufacturing are characterized by continuous variables. ▪ Examples include force, temperature, flow rate, pressure, and velocity. All of these variables (whichever ones apply to a given production process) are continuous over time during the process, and they can take on any of an infinite number of possible values within a certain practical range. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Continuous Vs. Discrete Control ▪ In reality, most operations in the process and discrete manufacturing industries include both continuous and discrete variables and parameters. Consequently, many industrial controllers are designed with the capability to receive, operate on, and transmit both types of signals and data. ▪ Hence, in digital computer process control, even continuous variables and parameters possess characteristics of discrete data, and these characteristics must be considered (why?) in the design of the computer–process interface and the control algorithms used by the controller. 10/63  Continuous Control ▪ This is also often termed as Automatic Control, Process Control, Feedback Control etc. In continuous control, the usual objective is to maintain the value of an output variable at a desired level such that the output y(t) follows the input r(t) as closely as possible, in value and over time. ▪ Parameters and variables are usually continuous ▪ Similar to operation of a feedback control system ▪ Most continuous industrial processes have multiple feedback loops, all of which have to be controlled and coordinated to maintain the output variable at the desired value. ▪ Examples of continuous processes: ▪ Control of the output of a chemical reaction that depends on temperature, pressure, etc. ▪ Control of the position of a cutting tool relative to work-part in a CNC machine tool ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Continuous Process Control ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Types of Continuous Process Control ❑ It is an automatic regulating system in which the output is a variable (physical parameters) such as temperature, pressure, pH value, flow, liquid level and so on. It is widely used in different industries like paper, sugar, petrochemical, rubber and so on. In the following paragraphs, the most prominent categories are surveyed 1. Regulatory control 2. Feedforward control 3. Steady-State optimization 4. Adaptive control 5. On-line search strategies 6. Other specialized techniques i. Expert systems ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. ii. Neural networks No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Regulatory Control ❑ Objective - maintain process performance at a certain level or within a given tolerance band of that level. ❑ Appropriate when performance (productivity, efficiency, and/or quality product) relates to a quality measure ❑ Performance measure is sometimes computed based on several output variables ❑ Performance measure is called the Index of performance (IP) ❑ The trouble with regulatory control (and also with a simple feedback control loop) is that compensating action is taken only after a disturbance has affected the process output. ❑ Problem with regulatory control is that an error must exist in order to initiate control action. The presence of an error means that the output of the process is different from the desired value. Feedforward control, addresses this issue  Regulatory Control Regulatory control is to the overall process what feedback control is to an individual control loop in the process, as suggested by Figure 5.2. Fig. 5.2 Regulatory control. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Feedforward Control ▪ Objective: anticipate the effect of disturbances that will upset the process by sensing and compensating for them before they affect the process. A mathematical model is used to captures the effect of the disturbance on the process. ▪ Complete compensation for the disturbance is difficult due to variations, imperfections in the mathematical model and imperfections in the control actions. i.e., delays and/or imperfections in the feedback measurements, actuator operations, and control algorithms. ▪ Usually combined with regulatory control ▪ Regulatory control and feedforward control are more closely associated with process industries than with discrete product manufacturing. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Feedforward Control Combined with Feedback Control ▪ The feedforward control elements sense the presence of a disturbance and take corrective action by adjusting a process parameter that compensates for ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. any No portioneffect the of this material disturbance may be will reproduced, in any form or have by any means, onpermission without the inprocess. writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Steady-State Optimization ▪ Class of optimization techniques in which the process exhibits the following characteristics: 1. Well-defined index of performance (IP) such as product cost, production rate, or process yield; 2. Known relationship between process variables and IP 3. System parameter values that optimize IP can be determined mathematically ▪ When these characteristics apply, the control algorithm is designed to make adjustments in the process parameters to drive the process toward the optimal state. ▪ Open-loop system ▪ Several mathematical techniques are available for solving steady-state optimal control problems, including differential calculus, calculus of variations, and various mathematical programming methods. 17/63  Steady State (Open-Loop) Optimal Control ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Adaptive Control Operates in a Time-Varying Environment ▪ Adaptive control is distinguished from feedback control and steady- state optimal control by its unique capability to cope with a time- varying environment. ▪ The environment changes over time and the changes have a potential effect on system performance ▪ If the control algorithm is fixed, the system may perform quite differently in one environment than in another. ▪ An adaptive control system is designed to compensate for its changing environment by altering some aspect of its control algorithm to achieve optimal performance. ▪ In a production process, the “time-varying environment” consists of the variations in processing variables, raw materials, tooling, atmospheric conditions, and the like, any of which may affect performance.  Adaptive Control ▪ AC is a type of control systems in which the system parameters are automatically adjusted to keep the system at an optimum level are called adaptive control systems. Such type of control systems itself detects changes in the plant parameters and make essential adjustments in the controller parameters to maintain optimum level or performance. ▪ Steady-state optimal control operates as an open-loop system. It works successfully when there are no disturbances that invalidate the known relationship between process parameters and process performance. Because steady-state optimization is open-loop, it cannot compensate for disturbances. ▪ When such disturbances are present in the application, a self-correcting form of optimal control can be used, called adaptive control. Adaptive control is a self- correcting form of optimal control that includes feedback control. ▪ Measures the relevant process variables during operation (as in feedback control) ▪ Uses a control algorithm that attempts to optimize some index of performance (optimal control)  Adaptive Control System ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Three Functions in AC 1. Identification function – current value of IP is determined based on measurements of process variables 2. Decision function – decide what changes should be made to improve system performance ▪ Change one or more input parameters ▪ Alter some internal function of the controller 3. Modification function – implement the decision function ▪ Concerned with physical changes (hardware rather than software) ▪ In modification, the system parameters or process inputs are altered using available actuators to drive the system toward a more optimal state.  Adaptive control Applications ▪ Adaptive control is most applicable at levels 2 and 3 in the automation hierarchy (Table 5.2). One notable example is adaptive control machining, in which changes in process variables such as cutting force, power, and vibration are used to effect control over process parameters such as cutting speed and feed rate. ▪ Adaptive control is not appropriate for every machining situation. In general, the following characteristics can be used to identify situations where adaptive control can be beneficially applied: (a) The in-process timing consumes a significant portion of machining cycle time. (b) There are significant sources of variability in the job for which adaptive control can compensate. (c) The cost of operating the machine tool is high. (d) The typical jobs are those involving steel, titanium, and high strength alloys. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book  AC Machining Systems Approaches ▪ In the development of AC machining systems, two distinct approaches to the problem can be used. These are (i) AC Optimization (ACO): In which an IP is specified for the system. This IP is a measure of the overall process performance such as the production rate or cost per unit volume of metal removed. Most of ACO systems attempt to maximize the rate of work material removal to the tool wear rate. The IP is a function of the material removal rate divided by the total wear rate. The trouble with this IP is that the tool wear rate cannot be measured online with the current measurement technology. (ii) AC Constraints (ACC): The systems developed for actual production are somewhat less sophisticated than the research ACO system. The production AC systems utilize constraint limits imposed on certain measured process variables. These are called adaptive control constraint (ACC) systems. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  On-Line Search Strategies ▪ Special class of adaptive control in which the decision function cannot be sufficiently defined ▪ Relationship between input parameters and IP is not known, or not known well enough to implement the previous form of adaptive control ▪ Instead, experiments are performed on the process ▪ Small systematic changes are made in input parameters to observe effects ▪ Based on observed effects, larger changes are made to drive the system toward optimal performance. ▪ On-line search strategies include a variety of schemes to explore the effects of changes in process parameters, ranging from trial-and-error techniques to gradient methods. ▪ All of the schemes attempt to determine which input parameters cause the greatest positive effect on the index of performance and then move the process in that direction. There is little evidence that on-line search techniques are used much in discrete parts manufacturing.  Other Specialized Techniques ▪ Other specialized techniques include strategies that are currently evolving in control theory and computer science. ▪ Intelligent control is another major field in modern control technology. There are different definitions regarding intelligent control, but it is referred to as a control Para diagram that uses various artificial intelligence techniques, which may include the following methods: ❖ Learning control, ❖ Expert control, ❖ Fuzzy control, and ❖ Neural network control. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Other Specialized Techniques ❑ Learning control: uses pattern recognition techniques to obtain the current status of the control loop; and then makes control decisions based on the loop status as well as the knowledge or experience stored previously. ❑ Expert control: based on the expert system technology, uses a knowledge base to make control decisions. The knowledge base is built by human expertise, system data acquired on-line, and inference machine designed. Since the knowledge in expert control is represented symbolically and is always in discrete format, it is suitable for solving decision making problems such as production planning, scheduling, and fault diagnosis. It is not well suited for continuous control issues. ❑ Fuzzy control: unlike learning control and expert control, is built on mathematical foundations with fuzzy set theory. It represents knowledge or experience in a mathematical format that process and system dynamic characteristics can be described by fuzzy sets and fuzzy relational functions. Control decisions can be generated based on the fuzzy sets and functions with rules. ❑ Neural network control: is a control method using artificial neural networks. It has great potential since artificial neural networks are built on a firm mathematical foundation that includes versatile and well understood mathematical tools. Artificial neural networks are also used as one of the key elements in the model-free adaptive  Discrete Control Systems ▪ Discrete process control systems deal with parameters and variables that are discrete and that change values at discrete moments in time. ▪ Parameters and variables are also discrete, usually binary (0 or 1, off or on, open or closed, etc.). ▪ The changes are defined in advance by the program of instructions ▪ The changes are executed for either of two reasons: 1. The state of the system has changed (event-driven changes) 2. A certain amount of time has elapsed (time driven changes)  Discrete Control Systems: Event-Driven Changes ▪ Executed by the controller in response to some event that has altered the state of the system. The change can be to initiate an operation or terminate an operation, start a motor or stop it, open a valve or close it, and so forth. ▪ Examples: ▪ A robot loads a workpart into a fixture, and the part is sensed by a limit switch in the fixture ▪ The diminishing level of plastic in the hopper of an injection molding machine triggers a low-level switch, which opens a valve to start the flow of more plastic into the hopper ▪ Counting parts moving along a conveyor past an optical sensor ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Discrete Control Systems: Time-Driven Events ▪ Executed by the controller either at a specific point in time or after a certain time elapsed ▪ Examples: ▪ The factory “shop clock” sounds a bell at specific times to indicate start of shift, break start and stop times, and end of shift ▪ Heat treating operations must be carried out for a certain length of time ▪ In a washing machine, the agitation cycle is set to operate for a certain length of time ▪ By contrast, filling the tub is event-driven ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Discrete Control Systems: Logic Control ❑These two types of changes (event-driven changes & time driven changes) correspond to two different types of discrete control are logic control & sequence control. ❑Both types are referred to as switching systems because they switch their output values on and off in response to changes in events or time ❑Example: in the operation of transfer lines and automated assembly machines, sequence control is used to coordinate the various actions of the production system (e.g., transfer of parts, changing of the tool, feeding of the metal cutting tool, etc.).  Discrete Control Systems: Logic Control 1. Logic Control – is used to control the execution of event-driven changes. A switching system whose output at any moment is determined exclusively by the values of the current inputs. ▪ No memory and does not consider any previous values of input signals in determining the output sig ▪ No operating characteristics that depend on time ▪ Output at any moment depends on the values of the inputs ▪ Parameters and variables = 0 or 1 (OFF or ON) ❑ Elements of Logic Control: basic elements, called logic gates: ✓ AND – output = 1 if all inputs = 1, zero otherwise ✓ OR – output = 1 if any input = 1, zero otherwise ✓ NOT – output = 1 if (single) input = 0, and vice versa Additional elements: ✓ NAND – combination of AND and NOT ✓ NOR – combination of OR and NOT  Discrete Control Systems: Logic Control AND and OR Gate Electrical circuits illustrating the operation of the logical (a) AND and (b) OR gate The NOT function is referred to as the negation or inversion of the variable.  Discrete Control Systems: Logic Control The logical NAND gate is formed by combining an AND gate and a NOT gate in sequence The logical NOR gate is formed by combining an OR gate followed by a NOT gate Symbols for Logical Gates: U.S. and ISO  Discrete Control Systems: Sequence Control 2. Sequential Control – is used to manage time-driven changes. A sequence control system or switching system that uses internal timing devices to determine when to initiate changes in output variables ▪ Outputs are usually generated “open loop” ▪ No feedback that control function is executed ▪ Sequence of output signals is usually cyclical, as in a high production work cycle ▪ The signals occur in the same repeated pattern within each regular cycle ▪ Common sequencing devices: ▪ Timer – output switches on/off at preset times ▪ Counter – counts electrical pulses and stores them  Discrete Control Systems: Ladder Logic Diagrams ❑ Ladder Logic Diagrams– A diagram in which various logic elements and other components are displayed along horizontal rungs connected on either end to two vertical rails. ▪ Types of elements and components: 1. Contacts - logical inputs (usually), e.g., limit switches, photo-detector 2. Loads - outputs, e.g., motors, lights, alarms, solenoids 3. Timers - to specify length of delay 4. Counters - to count pulses received ❑ Advantages of Ladder Logic Diagrams Familiar to shop personnel who must construct, test, maintain, and repair the control system Analogous to the electrical circuits used to accomplish logic and sequence control Principal technique for programming PLCs  Discrete Control Systems: Ladder Logic Diagrams Ladder Logic Diagram and Symbols  Discrete Control Systems ❑ There are many industrial actuators which have set of command inputs. The control inputs to these devices only belong to a specific discrete set. For example in the control of a conveyor system, analog motor control is not applied. Simple on-off control is adequate. Therefore for this application, the motor-starter actuation system may be considered as discrete having three modes, namely, start, stop and run. Other examples of such actuators are solenoid valves. ❑ Similarly, there are many industrial sensors (such as, Limit Switch / Pressure Switch/ Photo Switch etc.) which provide discrete outputs which may be interpreted as the presence/absence of an object in close proximity, passing of parts on a conveyor, or a given pressure value being higher or lower than a set value. These sensors thus indicate, not the value of a process variable, but the particular range of values to which the process variable belongs.  Discrete Control applications in discrete manufacturing ▪ Discrete control is widely used in discrete manufacturing as well as the process industries. ▪ In discrete manufacturing, it is used to control the operation of conveyors and other material transport systems (Chapter 10), automated storage systems (Chapter 11), standalone production machines (Chapter 14), automated transfer lines (Chapter 16), automated assembly systems (Chapter 17), and flexible manufacturing systems (FMS) (Chapter 19). ▪ All of these systems operate by following a well-defined sequence of start-and-stop actions, such as powered feed motions, parts transfers between workstations, and on-line automated inspections. ©2008 Pearson Educationnc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Discrete Control applications in process industries ▪ In the process industries, discrete control is associated more with batch processing than with continuous processes. In a typical batch processing operation, each batch of starting ingredients is subjected to a cycle of processing steps that involves changes in process parameters (e.g., temperature and pressure changes), possible flow from one container to another during the cycle, and finally packaging. ▪ The packaging step differs depending on the product. For foods, packaging may involve canning or boxing. For chemicals, it means filling containers with the liquid product and for pharmaceuticals, it may involve filling bottles with medicine tablets. ▪ In batch process control, the objective is to manage the sequence and timing of processing steps as well as to regulate the process parameters in each step. Accordingly, batch process control typically includes both continuous control and discrete control. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Computer Process Control ▪ Origins in the late 1950s and early 1960s in the process industries ▪ At that time, the only computers available for process control were slow, large, expensive, unreliable mainframes. The interrupt feature, by which the computer suspends current program execution to quickly respond to a process need, was developed during this period. ▪ In the late 1950s and early 1960s, oil refineries and chemical plants, use high-volume continuous production processes characterized by many variables and associated control loops. The processes had traditionally been controlled by analog devices, each loop having its own set-point value and in most instances operating independently of other loops. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Computer Process Control ▪ Direct digital control (DDC) system, in which certain analog devices are replaced by the computer, was installed by Imperial Chemical Industries in England in 1962. In this implementation, 224 process variables were measured, and 129 actuators (valves) were controlled. Improvements in DDC technology were made, and additional systems were installed during the 1960s. ▪ Advantages of DDC noted during this time included (1) cost savings by eliminating analog instrumentation, (2) simplified operator display panels, and (3) flexibility due to reprogramming capability. ▪ The development of the minicomputer in the late 1960s, process-control applications were easier to justify using these smaller, less expensive computers. ▪ Development of the microcomputer in the early 1970s continued this trend. Lower cost process-control hardware and interface equipment (such as an analog to-digital converters) were becoming available due to the larger markets made possible by low-cost computer controllers ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Computer Process Control ▪ Most of the developments in computer process control up to this time were biased toward the process industries rather than discrete part and product manufacturing. Just as analog devices had been used to automate process industry operations, relay banks were widely used to satisfy the discrete process-control (ON/OFF) requirements in manufacturing automation. ▪ The Programmable logic controller (PLC), a control computer designed for discrete process control, was developed in the early 1970s. ▪ Also, numerical control (NC) machine tools and industrial robots, technologies that preceded computer control, started to be designed with digital computers as their controllers. ▪ The term distributed control (DC) was used for this kind of system, the first of which was a product offered by Honeywell in 1975. ▪ In the early 1990s, personal computers (PCs) began to be utilized on the factory floor, sometimes to provide scheduling and engineering data to shop floor personnel, in other cases as the operator interface to processes controlled by PLCs. Today, PCs are sometimes used to directly control manufacturing operations. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Basic Control Requirements ▪ Whether the application involves continuous control, discrete control, or both, there are certain basic requirements that tend to be common to nearly all process-control applications. By and large, they are concerned with the need to communicate and interact with the process on a real-time basis. ▪ A real-time controller is a controller that is able to respond to the process within a short enough time period that process performance is not degraded. ▪ Real-time control usually requires the controller to be capable of multitasking, which means: coping with multiple tasks concurrently without the tasks interfering with one another. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Basic Control Requirements ❑ Correspond to the two types of changes mentioned previously in the context of discrete control systems (event-driven changes and time-driven changes); there are two basic requirements that must be managed by the controller to achieve real-time control: 1. Process-initiated interrupts: Controller must respond to incoming signals from the process (event-driven changes). Depending on relative priority, controller may have to interrupt current program to service a higher-priority need of the process. A process-initiated interrupt is often triggered by abnormal operating conditions, indicating that some corrective action must be taken promptly.  Basic Control Requirements 2. Timer-initiated actions: The controller must be capable of executing certain actions at specified points in time (time -driven changes). Timer-initiated actions can be generated at regular time intervals, ranging from very low values; e.g.; 100ms to several minutes, or they can be generated at distinct points in time. Typical timer-initiated actions in process control include: a) Scanning sensor values from the process at regular sampling intervals, b) Turning on and off switches; i.e.; motors and other binary devices associated with the process at discrete points in time during the work cycle, c) Displaying performance data on the operator’s console at regular times during a production run, d) Recomputing optimal parameter values at specified times.  Other Computer Control Requirements ❑ In addition to these basic requirements, the control computer must also deal with other types of interruptions and events. These include the following: 3. Computer commands to process ▪ To drive process actuators to accomplish a corrective action, or readjust a set point in a control loop. 4. System- and program-initiated events (related to the computer system itself): System initiated events - communications between computer and peripherals linked together in a network, in which, feedback signals; control commands; and other data must be transferred back and forth among the computers in the overall control of the process©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Other Computer Control Requirements Program initiated events - occurs when the program calls for some non-process-related actions, such as printing or display of reports on a printer or monitor. ▪ In both cases, events generally occupy a low level of priority compared with process interrupts, commands to the process, and timer- initiated events. 5. Operator-initiated events – Finally, the control computer must be able to accept input from personnel operator. Operator-initiated events include: (1) Entering new programs; (2) Editing existing programs; (3) Entering customer data, order number, or startup instructions for the next production run; (4) Requesting process data; and (5) Calling for emergency stops.  Capabilities of Computer Control ▪ The above requirements can be satisfied by providing the controller with certain capabilities that allow it to interact on a real-time basis with the process and the operator. These capabilities are : 1) Polling (data sampling or scanning) 2) Interlocks 3) Interrupt system 4) Exception handling ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  1. Polling (Data Sampling) ▪ Periodic sampling of data to indicate status of process. ▪ In some systems, the polling procedure simply requests whether any changes have occurred in the data since the last polling cycle and then collects only the new data from the process. ▪ This tends to shorten the cycle time required for polling. ▪ Issues related to polling include issues: 1. Polling frequency or rate – reciprocal of time interval between data samples 2. Polling order – sequence in which data collection points are sampled  1. Polling (Data Sampling) 3. Polling format – which refers to the manner in which the sampling procedure is designed. The alternatives in polling format include: 1. All sensors polled every cycle 2. Update only data that has changed this cycle 3. Using High-level and Low-level scanning, a) High-level scanning: in which only certain key data are collected each polling cycle (high-level scanning), b) Low-level scanning: if the data indicates some irregularity in the process, a low-level scan is undertaken to collect more complete data to ascertain the source of the irregularity. ❑ These issues become increasingly critical with very dynamic processes in which changes in process status occur rapidly.  2. Interlocks ❑ Interlocks provides a safeguard mechanisms for coordinating the activities of two or more devices and preventing one device from interfering with the other(s). There are two types of interlocks, input interlocks and output interlocks, where input and output are defined relative to the controller. 1. Input interlocks –is a signal from an external device(e.g., a limit switch, sensor, or production machine) that sent to the controller, Input interlocks are used for either of the following functions: a. Proceed to execute work cycle program. For example, the production machine communicates a signal to the controller that it has completed its processing of the part. This signal constitutes an input interlock indicating that the controller can now proceed to the next step in the work cycle, which is to unload the part. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  2. Interlocks b. Interrupt execution of work cycle program. For example, while unloading the part from the machine, the robot accidentally drops the part. The sensor in its gripper transmits an interlock signal to the controller indicating that the regular work cycle sequence should be interrupted until corrective action is taken. 2. An output interlock is a signal sent from the controller to some external device. It is used to control the activities of each external device and to coordinate their operation with that of the other equipment in the cell. ❑ For example, an output interlock can be used to send a control signal to a production machine to begin its automatic cycle after the work part has been loaded into it. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  3. Interrupt System ▪ A computer control feature that permits the execution of the current program to be suspended in order to execute another program in response to an incoming signal indicating a higher priority event. ▪ Upon receiving of an interrupt signal; the computer system transfers to a predetermined subroutine designed to deal with the specific interrupt. ▪ The status of the current program is remembered so that its execution can be resumed when servicing of the interrupt has been completed. ▪ An interrupt system is required in process control because it is essential that more important programs (ones with higher priority) be executed before less important programs (ones with lower priorities). A higher priority function can interrupt a lower priority function. ▪ The system designer must decide what level of priority should be attached to each control function. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  3. Interrupt System ▪ Interrupt conditions can be classified as internal or external. 1) Internal interrupt – generated by the computer system itself- ▪ Examples: ▪ Timer-initiated events such as polling data from sensors or sending commands to the process at specific points in clock time, ▪ System- and program initiated interrupts are also classified as internal because they are generated within the system. 2) External interrupts – generated external to the computer ▪ Examples: process-initiated interrupts, operator inputs ▪ The number of priority levels and the relative importance of the functions depend on the requirements of the individual process-control situation. For example, emergency shutdown of a process because of safety hazards would occupy a very high priority level, even if it is an operator-initiated interrupt. Most operator inputs would have low priorities.  3. Interrupt System ▪ To respond to the various levels of priority defined for a given control application, an interrupt system can have one or more interrupt levels (Table 5.4). 1) A single-level interrupt system has only two modes of operation: normal mode and interrupt mode. The normal mode can be interrupted, but the interrupt mode cannot. This means that overlapping interrupts are serviced on a first-come, first-served basis, which could have potentially hazardous consequences if an important process interrupt was forced to wait its turn while a series of less important operator and system interrupts were serviced. 2) A multilevel interrupt system has a normal operating mode plus more than one interrupt level as in Table 5.4; the normal mode can be interrupted by any interrupt level, but the interrupt levels have relative priorities that determine which functions can interrupt others. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  3. Interrupt System ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Example: Single-Level versus Multilevel Interrupt Systems Task 3 is the highest level priority. Task 1 is the lowest level. Tasks arrive for servicing in the order 1, then 2, then 3. (a) Task 3 must wait until Tasks 1 and 2 have been completed. (b) Task 3 interrupts execution of Task 2, whose priority level allowed it to interrupt Task 1.  4. Exception Handling ▪ In effect, Exception handling is a form of error detection and recovery discussed in Module 1-lecture 1 ▪ An exception is an event that is outside the normal or desired operation of the process control system. ▪ Dealing with the exception is an essential function in industrial control and generally occupies a major portion of the control algorithm. ▪ The need for exception handling may be indicated through the normal polling procedure or by the interrupt system. ▪ Examples of exceptions: ▪ Product quality problem ▪ Process variable outside normal operating range ▪ Shortage of raw materials or supplies necessary to sustain the process. ▪ Hazardous conditions, e.g., fire and controller malfunction. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book  Forms of Computer Process Monitoring and Control ❑ This section surveys the various forms of computer process monitoring and control, all but one of which are commonly used in industry today. The exception is direct digital control (DDC), which represents a transitory phase in the evolution of computer process control technology. ❑ In its pure form, DDC is no longer used today. DDC is briefly described to reveal the opportunities it contributed. ❑ Forms of computer process monitoring and control include: 1. Computer process monitoring: Process data, Equipment data & Product data 2. Direct digital control (DDC) 3. Numerical control (NC) and robotics 4. Programmable logic control (PLC) 5. Supervisory control (SC) 6. Distributed control systems and personal computers  Forms of Computer Process Monitoring and Control ❑ In process monitoring, the computer observes process and associated equipment, collects and records data from the operation. This is computer process monitoring. (a) Process Monitoring, ❑ In process-control, the computer is used to regulates the process. In some process-control implementations, the computer executes certain actions that do not require feedback data to be collected (b) Open-loop Process Control from the process. This is open-loop control. However, in most cases, some form of feedback or interlocking is required to ensure that the control instructions have been properly ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This (c) materialClosed-loop Process is protected under all copyright Control laws as they currently exist. carried out. This more common No portion of this material may be reproduced, in any form or by any means, without book permission in writing from the publisher. For the exclusive use of adopters of the Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  1. Computer Process Monitoring ❑ In process monitoring, the computer is used to simply collect data from the process. Therefore, the computer is not used to directly control the process where the control remains in the hands of humans who use the data to guide them in managing and operating the process. ❑ The data collected by the computer in computer process monitoring can generally be classified into three types : 1. Process data: measured values of input parameters and output variables that indicate process performance. When the values are found to indicate a problem, the human operator takes corrective action. 2. Equipment data: These data indicate the status of the equipment in the process. The data are used to: (1) monitor machine utilization, (2) schedule tool changes, (3) avoid machine breakdowns, (4) diagnose equipment malfunctions, and (5) plan preventive maintenance.  Computer Process Monitoring ▪ Product data: to satisfy government requirements, e.g., pharmaceutical and medical. A firm may also want to collect product data for its own use. ❑ Collecting data from factory operations can be accomplished by any of several means: ▪ Manual terminals located throughout the plant are used to entered shop data by workers. ▪ Or can be collected automatically by means of limit switches, sensor systems, bar code readers, or other devices. ❑ The collection and use of production data in factory operations for scheduling and tracking purposes is called shop floor control.  Direct Digital Control (DDC) ▪ DDC represents a transitory phase in the evolution of computer process control technology. ▪ Form of computer process control in which certain components in a conventional analog control system are replaced by the digital computer (The difference between direct digital control and analog control can be seen by comparing Figures 5.8 and 5.9). ▪ Components remaining in DDC: sensor, transducer, amplifier and actuator. ▪ Components replaced in DDC: analog controller, recording and display instruments, set-point dials, and comparator. ▪ New components in the loop include the digital computer, analog-to-digital and digital-to-analog converters (ADCs and DACs), and multiplexers  Direct Digital Control (DDC) ▪ It has also motivated the use of distributed control systems, in which a network of microcomputers is utilized to control a complex process consisting of multiple unit operations and/or machines. ▪ Applications: process industries ▪ The regulation of the process is accomplished on a time- shared, sampled-data basis rather than by the many individual analog components working in a dedicated continuous manner. ▪ With DDC, the computer calculates the desired values of the input parameters and set points, and these values are applied through a direct link to the process.  A Typical Analog Control Loop Figure shows the instrumentation for a typical analog control loop. The entire process would have many individual control loops, but only one is shown here Fig. 5.8 A typical analog control loop ▪ Typical hardware components include the: sensor and transducer, an instrument for displaying the output variable, some means for establishing the set point ©2008 Pearson ofEducation, theInc.,loop Upper Saddle(aRiver,dial), a comparator, NJ. All rights reserved. the This material is protected under analog all copyright controller, laws as they currently exist. an No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book amplifier, andAutomation, the actuator. Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Components of a Direct Digital Control System ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. Fig. 5.9 Components of a DDC system No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  DDC (continued) ▪ Originally seen as a more efficient means of performing the same functions as analog control. However, the practice of simply using the digital computer to imitate the operation of analog controllers was a transitional phase in computer process control. ▪ Additional opportunities for the control computer were soon recognized, including: ▪ More control options than traditional analog control (PID control), e.g., combining discrete and continuous control, on/off control or nonlinearities in the control functions can be implemented ▪ Integration and optimization of multiple loops to improve overall process performance ▪ Editing of control programs: Using a digital computer makes it relatively easy to change the control algorithm when necessary by simply reprogramming the computer. Reprogramming an analog control loop is likely to require hardware changes that are more costly and less convenient. ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover.  Numerical Control & Robotics ▪ Computer numerical control (CNC) – computer directs a machine tool through a sequence of processing steps defined by a program of instructions ▪ Distinctive feature of NC – control of the position of a tool relative to the object being processed ▪ Computations required to determine tool trajectory ▪ Industrial robotics – manipulator joints are controlled to move and orient end-of-arm through a sequence of positions in the work cycle ©2008 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Third Edition, by Mikell P. Groover. Programmable Logic Controller (PLC)  Programmable Logic Controller (PLC) ▪ A microcomputer-based controller that uses stored instructions in programmable memory to implement logic, sequencing, timing, counting, and arithmetic functions through digital or analog modules, for controlling machines and processes ▪ PLC used extensively for sequence control today in transfer lines, robotics, process control, and many other automated systems. ▪ Introduced around 1970 ▪ Replaced hard-wired electromechanical relay panels ▪ Today’s PLCs perform both discrete and continuous control in both process industries and discrete product industries ▪ In essence, a PLC is a special purpose industrial microprocessor based real-time computing system, which performs the following functions in the context of industrial operations:  Programmable Logic Controller (PLC) 1. Monitor input/sensors 2. Execute logic, sequencing, timing, and counting functions for control/diagnostics 3. Drives actuators/indicators 4. Communicates with other computers ▪ Advantages of PLCs Compared to Relay Control Panels Programming a PLC is easier than wiring a relay control panel PLC can be reprogrammed PLCs take less floor space Greater reliability, easier maintenance PLC can be connected to computer systems (CIM) PLCs can perform a greater variety of control functions ©2015 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Fourth Edition, by Mikell P. Groover.  PLC Components These components are housed in a suitable cabinet designed for the industrial environment. ©2015 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Fourth Edition, by Mikell P. Groover.  PLC Components 1. Processor – is the central processing unit (CPU) of the PLC; it executes logic and sequencing functions by operating on the PLC inputs to determine the appropriate output signals. The internal structure of the CPU depends on the microprocessor concerned. In general they have: (1) An arithmetic and logic unit (ALU) which is responsible for data manipulation and carrying out arithmetic operations of addition and subtraction and logic operations of AND, OR, NOT and EXCLUSIVE-OR. (2) Memory, termed registers, located within the microprocessor and used to store information involved in program execution. (3) A control unit which is used to control the timing of operations. 2. Input/output module – sections are where the processor receives information from external devices and communicates information to external devices. 3. Memory unit – contains the programs of logic, sequencing, and I/O operations 4. Power supply – converts 120 VAC to DC voltages of 5 V necessary for the processor and the circuits in the input and output interface modules. ©2015 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Fourth Edition, by Mikell P. Groover.  PLC Components 5. Programming device - is used to enter the required program into the memory of the processor. The program is developed in the device and then transferred to the memory unit of the PLC. 6. The communications interface - is used to receive and transmit data on communication networks from or to other remote PLCs. It is concerned with such actions as device verification, data acquisition, synchronization between user applications and connection management. ©2015 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Fourth Edition, by Mikell P. Groover.  PLC Components ©2015 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Fourth Edition, by Mikell P. Groover.  Typical PLC Operating Cycle ©2015 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Fourth Edition, by Mikell P. Groover.  Typical PLC Operating Cycle 1. Input scan – inputs are read by processor and stored in memory 2. Program scan – control program is executed ▪ Input values stored in memory are used in the control logic calculations to determine values of outputs 3. Output scan – output values are updated to agree with calculated values ▪ Time to perform the three steps (scan time) varies between 1 and 25 msec ©2015 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Automation, Production Systems, and Computer-Integrated Manufacturing, Fourth Edition, by Mikell P. Groover.  Additional PLC Capabilities ▪ Analog control – PID control available on some PLCs for continuous processes ▪ Arithmetic functions – permits more complex control algorithms to be implemented than conventional logic and sequencing elements ▪ Matrix functions – e.g., linear programming for optimal control ▪ Data processing and reporting – business applications ▪ Blurs the distinction between PLCs and PCs ©2015 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This materi