automaatikavahendid Ñðåäñòâà Àâòîìàòèêè a 2-2-0 5...

2016 Lecture 1

ISS0065 Control Instrumentation

Automaatikavahendid

Ñðåäñòâà Àâòîìàòèêè

A 2-2-0 5 ECTS E

Automaatikainstituut

Department of Computer Control

Kristina Vassiljeva U02-320 6202116

http://www.a-lab.ee/edu/courses → Control Instrumentation

1 Introduction

Assessment methods

• Tests: none;

• Homeworks: 2 works: electrical diagram + PLC programme with HMI;

• Labs: PLC (training) + 7 laboratory experiments.

In general, 10 tasks.

Exam prerequisites: all wome works must be done + at least 5 lab works must be defended.

Final grade:

- each work gives 5 /on time/ or 2 /with delay/ points

- written exam gives 50 points

K.Vassiljeva 1 ISS0065 Control Instrumentation

http://www.a-lab.ee/edu/courses

Lecture 1 2016

Courses on automation:

ISS0079/89

Programmable Logic

Controllers 1/2

ISS0065

Control Instumentation

realization of automation goals

by technical instrumentation

ISS0080

Automation and

Process Control

ISS0023 Intelligent Control Systems

ISS0065 Control Instrumentation 2 K.Vassiljeva

2016 Lecture 1

There are two di�erent approaches in automation: di�erent skills, terminology, culture.

1. Approach based on a process

- Old ones (boilers, petrochemical, polymers, ...);

- New ones (biotech, pharmaceuticals, nanotechnology, ...);

- Knowledge of the characteristics of the process

chemistry, physics, thermal engineering,etc.

- Problems: cost, product cost, quality, environment, etc.

- Control algorithms, process safety.

ISS0080 Automation and Process Control

2. Technological approach

- Equipment, instrumentation

Controllers, PLCs, computers, sensors, actuators, etc.

- Connecting devices: signals, networks, protocols;

- Tuning, programming, operation;

- Safety.

ISS0065 Control Instrumentation


Lecture 1 2016

2 Literature

1. Books UDK: 681.5, 681.58, etc.

Instrumentation Systems. Fundamentals and Application Control System Technology. (R.N.

Bateson),

Lessons In Industrial Automation (T.R. Kuphaldt) Lessons.

2. Journals (for engineers)

Instrumentation and Control Systems (I&CS),

Ïðèáîðû è ñèñòåìû óïðàâëåíèÿ (ÏÑÓ),

IOT Journal,

Automaatiov�ayla (Finnish).

3. Internet

• Companies producing equipment

http://www.siemens.com,

http://www.omron.com,

http://www.rosemount.com,

http://www.endress.com,

http://hpsweb.honeywell.com,

http://www.abb.com,

http://www.honeywellprocess.com.

• Instrumentation Usage

http://www.process-controls.com,

http://www.PAControl.com.

• Terminology

http://www.expertune.com/glossary.html.

• Problems in the �eld of automation

http://www.controlglobal.com,

http://www.controldesign.com,

http://www.modelingandcontrol.com/.

4. Course lectures

http://www.a-lab.ee/education.


http://www.pacontrol.com/download/Lessons-in-Industrial-Instrumentation.pdf

http://www.iotjournal.com/

http://www.siemens.com

http://www.omron.com

http://www.rosemount.com

http://www.endress.com

http://hpsweb.honeywell.com

http://www.abb.com

http://www.honeywellprocess.com

http://www.process-controls.com

http://www.PAControl.com

http://www.expertune.com/glossary.html

http://www.controlglobal.com

http://www.controldesign.com

http://www.modelingandcontrol.com/

http://www.a-lab.ee/education

2016 Lecture 1

3 Agenda

• Lectures 2 hours a week

Wednesday 14:00 - 15:30 U06-220

• Labs 2 hours a week U02�302

PLC −→ 2nd homework (PCL+HMI)

Controllers −→ reports

Lab reports should be defended in 2 weeks after experiment was carried out.

Laboratory works

3 - 15 weeks U02-302 PLC, Controllers, Sensors

• Homeworks

1. Electrical diagrams;

2. PLC + HMI.

Deadline is stated on the homework assignment.

On time defended lab report or homework gives 5 points.

Report or homework presented with delay gives 2 points.

3.1 Course objectives

• To show control system design and control equipment types;

• To describe PID controller types and tuning mechanisms;

• Choice of the right sensor and actuator device for the process;

• E�ective representation of the information (HMI);

• Ability to carry out the experiments and report its results.

3.2 Course outcomes

• Knows and able to use electrical schemes;

• Knows the most commonly used controllers and their operating principles;

• Able to describe good and bad features of various controllers;


Lecture 1 2016

• Understands the limitations that arise using simpli�ed models in complex systems, under-

stands representation;

• Able to design simple SFS programs (Structured Flow Chart/ jadajuhtimine/ áëîê-ñõåìû);

• Able to use instrumentation to test control systems;

• Able to carry out laboratory tests on the system to achieve the desired results;

• Determines the system characteristics from experiments and simulations;

• Selects suitable sensors and actuators for the controller;

• Able to use software to solve the control tasks.

4 History

How has technology changed?

4.1 From Industry 1.0 to Industry 4.0: the road to today's smart factory

Steam engine gave a start to industrialization. Factories became less dependent on manpower.

Mechanical production plants began manufacturing goods in grater quantities than ever before.

Production/assembly lines allowed the mass production which reduced working hours and cost of

the product. In the early 1970-s automation made its way into production. Manual operations were

taken over by machines with deployment of electronics and IT in production.

If Industry 1.0 represented the rise of water and steam power, 2.0 the advent of electric power,

and 3.0 computing capabilities, Industry 4.0 harnesses the inter-connectivity of machines, processes

and products. Based on cyber-physical systems, the Internet of Things and the Internet of Services.

It will generate enormous BIG data streams that can be harvested and analyzed for resource-e�cient

and ultra-high quality production. CPS-based industrial assistant systems are needed to support,

help and train the next generation of workers in smart factories. Augmented and dual reality

systems allow individualized work�ows and fast learning of new production processes [4].

4.2 Automatic control history

• Objectives and tasks of automation;

• Elements and components of control systems.

From pneumatic instrumentation to computer-controlled systems.


2016 Lecture 1

1st Industrial Revolutionintroduction of mechanicalproduction facilities poweredby water and steam

2nd Industrial Revolutionintroduction of mass production with the helpof electrical energy

3rd Industrial Revolutionapplication of electronics, IT and robots to further automate production

4th Industrial Revolutionon the basis of cyber-phisical production systems, mergingof real and virtual worlds

First mechanicalloom (1784)

End of 18th century

First production line (1870)

Beginning of the 20th century

Beginning of the 1970-s

First PLC Modicon 084 (1969)

Since 2010 Time

Smart factory

Deg

ree

of c

ompl

exity

Industry 1.0

Industry 2.0

Industry 3.0

Industry 4.0

Figure 1: Industrial Revolutions

Early theory: 1932 ampli�ers (Nyquist)

Practice: 1922 - Control of ships' movements

Two branches of automatic control applications:

1. Control the movement/motion

World War II (1939)

• tracking systems (servo).

2. Process control

chemical industry, food industry

• terminology did not work, �xed operating point;

• large time constants, delays.


Lecture 1 2016

Before 1940 (materials, energy) had been controlled manually: hand valves /ventiilid /âåíòèëè,

direct readings of local gages;

a large number of operators (knowledge of the process, experience);

warehouses for intermediate products storage (separates the process);

expensive labor, increased production, new equipment.

∼ 1950 Controllers (operating unit control rooms with monitor control boards) - pneumatic control

systems. Plant complexity grow necessitated the increase of accurate, up-to-date operating

information [2].

∼ 1960 State-space representation /olekumudel /ìîäåëü ñîñòîÿíèé.

∼ 1970 PLC (Programmable Logic Controller/ Programmeeritav loogikakontroller /Ïðîãðàììèðóåìûé

ëîãè÷åñêèé êîíòðîëëåð). The simplicity and accuracy of electronic controllers, recorders and

indicators made them the choice for instrument panels.

∼ 1980 MPC (Model Predictive Control), DCS (Distributed Control System / Hajus�usteemid

/ðàñïðåäåëåííàÿ ñèñòåìà óïðàâëåíèÿ).

∼ 1990 CIM (Computer-Integrated Manufacturing).

∼ 2000 Modular systems, multi-disciplined work.

∼ 2001 PAC (Programmable Automation Controller) is a 2 or more processor based device with

multitasking. PACs expand the capabilities of PLC, DCS and RTU (Remote Terminal Unit)

systems adding some capabilities from PCs.

∼ 2015 IIoT (Industry Internet of Things)? Intelligent assets; a data communications infras-

tructure; analytics and applications to interpret and act on the data.

∼ 2016 Telecommunications standards body 3GPP �nalized the speci�cations for NB-IoT tech-

nology. The standard will act as a common foundation for developers and engineers to design

NB-IoT applications, services and systems that work together.

Technological development and its impact on society.

Technology development is determined by the users.

- if technology is not used in society then it does not spread;

- passive relationship: live with technology what is not used and do not care about it.


2016 Lecture 1

Automation society is small, does not determine the overall development: we use what we have

and we watch the trends. Production may be a�ects some side-speci�c development (industrial

data communication).

The technological advances of the past years and the trends for more technical and specialized

equipment require better trained and educated personnel. Types of equipment in control systems

cover many disciplines: mechanical, electrical, electronic, computer science, chemical, environmen-

tal, etc [2].

• Works continuously 24 hours a day, 7 days a week.

• Di�cult working conditions:

outdoor environment (−40◦C . . .+ 100◦C);

dust, moisture, vibration, shock, disturbance;

explosive environment.

• Consequences of failure are expensive and dangerous (accidents).

• Devices have embedded computers and communications.

• Devices are intelligent

they predict, adapt, react in the best way, exchange information on production control and

business management.

• Equipment is reliable, equipment problems are rare; if forget how to manage them (run, pause,

tune) - skills will be lost.

5 Industrial Internet of Things

Industrial Internet of Things connects intelligent physical entities, such as sensors, machines, and

other assets to each other, to internet services, and to applications. The Industrial Internet of Things

(IIoT) architecture is based upon current and emerging technologies. The IIoT serves up data from

connected devices in the plant or in the �eld and then processes those data using sophisticated new

analytics and execution software systems. Smart connected products and machines can be more

�exible and perform better than their unconnected predecessors.

Today, the Internet of Things is in a chaotic emerging state, with no widely agreed upon standard

systems, networks, or interfaces.

An Industrial IoT system contains four main parts: intelligent assets; a data communications

infrastructure; analytics and applications to interpret and act on the data; and, of course, people.

Intelligent assets include plant instrumentation, equipment, machines, systems or other assets

enabled with sensors, processors, memory, and communications capability. In certain cases, these


Lecture 1 2016

assets may have an associated virtual entity or support software-de�ned con�guration and perfor-

mance. Intelligent assets will generate more data and share information across the value chain.

Powerful analytics and other software will help optimize both assets and systems. Predictive

analytics will be deployed to reduce unplanned down-time. Newly available information generated

by these tools will lead to new, transformative business models supported by new applications.

People will participate by having access to much more data, better analytics tools, and better

information, and will increasingly make decisions based on the analysis generated by these resources.

5.1 Technical Components

With traditional automation architectures, most of these intelligent, connected devices communicate

directly with a host controller, control system, or safety system or PC-based application located

right in the plant; with appropriate production- or asset-related data then passed up to supervisory

or business networks at the plant and/or enterprise levels. This largely remains the case, particularly

for mission-critical process control and plant safety functions.

However, as IoT technology migrates into industrial environments, we're seeing an increasing

number of primarily non-control or safety-related sensors and devices communicate directly with

remote, often cloud-based systems and analytics applications through the Internet where the data

are transformed into actionable information and timely alerts for operations and maintenance per-

sonnel.

In some cases, such as for smart �eld instrumentation, process control-related variables will

communicate with local controllers through digital plant networks, while secondary asset-related

measurements can be communicated directly to appropriate remote, IoT-based applications, by-

passing the control system entirely.

5.2 Information Technology Components

The IT supplier will be responsible for:

• IT infrastructure (including embedded cyber security);

• Non-control-related networking (including both wireless and wired infrastructures);

• Mobile device management;

• Remote access management;

• Data storage, management, and analysis;

• IoT application infrastructure;

• IoT communication infrastructure.


2016 Lecture 1

• No intelligenceor connectivity

Conventional• Connectableor connected• Provides data externally

Instrumented

+ Some localintelligence+ Software tunable asset+ Enhanced datafeeds

IIoT Enabled

Softwaredefined

+ Enhanced intelligence+ Active conditionmonitoring+ Self optimization+ Interact with ecosystem

Smart

+ Additional sensors+ Real-time analytics+ Onboard execution software+ New businessmodels+ Performance guarantees

Autonomous

Level of Maturity

Add

ed V

alue

Figure 2: Asset Capabilities

Standardization of the Industrial IoT architecture is one of the most important, and most

challenging, issues a�ecting adoption [6].

5.3 Role of the Human [5]

• The Human as Sensor

� Despite Sensor Technology, sensory Gaps will further exist in the Production Process

� Human Skills are necessary to manage complex Situations

• The Human as Decision Maker

� Agreements on networked Objects can generate Con�icts (e.g. opposing Priorities, scarce

Resources)

� Interventions with a running, self-controlled System are time-critical

� Tools are required for fast and quali�ed Decisions

• The Human as an Agent


Lecture 1 2016

� Work Contents are characterized by a high Complexity, Customer Individuality and

irregular Repeatability

� Requirements with regard to Time, Content and Location Flexibility of the Employees

increase signi�cantly

� The use of mobile Devices provides support in the Industry 4.0 Production (e.g. Alloca-

tion of Orders to Employees Groups in real Time, Agreements on Working Hours)

6 Automation tasks

Automation tasks arise from the business where production aim is a pro�t. They arise due to the

changes in production operations:

• changes in production volumes;

• changes in raw materials;

• quality requirements grow;

• shorter deadlines;

• market changes;

• safety, environmental standards.

Can be solved by automation and data processing.

Automatics is used in order to

- solve speci�c tasks (goals);

- provide a process speci�c characteristics (accuracy).

For business managers it is important to show how automation makes a pro�t.

E�ciency:

- do the same at lower cost;

- do more with the same amount of resources.

To solve automation tasks we need to know

• automatic control;


2016 Lecture 1

• information technology, computers;

• electricity, mechanics, chemistry, etc.

A deep knowledge of one of these parts can not compensate for poor knowledge of another.

6.1 Automation goals

• Pro�t / kasum/ ïðèáûëü - the main point!

pro�tability of investments.

• E�cient production

- routine work

algorithms, procedures, orders;

- availability of equipment

single device failures should not lead to the process halt (heating, electricity, water, ...);

monitoring of the operating devices;

achieved by: reservation, automatical switching, diagnostics, emergency alerts, sched-

uled repairs.

- material and energy savings

monitoring: what consumes what and how much;

(computers and telecommunication consume ∼ 2% of energy).

• Quality - customer satisfaction

stable production and quality monitoring.

• Satisfaction of rules, regulations and laws

- safety - to avoid danger situations for environment and sta�

achieved by: parametric monitoring, control of human activity, the localization of fail-

ures, operator assistance;

- satisfaction of environment protection norms

(waste water, gases, dust, etc.)

• Adaptation to changes - products, quantity, raw materials.

Objectives → tasks → control algorithms

An algorithm is technologically neutral and exists independently of the technology.


Lecture 1 2016

7 Control system

Control system implements the algorithm, shows the results, has a user interface.

The control system consists of parts: elements or components.

Mechanical or electrical part has speci�c features, can be installed and replaced.

From our point of view, components are:

• Sensors or instrumentation

• Actuators

• regulators, controllers (control units)

Their implementation gives the varying complexity systems:

• Control systems

• Ventilation systems

• Heating systems

• Security systems

• Automatic systems

• Automatic control systems

• Process control systems

We are interested in:

- System behavior: vibration, not a stable job, ...

- System integration: to the business environment

Control system original features:

• Continuously improving and modifying

which is a source of new errors!

• A strong dependence between system components


2016 Lecture 1

consists of sub-systems where data and communication protocols may di�er;

• Contains a lot of information and knowledge;

• Documentation is limited

has a complicated structure, several versions, tools work on speci�c versions only, incomplete

understanding of the system.

7.1 Classi�cation of control systems

Automatic system

keeps value c− r -stabilization

woks without human

Automatic control system

object

-machine

-device

Control

DeviceSensors

logical

subsystem

D

X Stabilization;


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X Startup/ shutdown;

X Works in real-time, controls safety requirements and performance;

X Accurate representation for the operator;

X Communication with other systems.

Process Control System

Process department, warehouse,...

PCS

Operator

-monitoring,

-decisions

-elimination of failures

Operator is an important person!


2016 Lecture 1

7.2 Control Systems architecture

SCADA Supervisory Control and Data Acquisition

RTU RTU Remote Terminal Unit

connects sensors with

main panel

Master

Station

collects, processes, delivers, manages: large amount of data, operator

based

7.3 Where is the knowledge/info saved?

- Standalone system

PLC, PC

autonomous, does not need control

- DCS Distributed Control System

tasks are shared between devices, stations, one database

WS

PS1 PS2

DB Work Stations

Process Stations

- Server-based systems

The critical parts are inside the enterprize

(I/O, protection circuits, ...)

Non-critical parts of the system are located away (HQ)


Lecture 1 2016

(supervised control, asset management, controllers tuning, optimization, production plan-

ning, etc.)

- Secure location

- Is used in many factories

Does not support real-time management!

Control system is:

• Requirements;

• Design;

• Making of;

• Maintenance, keep the devices running;

• Make changes to the control system;

• Integrate with a business environment;

• Go over to the new system.

Management of the existing control system

• Setup regulators/controllers;

• Setpoint adjustment;

• Change the controllers' program and parameters;

• Check of sensors;

• Maintenance of valves;

• Communications.


Bibliography

[1] Terrence L Blevins; Mark Nixon, Control loop foundation : batch and continuous processes.

Research Triangle Park, NC : International Society of Automation, 2011.

[2] Lawrence D. Goettsche, Maintenance of Instruments & Systems: Practical Guides For Mea-

surement And Control. ISA: The Instrumentation, Systems, and Automation Society,2004.

[3] Park, J., and Mackay, S., and Wright, E. Practical Data Communications for Instrumentation

and Control. Elsevier, 2003.

[4] WolfgangWahlster, Industry 4.0: From the Internet of Things to Smart Factories. URL:http://

www.digile.fi/file_attachment/get/Thomas%20Wahlster.pdf?attachment_id=121, 2015.

[5] Frank Wagner, INDUSTRY 4.0 � Transition to a Networked Factory of the Fu-

ture. URL:http://www.rdm.iao.fraunhofer.de/content/dam/iao/rdm/de/documents/I40_

Wandlung_zur_vernetzten_Fabrik_FW.pdf, 2015.

[6] Process Automation and the IoT: Yokogawa's VigilantPlant Approach to the Connected Indus-

trial Enterprise. URL:https://www.yokogawa.com/product/doc/whitepapers.htm, 2015.

19

http://www.digile.fi/file_attachment/get/Thomas%20Wahlster.pdf?attachment_id=121

http://www.digile.fi/file_attachment/get/Thomas%20Wahlster.pdf?attachment_id=121

http://www.rdm.iao.fraunhofer.de/content/dam/iao/rdm/de/documents/I40_Wandlung_zur_vernetzten_Fabrik_FW.pdf

http://www.rdm.iao.fraunhofer.de/content/dam/iao/rdm/de/documents/I40_Wandlung_zur_vernetzten_Fabrik_FW.pdf

https://www.yokogawa.com/product/doc/whitepapers.htm

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