Industrial Automation Technologies

Chanchal Dey, Sunit Kumar Sen, Chanchal Dey, Sunit Kumar Sen

• Publisher: CRC Press
• Year: 2020
• ISBN:
  9781000068788
• Edition: 1
• Topic: Tecnología e ingeniería
• Subtopic: Automatización en ingeniería

The book begins with an overview of automation history and followed by chapters on PLC, DCS, and SCADA –describing how such technologies have become synonymous in process instrumentation and control. The book then introduces the niche of Fieldbuses in process industries. It then goes on to discuss wireless communication in the automation sector and its applications in the industrial arena. The book also discusses theall-pervading IoT and its industrial cousin, IIoT, which is finding increasing applications in process automation and control domain. The last chapter introduces OPC technology which has strongly emerged as a defacto standard for interoperable data exchange between multi-vendor software applications and bridges the divide between heterogeneous automation worlds in a very effective way.

Key features:

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• Presents an overall industrial automation scenario as it evolved over the years

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• Discusses the already established PLC, DCS, and SCADA in a thorough and lucid manner and their recent advancements

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• Provides an insight into today's industrial automation field

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• Reviews Fieldbus communication and WSNs in the context of industrial communication

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• Explores IIoT in process automation and control fields

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• Introduces OPC which has already carved out a niche among industrial communication technologies with its seamless connectivity in a heterogeneous automation world

Dr. Chanchal Dey is Associate Professor in the Department of Applied Physics, Instrumentation Engineering Section, University of Calcutta. He is a reviewer of IEEE, Elsevier, Springer, Acta Press, Sage, and Taylor & Francis Publishers. He has more than 80 papers in international journals and conference publications. His research interests include intelligent process control using conventional, fuzzy, and neuro-fuzzy techniques.

Dr. Sunit Kumar Sen is an ex-professor, Department of Applied Physics, Instrumentation Engineering Section, University of Calcutta. He was a coordinator of two projects sponsored by AICTE and UGC, Government of India. He has published around70 papers in international and national journals and conferences and has published three books – the last one was published by CRC Press in 2014. He is a reviewer of Measurement, Elsevier. His field of interest is new designs of ADCs and DACs.

1

Industrial Process Automation

1.1 DEFINITION OF PROCESS

As per the dictionary, a process is defined as a series of actions which are carried out in order to achieve a predefined result. It is nothing but a systematic economic activity pertaining to manufacturing/service. In the case of manufacturing industry, raw materials are converted into finished products through some physical and/or chemical procedures.

In general, processes can be of various types like agriculture, aviation, automotive, banking, broadcasting, governance, media, mining, servicing, education, health care, retail, insurance, transportation, industry, and a host of others. Popular industrial processes are chemical, petrochemical, fertilizer, power, metallurgical, food processing, pharmaceutical, etc. In any ‘process’, productivity with assured quality is the most important aspect. Automation techniques are increasingly being incorporated in various processes to increase productivity with desired quality.

1.2 MEANING OF AUTOMATION AND CONTROL

The word ‘Automation’ is derived from Greek words ‘Auto’ (self) and ‘Matos’ (moving). Therefore, ‘Automation’ is the mechanism for systems that ‘move by itself’. ‘Automation’ is a set of technologies that results in operation of machines and systems without significant human intervention and achieves the desired performance superior to manual operation.

To operate an industrial process in a desired manner, control of its operation is needed at every possible step. Control is a set of policies and techniques that helps to achieve the desired variations of operational parameters and sequences for processes in manufacturing units and systems by providing the necessary input signals.

Here, it is important at this stage to understand the role of control in ‘Industrial Automation’.

• An automation system may include a control system, but the reverse is not necessarily true.
• The main function of any control system is to ensure that output must follow the set point or desired value. However, automation systems may contain more functionalities, such as computing set points for control system, monitoring system performance, plant startup or shutdown, job and equipment scheduling, etc.

Control engineering, as one of the cornerstones of automation, enables automation tasks to be accomplished physically.

• The job of a controller is essentially to capture a process variable and to compare the same with the set value to produce necessary control action, thus ensuring that in the steady state, the value of the process variable is in line with the specified set values.
• A controller is the most important block for running a plant/process in a desired manner; otherwise, without control, it would result in the process variables deviating from the set value. So, the use of controllers is vital with respect to economy, reproducibility, product quality, service quality, safety, and environmental protection.
• In order to meet these criteria, plant operators always try to continuously improve upon automation systems. Starting with classical pneumatic Proportional-Integral-Derivative (PID) controllers of early days, at present software-based digital PID controllers are being increasingly employed.
• In addition to PID controllers, various other additional features like data acquisition, sequencing, recipe scheduling, alarm handling, etc. are incorporated in plant automation.

1.3 NECESSITY AND EVOLUTION OF AUTOMATION

In early days, different units of a process plant usually used to behave as isolated islands, i.e., individual units of a process plant were not integrated. Coordinating these individual units cohesively is highly labor intensive. But, today’s manufacturing and process industries provide quality product in shortest possible time with lesser production cost and least downtime. Figures 1.1a and b show assembly line processes without and with automation, respectively.

FIGURE 1.1 (a) Labor-intensive assembly-line process without automation. (b) Assembly-line process with automation.

Thus, profit can be maximized by producing quality products in larger volumes with lesser production cost and time. Figure 1.2 shows the major parameters that affect the cost per unit of a mass manufactured industrial product.

FIGURE 1.2 Cost and profit relation.

To accomplish the aforesaid task, i.e., to maximize profit, a production process must satisfy four crucial parameters – all of which depend on interconnected hardware, software, and the plant or process equipment.

• Flexibility: The need to stay ahead in the competition and to get improved product quality requires reconfiguring assembly lines and redesigning processing facilities.
• Quality control: Today’s quality assurance (QA) or quality control (QC) demands high levels of coordinated data acquisition and analysis.
• Inventory control: Just-in-time business strategies mean lower overhead by reducing or eliminating warehousing needs.
• Speed: People who need products are also operating on just-in-time principles. If the same is not delivered on time, they would lose production time, and the suppliers of these products would ultimately lose customers.

Hence, well-designed automated hardware, software, and systems running on local area networks (industrial network) in the plant or factory floor can help to achieve these goals economically.

Automation in the manufacturing and process industries has evolved over the years starting from basic hydraulic and pneumatic systems to today’s modern robotic control systems. Most industrial operations are automated with the goal of boosting productivity and reducing the cost of labor. Since its inception, industrial automation has made rapid strides in the domains that were previously taken care of manually. A manufacturing organization that uses the latest technologies to fully automate its processes typically ensures improved efficiency, production of high-quality products, and reduced labor and production costs. Figure 1.3 shows the evolution of automation technologies over the years culminating in today’s robotic automation systems.

FIGURE 1.3 Evolution of automation technologies.

In the early 1970s, Enterprise Resource Planning (ERP), i.e., the business management software came as the first Manufacturing Resource Planning solution from Systems, Applications, Products in data processing (SAP). ERP standardized business practices with its reconfigurable features, but it is not customized. Enterprises typically developed code on top for their ERP systems to modify or replace inbuilt processes. But, as the ERP is not inherently designed for this, these organizations eventually found themselves carrying significant information technology (IT) overhead.

In the mid-1980s, ‘digital workflow’ systems eventually evolved to Business Process Management (BPM) software when IBM introduced system-to-system messaging between mainframes. It is customizable and Application Program Interface (API) driven. BPM is a strategic approach that concentrates on reshaping an organization’s existing business processes to achieve optimal efficiency and productivity. The BPM software is the foundational backbone to facilitate completion of an organization’s projects, providing a variety of tools to help, improve, and streamline how business processes are performed. BPM software components may include business analytics, workflow engines, business rules, web forms, and collaboration tools.

The concept of Robotic Process Automation (RPA) appeared on the automation technology scenario in 2012. RPA is a software technology that enables employees to better focus on high-priority tasks by pushing routine, monotonous tasks to software ‘robots’ to complete. These robots work directly across application user interfaces, automatically inputting data and triggering actions across multiple systems, acting on behalf of an employee. Due to its platform and API independency, it is a user-friendly tool that does not involve any programming. Robotic process automation technology enables nontechnical professionals to self-serve and configure robots to solve their own automation challenges.

1.4 ROLE OF AUTOMATION IN PROCESS INDUSTRY

Automation can play an imperative role in various segments of industrial processes. For example, an automated detailed market study can help to decide the proper time for raw material purchase, and the automated feedback survey helps to incorporate additional features in the product redesigning. Thus, by introducing automation in industrial processes, a number of benefits are straightway accrued, which are detailed below.

• Reduced production cost: A quick return on investment (ROI) outweighs the initial setup costs.
• Decreased part cycle time: Robotics can work longer and faster, which increases the production rate.
• Improved quality and reliability: Automation is precise and repeatable, which ensures the product is manufactured with the same specifications each time.
• Better floor space utilization: Reduced work area by automating the parts in a production line; the floor space can be better utilized for other operations and make the process flow more efficient.
• Reduced waste: Robots are so accurate that the amount of raw material used can be reduced, decreasing costs on waste.
• Staying competitive: Automation helps to achieve the highest throughput while keeping the production schedule and cost within the specified constraints.

1.5 ARCHITECTURE OF INDUSTRIAL AUTOMATION NETWORK

In modern industrial automation networks, usually a five-layered communication hierarchy model is used. It describes the equipment required, network architecture, communication modes between equipment, and the nature of information flow and its control. The five-layered hierarchy is discussed below.

• Field level: The field level comprises sensors, actuators, switches, etc. which are installed in the tanks, vessels, and pipelines that make up a process plant. Sensors provide information about the process variables (temperature, pressure, flow, level, etc.) and pass the signals to the I/O (input/output) level. These signals are then passed on to the actuators which control the opening/closing of valves or start/stop of pumps.
• I/O level: The main purpose of the I/O level is to marshal together input and output signals. The signals from the sensors are directed to the controllers and those from the controllers are directed to the actuators.
• Control level: At the control level, signals from the sensors (located in the field) are processed, and based on the desired process outputs, commands to the actuators are generated. Usually Programmable Logic Controller (PLC), Distributed Control System (DCS), and Supervisory Control And Data Acquisition (SCADA) are present in this layer.
• HMI level: The Human Machine Interface (HMI) level is primarily concerned with the organized and systematic display of plant operations passed from the control level. Data acquisition, recipe management, asset management, maintenance schedule tools etc. are used in this layer for better process management. Operators have entire plant information through schematic represe...