Enhancing Industrial Automation through Simulation and Design Engineering – The Descar.tech Approach

Industrial automation, defined as the application of control systems, computers, and information technologies to handle and process industrial operations with minimal human intervention, stands at the core of modern manufacturing and production industries

This technological paradigm enables machines and systems to operate autonomously, enhancing efficiency, precision, and productivity across various sectors. Within this framework, simulation and design engineering play pivotal roles, offering sophisticated tools and methodologies for creating, testing, and optimizing automated systems before their physical implementation. Through the integration of these engineering disciplines, industries are able to foresee potential issues, streamline production processes, and innovate at an unprecedented pace.

Descar.tech, a leader in integrating simulation and design engineering with industrial automation, exemplifies how this synergy can lead to groundbreaking advancements in automation technologies. By harnessing the power of simulation and design, Descar.tech crafts highly efficient, reliable, and innovative automation solutions that propel industries forward. This article embarks on an exploration of the intricate relationship between industrial automation and simulation and design engineering, showcasing how Descar.tech’s expertise not only enhances but revolutionizes this dynamic field.

Section 1: The Evolution and Scope of Industrial Automation

Brief history and evolution of industrial automation

The history and evolution of industrial automation is a fascinating journey through technological innovation, marked by key milestones and the development of technologies that have fundamentally changed manufacturing and production processes. Here’s a concise list detailing this evolution.

  1. Late 18th Century – The Industrial Revolution:
    • Definition: A period of major industrialization where manual labor began to be replaced by machines.
    • Fact: Began around 1760 in Britain, spreading globally over the next decades.
    • Example: The invention of the steam engine by James Watt in 1776, powering factories and mechanizing production.
  2. Early 20th Century – Introduction of Assembly Lines:
    • Definition: A manufacturing process in which parts are added to a product in a sequential manner to create a finished product faster than with traditional methods.
    • Fact: Ford Motor Company introduced the assembly line in 1913, reducing the time it took to build a car from more than 12 hours to two hours and 30 minutes.
    • Example: The Ford Model T, the first mass-produced automobile using assembly line techniques.
  3. 1940s – Numerical Control (NC) Machines:
    • Definition: Machines controlled by a set of instructions (codes and numbers) that were encoded on punched tape.
    • Fact: The first NC machine was developed in the 1940s by John T. Parsons in collaboration with MIT.
    • Example: NC milling machines, which could precisely cut and shape metal components.
  4. 1970s – Programmable Logic Controllers (PLC):
    • Definition: Industrial digital computers tailored for the control of manufacturing processes, such as assembly lines or robotic devices.
    • Fact: The first PLC, the Modicon 084, was introduced in 1969 by Dick Morley.
    • Example: PLCs are used in various industries for automation tasks, from controlling machinery on factory assembly lines to lighting fixtures.
  5. 1980s – Introduction of Robotics:
    • Definition: Programmable machines capable of carrying out a complex series of actions automatically, especially one programmable by a computer.
    • Fact: In 1980, the PUMA (Programmable Universal Machine for Assembly) robot was introduced by Unimation with General Motors.
    • Example: Industrial robots used in car manufacturing for welding and assembling parts.
  6. 1990s – Computer Integrated Manufacturing (CIM):
    • Definition: The manufacturing approach of using computers to control the entire production process.
    • Fact: This concept gained prominence in the late 1980s and early 1990s, integrating various technologies like CAD/CAM and ERP.
    • Example: Fully automated factories where design data is directly used to control machinery.
  7. 2000s – Industry 4.0:
    • Definition: The name given to the current trend of automation and data exchange in manufacturing technologies, incorporating cyber-physical systems, the Internet of Things, cloud computing, and cognitive computing.
    • Fact: The term was first introduced at the Hannover Fair in 2011.
    • Example: Smart factories where machines and systems are connected digitally across the entire production chain, allowing for real-time data analysis and decision-making.
  8. 2010s and Beyond – Artificial Intelligence (AI) and Machine Learning in Automation:
    • Definition: AI refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. Machine learning is an application of AI that provides systems the ability to automatically learn and improve from experience.
    • Fact: AI and machine learning have become integral to advancing industrial automation, with significant growth in applications seen in the 2010s.
    • Example: Predictive maintenance, where AI algorithms predict when machinery will require maintenance and preemptively service the equipment to avoid downtime.

This timeline highlights the major milestones in the evolution of industrial automation, showcasing how technological advancements have progressively automated the manufacturing and production processes to enhance efficiency, quality, and productivity.

Definition of Control Systems

A control system is a set of devices and management tools that monitor and control machinery or processes to achieve desired outcomes. It operates on the principle of feedback control, where data from the system is continually monitored and used to make adjustments to control variables, maintaining the system’s performance at the set parameters. Control systems can be simple, like a thermostat maintaining room temperature, or complex, such as those managing the operations of a nuclear power plant. They are fundamental in various applications, including manufacturing, aviation, automotive, and building management systems, ensuring efficiency, safety, and reliability.

Definition of Industrial Automation

Industrial automation refers to the use of control systems, such as computers or robots, and information technologies for handling different processes and machineries in an industry to replace a human being. It is the application of automatic control to the manufacturing process to increase productivity and reduce human error. Industrial automation integrates various technologies, including PLCs (Programmable Logic Controllers), SCADA (Supervisory Control and Data Acquisition) systems, and DCS (Distributed Control Systems), to create highly efficient and precise production processes. This technology enables industries to achieve mass production, improved product quality, and enhanced safety while reducing labor costs and production time.

What is the Use of Industrial Automation?

Industrial automation is employed to enhance operational efficiency, safety, and product quality in manufacturing. Its uses include increasing productivity by enabling 24/7 production cycles, ensuring consistent quality, reducing operational costs through efficient resource use, improving workplace safety by handling hazardous tasks, and facilitating data-driven decision-making. This technology supports scalability and reduces labor costs, ultimately leading to innovative and competitive manufacturing processes.

“Industrial process automation involves instrumentation, control, human interface, and communication subsystems, ensuring quality, consistent, and cost-effective production.”
K.l.s. Sharma. “Overview of Industrial Process Automation.” (2011)

Benefits of Industrial Automation

Industrial automation transforms modern manufacturing through a suite of benefits: it substantially increases productivity by enabling continuous operation, ensures consistent product quality with precision, improves workplace safety by taking over hazardous tasks, achieves cost efficiency through optimized operations, enhances data collection for better decision-making, allows for easy scalability to meet fluctuating demands, and reduces environmental impact by minimizing waste and optimizing energy use. These advantages collectively underscore the pivotal role of automation in driving economic efficiency, safety, and sustainability in the industrial sector.

  1. Increased Productivity: Automation elevates the capability to produce goods more efficiently, allowing for continuous operation of manufacturing processes around the clock. For instance, an automated bottling facility can significantly ramp up its output compared to manual operations, ensuring that production never has to pause.
  2. Consistent Quality: With high precision and minimal variation in tasks, automated systems ensure that every product meets the same high-quality standards. This is crucial in sectors like automotive manufacturing, where the precise fit of parts is essential for vehicle safety and performance.
  3. Improved Safety: By taking over dangerous tasks and working in hazardous environments, automation reduces workplace accidents and protects employees. Robotics in pharmaceutical manufacturing, for example, can handle toxic chemicals, mitigating human exposure to potentially harmful substances.
  4. Cost Efficiency: Through optimized operations, automation leads to significant reductions in production costs. In the food processing industry, automation not only minimizes waste but also optimizes energy use, contributing to lower operational expenses.
  5. Enhanced Data Collection: The ability to monitor and record a wide array of process variables in real-time allows for comprehensive data collection. Smart factories leverage sensors and IoT devices to track machine performance, facilitating a proactive approach to maintenance and efficiency.
  6. Scalability: The flexibility of automated systems to scale production up or down based on demand ensures that companies can adjust their output without incurring significant downtime or additional costs. E-commerce warehouses exemplify this, using automated systems to manage fluctuating order volumes with ease.
  7. Reduced Environmental Impact: Automation contributes to sustainability by optimizing energy consumption and reducing waste. Industrial facilities that incorporate automated energy management systems exemplify how technology can play a pivotal role in minimizing ecological footprints and promoting environmental stewardship.

Through these aspects, industrial automation proves to be a cornerstone of modern manufacturing, offering not just economic benefits but also enhancing safety and environmental sustainability.

The Four Types of Industrial Automation

Industrial automation technologies can be broadly classified into four main types, distinguished by their flexibility, scalability, and application specificity. These categories play a critical role in determining the appropriate automation strategy for a manufacturing process or production line.

1. Fixed Automation (Hard Automation)

  • Overview: Fixed automation involves the use of equipment that is configured to perform a specific task. It is characterized by high production rates and is typically used for mass production of a single product type.
  • Application: An example of fixed automation is a conveyor belt assembly line specifically designed for the manufacturing of a single model of car. This system is efficient but lacks the flexibility to adapt to different products without significant reconfiguration.

2. Programmable Automation

  • Overview: Programmable automation allows for the reprogramming of machinery to accommodate different product configurations. This type of automation is suitable for batch production where product specifications change frequently.
  • Application: A robotic welding system that can be reprogrammed for different types of welds on various car models illustrates programmable automation. It offers more flexibility than fixed automation but requires downtime for reprogramming.

3. Flexible Automation (Soft Automation)

  • Overview: Flexible automation systems are designed to manage a variety of tasks with minimal to no downtime for changeovers. These systems are highly adaptable, allowing for quick switches between product types.
  • Application: A manufacturing system equipped with CNC machines that can quickly switch between different machining operations for small production runs of custom parts is an example of flexible automation. It combines the efficiency of fixed automation with the adaptability of programmable automation.

4. Integrated Automation

  • Overview: Integrated automation involves the comprehensive and coordinated operation of various automated systems across the entire production process. This type involves the use of advanced technologies such as IoT (Internet of Things), AI (Artificial Intelligence), and machine learning for seamless operation.
  • Application: A fully automated factory where robots, conveyors, and CNC machines are all connected via a central control system, capable of autonomously adjusting operations based on real-time demand and supply data, exemplifies integrated automation.

These four types of industrial automation offer varying degrees of flexibility, efficiency, and complexity, providing solutions for every scale and scope of manufacturing needs.

The Three Major Systems Used in Industrial Automation

The implementation of industrial automation relies on several core systems that facilitate control, monitoring, and execution of manufacturing processes. 

1. Programmable Logic Controllers (PLCs)

  • Overview: PLCs are specialized computerized systems designed for industrial environments. They are used to control a wide range of machinery and processes, offering robustness, flexibility, and ease of programming. PLCs read inputs from sensors or manual inputs, process these inputs according to the programmed logic, and trigger outputs to control actuators or indicators.
  • Application: In an automotive assembly line, PLCs can control the operation of robotic arms, conveyor belts, and painting equipment, adjusting operations in real-time based on specific production requirements.

2. Supervisory Control and Data Acquisition (SCADA) Systems

  • Overview: SCADA systems are used for remote monitoring and control of industrial processes. These systems collect data from sensors across various locations, send the data to a central computer system, and then display this information on operator screens. SCADA systems enable operators to adjust process controls remotely, optimizing performance and detecting potential issues early.
  • Application: In a water treatment facility, SCADA systems can monitor and adjust the levels of chemical treatment, flow rates, and storage capacities across different stages of the process, ensuring water quality and system efficiency.

3. Distributed Control Systems (DCS)

  • Overview: DCS are used primarily in complex processes that are spread over wide geographical locations. This system consists of a central controller that communicates with a network of decentralized controller units, managing the operations of distinct process sections. DCS is known for its high reliability and real-time control capabilities, making it ideal for processes that require precise control and operational safety.
  • Application: In the petrochemical industry, a DCS might control the refining process, ensuring optimal temperature, pressure, and flow rates throughout the network of pipes and reaction chambers to maximize output and safety.

These three major systems—PLCs, SCADA, and DCS—form the backbone of industrial automation, each serving distinct functions from direct machine control to remote process management and integrated process control across wide areas. Their implementation is critical for enhancing productivity, ensuring quality, and achieving scalability in modern industrial operations.

Which industries use the most automation?

Several industries are at the forefront of integrating automation into their operations, significantly leveraging technology to enhance efficiency, productivity, and safety. The sectors that utilize automation the most include:

  1. Automotive: Renowned for its high degree of automation, from assembly lines to painting and welding robots, ensuring precision and efficiency.
  2. Electronics and Semiconductor Manufacturing: Utilizes automation for intricate assembly processes, testing, and packaging to meet high-volume production demands with precision.
  3. Food and Beverage: Employs automation for packaging, sorting, and processing to ensure consistency, safety, and scalability in production.
  4. Pharmaceuticals: Uses automation in drug formulation, packaging, and quality control to adhere to strict regulatory standards and enhance product safety.
  5. Oil and Gas: Leverages automation for exploration, drilling, and refinery operations to improve safety and efficiency in hazardous environments.

These industries highlight the diverse applications of automation, showcasing its critical role in enhancing productivity and operational efficiency across various sectors.

Levels of industrial automation

The highest level of industrial automation is often characterized by the integration and coordination of various advanced systems that facilitate seamless operation, data flow, and decision-making across the entire manufacturing and supply chain spectrum. Among these systems, Manufacturing Execution Systems (MES), Manufacturing Operations Management (MOM), Enterprise Resource Planning (ERP), and Advanced Planning and Scheduling (APS) play pivotal roles.

MES (Manufacturing Execution Systems)

  • MES operates at the shop floor level, managing and monitoring the real-time production process. It ensures that manufacturing operations are executed effectively, optimizing production output and maintaining quality standards.

MOM (Manufacturing Operations Management)

  • MOM encompasses a broader scope than MES, integrating various aspects of the manufacturing process from production to quality and maintenance. It provides a comprehensive overview and control of all manufacturing operations.

ERP (Enterprise Resource Planning)

  • ERP systems integrate all facets of an enterprise into one comprehensive information system that can be accessed by individuals across an organization. It covers finance, HR, procurement, supply chain management, and more, facilitating streamlined operations and strategic planning.

APS (Advanced Planning and Scheduling)

  • APS systems are used for production planning and scheduling, optimizing the use of manufacturing resources to meet demand. APS tools consider production capacity, material availability, and operational constraints to generate efficient production schedules.

Highest Level of Industrial Automation: Integrated Systems Approach

The highest level of industrial automation is achieved when these systems—MES, MOM, ERP, and APS—are fully integrated, enabling a seamless flow of information and coordinated decision-making from the shop floor to the top floor. This holistic approach ensures that strategic planning (ERP) aligns with operational execution (MES and MOM) and is optimized through intelligent scheduling (APS), resulting in a highly efficient, responsive, and agile manufacturing environment. This level of integration represents the pinnacle of industrial automation, where technology and process management converge to create smart factories capable of adapting to changing market demands and operational challenges in real-time.

The Significance of Simulation and Design Engineering in Industrial Automation

Simulation and design engineering stand as cornerstone disciplines within the industrial sector, particularly in the realm of automation. These fields amalgamate theoretical engineering principles with practical application, leveraging advanced software and methodologies to visualize, test, and refine processes and products before they are physically manufactured. Their significance spans across various facets of industrial automation, from conceptualization to optimization, embodying a blend of creativity, precision, and technological prowess.

Comprehensive Overview

Simulation Engineering is the process of using computer-based models to simulate the physical and functional behavior of potential products or processes. It enables engineers to analyze a wide range of scenarios and operating conditions, identifying potential issues and opportunities for improvement without the need for physical prototypes. This virtual testing ground is essential for exploring complex systems’ behaviors, such as fluid dynamics, thermodynamics, mechanical stress, and more, within a controlled, risk-free environment.

Design Engineering focuses on the conceptualization and detailed planning of products and systems. It involves creating precise specifications, drawings, and plans that serve as blueprints for manufacturing. This discipline integrates various engineering principles and design methodologies to develop innovative, functional, and feasible products. Design engineering is pivotal in transforming ideas into tangible products, ensuring that every aspect, from functionality to aesthetics, is meticulously considered.

Importance in Industrial Automation

The integration of simulation and design engineering into industrial automation is transformative, offering unparalleled benefits:

  • Innovation and Creativity: These processes foster a culture of innovation, enabling the exploration of new ideas and solutions beyond traditional constraints. Engineers can experiment with different materials, configurations, and processes to discover more efficient, cost-effective, and reliable methods of production.
  • Efficiency and Optimization: Simulation and design engineering contribute significantly to the efficiency of production lines. By identifying bottlenecks, optimizing resource allocation, and streamlining processes through virtual testing, these disciplines help in creating more efficient and productive manufacturing environments.
  • Risk Reduction and Safety: Implementing changes in virtual models significantly reduces the risks associated with direct modifications to live systems. This preemptive approach ensures safety and operational integrity by allowing for thorough testing before implementation.
  • Cost Savings: The ability to detect issues and optimize designs early in the development phase leads to substantial cost savings. By reducing the need for physical prototypes, minimizing material wastage, and preventing costly post-production modifications, simulation and design engineering contribute to more economically sustainable manufacturing practices.
  • Cross-disciplinary Integration: These engineering processes encourage collaboration across different engineering disciplines, ensuring that all aspects of the automation system are well-coordinated and integrated. This holistic approach enhances the overall functionality and reliability of automated systems.

In essence, simulation and design engineering are indispensable in the evolution and refinement of industrial automation systems. They enable the industrial sector to navigate the complexities of modern manufacturing demands, driving forward innovations that reshape the landscape of production and manufacturing efficiency. Through detailed planning, rigorous testing, and creative problem-solving, these disciplines lay the groundwork for the future of industrial automation, characterized by smarter, safer, and more sustainable operations.

Section 3: Integration Insights – Simulation and Design Engineering in Industrial Automation

The integration of simulation and design engineering with industrial automation marks a pivotal advancement in manufacturing, characterized by Descar.tech’s innovative approach. This section outlines the essence of this integration and its impact on the industry.

Integrating simulation and design engineering into industrial automation is crucial for enhancing precision, efficiency, and adaptability in manufacturing processes, paving the way for the creation of digital twins and sophisticated simulations.

Core Components of Integration

Descar.tech leverages state-of-the-art technologies and methodologies, including 3D modeling and computational analysis, to predict and optimize manufacturing outcomes, merging creativity with engineering precision.

Real-World Applications and Case Studies

Descar.tech has demonstrated success in various projects, like optimizing automated assembly lines for automotive manufacturers, showcasing the practical advantages of this integrated approach.

Descar.tech’s Unique Approach

Distinguished by its holistic adoption of Industry 4.0, Descar.tech integrates IoT, AI, and collaborative methodologies to develop adaptable and forward-thinking automation solutions.

Future Directions in Integration

The integration led by Descar.tech not only signifies a leap in manufacturing capabilities but also sets a benchmark for future advancements in industrial automation.

For more details or to get in touch with Descar,
you can contact them at +54 9 351 560 8436 or email them at info@descar.tech