A PLC – Programmable Logic Controller – is a tiny, rugged computer used in industrial automation. Though the CPU of the PLC is not as versatile as the one used in PCs for regular use, it is extremely fast for the tasks it is designed for, and unlikely to slow down in operation. The key to successful automated plants or process industry operations is in programming the PLC correctly. The 5 languages popularly used for PLC programming – Ladder Diagram, Sequential Function Charts, Function Block Diagram, Structured Text and Instruction List – are all part of the IEC Section 61131-3 Standard. This IEC Standard allows some ground rules that standardise PLCs and their languages. Each language has its pros and cons, and some PLC manufacturers have also evolved their own language for their PLCs. The programmer must be familiar with the PLC program syntax – which is how the program is written, the codes and the symbols used. An incorrectly programmed PLC can result in costly downtime and can even cause damage to the equipment or the plant.

How PLC Programming Can Help Scale Your Manufacturing Business

PLCs have been in use in industrial automation for over 50 years and have proved to be cost-effective and reliable in automating systems and processes. Before the PLCs, industrial machines were controlled by a huge array of relays, hardwired in a very specific way. PLCs replaced the cumbersome relay system with electronic solid-state control. A modern manufacturing plant comprises several machines that form an assembly line or a manufacturing cell, each having a specific role or function, and operate in a sequence to complete a cycle of operations. For example, a piece of sheet metal may pass through a cutting machine first, before entering a bending machine and then go to the drilling machine and end up with a grinding machine to metamorphose into a panel for mounting switches. This is an automated operation where the part moves through four machines automatically through conveyors without any human intervention, getting cut to size, bent at certain angles, holes drilled at appropriate places and finally rough edges are ground smooth. This entire operation is facilitated by the PLC, which has been programmed to follow the sequence and the time cycle, based on the trials taken to perfect the sequence. This process of automating production is what helps industries scale up their manufacturing business, by applying it to each machine and function, the machines together forming the production cell or assembly line.

How PLC Programming Can Help Automate Certain Processes

A typical manufacturing unit today is a combination of human efforts and mechanization. For example, in automobile manufacturing, the assembly of individual parts like engine and gearbox may involve human labor, but operations like the welding of the chassis and painting of the car after assembly are mechanized and fully automated. These tasks are performed by robots, which are also synchronized to perform in the desired sequence through PLCs. Increasingly, artificial intelligence or AI plays a role in such complex tasks. The role of AI in manufacturing is on the increase, as it becomes more data driven, the data collected during machine operation and analyzed to gain more insights. These insights help optimize the processes further.

Today most processes in the manufacturing industry can be automated by using a series of workstations linked by a transfer system operated by robotics and control systems. It must be understood that repetitive tasks are mostly automated, and the sequence of operation is well known and understood, which forms the basis for programming of the PLC. Each workstation performs a specific operation, and the product moves forward progressively until the task is completed and the final product is ready. For example, in a bottling plant, empty bottles are picked up automatically from the crate, arranged on the conveyor system where they are first washed automatically at one workstation, dried at the next, filled with the appropriate content, capped, labelled and finally loaded in crates, ready for dispatch, without any human intervention. All these are repetitive operations, and can be programmed in a PLC, which receives signals from input devices, such as sensors and switches, and based on the logic program, activates output devices like motors or other machinery. The role of human workers in such an environment is to just supervise and monitor the operation and intervene only in case of sudden stoppage of the machine, to initiate corrective action.

PLC Programming: The Key to Better Manufacturing?

The PLC is at the heart of the automation system in the manufacturing environment and programming determines how it works in operation. This means PLC programming is the key to better manufacturing. The PLC basically has a few important components – the CPU, I/O modules, rack and power supply. The CPU is the brain of the PLC which does all the calculating and works at an extremely high speed. The I/O or input/output modules connect the field inputs (basically sensor data) and outputs (signal for devices that produce actions for movement of machinery). The rack facilitates the data exchange between the CPU and the I/O modules, and the power supply does what the name suggests – provide energy. Programming is what makes this entire operation work in a predetermined sequence – read the machine parameters, provide the inputs, and based on the operational requirements, and let the CPU take corrective measures that are transmitted as output for appropriate action. Parameters like temperature, pressure, speed, etc., of the machinery are thus controlled and kept within specified limits for safe and trouble-free operation without any stoppage or breakdown. There are hundreds of such operations performed in a typical manufacturing plant, and the programming of the PLC is what keeps the plant running smoothly which in turn facilitates better manufacturing operations.

Pros and Cons of Outsourcing your PLC Programming Projects

More and more companies today are automating their operations. Apart from new factories and manufacturing plants that start with automation, almost all legacy plants are also undergoing modifications and upgrades, automating many if not most operations. This has resulted in great demand for software and coding specialists, and consequently creating the need for outsourcing certain requirements. PLC programming is a skilled task and involves hours and hours of coding, which is getting even more complex in the age of IIoT and connected plants, with data driven decision making and use of artificial intelligence and machine learning algorithms. So what are the advantages and disadvantages of outsourcing such a critical task?

One of the main benefits of outsourcing is that companies get a depth of expertise that is rarely available in-house, and even if one tries, such talent comes at great cost, which the volume of work may not justify. Outsourcing companies are staffed by experienced industry professionals at the top, and programming experts at other levels, a combination which makes for swift execution, which together with the cost advantages works highly in favour of the company. The trend of outsourcing is not new; it has been perfected over the last two decades so today the outsourced companies understand the product development cycle. Backed by their experience of doing similar tasks over a long period, they also understand the users’ needs and are able to deliver what is exactly asked for. Moreover, today the cost of communications is minimal and modes multiple, so remaining in constant touch to resolve issues as they arise is no longer a problem. Companies large and small can benefit from outsourcing in view of these advantages.

There are of course some disadvantages in outsourcing, the foremost being the risk of cybersecurity breaches and compromising the intellectual property. Not all outsourced organizations have the professional integrity to allay all such fears. The other major concern – poor quality of work – often results from wrong choice or inadequate checks during due diligence. One should however be cautious when outsourcing about the cost, and insist on transparency on that front, lest there be hidden costs which could make the project very expensive! Also, not many outsourced companies have the credentials to undertake challenging tasks. A little less common, though by no means negligible, is the problem of cultural incompatibility in the age of globalization, where certain geographies may be less amenable to sharing such working relationships.

Conclusion

Successful businesses today are thriving on automation and more automation. The Covid pandemic and the resultant lockdown that shut down most businesses also brought home the fact that those businesses that were high on the automation adoption curve could face the lockdown with lesser disruption, with minimum manpower. Automation in the manufacturing business relies on machines, which in turn are operated with the help of PLCs. As more and more businesses choose automation to run their production lines, PLC programming will be their critical link to improved productivity. However, companies that are just embarking on their automation journey may well tread cautiously, and consult with professional agencies, both about the feasibility of going in for automation, and the ways to implement it. In an era of specialization, it is difficult for enterprises to have all the talent in-house. Automation, robotics and digitalization are words often used today, but not all businesses can profit from the high capex that these technologies need. At the same time, it is not possible to scale up without adopting modern methods. Professional expertise can guide companies in this endeavour.

Automation has already removed the drudgery from the manufacturing process. The automotive industry is a popular example of how automated assembly lines in conjunction with robotic welding and painting shops are rolling off on an average 120 cars a day from a typical plant. While the automobile industry is an early adopter of automation, today Industry 4.0 is ushering in a new era of digitalization where decisions are driven by the data analyzed in real time to further automate manufacturing with the help of intelligent robotics. The ultimate goal of the entire concept of Industry 4.0 is autonomous manufacturing in factories of the future, with minimal human intervention.

How AI-Powered Robotics is Transforming Manufacturing Today

The digital transformation of manufacturing goes hand in hand with the combination of robotics and a host of digital technologies – most notably smart sensors – with artificial intelligence (AI) and machine learning (ML) as the cutting edge. Conventional robots used in the manufacturing industries for the last several years had limited capabilities in terms of movements and nature of operations, though they are highly efficient in operation for mass production, for jobs like welding, painting and pick and place. AI-powered robots, on the other hand, are equipped with a wide variety of sensors and are ideal for performing many more tasks like assembly of precision parts and components, inspection of parts and components for flaws and defects, and sorting and packing of finished products. These AI-powered robots are data driven, the data collected from a host of sensors either integrated inside the robots or placed strategically in the operations area from where they provide highly accurate measurements for precise movement control and accurate monitoring of the process. These new generation robots are automating tasks that were so far from the preserve of human workers and performing them with much more efficiency and high accuracy. A robotic workforce is now ready to take over more and more functions on the shop floor, leaving human workers free for more creative jobs and pursuits. This also goes well in the advanced economies where robots are making up for a dwindling workforce. The future of manufacturing is linked closely with the future of robotics.

How Robotics and AI in Manufacturing has Changed

The robots of the previous generation basically automated routine and repetitive tasks, and were mounted in fixed positions. These were highly suitable for mass production where day in and day out, the same models of cars or the same type of white goods were manufactured. The present trend of flexible manufacturing usually means more customization, smaller batch sizes, and different types of products manufactured on the same assembly line, with the changes effected in machines and robots via programming alterations. The assembly line itself has changed in many cases and made way for manufacturing cells in smaller configurations more suited for flexible manufacturing, where AI-powered robots have taken over more and more tasks from their human counterparts. These are collaborative robots that are free from safety cages, are smaller, more agile and mobile, often mounted on autonomous guided vehicles (AGVs), moving unobtrusively around the shop floor. Thanks to artificial intelligence, these robots are not only easy to program and self learn, but they also teach other robots, saving time and human resources. They have better architecture and more computing power and data storage capacity, which make them ideal for more autonomous operations, towards realizing the goal of smart factories. The outlook for robotics, vis-à-vis the role of robots in manufacturing, is thus very positive. While there are many pros of robots in manufacturing, one cannot ignore the flip side. The few cons of robots in manufacturing include the high initial investment. But globalization also means that unless manufacturing is competitive with respect to the more advanced economies, developing nations cannot find their rightful share in the market.

The 2 Things That You Must Start Doing to Remain Competitive

The world of technology is constantly evolving and so is the manufacturing process. This evolution of the manufacturing industry is evident in the implementation of AI and Robotics. There are many things manufacturers can start doing if they must remain competitive, but if one has to name just two, these should be:

1. Know your consumer; and
2. Innovate and adapt.

Understanding consumer likes and preferences is a key to success in business. This is easier said than done because often the masses either have unlimited wants and needs, and are unable to meet them. An astute businessperson is one who finds a way to meet some of these needs at optimum cost and cater to the requirement anticipating what the consumer really needs.

The second, and more important thing, is to innovate and adapt to the latest trends in manufacturing, in order to make the product most economically and efficiently, without compromising on quality. This is possible only with the use of latest technologies, and in the case of manufacturing, use of automation and robotics.

The Benefits of Implementing Data-Driven Manufacturing Practices

Data has often been compared to oil or gold, which are high value commodities, indicating the importance of data. Manufacturing being a high risk, capital intensive business should always be based on data derived from various sources. In the digital era, smart and affordable sensors in conjunction with the Industrial Internet of Things (IIoT) have made data capturing easy, but not all enterprises have succeeded in making use of this data, which is humongous and unstructured at the source. Use of artificial intelligence in data analytics helps in getting the structured data, which is further refined by applying machine learning algorithms. Once implemented, data driven manufacturing has several benefits that come with better planning, enhanced productivity and optimization of resources, besides better maintenance practices that prevent unexpected downtime.

The Benefits Can Be Summarized Thus:

Greater transparency: Structured data clearly brings out the facts of the entire process offering better visibility, discovering bottlenecks and exposing inefficiencies and poor maintenance practices, helping a better understanding of the situation by all stakeholders, which also instills accountability.

Improvement and innovation: Better visibility of the process of manufacturing automatically leads to continuous improvement to overcome the drawbacks, and promotes innovation to overcome the difficulties, incentivizing performance as well as engendering a competitive spirit among the workers as the metrics are now measured and monitored.

Predictive maintenance: With better data analytics, it is easier to implement predictive and prescriptive maintenance practices based on machine monitoring and anticipating failure, which avoids unexpected downtime. Maintenance schedules can be planned in advance to avoid stoppage of work during busy production schedules.

Faster decision making: Insights gained from data analytics helps in making quick decisions about inventory planning and streamlining of supply chain with further optimization of resources, that avoids both – sudden running out of parts and components as well as pile up of surplus inventory. With faster decision making, organizations benefit from quick order fulfillment and better customer satisfaction.

Cost reduction: Lessons derived from data analytics help streamline the total production process that eliminates inefficiencies, optimizes manpower with more automation, and minimizes waste. With incremental measures like these, production efficiency increases resulting in overall cost reduction, also improving product quality in the process.

Conclusion

With all the available resources today in terms of data gathering and analytics, there is little surprise that the future of manufacturing will be data-driven. As analytics get better with AI and ML working in tandem to further improve the predictions and increase transparency, manufacturing industries stand to gain the most. This would be achieved by following a three-pronged approach: deriving actionable insights; predicting future outcomes; and enabling self-optimizing systems for autonomous self correction. However, there are some critical challenges in the process, especially when it comes to legacy plants and organization cultures that still follow the siloed approach preventing information sharing. Another area is system security and the growing cybersecurity concerns with the proliferation of IIoT devices that are vulnerable to hacking. These are the areas that need professional expertise and enterprises must be willing to seek help from the right quarters.

The first industrial robot was deployed in 1961 and could perform only a few basic operations. Years after that have seen tremendous advances in robotics in terms of design, construction, ergonomics, operation and expansion of areas of application. Robots today are deployed in large numbers in industry to perform jobs more efficiently and accurately than human beings, often in hazardous working conditions. Thanks to their ability of continuous working, robots are also cheaper than human labor for a given operation, when used in a mass production environment. With design optimization and advancements in mechatronics, IoT connectivity and other emerging technologies, robots have become lighter and more versatile, also easy to program and deploy. These trends indicate that going forward, robotic manufacturing is here to stay.

Robots – the Future of Manufacturing?

As robots take over more and more functions – apart from assembly operations, robots equipped with machine vision now also do inspection of finished products to detect errors – the future of manufacturing is inextricably linked to the use of robots. Countries that are leaders in manufacturing like Japan, Korea, Taiwan, Singapore and Germany are also the countries that are high in robot density. A World Economic Forum study indicates how industrial robotic automation leads to an increase in the quality of exported products. Across all countries, a 10% increase in robot stock results in a 1.2% increase in quality; but the strongest quality gains accrue to developing economies, where a 10% increase in robot stock leads to a 2.7% gain in quality. If the developed world relies on industrial robotic automation to tide over their labor shortages, developing countries are left to catch up with them just in order to compete in the marketplace, with quality dominating customer preferences.

The Current State of Robots in Manufacturing and How They are Changing Lives

The post-Covid boom in demand for various categories of products ranging from automobiles to consumer durables and consumer electronics has led to a further growth in the sale of industrial robots. The preliminary results for 2021 robot sales published recently by the IFR indicate a strong recovery with a new record of 486,800 units, surpassing the pre-pandemic record of 422,000 installations achieved in 2018. What is remarkable about this growth is the fact that for the first time, the electronics industry has surpassed the automotive industry as the largest consumer of robots globally. India, for example, is now attracting significant investments in electronics manufacturing under the PLI scheme. Apart from mobile phones where the country is now the World No. 2, semiconductors is a major focus area of the PLI scheme, where robotic integration is an important part of the manufacturing process.

Use of robots in manufacturing has many advantages that have a positive impact on those engaged in manufacturing industries. The foremost among these is robots perform routine and repetitive jobs – assembly, welding, painting, machine tending, pick-n-place and palletizing, gluing/sealing and inspection – more efficiently and with higher accuracy, in the process also freeing human labor to do more creative and better things that robots cannot. For example, robots cannot design and innovate, nor can they plan, organize and strategize – activities that are best performed by humans – which contribute to business growth. Similarly, robots operate in conditions that are hazardous for human workers, like furnaces and forge shops, chemical industries, weld and paint shops, etc. These are jobs that not many are willing to do. Similarly, autonomous mobile robots (AMRs) are today widely deployed in logistics and warehousing operations, especially by ecommerce companies. AMRs are far more efficient than automated guided vehicles (AGVs) that were more commonly used earlier. The size and scale of these operations is beyond human capabilities to perform accurately in a given time frame. By taking on these tasks, robots free human workers from the drudgery of monotonous and hazardous activities. The other positive impact of robots is that their high efficiency and productivity benefits not only the end user – the customer who gets the products and services at lower cost – but also the manufacturer, who makes better profits.

The Scope of Robotics in Manufacturing and its Impact on Society

If the preceding paragraphs presented a contemporary scenario of use for robotics in manufacturing, the scope for industrial robotics is far more expansive as more and more enterprises embark on their digital transformation journey. In an article that captured expert views on future forecasts for robotics, Sami Atiya, president, ABB Robotics & Discrete Automation, predicted in 2022, will see more demand for flexibility and more businesses embracing robotics. As the manufacturing ecosystem envisaged by Industry 4.0 gradually becomes a reality, robots with more advanced capabilities would work side by side with their human counterparts. This has already begun happening with the evolution of collaborative robots or cobots as they are called. Unlike industrial robots, cobots are not confined to separate caged areas for safety as they are equipped with sensors and soft skins to work in close proximity with human workers without colliding with them.

The most important development for robotics in manufacturing is the use of machine vision systems, artificial intelligence and machine learning algorithms. These technologies make robots intelligent for the connected factory, where all operations are synchronized and coordinated centrally. By 2035, AI is estimated to have the potential to increase labor productivity by up to 38%, but on the flip side, it will result in many more jobs taken over by robots. This is precisely what is causing serious concern for policy makers with unemployment causing adverse social impact. However, the International Federation of Robotics downplays these concerns of negative robot impact on society by maintaining that robots substitute labor activities but do not replace jobs as less than 10% of jobs are fully automatable. As an example, IFR quotes the automotive industry of US and Germany, which now employs more people despite increased use of robots. Besides, the technologies that unleash the potential of automation and robotics also create many more jobs, for design, engineering and maintenance of those systems, it says.

How Far Can Robotics Go?

As the cliché goes, robots have just scratched the surface as far as applications are concerned; they are capable of performing many more tasks than what they are doing presently. In the factory of the future, it is said, only the walls, floor and ceiling would be fixed and everything else – machinery and equipment – would be moving. Actual production would be based on the orders received and products to be made, with no limit on the minimum batch size. This will be facilitated by autonomous mobile robots with machinery and parts moving from module to module to execute the production schedule. From collecting parts from the inventory to picking them up for assembly, the assembly itself; inspection of finished products and packaging them for delivery, robots will perform most operations to realize the ultimate goal of lights out manufacturing.

Robots are also finding applications in areas like waste segregation for better recycling. Colorado (US) based company AMP Robotics applies machine learning to differentiate waste, a core capability that has been missing from the industry. The company uses robots based on its AI platform to recognize patterns of specific recyclable materials within a complex waste stream. Founded in 2015, AMP Robotics today has a global footprint with presence in most European countries and Japan, apart from North America. Applications of robots in medicine, healthcare and the services industry are growing too, restricted only by imagination.

Conclusion

The fact that modern day robots are an excellent example of technological advancements is no secret, as are the benefits of industrial automation. The industry has gained tremendously from their high efficiency and productivity, with matching ROI. Yet robots have their limitations. They are not a universal solution for the manufacturing industry. Eminently suitable for certain jobs, use of robots without proper due diligence can ruin a reasonably profitable company, burdened with costly equipment it did not need. Robots are expensive to buy and though they are now easier to program, they need skilled operators. Yet, in a competitive world, every manufacturer needs to assess the requirements for scaling up production or take the existing business to a new level. Every manufacturer now must consider steps to get started with robots, which calls for professional expertise and a realistic assessment of the ROI. Jobs that are presently done profitably in manual mode of operation do not need to be automated unless robots offer an economical alternative.

But for any business, now is the time to learn everything about robots and robotics, including the why, when, where and how to buy them. Professional agencies like ENWPS have the necessary expertise in automation and robotics with over 24 years of rich experience in installation, programming and commissioning of robots in manufacturing industries.

SCADA or Supervisory Control And Data Acquisition, as the term indicates, is a computer-based control system. Originally developed for industrial plants and production facilities, SCADA can be used at any place where machines and equipment need to be monitored and controlled, e.g., warehouses, utilities, buildings, etc. This is done by automating the functions of collecting, processing, monitoring and display of data gathered from the equipment through remote field devices. The system gathers and monitors metrics like pressure, temperature, flow rate, pH, etc., the values of which are compared with the defined set-points, and action is initiated to perform corrective tasks by remote control for smooth running of the plant or utility. The SCADA system architecture comprises both hardware and software elements.

How SCADA Programming Works

SCADA monitors and controls processes through field devices like sensors and relays that generate the inputs and outputs. Inputs form one of the four main components of SCADA, the other three being: RTUs or Remote Terminal Units; HMIs or Human-Machine Interface; and the Communication Network. To understand how SCADA works, one must understand how these four components work. The inputs are collected by networked devices and sensors mounted on the equipment like motors or pumps in the form of signals that contain the information like power supply, temperature, pressure, vibration, etc. Though devices and sensors generate the inputs, they cannot read or interpret them. This is done by the second component, the RTUs and PLCs, which are computerized units that acquire the site data like meter readings, pressure, voltage, equipment status, etc. The RTUs/PLCs pass on the inputs to the third major component, the HMIs that are located at the central control room where the information from the signals is displayed in readable and actionable form – graphically or through indicators – for quick response, which is again communicated through the same RTUs for corrective action through relays and actuators. The fourth major component of SCADA is the communication network, which completes the system. The four main components of SCADA thus have four corresponding functions – Data Acquisition, Data Interpretation and Action, Data Presentation and Networked Data Communication. Apart from the four main components, there are other components and tasks like the supervisory system and programming that complete the SCADA architecture.

What Benefits Does SCADA Programming Have for Big Data Integration?

Data is what is driving decision making in industry through digitalization, be it process or discrete manufacturing. This data is gathered from the entire plant or process industry operations spread across multiple locations, through field devices. IoT devices and edge computing has further enabled capturing of data that was earlier not possible to collect and monitor, giving rise to the term Big Data. If a manufacturing industry has operations spread across different locations and countries, all these can be controlled by web-based SCADA centrally, replacing various other monitoring software and devices. Mere gathering of data is of little use unless it is analyzed and contextualized, a function that SCADA facilitates. Data analytics help identify problems before they cause a breakdown resulting in costly downtime. The insights thus gathered also help plant managers to schedule maintenance and avoid unplanned downtime. These insights are also useful in better management of running equipment and avoid idle time, saving energy or improving efficiency. It can thus be observed that SCADA systems have grown in sophistication and are integrated with all data sources of equipment and operations across a wide area and multiple locations, facilitating better decision making and raising the overall equipment effectiveness (OEE).

SCADA System Architecture and Its Components Explained

First developed in the 1950s, SCADA is now in its fourth generation and increasingly powered by IoT devices. Despite this evolution, the basic components of the system remain the same, with addition of more devices, and modern digital communication systems.

The SCADA system architecture, in its most simple form, is like a tree diagram. The SCADA host is at the apex, which branches down to SCADA nodes or servers, which in turn connect to the RTUs or PLCs that are connected to the field devices, representing the tree structure.

A typical SCADA system consists of the following basic components, a mix of hardware and software:

1. Human Machine Interface (HMI) – basically an input/output device, the HMI presents the information to the human operator graphically for control and action. The HMI is linked to the databases that provide all necessary data and information about system parameters, maintenance procedures, etc., which is programmable depending on the process requirements.

2. Supervisory System – also referred to as Supervisory Station, this comprises the software and servers that communicate between the field equipment and the HMI software running on the control room workstations. The supervisory station comprises a single PC in smaller SCADA systems. For larger SCADA systems, it comprises multiple servers, disaster recovery sites and distributed software applications.

3. Remote Terminal Units (RTUs) – these are part of the hardware, microprocessor controlled electronic devices. The RTUs that receive data from the sensors and send it to the supervisory system and in turn receive messages from the master system for controlling the connected equipment.

4. Programmable Logic Controllers (PLCs) – these are alternative devices to the RTUs connected to the sensors for collecting and transmitting the input/output. PLCs have certain advantages over RTUs like flexibility, configurability, versatility and affordability.

5. Communication Infrastructure – SCADA systems use various communication systems like directly wired, radio or a combination depending on requirements. Large operations spread over wider locations like utilities and process industries also use optical networks like SONET/SDH.

6. SCADA Programming – this is done via standard interface and is used to create maps and diagrams that provide important information in case of an event or process failure. Programming is done by using C or other appropriate language using standard interfaces.

How SCADA Systems Operate from Development Phase to Implementation Phase

With the evolution of SCADA over the past 50 years and more, the system has become more affordable and easier to implement, yet has grown in complexity with several added functionalities. Today there is a wide choice of industry and sector specific SCADA systems in the market – off-the-shelf or customized – as also vendors for the software and hardware components should any enterprise decide to build their own. Either way, before implementing the system there are a few steps that need careful consideration:

• Clearly understanding of the process requirements
• Current data collection process
• Server for data collection points
• Additional data collection points
• Centralizing data monitoring
• Determining the software for data
• Graphical representation of data and controls, and
• Defining the level of automation and controls.

Once the SCADA system is set up with the hardware in place, it is run by the software and facilitates interaction with the plant or process facility. The HMI display shows the running status of all the field equipment, and issues alerts and informs maintenance schedules, etc., as programmed.

Conclusion

SCADA system is one of the most commonly used industrial control systems to manage most types of industrial process. Though seemingly simple, a modern SCADA system is complex in operation. The choice of the system – off-the-shelf or customized – needs careful consideration as there are pros and cons. An off-the-shelf system is faster to deploy than a customized one, but sometimes a customized system makes better sense. Professional expertise can help ease the pain points in implementing SCADA for any given operation. Pune based ENWPS has the necessary domain expertise and experience for helping companies build and operate SCADA systems of any size and scale. Its experts can help in system selection and implementation, programming, and maintenance to ensure a trouble-free operation.

The term Industry 4.0 originated with a project of the German government in 2011, which evolved around turning the concept of Cyber Physical Systems into a production system, with Smart Factory as one of the goals. Robots, with their many advantages like continuous operations with minimal supervision, and increasingly the ability to work together with their human coworkers, are an important part of this new manufacturing ecosystem. The first industrial robot introduced in the early 1960s could perform only pick-and-place operations initially. But soon robots were programmed to do other tasks like welding, assembly, painting and even final inspection. Advances in technology have further improved the efficiency of robots, resulting in massive productivity gains without compromising on quality.

Industry 4.0 and its Impact on Manufacturing

Implementation of Industry 4.0 in manufacturing environment involved equipping machines and systems with lots of embedded sensors and controls connected by software, an Industrial Internet of Things (IIoT) that created a network of physical objects. It also implied increased use of robotics in manufacturing besides applying emerging technologies like machine vision and virtual reality for remote operations and troubleshooting. These technologies have made robots intelligent and autonomous, paving the way for smart manufacturing, eliminating unplanned maintenance that disrupts production. In fact an early benefit of Industry 4.0 was linking robots together across manufacturing plants by General Motors, in collaboration with Fanuc, Rockwell Automation and Cisco, to deliver ‘Zero Downtime’ (ZDT).

Accelerated Automation for Greater Productivity and Efficiency

One must understand that automation in industry predates Industry 4.0, as also robotics. Even before the formal launch of Industry 4.0, industrial processes and manufacturing systems were highly automated, and robots were widely used in assembly operations, especially in automotive manufacturing, packaging and other applications. What the forces unleashed by the Fourth Industrial Revolution did was to accelerate the process of automation and take it to a new level, further increasing efficiency and raising productivity. It paved the way for greater use of robots in manufacturing, ranging from use of traditional robots in machine tending and pick and place operations, to extended use of robots in inspection lines in tandem with machine vision technologies, and use of automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) on the shop floor intralogistics operations.

Advantages and Disadvantages of a Robotic Workforce

There are many advantages of using robots in manufacturing – in fact, the world is rapidly moving towards a robo-economy where most tasks performed by human labour are taken over by robots.

With growing ease of use, more and more robots are now deployed in manufacturing activities globally. This is particularly true of companies facing labour shortage like Japan, Korea and Singapore where the robot density – the number of robots per 10,000 humans – is the highest. But even China, with its abundant labour, is scaling up, in order to scale up production to compete globally. Unlike humans, robots do not get tired and there is no absenteeism with the robotic workforce. Besides, they perform tasks that are beyond human capability and endurance, also in hazardous locations. Ranging in size from small to very large, robots are versatile and can be programmed to perform multiple tasks, switching from one type to another. They are also highly precise and accurate, improving the quality of job output tremendously. Being fast, they are also highly productive.

Having listed the advantages, it is also important to look at the disadvantages – is the robotic workforce worth it? Are robots taking over human jobs and causing unemployment?

Though robots are getting more affordable, the cost is still beyond most business units, especially the SMEs, which create an uneven playing field, putting them at a disadvantage. But more important is the fact that improperly thought robotic plans can put such companies under financial strain. Robots serve a purpose in high production environments and not all units call for such high output. Robots also need skilled persons – operators and supervisors that add to the costs. In the absence of skilled operators and supervisors, robots could cause inadvertent harm – damage as well as injuries. Above all, in a labour surplus country like India, massive deployment of robots will only create more unemployment and social unrest.

Robotics in Manufacturing – A Global Perspective

Globally, the use of industrial robots is accelerating rapidly. According to the 2021 World Robot Report released by the International Federation of Robotics, the average global robot density in the manufacturing industries is now 126, which is nearly double the number five years ago – it was 66 in 2015. South Korea with a robot density of 932 leads the pack, followed by Singapore (605) and Japan (392). Germany follows close behind with 371. All these countries are leaders in manufacturing with global exports. Their high industrial production is achieved by their highly robotized production lines which also play a role in maintaining high quality of the products. China, with a robot density of 246 is the fastest growing country in robotic deployment, despite its labour surplus, for the simple reason that it is competing with these manufacturing giants for a share of the global market.

Today, India is working hard to raise its manufacturing output with a slew of incentives and schemes, especially in electric and electronic goods. Globally, these are highly automated industries with large scale deployment of robotic assembly. To compete globally, there is no option but to go for the most modern production techniques, something which is happening with the new units coming up under the PLI scheme. With a robot density of just under 5, India has a lot to catch up, but it is one of the strongest growing economies among the emerging markets in Asia, according to a 2019 IFR report, when India ranked 11 in terms of annual installations of industrial robots.

Conclusion

The industrial robotics revolution unleashed by Industry 4.0 is the future of manufacturing, whether those who are apprehensive about robots taking over jobs like it or not. With the highly industrialized countries taking the lead, the developing countries ought to follow the trend, as labour costs are increasing as China has realized at some cost.  According to GlobalData, a leading data and analytics company, the robotics industry will pass the $500bn mark in 2030, after a decade of growing at double-digit rates. That is an impressive figure for an industry that generated global revenue of just $45.3bn in 2020.

The Indian industry must prepare itself for the inevitable. Robots are coming and at a rate faster than we can imagine. Feasibility studies, application examples, training personnel for the necessary skills are some of the measures they can follow, by consulting with professional agencies, if required. ENWPS, for example, specializes in automation and robotics and has over 24 years of experience in installation, programming and commissioning of robots in manufacturing industries.