Fourth Industrial revolution aka Industry 4.0 refers to the modern phase of the industrial revolution that concentrates specifically on automation, machine learning, real-time data, and inter-connectivity. It is dramatically altering how businesses operate resulting in rapid changes for resourcing, technological and capital investments.
Industry 4.0 is the integration of physical production and operations with advanced digital technology to create an exceptionally connected and holistic ecosystem (smart machines) for manufacturing and supply chain management.
These smart machines have embedded software systems, modern control systems, and an internet connectivity. This complete collaboration of machines via internet is also known as the Internet of Things (IoT). This way, machines, operators, and whole system can communicate enabling new ways of production, value creation, and real-time optimization.
Before probing further into this latest transformation of manufacturing industry, it is essential to understand how exactly this sector has evolved since the late 1700s. So far there have been 4 distinctive industrial revolutions.
Four Industrial Revolutions
The first industrial revolution happened in 1784 with the first mechanical weaving loom. This period saw the migration of manual labor performed by people and work animals to a more optimized form of labor performed by people using steam-powered engines and machine tools.
The world entered the second industrial revolution (also known as the Technological Revolution) in the early 20th century with the advent of steel, petroleum, and the use of electricity in factories. Electricity enabled manufacturers increased efficiency and made factories more flexible. During this revolution, major manufacturing concepts were created like the assembly line in 1870 to boost productivity.
The next revolution started in the late 1960s with the advent of electronics made of silicon and the introduction of the computer. This saw a major shift away from analogue and mechanical technology to digital technology and software. The first programmable logic control systems were created by Modicon in 1968.
The latest industrial revolution or Industry 4.0 (i4.0) has emerged due to the emphasis that digital technologies are having on businesses. The technology advancements offer a comprehensive, interlinked, and holistic approach to manufacturing. It connects the physical & digital, allowing for better collaboration and access to departments, partners, vendors, products, and people.
What is Industry 4.0 and Smart Manufacturing?
“Industry 4.0” refers to the integration of industrial manufacturing and information technology based on cyber-physical systems, Internet of Things and Cloud Computing.
Industry 4.0 enables and supports new scenarios in manufacturing where humans, machines, production lines, software systems, such as MES and ERP systems, and the products themselves communicate and cooperate in real-time to enable decentralized decision making and a self-organized production.
This approach includes all phases of the product lifecycle (product idea, development, production, usage, maintenance, and recycling) and all participants of the value chain (company-internal and -external, such as suppliers and customers) and thus allows a complete optimization of the value chain.
Smart Manufacturing is a general term often used to reference the modernization of the manufacturing process.
A Big Opportunity for The Manufacturing Industry
Industry 4.0 allows the manufacturers to differentiate themselves from their competitors. The workforce must consist of professionals with both IT and analytical skills. That being said, it is crucial to hire individuals that have a mindset of growth and digitization rather than only tech or analytical skills.
Even small manufacturers can reap the fruits of Industry 4.0. Instead of spending a fortune on buying costly equipment and modifying processes, they can associate with other big manufacturers, business consultants, and research institutions. The companies offering machines-as-a-service could also be of great help for small manufacturing businesses.
As customer-centric business processes lie at the core of this industrial revolution, the manufacturing companies have an opportunity to maximize their bottom line. Superior customization abilities, feedback from each consumer, analysis of consumer behavior, and innovative designs are some of the key drivers.
The 7 pillars of Industry 4.0
Industry 4.0 has more layers to it compared to previous industrial revolutions. Its components consist of cutting-edge technologies, advanced processes, and methods to ensure communication between them. Though the components might vary a bit by industry or region, the following seven pillars are common to most of the manufacturing units that have embraced Industry 4.0:
Big data constitutes massive data sets analyzed through computer programs to reveal meaningful patterns. One of the fundamental aspects of Industry 4.0 is a collection of industrial data from multiple sources. The enormous amount of data is pooled into a data lake and utilized to streamline the processes. Two other pillars of Industry 4.0, AI and IoT are entirely dependent on big data to generate desirable results.
For data storage, the organizations rely upon industrial control systems and enterprise resource planning systems, along with documents and spreadsheets.
Take an example of big data in oil and gas companies. Their operational units can receive data from hundreds of electric submersible pumps, equal to millions of records per day. When used strategically, the data helps in improving efficiency by a high degree.
Digital twins mean digital replicas of physical assets. Creating digital replicas pf physical products saves time, money and many other resources for businesses. A digital twin or virtual model of any product can help creators in altering the designs or material before actually constructing or producing a real physical product.
Around 53 per cent of executives from different industry verticals plan to integrate this technology into their operations by 2028.
The operators can identify performance, features, and potential issues of the virtual simulated model (digital twin) through this technology. Digital twinning reduces downtime and improves quality.
Internet of Things (IoT)
By utilizing actuators, sensors, and automation systems, the manufacturing units can generate data from their machines and processes for predictive maintenance and enhanced efficiency.
The Artificial Intelligence algorithms alert the companies about minor deviations during production that can lead to quality drops. While designing a product, AI algorithms enable product designers to explore each possible configuration. Through a unique algorithm called generative design software, suitable production methods, material types, budget constraints and time limitations could be identified.
A device is integrated into a manufacturing machine that monitors criteria under varying conditions, including temperature levels, pressure, cog movements, and oil & airflow. The IoT records an abnormality related to the working of a machine. It gives sufficient time to make decisions on whether to repair/replace a part of the entire machine.
Around 60 per cent of tech decision-makers who participated in a survey by Oracle favored cloud computing technology.
The industries can create an environment of digital integration and collaboration by relying on cloud technology. Cloud computing enables real-time data exchange of information, connects people, and offers real-time visibility. Using cloud also helps in managing the manufacturing processes and supply chain becomes efficient, with improved risk management. Companies are benefitting in terms of better flexibility, enhanced production capacity, and cost control.
The interconnected nature of the fourth industrial revolution translates into cyberattacks that are more severe and widespread. The manufacturing units need to have cybersecurity strategies that are integrated into IT and organizational strategies. These strategies also need to be resilient, vigilant, and completely secure.
The industries are already considering a multi-layered security framework, including the NCSC Cyber Essentials model and the CIS Controls model. Various firms are adopting a Zero Trust architecture, which lets only authorized users on authorized devices using approved applications to access the network.
According to a report by ResearchLinker, the cybersecurity market is expected to cross 31.4 billion dollars by 2025, with manufacturing and telecom being the most prominent adopters.
Industry 4.0 is a flag-bearer of connectivity between machines, staff members and stakeholders. This requires a combination of multiple software packages, computing systems, and business processes to develop a more extensive system. This combines software applications and sub-systems to new novel functionalities, thereby boosting the value of a system.
For effective system integration, the companies must seek standard platforms that can integrate new products as soon as they appear in the market. Also, the engineers must develop proficiency in both automation and project management skills to ensure the effective merger of information technology (IT) and operational technology (OT). This will help businesses by creating agile manufacturing environment and enabling real-time production corrections and quick alterations.
The devices that require little or no human intervention for their operations are referred to as autonomous systems. In a manufacturing unit, such systems make decisions autonomously by recognizing and learning from their environment. Such systems operate round the clock without compromising with quality and speed. It is possible to deploy autonomous robots in highly hazardous environments to generate desired outcomes.
While integrating such systems, the manufacturing units must ensure the robots come with security algorithms and sensors that do not interfere with the infrastructure of the production facility.
SMEs can opt for flexible leasing options related to autonomous systems in the initial stages. Various organizations having little operator experience may also consider utilizing autonomous robots as a service.
Major hurdles in implementing Industry 4.0
This data-driven realm of machines and processes has its own set of challenges. Myriad companies feel that adoption of the Industry 4.0 is not as straightforward as it looks on paper. Let’s zoom in on the significant challenges faced by manufacturing units.
Security and safety concerns
Plenty of incidents from the recent past prove that security and safety are one of the main concerns related to Industry 4.0. Numerous energy companies faced attacks in 2016. The attack on the Electricity Board of Ireland in 2017 also prove the same. The organizations need to identify how the resources to secure the technology will come. The need for establishing global standards to smoothen the development is another concern.
If we talk specifically about energy and utility-related industries, the issue is primarily of physical security rather than that of cybersecurity. Talking about cybersecurity, the smaller suppliers are prone to cybersecurity attacks due to their lack of resources.
Merger of OT and IT
The merger of Information Technology (IT) and Operational Technology (OT), which is a crucial strategy of Industry 4.0 comes with plenty of challenges. It gets challenging to redefine the roles and responsibilities of individuals in operations, especially when they are accustomed to handling their own systems. IT outages is another major issue that affects the customer-facing systems. Various companies have an inefficient system of identifying and tracking risks. The cyberattack on operational systems can be dangerous for the environment, infrastructure, and the individuals involved in the operations.
Greenfield and Brownfield
Owing to high ROI and low investment, various companies opt for Brownfield fields. One of the major issues with this approach is the difference between design standard utilized in the existing system and the latest standards. Lack of understanding and details of the current facilities, which lead to poor planning, is another challenge. Various new and already existing equipment aren’t compatible.
Talking about Greenfield projects, they are preferred because of their straightforwardness and lack of complexities. The companies find the implementation challenging because the projects are situated away from the city, which makes it difficult to access all the amenities. There is an increase in the commute time of workers. Negative impact on the environment is also witnessed.
Apart from recruiting skilled workers, companies face challenges related to the existing employees. They need to train their workforce to operate robotics systems and related automation tools. External training centres or in-house departments will be required for the same. As the automation systems continuously evolve, the organizations will have to ensure their existing keep on adapting as per the new technological updates. The existing workforce that’s used to work manually will resist technological modifications. The companies will have to focus on changing their mindset to ensure a smooth transition with minimum hindrances.
Balancing productivity with fewer resources
The organizations need to identify the ways to deliver more and quicker with limited resources. Machine reliability is a factor, as production goes to halt if equipment stops working. A lot of organizations don’t utilize their machines to the fullest, thereby leading to wastage of resources. Various phases of production might require more energy, which results in unnecessary expenses. Another possible challenge is shutdown time of plant during refits.
Implementation of innovative methods
Various organizations, especially in the developing countries, will find it challenging to cope up with the growing trends of implementing innovative practices. A lot of them will find it difficult to match their competitors in this regard. As a result, they will start to lose market share. The traceability in the supply chain is another area where innovation is expected.
Multi-step approach for Industry 4.0 integration
The starting point of successful Industry 4.0 integration begins with a structured approach involving various steps. A three-step process to achieve this is discussed below:
Deployment of sensors and controls
The use of sensors in a manufacturing plant enables collection and analysis of data with the help of I/O and cloud interfaces. This maintains optimal industrial conditions through continuous monitoring. Process control is one of the key applications of smart sensors in industries like aerospace, automotive, and manufacturing. The companies using smart sensors and controls have reported a reduction in downtime and expensive equipment failures.
Sensors are also effective in logistics. Stacking of containers could be optimized through sensors. By using sensors, the self-driving cars in a factory can determine its location.
Making the sensors more robust
A need for robust design arises that can survive harsh conditions of manufacturing units. Highest level of accuracy is also prerequisite to deliver precise information to the systems in a factory. Such sensors detect even the little modifications in the parameters that are to be measured.
Sustainable designs that require minimum maintenance and recalibration process. This can be achieved through engineered sensor packaging. The aim is to protect sensitive sensing elements with a strong casing.
To successfully implement the sensors at a plant level, the companies have to properly map the factory floor in their central computer system. For the sensors in automated guided vehicles, the use of RFID technology embedded in the floor paths is an ideal solution.
The creation of a development board is also crucial that is capable of hosting the sensors that a manufacturing unit needs. The development of software for the system is made possible with this strategy.
For plant-level implementation, proper training of concerned employees is equally important. They should know how to recalibrate the sensors in case the readings show anomalies. The responsibility of identification of a new set of sensors required during scale-up is another key responsibility area.
The Industry 4.0 Maturity Index
The transformation of a manufacturing unit from a regular computerized workshop to a place that conforms to Industry 4.0 can be explained by the Maturity Index. The speciality of this index is that each phase builds on the earlier one.
STAGE ONE: COMPUTERIZATION
Through Information and communication technologies (ICT), the manual production activities are computerized. The technologies used are in isolation from one another. Computerization leads to increased precision and reduced costs.
STAGE TWO: CONNECTIVITY
The connected components replace the isolated ICT equipment of stage one. The connectivity discussed in this phase is restricted to enterprise integration.
STAGE 3: VISIBILITY
A production facility can have the visibility of its systems in real-time with the help of data collection abilities. The use of sensors at different phases of production enables this. The production managers make decisions that are based on information instead of their experience.
STAGE 4: TRANSPARENCY
Having transparency in an organization helps in identifying the reasons behind the occurrence of earlier and current events. Engineering knowledge is utilized to analyse the recorded data for this purpose.
STAGE 5: PREDICTIVE CAPACITY
The companies predict the future by assessing data. Various scenarios are simulated to identify possible threats. The necessary counteractions could be, therefore, taken to minimize their impact.
STAGE 6: ADAPTABILITY
By deploying complete automation and connectivity, a company enable a system to react automatically to evolving exogenous conditions. It is crucial to understand inter-dependencies throughout the system, along with its influences. This ensures the system can easily adjust to new circumstances.
Benefits of Industry 4.0
Thanks to the current wave of the industrial revolution, the companies can expect more streamlined processes with minimum production errors and downtimes. All these benefits translate into an increased bottom line. The companies that follow the norms of Industry 4.0 report most of the advantages discussed below:
Improves operational efficiency
One example of operational efficiency is the availability of staff to perform the changeover of machines as per the allotted time. Also, raw materials that enter the production stream during the next batch does not bottleneck the production floor. This is made possible with IoT-connected equipment, which enables the system to analyze variables like bottlenecks and staff assets.
Another application is the ability of the frontline managers to assess the reasons behind equipment inefficiencies. They rely on real-time data of assembly lines for this purpose.
The real-time data collected across the supply chain is analyzed to improve the design, operation, and products via instant feedback, which leads to improved manufacturing productivity.
McKinsey & Company has predicted a 45 to 55 per cent boost in productivity of technical professionals by moving to automated production.
This can be achieved through human-robot collaboration, digital performance management, and remote monitoring. The same report by McKinsey also reports how remote temperature monitoring has led to an increase in productivity in the pulp and paper industry.
Creates new business opportunities
This happens at two levels. First, the innovative product designs with Industry 4.0 practices enable the companies to launch new product lines or enhanced variants of existing ones. Second, the development of different sensors, robotic equipment, and software with applications in smart factories can be lucrative opportunities. The budding entrepreneurs can consider the domain of industrial IoT SAAS, but this arena is already dominated by numerous players. Another promising area is predictive maintenance — a service that combines machine learning with acoustic/vibration monitoring to detect early-stage defects will be in huge demand soon.
Predictive maintenance, if implemented efficiently, not only reduces downtime but virtually eliminates it. Let’s explain it with an example. The spindles in milling machines tend to break due to regular usage, resulting in costly repairs. By collecting data from each spindle using ultrasonic sensors, it is possible to identify a fragile spindle. Scheduled maintenance is thus issued through the alerts.
Downtime negatively impacts the bottom line because:
- The manufacturing of the products slows down
- The company has to pay for idle workers.
- Repair/replacement costs a lot.
- Power consumption to restart the machine increases.
The right set of sensors and data analytics algorithms ensure the equipment and processes operate seamlessly, thereby improving the bottom line.
Maximizes asset utilization
The utilization of assets is maximized by generating maintenance schedules and plans that let the production units minimize maintenance costs and downtimes. The focus is also on optimizing the duration and timing of the maintenance process. Flexible manufacturing operations also result in effective asset utilization. Consider autonomous mobile robots (AMR) — these bots take care of tasks like product transportation, thereby letting employees perform more higher-value tasks.
Enables the firms to sell products as a service
Instead of selling a product, product-as-a-service model lets the tech firms enjoy recurring revenue. Take the example of a power-by-the-hour service agreement by Rolls Royce. It offers IoT-enabled engines at a fixed per-hour rate to the customers. The company takes care of predictive maintenance through machine data sent to Rolls-Royce centres for monitoring. An additional advantage of IoT-enabled models is that the OEMs get a chance to better their products by utilizing the data available from the equipment.
Reduces asset lifecycle costs
To reduce asset lifecycle costs, maintenance activities are scheduled and executed during the same period as set-up activities. Several maintenance tasks are clubbed together with the help of predictive maintenance-based planning, thereby minimizing wastage of time. The companies ensure the spare parts, equipment, and personnel are present at the right times and right places by optimizing the utilization of the maintenance resources.
Enhances worker safety
The managers and other concerned parties can monitor the status of the line, facilities, and machines to respond to potential safety threats. It’s possible to proactively replace/repair faulty equipment based on anomalies related to noise levels, air quality, and temperature. By wearable sensors, it’s possible to track the health and behaviour of frontline workers that work in hazardous conditions.
The alerts received through connected devices can signal the workers when they must take a break to avoid fatigue or similar health issues. In several cases, human workers could be replaced by autonomous robots to handle dangerous equipment.
Boosts product innovations
With the implementation of Industry 4.0 approach, the companies are accelerating their product innovation process. While designing a product, AI algorithms enable product designers to explore each possible configuration. Through a unique algorithm called generative design software, suitable production methods, material types, budget constraints and time limitations could be identified.
Receiving feedback from customers via IoT systems enables the designers to create something innovative that precisely matches the customers’ expectations.
Increases understanding of customer demand
By utilizing technologies like artificial intelligence and advanced data analysis, it is possible to determine a customer’s demands. This enables mass customization, which involves heavily customizing of orders by the customers. Automated and semi-automated robots are integrated into production lines to deal with such high degrees of variety.
The companies are also integrating modular material handling equipment that can fit into already existing plant layouts.
Talking about the current trends, the concept of lights-out manufacturing is being considered by several organizations. This approach of a fully automated work environment is gaining traction in the wake of COVID-19 pandemic. Such a scenario reflects why automated and data-driven manufacturing processes are a necessity.
Tele-operation is another emerging area in the realm of Industry 4.0. With this new trend, it’s possible to operate a machine or equipment from a distance. When the remote control is used to control a robot from a distance, the concept is referred to as telerobotics.
The world will also witness investments in communication technology as an integral part of Industry 4.0. The manufacturers have to reinvent each process for successfully capitalizing on the digital world. Merging digital technologies with traditional practices is the key to become more scalable, agile, innovative, and quicker, thereby getting ready for the future.