The manufacturing sector contributes to the growth of the world economy in more than one way. It is one of the vital sectors where productivity and sustainability are driven by new trends and innovations in the market. While most of us are aware that the future trends include process automation, additive manufacturing, Industrial Internet of Things (IIoT) and artificial intelligence (AI), there are various other developments such as smart sensors, immersive technology machines that have surfaced after the pandemic. These new trends ensure that the work is carried out seamlessly without the help of human resources, which is crucial in these uncertain times.
During the pandemic, the manufacturing industry faced a lot of challenges such as human resource shortage, skill gap, and supply chain disruptions, among others. Even though COVID-19 pushed the progress of the manufacturing sector to a great extent, the silver lining in the grey clouds was the demand it created for finished products. Thus, the manufacturing industry is now working to adapt and introduce tech innovations so that there is minimum resource wastage and maximum gains through the creation of world-class products. Some of these important trends include:
Industrial automation
Automation may not be new, but with the introduction of robotic technology, it has become accessible, easy and economical. It has also mitigated and eliminated potential risks and dangers to human lives, thus making the production process safer. Simplifying several techniques such as material handling, assembly, and painting, automation is a crucial technology that will shape the manufacturing sector.
Moreover, labour is scarce due to frequent lockdowns and restrictions imposed due to the pandemic. Thus, automation makes the manufacturing process smoother, efficient and effective. It also maintains quality and consistency. At the same time, it generates a demand for new roles in manufacturing.
According to Industrial Automation Market Size, Share & Growth Report, 2021-2028, “the global industrial automation market is projected to rise from USD 191.74 billion in 2021 to USD 355.44 billion in 2028 at a CAGR of 9.2 per cent in the 2021-2028 period.”
Industrial Internet of Things (IIoT)
In recent times, IIoT, one of the key components of the Industry 4.0 technology cluster, has become more widespread in the industry. The Industrial Internet of Things focuses on providing additional capabilities at a lower cost by leveraging new technologies such as LTE, 5G, WiFi and other wireless connectivity technologies.
According to Gartner’s Strategic Planning Assumptions, only 10 percent used IIoT in 2020. Yet, the report suggests that the numbers are expected to rise to 50 per cent by 2025. Not only this, by 2025, 25 percent of large global industrial enterprises will either acquire or invest in the IIoT, 5 percent higher than it was in 2020.
The Industrial IoT helps to facilitate easy access to real-time data services, thus allowing connectivity of multiple systems present in an industrial process. The capability of IIoT in improving operational efficiency and safety opens the doors for further adoption of Internet of Things technology for various industrial processes. Considering how the pandemic has led to a surge in the integrated digital-human workforce, the development of industrial internet and its digital adoption are expected to pave the way for new opportunities.
Additive Manufacturing
In layman’s terms, additive manufacturing means 3D printing. This emerging technology allows firms to bring their designs to life. The market research firm Wohlers Associates, in its report -Wohlers Report 2021-stated that the additive manufacturing industry expanded by 7.5 per cent to nearly $12.8 billion in 2020. “Growth was down considerably, compared to average growth of 27.4 per cent over the previous 10 years,” the report noted.
Additive manufacturing has gained much momentum in the past few years, changing how manufacturers tackle their multiple challenges. For instance, during 2020, when the majority of the countries were reeling under severe pressure of COVID-19 cases, various universities, tech firms and 3D print enthusiasts came together and produced 3D printed PPE kits and other emergency items like valves.
Reports suggest that additive manufacturing reduces energy consumption by 25 per cent, cutting waste material and materials cost by up to 90 per cent, compared to the traditional method. Along with this, the method can improve productivity and improve design flexibility and production time.
Data Science
Big Data is changing the landscape of the manufacturing industry and data scientists are now considered the new factory employees. Manufacturing firms in different sectors are integrating data into their operations as it provides valuable insights aiming to maximise profits and minimise risk while evaluating the production process. In addition to this, it also helps in predictive maintenance, computer vision, sales forecasting and predicting quality.
● Predictive maintenance: Any production halt can cause a massive loss to the firm. Hence, data science allows real-time monitoring of all machines via sensors, which can be used to analyse to find the reason behind the machine failure. The same data can also predict the time to failure and optimal maintenance time prediction.
● Computer vision: Data science minimises any human involvement in identifying faulty or over-used parts in a computer system. Today’s AI technologies like CNN, RCNN, and Fast RCNN work more efficiently than humans while inspecting a computer system in less time. Hence, it significantly reduces time consumption and costs.
● Sales Forecast: In manufacturing, knowing futuristic trends gives a firm an extra edge over the market and profits. This is where data science comes in handy as it can predict future trends by analysing the previous data collected. Nowadays, firms use techniques ranging from ARIMA to LSTM to optimise their resources to use the data to generate profits and fulfil market demands.
● Predicting quality: With the help of statistical control, manufacturers can predict the quality of the products being produced at their factories.
Artificial Intelligence and Machine Learning
AI is the intelligence that has the potential to replicate cognitive capabilities that are linked with humans. While on the other hand, ML generally refers to the potentiality of a computer to learn or boost performance via examining and interpreting data. It can be said that ML plays a crucial role in both AI and data science. In AI, machine learning tools are used in real-time to allow machines in a factory to perform their functions. At the same time, ML in data science is used to analyse the collected data to unlock patterns and make futuristic predictions.
Moving away from the definitions and their roles, AI plays a significant role in the manufacturing industry. It helps in better product development, quality improvement and also leads to market adoption. It is essential to mention that while AI, ML, and data science sound similar, each has a different role and outcome in the industry.
Smart Devices
Smart devices lay the foundation of smart systems and smarter machines. These devices are the gateway to information a business needs to perform its tasks accurately and on time. This is why every industry is seeking more intelligent devices and products. It creates a mesh of information in an operational chain that multiple people can access from various points.
These state-of-the-art technologies and other smart devices might initially sound a bit expensive, but the outcomes it generates overcast the cost spent. It adds a layer of intelligent functionality around the existing operating model of a factory, establishing necessary communication, computation and control functions by networking with other smart devices present in the factory.
With the help of these smart devices, computers can collect data about the machine’s health, the quantity of the raw materials, the productivity of the workforce, and the production time. Once the data is collected, it can be used to make the right judgements at the right time, further leading to increased uptime, improved manufacturing agility, increased safety, and lower costs.
Finally, technology, innovation and digital adoption is the future of manufacturing. IoT and data science in the manufacturing industry needs more exploration. Keeping this in view, new applications are being discovered on a daily basis and various solutions are being invented. We will witness how these advancements will bring a new wave of change in the manufacturing industry in the coming times. It goes without saying that the manufacturing industry will need to grow at the same pace as technological improvements to make full use of the innovations.
