The past few years have been turbulent for the manufacturing industry. Global supply chain disruptions, major swings in customer demand, productivity stagnation and continuing inflationary pressure call for a considerable operational and capital cost reduction, forcing enterprises to rethink their manufacturing strategies. To address these issues, leaders across the manufacturing domain are looking for the right digital technologies and strategies, with a key focus on optimising employee productivity, safety and collaboration.
Companies are leveraging the fourth industrial revolution, or Industry 4.0, to achieve faster and more sustainable improvements, depicted by “lighthouse” manufacturers, which are leading the implementation of Industry 4.0. Lighthouses are factories that have taken Industry 4.0 from pilots to integration at scale, thus realising significant operational and financial benefits. As of November 2022, the World Economic Forum and McKinsey identified 114 sites around the world as lighthouses. This approach lets manufacturers look beyond productivity and focus on improving five areas of impact, including sustainability, agility, speed to market, customisation and customer satisfaction.
Other leading manufacturers are converging digital and physical worlds, wherein sophisticated hardware is combined with innovative software, sensors, big data and analytics to produce smarter products through more efficient processes and closely connected manufacturers, suppliers and customers.
A look at the key technologies dominating the manufacturing sector…
Robots and cobots
With industrial robots becoming more advanced and affordable, an increasing number of companies are beginning to integrate them with their workforce. Industrial robots have several applications in manufacturing due to their wide array of abilities. Typically, robots in this sector are used for pick and place, packaging and labelling, assembly and disassembly, product inspection and testing, painting and welding. Meanwhile, a collaborative robot, or cobot, is designed to carry out repetitive tasks, thus allowing human resources to focus on problem-solving and decision-making. Cobots are a highly preferred technology among manufacturers, owing to their precision, accuracy and ability to constantly perform monotonous tasks. As a result of the Covid-19 pandemic and social distancing norms in workplaces, the adoption of cobots on factory floors has soared. According to a report by ABI Research, a total of 45,000 cobots and 452,000 mobile robots are expected to be shipped in 2022, a 65 per cent and 51 per cent increase respectively from 2021.
Automation is not entirely new in manufacturing, but has now witnessed more widespread adoption. It is made possible with user-friendly robotics solutions, simple manufacturing process management systems, and human-robot collaboration. Robotic process automation (RPA) enables the automation of rule-based operations to improve process execution speed and accuracy. It helps execute different processes such as inventory management, regulatory compliance, purchase order processing, invoice verification, and customer service. The automation of such processes helps organisations shift their focus from repetitive tasks towards growth and quality improvements. The key benefits of implementing RPA in a manufacturing set-up include up to 40 per cent reduction in opex, increased control over processes, error-free and consistent results, optimised employee performance, significantly lower downtime, and identification of anomalies. Further, RPA solutions are easy to implement and do not require coding. It can also be seamlessly integrated with existing legacy systems at a low cost.
Internet of things (IoT) enables manufacturers to connect with and monitor various components of their operations. IoT can be used to create networked devices and machines, which can generate valuable manufacturing data. The data and insights will allow manufacturers to alter, optimise, or improve every facet of the manufacturing process. According to a PwC survey, over 70 per cent of industrial manufacturers are testing or building IoT solutions in their projects.
IoT minimises the need for manual intervention, which helps save labour costs and eliminates the risk of human error. Further, IoT enables manufacturers to speed up response time to factory issues; optimise efficiency, safety and cost-cutting; track and collect machine data to create a database; and make informed and strategic decisions using real-time data. It makes inventory management a seamless process with radio frequency identification (RFID). Items in the inventory get RFID tags, and each tag has a unique identification number comprising encoded digital information about the item. RFID readers can scan the tags and the data is then transmitted to the cloud for processing. In addition, IoT has introduced smart meters that can monitor the consumption of water, electric power and other fuels.
Artificial intelligence (AI) enables process plants to integrate and analyse data and produce insights and predictions that help drive informed decision-making. Machine learning (ML) is a subfield of AI that crunches huge data sets to spot patterns and trends. It uses the results to build models to forecast demand and supply trends, estimate the most optimal intervals for maintenance scheduling, and indicate early signs of anomalies. AI and ML can help boost various aspects of manufacturing operations, including inventory management, supply chain visibility, warehouse cost reduction, asset tracking, and transportation cost reduction.
AI systems also power predictive analytics, which helps address operational challenges and disruptions in supply chains as well as the workforce. A McKinsey report reveals that AI can enhance forecasting accuracy in manufacturing by 10-20 per cent, which translates into a 5 per cent reduction in inventory costs and a 2-3 per cent increase in revenues.
Enterprise resource planning (ERP) technology has existed in the manufacturing sector for years but is being used widely with the availability of cloud-based software-as-a-service (SaaS) options. These SaaS solutions are easy to deploy and more affordable for small businesses. ERP allows users to collect, store, manage and interpret data while tracking business resources and keeping track of all points of the supply chain.
ERP systems enable manufacturers to automate various operation areas under a single comprehensive system. This universal touchpoint allows them to oversee the entire manufacturing operation and make improvements and adjustments as required.
3D printing, technically referred to as additive manufacturing, creates 3D objects by successive layering material using a digital file containing a computer-aided design drawing. 3D printing uses fewer materials and creates less waste than traditional manufacturing methods. It has seen rapid uptake across a range of products in manufacturing, from small items such as cutlery to far more complex fields such as healthcare. Moreover, 3D printers are becoming more accessible with an increasing number of local service providers offering outsourcing services for manufacturing. A potential advantage of the technology is mass customisation. For instance, it allows the manufacturing of made-to-measure prostheses or tools in the healthcare industry. 3D printing will also drive a high degree of personalisation as individual products can be made without concerns about economies of scale. It will also spur innovation by allowing rapid prototyping. Airbus, for instance, has been using 3D printing for over 15 years. The company uses the technology extensively for localised on-demand production of tools, such as jigs and fixtures.
Driven by IoT, AI and ML, predictive maintenance is a proactive maintenance approach that helps manufacturers detect potential equipment issues and failure patterns before they lead to machinery breakdown. It uses real-time data collection and historical analysis in areas such as vibration detection and ultrasonic monitoring to provide unprecedented insights into equipment operations. Incorporating the technology into manufacturing processes can save on maintenance costs and reduce downtime while extending the life of machinery. IoT-powered predictive maintenance allows manufacturers to devise performance metrics, monitor equipment performance from afar and automate data collection processes. According to McKinsey, predictive maintenance programs will reduce costs by about 20 per cent for maintenance and cut unplanned machine outages by 50 per cent. Meanwhile, a report by Deloitte states that on average, predictive maintenance increases productivity by 25 per cent, reduces breakdowns by 70 per cent, and lowers maintenance costs by 25 per cent.
Augmented reality (AR) has various use cases in manufacturing. It helps identify unsafe working conditions and envision a finished product. Manufacturers can monitor activities in the factory, the location of workers and any breakdowns in machinery. AR also helps sales representatives to present images of products, prototypes, catalogues and diagrams to customers. The technology allows for the replication of holograms along with animated 3D elements, text, video and images. It can also be used to train and protect employees at all times without wasting resources.
The way forward
Enterprises are collaborating in hyperconnected value networks, using new-age technologies to enhance productivity, develop new customer experiences and improve their environmental impact. As the global market and industry dynamics push manufacturers to reconsider their strategies, smart manufacturing powered by IoT-driven data and analytics will drive the sector in the coming years.