There’s no question that digital transformation is at the heart of the future of manufacturing. But what exactly makes a factory ‘smart’, and what are the technologies that will drive this digital revolution? In a nutshell, smart factories are manufacturing facilities that rely heavily on digital technologies to improve efficiency and productivity. This means incorporating 3D printers, cobots, 5G, artificial intelligence, SERP, cloud computing, edge computing, and more into the manufacturing process.
With so many cutting-edge technologies at play, smart factories are able to operate at a level of speed, precision and flexibility that traditional factories simply can’t match. And as the world increasingly relies on digital manufacturing processes, smart factories are only going to become more prevalent – and more important.
There is certainly no one ‘silver bullet’ when it comes to creating a smart factory. Rather, it is a myriad of emerging technologies coming together to take manufacturing into a new era. Here, we highlight some of the key tech that will be integral to achieving this vision, but it’s first worth highlighting the power behind these technologies, the fuel that’s driving them; quite simply, data.
The last decade has seen a meteoric rise in the amount of technology and connected devices deployed within the UK manufacturing space. And, as machines and industrial processes have become more complex, sophisticated and connected, the volume of data they are generating has skyrocketed.
This increase in data granularity means that manufacturers have greater visibility than ever before into their products, processes and systems with unprecedented opportunities to create insights to drive the business forward and guard against future disruption and challenges.
However, there has been a sense of not seeing the wood for the trees. The sheer volume of data being generated means that manufacturers are facing growing challenges, not only around data storage and collection, but in how to extract meaningful insights from the data that they have; after all, data is not like oil – it has no value if it’s not being used.
There is also additional problems being thrown up around data security, governance, skills and integration. For many manufacturers of course, this is all new territory. In generations gone by, there was little or no data being generated within many organisations, let alone a requirement for the skills needed to create value from it.
As such, many manufacturers are in need of help and guidance around what to do with their data, to say nothing of the fact that many are still juggling digital transformation strategies alongside the management and integration of legacy equipment.
However, there is no questioning the value and potential of the data that is now at manufacturers’ finger tips. Here are some of the technologies that stand to benefit.
| 3D printing | Enterprise resource planning (ERP) |
| Robotics | Manufacturing execution systems (MES) |
| Cobots | Cloud computing |
| 5G | Edge computing |
| Artificial intelligence (AI) | Digital twins |
| Machine Learning (ML) | Virtual reality (VR) |
| IIoT | Augmented reality (AR) |
| SERP | Cyber security |
3D printing
A smart factory wouldn’t be complete without a few 3D printers. These versatile machines can create parts and products from scratch, using digital designs as a guide. And because they can produce items on-demand, they’re perfect for prototyping, small batch manufacturing or even custom orders.
3D printing, or additive manufacturing to give the technology its proper title, is creating a whole new world for design engineers. Ideal for rapidly creating functional prototypes and end-use parts that are high in detail, it has opened the door to complex geometries that are impossible via any other means.
Far from a one-size-fits-all technology there are a variety of processes, techniques and materials used in 3D printing, including stereolithography, selective laser sintering, multi-jet fusion, polyjet, fused deposition modelling (FDM), vacuum casting and direct metal laser sintering, which can all be used to quickly build parts in a range of plastics and metals.
3D printing can help reinvent manufacturing and the future of design. In the modern world customers are demanding far greater levels of personalisation and customisation of products, and as such, 3D printing can be a differentiator in how manufacturers plan their supply chain strategies. Why stock a complete assembly of parts in high quantities when you have the capability to quickly print the exact part required on-demand, which will reduce the need for spares?
Robotics
It’s predicted that by 2030, over 85 million positions will be unfilled in the UK, hampering economic growth and presenting challenges for organisations to find new ways to plug gaps in workforces. Other economic factors like Brexit, component shortages, supply chain disruptions and the legacy effects of the COVID-19 pandemic are exacerbating the problems. This is bringing into sharp focus the need for industry in the UK to embrace robotics and automation.
Robotics provides the means to transform the productivity and global competitiveness of UK manufacturing, but only if long-standing barriers to adoption are finally overcome. And, when it comes to the roll out of robotics, the UK has some catching up to do compared to other nations.
However, far from stifling innovation and setting back forward-thinking strategies, the tumultuous events of the last 18 months have in fact accelerated the roll out of new technology, and 81% of manufacturers are now considering investing in robotics.
As the benefits of automation become even more ubiquitous and UK manufacturers better prepare themselves against future uncertainties, it must also be acknowledged that the UK will be starting from a few rows back on the grid, currently sitting some way behind other nations when it comes to robotic roll outs.
The UK currently ranks 24th in the world when it comes to the number of robots installed per 10,000 employees, with a density of 101 units – the only G7 country with a robot density below the global average (incidentally the country in first place, South Korea, has 932).
Cobots
Collaborative robots, or cobots, are another key component of smart factories. These physically versatile machines are designed to work alongside humans, making them ideal for tasks such as packaging and assembly. And thanks to their user-friendly interfaces, cobots can be easily trained to perform new tasks as needed.
The UK has traditionally been slow on the uptake when it comes to robotics, however, running as a parallel stream of automation, cobots are experiencing fast growth, particularly within the SME sector which has the greatest opportunity for transformation.
Unlike traditional robotics, cobots can be deployed within a matter of weeks, and therefore can quickly save money. Other advantages of cobots for manufacturers is that they are easy to setup and programme, and flexible enough to be moved around the factory.
Cobots have the potential to take over 3D jobs – dirty, dangerous and dull – many of which are still performed by humans. By working with cobots, employees can then focus their time on more fulfilling roles, and reduce their time spent on mundane tasks, improving overall wellbeing. This includes getting rid of the night shift, known to have an adverse effect on the health of workers.
5G
5G is the next generation of wireless technology, and it’s set to revolutionise manufacturing. That’s because smart factories rely heavily on data, and 5G will provide the high-speed, low-latency connections that are needed to transmit large amounts of that data quickly and efficiently.
5G can provide the means to tackle the manufacturing sector’s greatest challenges, from achieving net zero and attracting future talent to maximising uptime and accelerating product development.
Offering almost limitless capability, the next generation of mobile connectivity has the potential to revolutionise every phase of a manufacturing operation, and with so many prospective applications, manufacturing is one of the sectors expected to benefit most from 5G’s arrival.
5G is around ten times faster than 4G, with peak speeds capable of reaching above 1gbps (gigabit per second). And, unlike previous generations, 5G isn’t simply an upgraded communication network. It has been built from the ground up to deliver better user experiences, empower new deployment models and deliver new services.
Artificial intelligence (AI)
Artificial intelligence (AI) is another area where smart factories are leading the way. AI can be used for tasks like predictive maintenance, quality control and material handling. And as AI technology continues to evolve, smart factories will only become more efficient and effective.
The AI utopia will see combinations of data collected from sensors, machines and people and then applied to algorithms designed to optimise operations or achieve lights out manufacturing. While we are some way off achieving that scenario there are many other use cases where manufacturers are adopting AI quickly and across the entire value chain of the industry.
Use cases exist around workplace safety, machine/building management, machine vision and cyber security. Combining AI/ML with other technologies such as sensors, machines and human inputs will dramatically improve operations and likely lead to new forms of innovation and productivity in the industry.
Machine learning (ML)
Machine learning refers to a method of data analysis that enables computer programs to grow and learn by studying predictive and statistical analytics, rather than by being explicitly programmed.
In the manufacturing industry, machine learning (ML) is a critical subset of artificial intelligence (AI), and involves the use of sophisticated algorithms to learn from and make predictions based on data.
These technologies can analyse vast amounts of production data to identify patterns, optimise workflows and predict equipment failures. For example, ML algorithms can continuously monitor machinery performance, detecting subtle anomalies that may indicate future breakdowns, thus enabling predictive maintenance.
Additionally, ML can be used to refine production schedules in real-time based on demand forecasts and resource availability, ensuring maximum efficiency and minimal downtime. By integrating AI and ML, manufacturers can enhance quality control, streamline supply chains and drive overall operational excellence.
This type of AI is similar to that of data mining as it involves the process of searching through data to look for patterns. However, in the case of machine learning, the computer program uses the data to adjust its own actions accordingly, therefore reducing the need for human intervention.
Machine learning and predictive data analytics have the potential to improve yield rates for manufacturers at the machine, production cell and plant level and it is now within the grasp of every manufacturer to assimilate machine learning into their operations and become more competitive by gaining predictive insights into production.
IIoT
The Industrial Internet of Things, more commonly referred to as the IIoT, is the use of smart sensors, actuators and other devices, to enhance manufacturing and industrial processes. These devices are networked together to provide data collection, exchange and analysis. Insights gained from this process aid in more efficiency and reliability.
IIoT uses the power of smart machines and real-time analytics to take advantage of the data that machines have produced in industrial settings for years. The driving philosophy behind IIoT is that smart machines aren’t only better than humans at capturing and analysing data in real-time, but they’re also better at communicating important information that can be used to drive business decisions faster and more accurately.
Connected sensors and actuators enable companies to pick up on inefficiencies and problems sooner, saving time and money while also supporting business intelligence efforts. In manufacturing specifically, IIoT has the potential to provide quality control, sustainable and green practices, supply chain traceability and overall supply chain efficiency. In an industrial setting, IIoT is key to processes such as predictive maintenance, enhanced field service, energy management and asset tracking.
The IIoT has the power to change and enable processes from raw materials and the supply chain all the way through to the final product, and sometimes even on into a deeper relationship with the product’s use and direct consumer engagement.
SERP
Smart factory floors are often equipped with SERP systems, which stands for ‘self-healing error-proofing’. These systems use sensors to detect errors in real-time, then take corrective action to prevent them from happening again. This helps to reduce waste, improve quality and keep production lines running smoothly.
Enterprise resource planning (ERP)
ERP can be a game-changer in a sector such as manufacturing where efficiency is king. ERP acts as a centralised method of managing every aspect of facility operations and processes and allows for unprecedented visibility, coordination and management across the disparate processes that make up a manufacturing business — ultimately resulting in greater operational efficiency.
Given the numerous processes that must occur every day just to keep a facility running, ERP and manufacturing are natural bedfellows. Not only can ERP aid inventory management, supply chain, maintenance and quality assurance, it also enables these processes to talk to each other.
Manufacturing execution systems (MES)
Even today manufacturing businesses typically have low levels of integration between office information technology (IT) and operations technology such as automation systems on the shop floor (OT). Manufacturing execution systems (MES) provide the meeting point for their convergence.
While ERP is the business system, offering the big picture view and used predominantly by office workers, MES is the manufacturing system, carrying detailed production information and is used by factory workers. MES is user-friendly, fast and many of the processes are automated.
MES unite quality, production, maintenance and inventory operations under one umbrella and has the capability to dramatically change manufacturing operations by reducing spoilage rates and waste, increasing uptime and productivity, and making non-value added manpower a thing of the past.
A valuable first step on any digital transformation journey is to connect measurement systems, quality data, machines, sensors and PLCs to a centralised MES, and utilise it to tag critical assets and track their usage.
Cloud computing
Cloud computing is a must for smart factories and digital transformation. That’s because cloud-based systems offer the scalability and flexibility that smart factories need to stay agile. Plus, they can help to reduce costs by eliminating the need for on-site hardware and software.
By delivering computing services such as servers, storage, databases, networking, software, analytics and intelligence over the internet (or cloud), manufacturers can achieve faster innovation, flexible resources and economies of scale. Cloud services typically operate a pay as you use model, helping companies to lower operating costs, run infrastructure more efficiently, and scale as business needs change.
As well as cost and speed, other advantages of cloud services include being able to deliver the right amount of IT resources when they are needed, and from the right geographic location; eliminating the need for complex on-site infrastructure such as ‘racking and stacking’, hardware setup, software patching, and other time-consuming IT management chores; and of course, increased reliability and security. In addition, many cloud computing services run on a worldwide network of secure data centres, which are regularly upgraded to the latest generation of fast and efficient computing hardware.
Edge computing
Edge computing systems are designed to process data locally, rather than sending it to the cloud, bringing enterprise applications closer to data sources such as IoT devices or local edge servers.
This helps to improve response times and reduce latency, which is critical for manufacturing applications. This proximity to data at its source can deliver strong digital transformation benefits such as faster insights, improved response times and better bandwidth availability.
Fundamentally, data is processed and analysed closer to the point where it’s created. Edge computing can help unlock the potential of the vast amounts of data being created by evermore powerful connected devices. This increased analytics capability in edge devices can power innovation to improve quality and enhance value, plus provide deep insights and predictive analysis in near-real-time.
Digital twins
A digital twin is essentially an assistance system for production facilities which uses integrated simulation models to find solutions quickly when problems arise. These simulations give operators a glimpse into the heart of physical assets to determine ideal operational workflows, drawing on current data flows to swiftly find clear options to help the system operators reach a decision; without the time and cost that would be involved in testing theories in the real world.
These highly complex virtual models act as an exact counterpart (or twin) of a physical ‘thing’. Connected sensors on the physical asset collect data that can be mapped onto the virtual model. Operators looking at the digital twin can see crucial information about how the physical version is performing in the real world.
Digital twins are vital tools to help engineers and operators understand not only how products are performing, but how they will perform in the future. Analysis of the data from the connected sensors, combined with other sources of information, allows accurate predictions to be made.
Virtual reality (VR)
From product development to production implementation, through to training and customer support, the opportunities opened up by VR are enabling organisations to drastically enhance their manufacturing capabilities and performance.
Accelerated following the pandemic, VR is a key tool within the manufacturing arena, providing more focused and impactful training as the technology enables apprentices to better retain information, compared to traditional training methods.
It also helps to improve cross-division communication between design, engineering and sales and marketing, and can also avoid costly mistakes by communicating design changes to identify costly issues pre-assembly. Not only does VR reduce the number of physical prototypes that are needed, which results in a quicker time to market, but also allows for additional time for design refinement on the project.
Viewing an object at its true scale is the best way to review large structures as imagery and animation will never tell the true story of proportions on transport, construction or architecture. VR provides those reviewing a model with more confidence and improved decision making.
A well deployed VR solution enables multiple users, in multiple locations, to experience the same scene at the same time, complete with avatars of each other. This saves money on travelling for on-site design reviews or costly prototype transportation for physical reviews.
Augmented reality (AR)
Augmented reality (AR) is one of the most exciting and impactful technologies making its way into today’s manufacturing industries. Because AR applications work on a multitude of devices tailored to almost any environmental situation, AR is no longer a restricted technology, or a tradeshow gimmick.
Unlike VR, which creates a fully virtual environment around its users, AR creates an illusion, as if virtual objects coexisted within the physical world. Simply put, AR is a means to present operational information in a completely new way – enveloped in a person’s view of their real environment and acting as the perfect ‘digital assistant’.
AR makes that digital assistance interactive, more practical to absorb, understand and act upon, because it relies on our innate mental capacity to process a huge variety of information from the physical world.
Despite some challenges, the first industrial AR applications on mobile devices are increasingly shifting to hands-free wearables such as head-mounted displays or smart glasses.
Enhanced mobile broadband (eMBB) will become available, in an incremental fashion, over the next few years. It will increase bandwidth by an order of magnitude over 4G, further facilitating the adoption of high-definition (HD) video-streaming and AR. Ultra-reliable low-latency communication (URLLC) will reduce the achievable latency and enhance the reliability of communication.
Cyber security
The drive towards a more digital future is key to the prosperity of manufacturing. However, digital transformation heralds a new era of connectivity which brings with it rising levels of cyber vulnerability. Indeed, 2021 saw manufacturing overtake financial services as the most cyber attacked industry.
Connectivity is taking manufacturing to the next level, helping to provide greater efficiency, visibility and productivity. However, each connected device represents a vulnerability and a potential avenue of attack for malicious actors with mischief in mind or devious designs on data.
Unlike the consumer space, manufacturing, a sector that is still in the relative early stages of digital transformation, is perhaps not fully aware of the dangers that can be ushered through the doors of a plant or factory with the deployment of emerging, digital, connected technology. To say nothing of the growing sophistication of the various threat actors at large.
There’s no doubt that smart factories, driven by technology, are the future of manufacturing and will lead to the creation of a hyperconnected supply chain that offers a digital thread throughout the business and a real-time view of product lifecycles.
However, before manufacturers get too excited about digital transformation, it is vital that the cyber risks involved are known and understood. The risks involved for manufacturers, and the consequences of a ‘it won’t happen to me’ approach, needs to be understood and taken seriously within the sector.
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