Transitioning to Smart Manufacturing – A Practical and Cost-Effective Approach
The business case for implementing smart factory technologies is compelling, with tangible improvements in revenue, output, quality, and safety, alongside reduced costs. It is not surprising, therefore, that smart manufacturing technologies are becoming an increasingly important competition driver.
The technologies that are part of the Smart Factory include cloud computing, edge computing, vision systems, robotic process automation, predictive analytics, machine learning, artificial intelligence, big data, and industrial internet of things, as well as augmented, virtual, and mixed reality.
Each one individually has significant potential and creates opportunities for your business. When combined, the benefits increase considerably.
Implementing smart manufacturing solutions is not without risk, however, so where do you start? If you’ve already started, where do you go next? What are the practicalities of making the transition to smart manufacturing?
Important Practicalities to Consider
There are some important practical considerations to think about before embarking on major smart manufacturing projects. Many of these considerations relate to change management and include ensuring there is senior leadership buy-in, sufficient skills available for the initiative, and support for those involved.
Other considerations include the divide that sometimes exists in many manufacturing organisations between IT and OT. The success of smart manufacturing initiatives often hinges on these critical business functions working together.
Two other important considerations are worth mentioning:
- Integration – you will have different machines, equipment, devices, sensors, platforms, and systems that make up your manufacturing operations and supply chain management processes. The integration of these various technologies and machines is an important step.
- Connectivity – connectivity and the transfer of data are crucial to the implementation of smart manufacturing solutions, so it is essential to have a robust IT infrastructure to provide the required level of connectivity.
Finally, it is important to focus on business value when deciding on strategies and implementing smart manufacturing solutions. Without a proper focus on business value, improvements can be made in specific areas, but the benefits won’t extend much further. The best approach is to look at the overall objectives of the business to decide on the smart manufacturing technologies that offer the most value.
Progressing Towards a Smart Manufacturing Approach
You need to move to the next stage of your smart manufacturing journey, but what should you do first? How do you ensure you don’t take missteps? How do you progress without diverting significant resources? Can you get a short-term and medium-term return on investment as well as a long-term return?
Let’s look at three key strategies:
- Trial projects
- Structured incremental implementation
- Simulation tools
A combination of the three, depending on the status of your existing operations, is often the best approach to keep costs under control, maximise return on investment, and ensure the transition is as smooth as possible, particularly in relation to product output and customer impact.
Trial projects can be a useful approach in a wide range of situations, not just at the start of your Smart Manufacturing journey. With a trial project, you can ringfence costs and structure the work parameters as tightly as you want.
This will let you identify risks and areas for improvement, and it will demonstrate where you may encounter resistance, bottlenecks, or barriers when you start to scale up.
In addition, a trial project will give you a better indication of the real return on investment you can achieve from transitioning to Smart Manufacturing.
Structured Incremental Approach
Whether you go with the trial project option or not, adopting a structured, incremental approach is almost always the best option.
How far you go and how quickly depends on your current circumstances and immediate plans. For example, it might save you in the long run if you increase the scale of a project if it requires a considerable investment in new equipment.
It’s important you don’t go too far too fast, however. Upgrading all your legacy systems in a short period of time is rarely the best option, for example. Rather than a big bang investment, the more successful approach is usually a carefully planned evolution.
The most obvious reason for this is the fact it might not be practical, for financial or other business reasons, to upgrade all legacy systems in a short space of time. Furthermore, it might not even be necessary, i.e., you might not need to upgrade all your legacy systems to achieve your Smart Manufacturing goals.
It is also possible to explore and analyse the implementation of Smart Manufacturing processes and technologies in your facility using simulation tools. One of the most effective is using digital twins.
By creating digital twins of your current equipment and processes, you can model various options and scenarios to identify the best approach, helping you decide on the next Smart Factory steps to take.
Starting and Continuing the Transition
Smart Manufacturing may be a buzzword, but the technologies involved are driving transformational change in manufacturing companies in all sectors, including the life sciences sector. Companies that take a strategic approach and continuously improve their operations with new smart factory initiatives will be best placed to respond to the needs of the market today and in the future.
The Business Case for Smart Manufacturing
Advances in Smart Manufacturing technologies are changing the manufacturing sector forever. However, those technologies don’t change your core priorities and goals.
New technologies or not, you still need to deliver high-quality products that your customers need and want, plus you must maximise competitiveness, productivity, and profitability.
Marrying up a transition to Smart Manufacturing with your goals and priorities is not always easy.
We have looked at specific, practical, and cost-effective approaches to implementing Smart Manufacturing solutions and moving your production lines forward in other blog posts. A good starting point, though, is to consider the business case for doing so.
Of course, you will probably need to develop a specific business case for your facility. However, buying into the high-level pitch for Smart Manufacturing is an important first step.
Smart Manufacturing – The Business Case
The reality is the technologies that make smart manufacturing possible will have an impact on your business. This impact applies however quickly you proceed and how far down the Smart Manufacturing route you go in the near term.
Even if you do nothing regarding the implementation of Smart Manufacturing technologies in your facility over the next 12-24 months, by not moving forward, you risk falling behind or missing opportunities that could be beneficial to your business.
Why? Many of the challenges and opportunities that are becoming more important to the manufacturing sector are being driven by market trends, advances made by your competitors, regulatory requirements, and changing consumer behaviour and expectations.
Here are two examples by way of illustration:
Smart manufacturing technologies make it possible for manufacturers to move towards the mass customisation of products. This mass customisation trend will change the offering that is available to the consumers and users of the products you produce. In fact, marketplace expectations are already changing.
While industries like pharmaceutical and medical device manufacturing are not as far advanced as other industries, the direction of travel is firmly towards mass customisation. Manufacturing flexibility is increasingly important too.
New Product Introductions
The practical and regulatory requirements for introducing a new product on the market are as complex today as they have ever been. However, Smart Manufacturing technologies throw an important consideration into the mix.
Specifically, Smart Manufacturing technologies streamline and automate many NPI processes. Therefore, organisations that embrace Smart Manufacturing solutions will introduce new products faster while maintaining compliance and quality standards. This reduced NPI timescale greatly enhances competitiveness.
The Sooner the Better
The above are just two examples of the many ways that Smart Manufacturing can (and is) impacting your business. So, the summary is the sooner you get started with implementing Smart Manufacturing solutions, the better.
How you do that will depend on your business. The process requires a detailed assessment of the readiness of your organisation, as well as an analysis of where first to target Smart Manufacturing solutions with a focus on maximising improvements, delivering a healthy return on investment, and ensuring scalability for the future.
Benefits of Smart Manufacturing
- Improvements in OEE – overall equipment effectiveness.
- Increased efficiency, but not just in the operation of machines and equipment. Smart Manufacturing technologies also enable the more efficient use of resources, as well as delivering material efficiency benefits and helping make your operations more energy efficient.
- Reducing both planned and unplanned downtime through digital twin technologies, machine learning, and predictive analytics.
- Improved quality control.
- Opening up the potential of new business opportunities with the introduction of new product lines, mass customisation strategies, and more.
- More effective and efficient regulatory compliance processes.
- Increased output that will improve revenues and profits while also delivering capital expenditure avoidance.
- Improved customer satisfaction by consistently and reliably delivering high-quality products, in addition to responding quickly to queries and complaints.
- Building a closer direct connection with your customers.
- Increasing the variety of products that you can produce on a single production line.
- Overall improvements in productivity.
- Enhanced insight at all levels of the business, from supply chain management to how customers use products to predicting future market demands.
Drivers for Transitioning to a Smart Factory
When making a business case for Smart Manufacturing, it also helps to understand the drivers of change. Some of the most important of these drivers include:
- Customer demand and expectations – these constantly evolve, with one major current trend being mass customisation. Market factors that increase or decrease demand unexpectedly and/or in short periods of time are also factors.
- Agility and flexibility – i.e., ensuring your business is in a position to take advantage of the new opportunities that Industry 4.0 and Smart Manufacturing technologies present.
- Productivity and improving OEE – the constant push to improve performance and efficiency, particularly in the face of increasing demands.
- Availability of skills and resources – many businesses in a range of industries struggle to recruit and retain the operatives and technicians they need, so they are looking to technology as the solution.
- Compliance – additional compliance requirements on manufacturers, particularly in highly regulated sectors like pharmaceuticals and medical device manufacturing, results in a push for innovative solutions. Some of this comes from regulators, but manufacturers striving to keep compliance costs under control are also a factor.
- Business opportunities – Smart Manufacturing technologies have the potential to transform businesses, creating opportunities in new markets, product development opportunities, business model innovation, and more.
- Sustainability – sustainability is increasingly important in all businesses. Smart Manufacturing technologies can increase energy efficiency and reduce waste across the entire product lifecycle.
Getting Started with Smart Manufacturing
The business case for Smart Manufacturing is strong, although the way it is presented and tailored will differ depending on your organisation. To move to the next stage, find out more about the practical and cost-effective ways to transition your current facility using Smart Manufacturing processes, methods, and technologies.
Infographic: Computer System Validation Vs. Computer Software Assurance
The FDA (US Food and Drug Administration) is due to release guidance on Computer Software Assurance. That guidance aims to put critical thinking at the centre of Computer System Validation (CSV) processes.
In our latest infographic, we highlight the main differences between traditional CSV and the new Computer Software Assurace (CSA) approach.
- Perceived as a barrier to automated solutions and innovation
- All software validated as if it’s product software
- The primary focus is securing evidence for auditors
- Duplication of vendor documentation and effort
- High occurrence of deviations due to tester error
New Computer Software Assurance
- A more flexible, less burdensome, and faster risk-based approach
- Various assurance approaches depending on the system/feature risk
- Apply critical thinking to ensure the software is safe and meet its intended use
- Reduced testing activities resulting from better supplier qualification and collaboration
- Reduced number of deviations due to tester error
Is Your Company Ready for the FDA’s Upcoming Guidance on Computer Software Assurance?
Technology and computerised systems have evolved greatly over the past 20 years. In that time, cloud computing has become mainstream, and big data is here. When you also add the fourth industrial revolution (Industry 4.0), it’s clear that new manufacturing and business technologies will be truly transformative in the coming years.
Yet, in the Life Sciences industry, the uptake of new automated solutions and technologies has been slow relative to other manufacturing industries. It is a trend that regulators have been seeking to fix.
The FDA’s Case for Quality initiative was set up to promote industry collaboration and encourage innovation, automation, and digital technologies. By working with those in the industry, the FDA was able to identify best practices and learn the barriers that exist for manufacturers.
It quickly became apparent that CSV, as it is applied today, is perceived as a barrier to technology implementation, where companies produce excessive, non-value-adding documentation that is driving longer validation cycles and increasing expenses.
Manufacturers are reluctant to invest in highly automated technologies as the validation cost is so high. It has become clear that the approach to validating such computer systems has not kept pace with technology advancements.
Enter Computer Software Assurance (CSA), the FDA’s upcoming guidance that aims to place critical thinking at the centre of the CSV process.
What is CSA?
Computer Software Assurance is a risk-based approach to computerised systems that is product quality-focused and patient-centric. It encourages critical thinking based on product knowledge.
The FDA, recognising that CSV has become a barrier to technology, is releasing the new guidance to tackle the issues faced by manufacturers, while also offering greater flexibility in achieving software assurance.
The guidance highlights new ways of approaching non-product software, i.e., QMS, ERP, PLM, MES, LIMS, etc. It states that assurance activities should be value-driven, patient-focused, and streamlined using existing technologies such as automated testing tools.
Here are some areas that the new guideline seeks to address.
A risk-based approach to validation is not a new concept. However, regulated companies have struggled with balancing the overall validation effort based on the software risks identified. As a result, companies fall into the trap of applying a one-size-fits-all CSV approach, where lower-risk systems are evaluated to the same scrutiny as high-risk systems. This approach produces a burdensome level of documentation, drives longer validation cycles, and increases expenditure.
The new guidance advocates a risk-based validation approach and also switches the focus from validation to assurance.
How will this affect you? One of the main areas is that there will be a significantly reduced validation requirement for software applications that have no direct impact on product quality or safety. In this situation, the recommendation from the FDA is to use current processes like the qualification of suppliers, as well as risk-mitigating process controls.
Even with an audited or trusted vendor, regulated companies still tend to reproduce documentation and test out-of-the-box software functionality that has already been tested by the vendor. Under the new guidance, if a vendor’s documentation is deemed to be of good quality, efforts should focus on ensuring the software meets its intended use rather than reproducing documentation for the sake of audit readiness.
With traditional CSV, regulated industries have adopted a conservative approach to testing, where too much focus is on documentation, manual testing, and evidence gathering. It is common to see this robust and scripted test approach applied to every system and function, regardless of its associated risk classification.
There is more flexibility with the assurance approach that CSA facilitates, as well as flexibility with acceptable records of results. There is also the introduction of the terms Scripted, Unscripted, and Ad Hoc Testing.
Scripted testing is widely used today in traditional CSV. It contains test objectives, step-by-step test procedures, expected results, independent review, and approval. CSA guides companies to continue using Scripted testing but only for high-risk features of a system that directly impact the product or patient safety.
An Unscripted test is testing without detailed instructions but with a clear objective and pass/fail criteria. Unscripted testing is to be used to test lower risk features of a system. Importantly, Unscripted testing still means you have to test, and details of test failures should be recorded as normal.
Ad Hoc Testing
Ad Hoc testing is similar to Unscripted Testing but does not require pre-approved protocols. This assurance approach may be in the form of exploratory testing, and it is considered the least-burdensome assurance option. It should be used for low-risk systems.
Efficiency Savings that Will Increase Innovation
By applying critical thinking and a risk-based approach, these assurance processes can be easily implemented on a feature-by-feature basis, as shown by the simple example illustrated below.
Unscripted and Ad-Hoc testing are seen as the right level of documentation for medium to low-risk features. CSA will consider these approaches to be an acceptable record or results. It is expected this new approach will result in a 30 – 50% reduction in time and costs, so it will therefore increase and accelerate innovation.
Preparing for CSA
The new CSA guidance is expected to be released in the coming months. The FDA has stated that companies can (and should) proactively take these principles into consideration. The recommendation is to create a transition plan and to pilot new methodologies on a subgroup of systems before rolling out to your entire organisation.
For some companies, moving to CSA will be a cultural shift compared to the current way of doing things. It is therefore critical the quality leadership team embrace CSA to enable its adoption throughout the organisation.
Now is also the perfect time to leverage automated testing and continuous data monitoring tools to streamline assurance activities that the new guidance supports.
Digital transformation is gathering pace in the life sciences industry due to Industry 4.0. The COVID-19 crisis is also spurring on innovation.
Traditional CSV practices are no longer compatible with emerging automation and digital technology solutions. It is time to implement a streamlined validation approach based on critical thinking that will support Industry 4.0 and will ultimately drive better patient outcomes and faster time to market.
How Industry 4.0 Supports Flexibility and Mass Customisation
“Any customer can have a car painted any colour that he wants so long as it is black.”
That’s a quote from Henry Ford, the founder of the Ford Motor Company. It’s a famous quote, but what does it have to do with flexible manufacturing and mass customisation? Does it have any relevance in the era of Industry 4.0 as we look towards the next industrial revolution, Industry 5.0? Is there anything we can learn from an idea that appears so outdated?
According to his autobiography, Ford made the famous comment in a meeting with his team in 1909. The comment was part of an announcement that the Ford Motor Company would, from then on, only be making one model of car – the Model T.
Ford’s thinking at the time was clear. In another part of his autobiography, Ford writes:
“No business can improve unless it pays the closest possible attention to complaints and suggestions. If there is any defect in service then that must be instantly and rigorously investigated, but when the suggestion is only as to style, one has to make sure whether it is not merely a personal whim that is being voiced.”
So, Ford’s approach was to get the design of the product right and then manufacture that product and that product alone at a massive scale.
It was a successful approach, too. When he made the famous “any colour so long as it’s black” quote, Ford was producing just over 10,000 cars a year. Ten years later, the company had produced half-a-million Model T Fords, and five years after that, it was producing two million.
100+ Years On
Industry 4.0 technologies are changing the reality from Ford’s era unlike any other technologies that have come before. Today, for example, it is now possible to meet the demands of customers for product customisation while also getting the design right.
In the life sciences sector, that means customised medicines, therapies, and medical devices that meet quality standards and regulatory requirements, while also being economical to produce.
It’s also possible to have a flexible production process where different products with different tools and moulds can be produced on the same production line.
For example, dynamically programmed robots with interchangeable tooling enable manufacturers to quickly and effectively switch between models manufactured with negligible efficiency loss.
Industry 4.0 technologies, processes, and ways of thinking make this possible.
Crucially, it’s also possible to do all the above while maintaining productivity and operational efficiency. As a result, new profit-making opportunities become a reality.
What is Mass Customisation?
Mass customisation is the ability to manufacture what the customer wants profitably and with no loss of productivity. The aim is to make the manufacturing process more customer oriented.
What is Flexible Manufacturing?
Flexible manufacturing is a manufacturing strategy involving production lines that can quickly and easily change the type of product being produced. The process of switching between product types is automated.
The Technologies Driving Change
Back in Ford’s day, designers designed products with minimal input from consumers. Engineers then worked on refining the design and getting the production processes right, in addition to making sure the production process was as effective and efficient as possible.
The product then left the production line and entered the distribution chain, with little connection between it and the factory floor.
In other words, the connection between the customer, the manufacturing process, and the design process, was minimal. The supply chain was also disconnected and disjointed.
Industry 4.0 turns this completely on its head. Sensors and communication technologies mean machines in the production line can interact, collect data, and issue instructions autonomously. These processes can be integrated with the supply and distribution chains, connecting other business units, and driving efficiency savings even further. Supply chain collaboration and oversight, product traceability, OEE optimisation, and more happen in real-time.
However, the real gamechanger when it comes to flexibility and mass customisation is the use of sensors in end products. With this technology, manufacturers can create digital twins of products that are being used by customers in the real world, with the digital twin receiving real-time updates from sensors on the physical products.
Non-Linear Product Lifecycle
Digital twin and simulation technologies offer a number of benefits to manufacturers, including predictive maintenance and making faults easier and faster to repair.
One of the biggest benefits, however, is how the use of sensors and digital twin technologies can influence the design process. Product designers no longer have to rely on gut instinct, limited research, or outdated usage data.
With Industry 4.0 technologies like digital twins, designers can use real-time data to produce products that customers really want.
In other words, the product lifecycle becomes non-linear.
A non-linear product lifecycle makes it possible to customise products for different customer segments, improving customer relations and the customer experience. Even single-unit production runs are possible, i.e., true product personalisation.
Mass Customisation Gets You Closer to Your Customers
Remaining competitive and relevant to your customers is essential, as is improving the customer experience, from the service they receive to shipping lead times to product quality.
Arguably, however, the most eye-catching benefit of mass customisation and manufacturing flexibility has to do with the relationship you have with customers. Industry 4.0 technologies, as well as mass customisation and flexible manufacturing strategies, get you closer to customers.
As a result, you can establish a more robust direct link with customers, strengthening your brand, building customer loyalty, improving customer and marketplace knowledge, and ensuring you stay out in front of emerging trends, changing values, and evolving expectations.
What Can We Learn from Ford’s Famous Quote?
There is a connection between Ford’s approach in the early 1900s and the opportunities presented by Industry 4.0 today. Specifically, two of the biggest things that Ford got right back in 1909 was to:
- Focus on the customer – he understood that the vast majority of his customers preferred to have a reliable car they could afford rather than one where they could specify a particular colour.
- Focus on profitability – Ford also understood he had to deliver on the above expectations of his customers in a way that was profitable for his company.
Hence, the get-it-right-and-then-make-them-all-the-same approach.
Manufacturers need to follow Ford’s lead, albeit with a 21st-century twist.
- Focus on the customer – customers still want products that work, and they want those products to be affordable, but they also want products tailored to their needs, i.e., they want customised products.
- Focus on profitability – manufacturers need to offer flexibility and customisation to remain competitive, but they must do so profitably.
Industry 4.0 technologies make both the above possible: sensors, automation, robotics, machine learning, data analysis (particularly anomaly detection), digital twins, equipment integration, and more.
It is manufacturing’s next evolutionary step, as Industry 4.0 technologies, processes, and systems become the norm, and we start moving towards Industry 5.0.
Top Smart Factory Trends in 2021 for the Life Sciences Sector
It is common to look at the trends that will impact smart manufacturing over the next 12 months and beyond at this time of year. We are in unprecedented times, though, making the manufacturing trends that will impact the life sciences sector in 2021 even more important. Here are some of the key points you should be aware of.
Technologies Used to Adapt to COVID-19 Realities Will Become Mainstream
The COVID-19 pandemic has had a significant influence on the working practices and strategies of organisations across almost all sectors. Companies have had to adapt, whether to survive the pandemic, to deal with increased demand, or to continue operations safely and in adherence with social distancing rules.
Some of those adaptations will continue beyond the pandemic, particularly in relation to technologies and processes used in manufacturing organisations. Two examples are 3D printing and remote support.
3D printing enabled the rapid production of PPE in the early days of the pandemic, demonstrating the potential of this technology. It will continue to be important over the coming years.
Remote support is even more of a game-changer as it provided organisations with a socially distanced solution to dealing with maintenance and other technical issues. The effectiveness of remote support, the cost and time savings involved, and the ability to keep systems secure and compliant, means the use of remote support will continue long after the pandemic has ended.
Mass Customisation Will Continue to Replace Mass Production
Manufacturers in many industries are moving further and further away from mass production models in favour of mass customisation. Mass customisation is made possible through smart factory technologies and solutions and brings a range of benefits to manufacturers in the life sciences sector. Those benefits include bringing you closer to your customers.
Resilience and Flexibility Will Be Prioritised
The COVID-19 pandemic severely tested the resilience and flexibility of organisations in a range of sectors.
Even for manufacturers who remained busy, COVID-19 put a spotlight on resilience and flexibility, in many cases moving both higher up the priority list than things like disaster recovery.
For manufacturers, a key focus for resilience and flexibility is the supply chain. This focus includes taking steps to increase their visibility across all supply chain components.
This enhanced visibility brings additional benefits, too, benefits that are becoming more and more important. An example includes the provenance of materials where there is a growing focus on things like labour conditions and fair trade across all parts of the supply chain.
Building resilience and flexibility into manufacturing supply chains also involves solutions that enable real-time communication and decision making across all supply chain components.
Improved collaboration is seen as essential, too, with the aim of evolving supply chains into collaborative networks rather than connected but independent entities.
Increasing Use of Remote Monitoring & Predictive Analytics
Reducing unplanned downtime has always been a priority for manufacturers. Industry 4.0 technologies help significantly, particularly remote monitoring and predictive analytics technologies.
With these technologies, engineers and technicians can monitor equipment and machines in real-time, identifying maintenance requirements before problems occur. They can then develop potential solutions before they visit the job site, reducing the amount of time they need to be on location.
In fact, the visit to the job site might not even be necessary with the use of remote support processes and technologies, including Microsoft Teams and mixed reality tech.
From a COVID-19 perspective, remote monitoring of machines and predictive analytics also helps pharmaceutical and medical device manufacturers optimise the process of bringing third parties on-site, while also minimising the frequency of these situations from occurring.
Increasing Focus on Data and Ensuring Data Quality
A trend that could be on this 2021 list is the increasing use of AI (artificial intelligence) in manufacturing. While AI offers significant strategic value for pharmaceutical and medical device manufacturers in a range of areas, the potential of AI solutions depends on the quality of data that the algorithms use. So, expect 2021 to be a year of data capture and quality focus.
The Era of the Distributed Cloud
Cloud computing is increasingly becoming the norm in manufacturing organisations, including in the life sciences sector. However, there are still concerns held by many organisations and executives about the security of their data when it is moved off-site to a third-party platform.
The distributed cloud provides a solution to these concerns. With a distributed cloud, you can run the infrastructure of a public cloud in various locations. These locations can include your premises, other data centres, and the infrastructure of your cloud provider. You can then manage and control everything through a single system.
The distributed cloud even makes it possible for manufacturing organisations to utilise the edge cloud, or edge computing. The edge cloud is where computing – applications or servers – run at or close to the source of the data.
Aside from addressing security concerns, distributed cloud and edge cloud technologies help organisations comply with privacy regulations in multiple jurisdictions. The technologies can also improve the real-time processing of large amounts of data.
Upskilling the Workforce Will Be Essential
The automation technologies being deployed in the manufacturing sector are leading to a change in the skills needed on and off the factory floor. Previously, manufacturers needed workers for repetitive tasks. Today, they need knowledge workers, i.e., workers with the skills to implement, operate, and maintain the automation, collaboration, and data-based technologies that are becoming the norm.
So, companies will seek to recruit knowledge workers. However, they are in short supply, so upskilling the existing workforce will also become a priority.
Decreasing Emphasis on Industry 4.0 Driven by an Increasing Focus on Industry 5.0
While Industry 4.0 is still the here and now for many organisations, it is a concept that has been around for several years. Many of the technologies, processes, and systems that make Industry 4.0 solutions possible already exist. They continue to be improved, and new technologies are being developed, but there is now an increasing emphasis on the stage after industry 4.0 – Industry 5.0.
Where Industry 4.0 focuses on digital transformation, particularly through automation, Industry 5.0 is about deepening the integration between people and smart machines/robots. Watch this space.
What is Digital Twin Technology and How It Benefits Manufacturing in the Industry 4.0 Era?
Understanding what is happening now on your production line, and predicting what will happen in the future, is essential for maximising OEE, optimising productivity, and improving business profitability. You can achieve all these things with digital twin technologies.
Digital twin technology is one of the most important Industry 4.0 technologies currently available. Digital twins give you insights into all aspects of your production line and manufacturing process.
You can then use these insights to make better decisions, plus you can automate the decision-making process with the dynamic recalibration of equipment, production lines, processes, and systems.
In other words, digital twins provide engineers with virtual tools that allow them to look at, explore, and assess physical assets, processes, and systems. With this ability, it is possible to get an accurate view of what is happening now, as well as what will happen in the future.
What Is Digital Twin Technology?
A digital twin uses virtual and augmented reality as well as 3D graphic and data modelling to build a virtual model of a process, system, service, product, or other physical object. This digital twin is an exact replica of the physical world. Its exact replica status is maintained through real-time updates.
It is a technology that is applicable to a wide range of environments, including the monitoring of products while they are in use and through the entire product life cycle.
In manufacturing, you can use a digital twin technology at various levels:
- Component level – focused on a single, highly critical component within the manufacturing process.
- Asset level – creating a digital twin of a single piece of equipment within a production line.
- System level – using a digital twin to monitor and improve an entire production line.
- Process level – this looks at the entire manufacturing process from product and process design and development, to manufacturing and production. It also applies to distribution and the use of the finished product by customers/patients throughout the entire life cycle, as well as for the development of future products.
So, A Digital Twin is a Simulation?
Not exactly. A digital twin starts as a simulation, but the difference between a digital simulation and a digital twin is real-time updates.
With a simulation, engineers can run tests and conduct assessments on a simulated version of a physical asset. The simulation is static, however. In other words, it doesn’t keep pace with the physical asset unless the engineer inputs new parameters into the simulation.
A digital twin, on the other hand, receives real-time updates from the physical asset, process, or system. Therefore, the tests, assessments, and analysis work conducted by engineers are based on real-world conditions. As the state of the digital twin dynamically changes as it receives new data from the physical world, it matures, producing outputs that are more accurate and valuable.
How Does Digital Twin Technology Work?
A digital twin comprises three main elements:
- Past data – historical performance data of individual machines, overall processes, and specific systems.
- Present data – real-time data from equipment sensors, outputs from manufacturing platforms and systems, and outputs from systems throughout the distribution chain. It can also include outputs from systems in other business units, including customer service and purchasing.
- Future data – machine learning as well as inputs from engineers.
Applications for Digital Twins
Some examples of typical applications for digital twins include:
- Using predictive maintenance to maintain equipment, production lines, and facilities
- Getting a better understanding of products by monitoring them in real-time as they are used by real customers or end-users
- Manufacturing process optimisation
- Enhancing product traceability processes
- Testing, validating, and refining assumptions
- Increasing the level of integration between unconnected systems
- Remote troubleshooting of equipment, regardless of geographical location
What Engineers and Manufacturers Can Do With Digital Twins
First, a digital twin lets you monitor a manufacturing component, asset, system, or process in real-time. This enhanced monitoring capability gives a deeper understanding of what is happening on your production lines and in the wider manufacturing process.
With machine learning and inputs from expert engineers, you can also use the digital twin to identify problems before they occur and predict future outcomes. These predictions include outcomes within existing parameters as well as outcomes if those parameters change.
Digital twin technology supports other Industry 4.0 technologies, too, helping to improve OEE, reduce waste, improve batch changeover times, improve product quality, enhance traceability, and more. It allows for efficient design and development, linking three-dimensional models with simulation and equipment control code emulation.
In addition, having a digital twin enables virtual troubleshooting and support, removing the physical restraints of expert engineers having to be at your location. The technology can also form the basis of customer interactive dynamic supply chains.
Remember, the above includes just some of the things you can achieve using digital twin technologies. There are also manufacturing process development advantages, product development advantages, distribution chain efficiency advantages, and more.
The Benefits of Digital Twin Technology
The benefits that digital twin technologies offer your business include:
- Increased reliability of equipment and production lines
- Improved OEE through reduced downtime and improved performance
- Improved productivity
- Reduced risk in various areas, including product availability, marketplace reputation, and more
- Lower maintenance costs by predicting maintenance issues before breakdowns occur
- Faster production times
- New business opportunities such as mass customisation, mixed manufacturing, small-batch manufacturing, and more
- Improved customer service as customers can remotely configure customised products
- Improved product quality and enhanced insight into the performance of your products in multiple real-time applications and environments
- More efficient supply and delivery chains
- Improved profits
Where to Next?
Digital twin technologies are available now and can bring the above benefits to your business in the short-term as well as the medium and long-term. Plus, the use of digital twins is a growing trend.
To remain competitive, the time to start analysing and implementing this new and potentially disruptive technology is now.
Benefits of Microsoft Azure for Manufacturers in the Life Sciences & Technology Sectors
Implementing Industry 4.0 and smart factory solutions in your manufacturing operation requires a fresh approach to solution delivery, platform implementation, and IT infrastructure. Central to most solutions is the use of cloud technologies, such as Microsoft Azure.
At SL Controls, we have extensive experience working with a range of cloud solution providers. Plus, we offer a service that is platform agnostic.
However, we favour the Microsoft Azure platform for building, deploying, and managing smart factory solutions in the cloud, particularly for companies in the life sciences and technology sectors. This is because of the range of features, scope, and flexibility of Azure, in addition to a range of other factors.
Microsoft Azure – the Basics
At its core, Microsoft Azure is a cloud computing platform. Azure makes it possible to build, implement, and manage solutions in the cloud. This makes Microsoft Azure a blend of platform as a service (PaaS) and infrastructure as a service (IaaS).
With Azure, it is possible to develop solutions that would have traditionally run on servers at your location, as well as new solutions that are only possible because of cloud and Azure-specific technologies.
Of course, Microsoft isn’t alone in the cloud computing market. There is a range of competitors, from new start-ups to some of the biggest companies in the world, including Amazon’s AWS offering and Google’s cloud platform.
Below are some of the reasons our leadership team, senior engineers, and project managers at SL Controls prioritise Microsoft Azure where practical.
Minimises the Hardware You Need On-Site
Production machines, equipment, sensors, platforms, and systems can all be connected to the Azure cloud and integrated to deliver on your requirements.
Hybrid Cloud Compatible
Azure solutions can be developed to meet the needs of your business, whether that means solutions on one cloud, across multiple clouds, at your location, or at the edge (i.e., at or close to the source of your data).
The hybrid computing capabilities of Azure allow you to create private cloud infrastructure using Azure Networking, enabling compliance at all levels. This is particularly beneficial for manufacturers in the life sciences sector, including those in the pharmaceutical and medical device industries.
Applications that your company may already use are fully integrated with Microsoft Azure. This includes Outlook, SharePoint, Teams, and Office 365. This reduces the learning curve, so helps with the implementation of new solutions and systems.
The Highest Levels of Security
Starting with password security, Microsoft Azure has a single sign-on feature. This makes it easier to manage large numbers of users. It also makes it easier for people in your organisation to access their platforms, systems, applications, and data without a complex set of passwords to remember.
Plus, you can implement even greater levels of control over access as required. For example, you can make access to parts of your system either device or location-specific, reducing the potential for unauthorised access.
Azure also benefits from Microsoft’s advanced threat management and enterprise-level security.
In addition, Microsoft takes a proactive approach to compliance in relation to its Azure platform, and it invests significantly in security. According to the latest figures from the company, it invests USD $1 billion every year protecting the data of its customers.
High Levels of Flexibility, Helping to Future-Proof Your Organisation
Microsoft Azure is fully scalable according to business requirements as you move further down the digital transformation and Smart Factory journey.
The platform also supports all programming languages and development frameworks, ensuring flexibility in the development process when creating the new solutions that your business needs.
Backup and Data Recovery
Microsoft Azure has a Geo-Redundant Storage feature. This means backups of your data are automatically stored in data centres in a different geographical region than the data centre location of your main system. So, if something happens with the data centres in your region, a backup will still exist.
Microsoft Azure is a core part of the company’s business, and it has committed to continually developing and improving the platform.
At SL Controls, our only goal is to develop solutions that meet your requirements. If you need solutions built on different cloud platforms or technologies, we have the skills and capabilities that are required.
Many companies in the life sciences and technology sectors already use Microsoft platforms, solutions, and technologies, including Azure. This, combined with our experience developing and implementing new and innovative Industry 4.0 solutions, means we have confidence in the Azure platform to deliver on the rapidly evolving requirements of manufacturing companies.