Additive Manufacturing and 3D printing are key enablers for more sustainable production, supply chains and services. In fact, the global additive manufacturing market is projected to grow by almost 24 percent between 2023 and 2025, and the market for 3D printing is expected to almost triple in size between 2020 and 2026. With everything from airplane parts to hearing aids created through additive manufacturing, it is clear that this technology is special and has the potential to dramatically impact business practices and address sustainability demands. 

Before looking more closely into how additive manufacturing is driving a more sustainable tomorrow, it is good to take a step back and examine current manufacturing challenges. At the core of the need for improvement is that customers want everything faster and with more flexibility in quantity, which puts a strain on traditional development, production, and distribution channels. Meanwhile, the business leaders need to balance that demand with a clear need for sustainable practices and processes. In general, taking care of resources, providing greater efficiencies throughout the entire supply chain, and developing a more circular economy are all things the manufacturing sector must pull together to achieve sustainability success.  

In addition, the new CO2 certification process in Europe puts additional pressure on manufacturers and supply chains. Paying for CO2 emissions clearly changes the cost-change paradigm. Producing emissions while manufacturing as well as shipping a product around the globe will become an expensive game. Tackling this issue will require a radical rethinking of the whole value chain.  

To dramatically overhaul the value chain, address customer demand, and reach sustainability goals, manufacturers must undergo a digital transformation. Connecting the real and the digital world provides manufacturers with the data and insights needed to make well-informed decisions on how to optimize processes and increase efficiencies.  

Digitalization offers multiple opportunities to gain a competitive advantage by improving product design, factories, supply chains, and after-sales services (spare parts) with digital twin solutions. By mimicking the product or whole supply chain in the digital world, manufacturers can simulate, test, and predict scenarios in real-time while optimizing production processes and operations. Digitalization creates the necessary transparency for better decision making through access to data. Consequently, digitalization is the foundation of many of the sustainable manufacturing processes that are already in use today – everything from low-energy robotics to modern additive manufacturing methods. 

Additive manufacturing is known to be a technology which is “digital by nature,” meaning that the process itself would not work without digital technology connected to it. At the process level, 3D printing has the power to alter production, supply chain, and post-sales support practices throughout the manufacturing sector.  

The sustainable importance of additive manufacturing is more obvious in some areas than others. Here are a few known benefits of this technology: 

1. Improving Resource Efficiency During Production Processes 

A key advantage of 3D printing can be experienced during production. Digital methods save natural resources through more efficient processes. The parts 3D printers produce are close to their final intended shape. Barely any material needs to be removed in contrast to grinding or milling production methods.  

The accuracy of today’s digital printing methods means that products are made right the first time with little need for rejections or modifications post-production. Since there are no molds or other tools required in 3D printing (compared to on-demand technology), the requested order size is made without any overproduction, waste, or additional storage costs. 

Overall, resource efficiencies are ensured thanks to a combination of simulated printing processes before production runs, optimized print pathway automation, and the potential to use digital warehousing techniques to validate which parts are – or will be – most in-demand.  

2. Saving Emissions By Reducing Supply Chain Lengths 

Supply chain length reduction means establishing a less costly and greener supply chain. Additive manufacturing enables the creation of parts and products closer to the end consumer and could even allow for printing in customers' homes. By decoupling manufacturers from global logistical operators, it also helps to make supply chains more resilient and less susceptible to international or weather events, as well as reducing the carbon footprint. The lower supply chain costs of additive manufacturing might even outweigh the higher costs in the location of production. Emissions associated with road haulage and international shipping will be vastly reduced. Localized 3D printing hubs will be able to bundle several production runs to make transportation to end users even more efficient and sustainable. 

Another key to additive manufacturing’s sustainability capabilities is that it produces fewer parts than traditional manufacturing. The thumb rule is that if a conventionally manufactured component consists of 100 parts, the same additively manufactured component can potentially consist of only 10 parts or even less. This shortens the value chain extremely including the complete energy consumption.  

Think of it this way – fewer parts and production steps require less logistical expertise to move goods around the world. Additionally, fewer machines need less space / storage, less resources, and in the end less energy.  

3. Enabling Smart Repairs and Upcycling Options 

The after-sales aspects of additive manufacturing should not be overlooked when considering sustainability. For one thing, additive manufacturing technologies such as cold spraying or laser melting can help to lengthen product lifecycles by reproducing worn-out parts or even worn-down sections of them. For example: With a local 3D printing service, customers can obtain the necessary part and replace it, thereby extending the product's lifespan, even improving the part’s performance, or enabling new features. Maintenance services can be strongly optimized, as parts can be produced whenever and wherever needed, making the process way more effective, saving a maximum of time. 

To enable this process, manufacturers need to have the relevant files available in a digital warehouse that allows end users to select the part(s) needed and print them directly. Since customers can access the parts in real-time, there is no need for warehousing of spare parts.

Most of us can understand how additive manufacturing drives sustainability by improving resource efficiency during production or how it can save emissions by limiting the length of the supply chain. But there is one area where additive manufacturing boosts sustainability that may not be as obvious – the product design and its performance when it comes to energy.  

3D product design can improve energy efficiency of products like no other technology can, not just in production but over the course of its lifecycle. Manufacturers may be surprised how easily 3D printers produce complex structures. This not only saves material resources, but it also saves the energy used to generate the material. With additive manufacturing it is also possible to produce significantly lighter products. Less weight means lower fuel consumption and lower distribution costs. 

The biggest energy savings are achieved through flow-optimized design and maximization of thermal energy absorption capability. This means that, simply by optimizing parts of the bigger product slightly through complex geometries only additive manufacturing is capable to produce, it might already improve its energy efficiency significantly.  

For example, with an aerodynamic part in a turbine produced through additive manufacturing you can manufacture near-shape cooling channels right below the part surface. With the increased efficiency in cooling the turbine can run at a high temperature creating lowering energy costs over its entire lifespan. In this situation, additive manufacturing optimized not only the part but the entire product, in this case the turbine.  

But additive manufacturing can even increase sustainability and energy efficiency for already sustainable technologies. Take the electric motor, for instance: by printing components more precisely, the effectiveness of the engine can grow even more – to new heights.  

A word of caution - leaders should not apply additive technology just to say they can. The technology needs to serve the business needs, solve problems, and entail significant benefits for production processes.  

Here are a few things to keep in mind for successful additive manufacturing: 

It’s not all about technology. While additive manufacturing can dramatically change a manufacturing business’ level of sustainability, it is not all about technology. In fact, the confidence and support of the people in your organization can make or break your success. Leaders are encouraged to remember that there is a human component regarding changes that will be inevitable when moving from legacy production methods to more sustainable 3D printing processes. Good change management programs are essential. 

Optimize and design new part(s) first…based on business purpose and then print the optimized version for actual value. There is no point in copying the initial traditionally produced part. In fact, doing so, might even be more expensive. Instead, the value of additive manufacturing lies in using the right simulation tools like digital twins and Artificial Intelligence to achieve application-optimized geometries and printing them very precisely.  

Invest in the infrastructure. Manufacturing enterprises must invest in the necessary infrastructure to benefit from additive manufacturing processes and the greater sustainability they can generate. Some businesses will inevitably decide to purchase 3D printers and the associated digitalization tools that go with them. However, it is also extremely convenient for manufacturers to outsource 3D printing requirements at a lower cost due to shared resources. Sharing the resources of an expert in additive manufacturing with other organizations means even more sustainable outcomes can be achieved because fewer resources need to be retained in-house for printing products, parts, and prototypes. In some cases, depending on the individual situation (location, ecosystem, and customers), there will be no need for a factory in the first place. 

Shape business strategy around sustainable goals and scale accordingly. Senior managers and executives must reassess corporate strategies if they are to find the success of additive manufacturing. Furthermore, meeting the demands of customers will require the adoption of services in a portfolio more closely aligned to 3D printed solutions. Producing 3D printed product designs is the first step, but manufacturers also need to consider material choices carefully because that will directly impact future sustainability and distribution.  

Additive manufacturing successes and advocates have reframed the story from “the technology reducing machines in production” to focusing on its potential to expand manufacturing opportunities. It may become a competitive advantage for some manufacturers. It may change the rulebook for production. It may be the answer for radically improving your business strategy. It could be the critical action your business needs to address the societal imperative to deliver a more sustainable future. What’s stopping you from finding out? 

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For CEOs of industrial manufacturing firms, one of the biggest concerns arising from the COVID-19 pandemic has been supply chain disruption. One study put the average cost to large businesses (those with revenues above USD 1bn) at around USD 184m in 2021.

Throughout 2020, the number of organizations experiencing 20 or more supply chain disruptions increased by a factor of six, according to the Business Continuity Institute’s 2021 Supply Chain Resilience report. This ranged from the Suez Canal blockage to container pileups in Shanghai and other major ports. If this wasn’t enough, ongoing climate change issues as well as geopolitical changes were the missing cherry on top. The same report found that the proportion of senior management showing a medium or high commitment to supply chain risk rose by nearly 10 percent to 82.7%. This goes to show that these global influences have the effect of transforming supply chains into revenue assurance drivers rather than cost reduction pillars.

Faced with this increasing volatility, uncertainty, complexity and ambiguity, the number one priority for sector leaders is to build resilience into the supply chain. Due to the pandemic leaders’ priorities shifting to business continuity and their realization that connectivity is the golden ticket, the challenge lies in a successful way to accomplish this.

The global supply chain market is expected to experience a compound annual growth rate of 11.2% from 2020 to 2027 – a market value surge from USD 15bn to USD 37bn. With the added speed bump of supply chain disruptions, it’s time to build resilience into your supply chain, and business leaders are reaching for plentiful and readily available technological developments to do so. Currently, the IIoT-based solution showing the most potential when creating a resilient supply chain is the use of digital twins to mimic supply chains and productivity networks.

In recent years, the digital transformation of supply chains has made them increasingly dynamic and complex. Catalyzed by the pandemic and other previously mentioned supply chain hurdles, manufacturers have sought out new ways to optimize supply chains to ensure transparency. To do so, in-depth understanding and visibility of the entire end-to-end ecosystem of suppliers and customers – their needs, strengths, weaknesses and potential risk factors – is the Holy Grail.

This ideal of a fully connected ecosystem providing real-time data starts by connecting your own supply chain. Only once you have complete visibility of your own end-to-end operations, connection with the wider ecosystem can be achieved, enabling you to create a holistic overview and transparency from customer to supplier.

Based on this holistic overview, you need to decide on your own business goals and adjust your digitalization strategy accordingly. Easier said than done? Not necessarily. The important thing is not to drown in the ocean of possibilities and to keep your eye on your business goals, letting them dictate the level of detail your digital solution requires.

It’s estimated that up to 93% of all IoT Platforms will contain some form of digital twin capability by 2027. So what exactly is a digital twin? And how does it tie in with a connected supply chain? To put it simply, a digital twin is a virtual representation of a physical product or process. By feeding it with data, it can be used to model the current situation in real time, test ‘what if’-scenarios for the future and, in some instances, even provide ‘best practice’ to the modelled disruption. As such, it provides predictive insights, highlights areas of weakness or potential failure and enables timely preventative action.

By incorporating the latest technical innovations (eg multi-physics simulation, AI, data analytics and machine learning), digital twins can demonstrate the impact of usage scenarios, environmental conditions and other variables to improve the resilience of a supply chain. The digital twin is therefore the ultimate goal in connecting your supply chain, yet you need to learn to walk before you can run. Start by determining the digital journey most adequate for reaching your business' set goals and drivers. Luckily, there are a few maturity levels you can reach before chasing the Holy Grail of the digital twin, and there is likely a data solution for every organization and budget.

To provide visibility and transparency on an operational level, applying a digital map or model might suffice, as it provides basic insights into your operations. However, if you want to leverage data to simulate and explore various possible scenarios and the effects of changes before implementing them in the physical supply chain, a digital shadow might be the best approach. However, only a digital twin can create enough insights to enable real-time connection and provide concrete simulations for operational, tactical as well as strategic decision making.

The key to realizing this ideal scenario is leveraging the correct data in the correct way by the correct people. However, as with any form of digitalization, there are several factors to consider when starting the journey to executing a digital twin.

Firstly, it’s crucial to always have your goals in mind: the business outcome you want to achieve should be the foundation for your decision as to which data model to use. For certain organizations, it may not be necessary to apply an end-to-end digital twin at the very beginning of your digital transformation journey. Trying to navigate through the buzzwords and promises from solution providers and staying true to your core needs is therefore an important first consideration. Applying technology just for the sake of applying technology is never the solution!

Secondly, a digital twin is only as good as the data it gets fed. Therefore, you need to gather useful data and that’s the tricky part. When creating the digital twin, connecting your internal data is advised, as this is the data that’s readily available to you. However, it’s important not to fall into the trap of data overload, which can result in too many insights slowing down and clouding the decision-making process. Once you have an internal connected supply chain in place, you can start reaching out to your ecosystem to further increase connectivity. It’s essential to take the time to understand relevant data management solutions for your business goals and ecosystem.

Everybody knows that data is the new gold in business, and companies are often reluctant to give it up lightly. This results in a potentially complex process of connecting your full ecosystem, as you need to convince all stakeholders about the joint value that can be created through sharing knowledge and creating transparency. As soon as they’re fully connected and sharing their data, you can collectively create the most detailed digital model possible, which will benefit everybody along the chain.

However, in reality it’s unlikely that every member of your ecosystem will share the data needed to simulate a complete supply chain digital twin, but that does not mean the end of the line for your digital twin journey. The good news is that there is a sophisticated workaround to help you overcome this particular roadblock: artificial intelligence (AI). Through AI, it’s possible to model the missing data and thus fill in gaps in your data lake. Furthermore, other data sources can be fed into AI to derive expected impacts to the supply chain from striking events, for example the news of a flooding in a particular region in the world can be overlaid with your supplier base and the digital twin can preempt potential impacts and solutions.

Now that your data is in place and connected, the true benefit of a digital twin emerges. Real time connection and seamless data flow will enable direct transparency of your data, and customized visualization, dashboards and alerts will allow for rapid decision making. The only question is, will your decision-making processes be able to keep up with this increased speed of knowledge?

Data digitalization and process optimization need to be harmonized, as data without a process is useless, and a process without data is inefficient. Future supply chains will be a combined learning network of humans and technology, so alongside building your digital twin, it’s important to invest in the creation of a flexible workforce willing to adapt its skillset to facilitate a bionic supply chain. After all, the most powerful intelligent network is still the human mind, and it’s fundamental in deriving and acting on the benefits of a supply chain digital twin.

When applying connected supply chains in the industrial manufacturing environment, it is important to shed light on how their connection to the green, lean, and digital factories of the future will look like. In this specific context, the successful creation of supply chain digital twins depends on the quality of data from every factory, warehouse, or nod within the supply network. This means that it is best practice to successfully develop digital twins of your factory in the first place. This will make the trick for the whole network as data could be provided seamlessly.

At the same time, it is crucial to understand that the factory of the future and its successful operations heavily depend on seamless data flows, processes, connectivity, and agility on a large scale in order to ensure individual productivity, robustness, and delivery excellence. Ever changing markets, customer requirements and supply disruption can only be managed sustainably by building agility and reactiveness into the mix. The supply chain digital twin can be the dealmaker in this context enabling the transparency needed beyond one’s own facilities. In the end, the factory of the future, being green, lean and digital in nature, is both enabler and benefactor from the creation of a supply chain digital twin. Seamlessly, connected supply chain can build the basis for factories and whole networks to decarbonize operations.

Increased connection and digitization open the possibility of creating supply chain digital twins, but it’s not actually the digital twin that creates the value for your business. A digital twin is simply the vehicle you need to enable a fully connected supply chain, and the strategic connection with your individual business goals is the key that makes your vehicle perform. As a result, your entire ecosystem will gain a competitive advantage.

Siemens Digital Industries Logistics (DI LOG) has already paved the way towards a comprehensive digital supply chain twin with their end-to-end resilience solution. This platform helps both Siemens and its partners to proactively manage supply chain and operations based on real time tracking and data-driven alerting functionalities for all involved parties within the network.