Sustainability and digital transformation

June 28, 2022
Industry insights

Manufacturers today are increasingly being driven to address environmental sustainability in their production, caused by increased political and regulatory pressures, as well as shifting demands on consumer sides. Parallel to this, Industrial IoT and Industry 4.0 technologies have been gaining traction for years. These technologies have been hailed as one of the key factors in improving the efficiency and sustainability of manufacturing processes, but what exactly happens at the intersection of the digital transformation of factories and sustainable manufacturing? In this article, we intend to provide an overview of some of the key aspects of sustainable manufacturing and how manufacturers can benefit from deploying Industrial IoT and Industry 4.0 technologies as part of their journey towards more sustainable production methods. In addition, we will also highlight some specific solutions and use cases we have come across that have the potential to improve the sustainability of manufacturing processes.

The industrial sector plays a significant part in the production of greenhouse gases. In 2020, the estimated portion of all greenhouse gas emissions attributable to the sector was 23,8%.


Sustainability in manufacturing

Sustainable manufacturing is defined as “the creation of manufactured products through economically-sound processes that minimize negative environmental impacts while conserving energy and natural resources” (Meng et Al., 2018). While the concept of sustainability can be considered to contain social, economic and environmental aspects (Khan et al., 2021), our focus in this article lies within environmental sustainability. But how can the goals of environmental sustainability be achieved in manufacturing?

A McKinsey report (Hammer & Somers, 2021) highlights 5 key aspects of resource-productive operations to be addressed when making the manufacturing operations more sustainable:

1. Lean manufacturing: this is a core principle in both efficiency-increasing and environmentally friendly manufacturing for obvious reasons, as eco-efficiency comes as a by-product of efficiency improvements and the elimination of waste and losses.  

2. Think limits: this aspect encourages the manufacturers to set ambitious goals by thinking of the theoretical limits of their production as opposed to just benchmarking their performance against that of their competitors. It allows the identification of underutilized potential also in terms of resource and energy efficiency. The OEE (Overall Equipment Efficiency) is perhaps the single best metric for measuring the possibilities of production - it takes into account the availability, performance, and production quality of machinery:

  • Availability: the ratio between the actual run time and planned production time
  • Performance: takes into account anything that leads to the manufacturing process to run at less than maximum speed, forming a ratio between net run time and the run time.
  • Quality: ratio between the number of good products and the total number of products produced (www.oee.com)  

3. Profit per hour: the authors have identified profit per hour to be one of the most significant and encompassing metrics in the endeavor of optimizing industrial performance. For a single metric, it includes a complex and comprehensive set of both cost and revenue drivers that affect the overall performance. With regards to sustainability performance, the metric contains multiple relevant aspects such as resource consumption and waste generation and can benefit significantly from the introduction of process-optimizing Industry 4.0 technologies.

4. Holistic approach: focusing on only one sub-area of an organization, such as the technological status quo, will never yield the best possible results. When attempting their transformation towards environmental sustainability, organizations must address need for retraining within the workforce, identify the relevant KPIs, and transform the management system where necessary.

5. Think circular: circular economy implies the consideration of products as future resources and trying to optimize their use through several life cycles, as opposed to seeing them as products to be disposed of at the end of their current use cycle. This has tremendous potential for environmental and sustainability considerations but remains a somewhat underutilized principle requiring further development.

Ultimately, the ideal approach of sustainable manufacturing takes an integrated approach to sustainability, encompassing aspects of product and process design, manufacturing, and operations, addressing the relevant aspects to reduce the environmental burden caused by the economic activity. Life Cycle Assessment (LCA) is one way of comprehensively evaluating the environmental impact of certain activities, including manufacturing processes, as it aims to consider the full environmental cost of the investigated activity through its life cycle (Posinasetti, 2018). Within the manufacturing process, goals of sustainable manufacturing can be also addressed by specifically focusing on the following aspects: consumption of resources such as energy (may contain the type and origin of energy) and water, and generation of emissions and waste. (Posinasetti, 2018)  

Industrial IoT and Industry 4.0 technologies and their effects on environmental sustainability

The 4th industrial revolution is the digital transformation of manufacturing processes, making use of modern technologies such as IoT (Internet of Things), AI (Artificial Intelligence), and machine learning, and thereby gaining elevated levels of interconnectedness, controllability, and automation within factories which leads to more efficient manufacturing processes. But how do these technologies affect and interact with the goals of sustainable manufacturing? Research into the interconnection between the 4th industrial revolution and environmental sustainability has drawn attention to the causal relationship between Industry 4.0 technologies and sustainability, and vice versa.  

As a starting point, Meng and others (2018) mention energy efficiency as one of the critical goals of smart manufacturing and highlight multiple smart technologies that may positively contribute to the goals of sustainable manufacturing. Indeed, intelligent technologies by default attempt to improve the efficiency of production processes, increase productivity, and drive down the cost of production, which in itself contributes to a more sustainable production process. Hammer and Sommers (2021) mention lean manufacturing as one of the core principles of sustainable manufacturing, and smart technologies can significantly contribute in that regard. Smart technologies can be utilized to optimize the production processes at multiple levels, and large amounts of data can be collected and used to optimize machinery, maximizing productivity while minimizing resource usage, such as energy consumption in real time (Rogers, 2014). Industrial IoT technologies and Industry 4.0 technologies, for example, enhance interconnectedness of systems and units in the shopfloor, making large amounts of data easily available, and can significantly contribute to the optimization efforts and help in minimizing the resource usage (Terry et al., 2020). Beltrami and others (2021) also identified promising perspectives for technologies such as CPS (Cyber-Physical Systems), IoT, cloud computing and additive manufacturing in sustainable manufacturing. Such benefits could be gained, e.g., through real-time automated and interconnected performance monitoring, optimization, and production control, leading to a decrease in materials used and waste generated. Utilizing smart manufacturing technology as opposed to traditional large-scale manufacturing can help produce goods with 50-75% less energy (Terry et al., 2020). The most obvious benefit from Industrial IoT and Industry 4.0 technologies thus comes from enabling the more effective deployment of the principles of lean manufacturing, supporting the goals of efficient and minimal resource use, minimized losses and highly optimized manufacturing processes.  

An example of how AI-related solutions are improving environmental sustainability: AI-enabled use cases have helped organizations gain significant sustainability-related benefits, and the future benefits of such solutions are expected to be even greater.

In their research of the intersection between sustainable manufacturing and IoT technologies, the European Environmental Agency (Berg et al., 2021), refers to a twin transition, implying that the green and digital transitions within the European Union and its industrial sector may be seen as highly complementary and integrated, with a particular emphasis on transitioning towards a more circular economy. The authors highlight the potential of Industry 4.0 in both, the creation of cleaner ways of production, as well as assessing and minimizing the environmental footprint of Industry 4.0 technologies themselves.

Though care is required in evaluating the interaction between sustainable manufacturing and Industry 4.0 technologies, it is clear that the technologies, when correctly utilized and deployed, provide opportunities for sustainable manufacturing. A research paper investigating the potential impact of Industry 4.0 technologies in the global GHG emissions found that such technologies have the potential to decrease the overall global GHG emissions by 6-15% by 2030 (Malmodin & Bergmark, 2015).

Specific solutions improving environmental sustainability

The interrelation between smart manufacturing technologies and sustainable manufacturing can be divided into solutions and technologies that directly aim to address environmental aspects of production, and those that lead to improvements in sustainability metrics as a by-product of other improvements. Several solutions are available which contribute to sustainability in manufacturing, both directly and indirectly, leading to performance-improvements in manufacturing processes at scale.

Autonomous Energy & Resource Optimization is an example of a solution with the direct aim of contributing to the environmental sustainability within the production process. The solution, utilizing Optimitive technology, is based on using sensors to capture machine and environmental data and utilizing AI and machine learning to assess and optimize the energy consumption of the machinery in real-time. Thus, its direct aim is to contribute to environmental goals by reducing energy consumption while automatizing the optimization process to a high degree. The solution is especially useful in scenarios where processes are energy-intensive and where process parameters require regular re-adjustment by operators. On average, implementing autonomous energy & resource optimization can lead to a decrease in energy consumption of up to 15%, reduce operating time required for manual adjustments by 20%, and increase the process speed by 5%.  

Other potential solutions directly addressing environmental sustainability include:

  • monitoring emissions of the production process,
  • HVAC monitoring and optimization,
  • carbon offset monitoring, and  
  • waste-to-energy monitoring.  

In addition to the solutions directly addressing environmental goals, many solutions contribute to efficiency increases in the manufacturing processes, thus also decreasing resource consumption and scrap loss creation. Examples of such solutions include Autonomous Yield and Throughput Optimization and AI-powered machine vision for quality inspection, in collaboration with ANTICIPATE, for instance.

Sustainability lighthouses

Looking at sustainability in manufacturing, which companies are currently the most succesful examples of reducing the environmental impact of their operations? For prime examples of sustainability in industrial operations, the Global Lighthouse Network presents a list of companies that have succeeded in implementing intelligent technologies to minimize their environmental footprint (Betti et al., 2021). One of the major aspects addressed by these factories is eco-efficiency, referring to the adoption of intelligent technologies that boost both the productivity and sustainability of processes simultaneously. Productivity gains come from several performance indicators such as productivity, cost, and quality, whereas sustainability gains in this regard stem from reducing consumption, resource waste, and emissions. Within the global lighthouse network, 64 percent of the factories reported a positive sustainability impact because of adopting industrial automation technologies, either due to direct efforts to address environmental issues, or as a by-product of addressing other aspects of manufacturing. Sustainability lighthouses have now emerged as a new term to encompass those factories in the lighthouse network that have demonstrated the ability to utilize smart technologies in such a way that it significantly drives forward the sustainability efforts with notable achievements.  

Conclusion

It is clear, that the 4th Industrial Revolution has potential in having a positive impact on the environmental sustainability of manufacturers. Caution is required though, as the consequences of adopting smart manufacturing technologies are manifold and do not automatically lead to improvements in important environment related KPIs. Industrial IoT and Industry 4.0  technologies have to be thoroughly integrated and there has to be a high level of managerial commitment to ensure their adaptation to the fullest potential, and attention should be paid to use the industrial automation technologies for sustainability gains specifically. We warmly encourage you to reach out to us or consult the sources of this article for a more thorough insight.

Sources:

Malmodin & Bergmark,  Exploring the effect of ICT solutions on GHG emissions in 2030, (2015), Proceedings of EnviroInfo and ICT for Sustainability 2015, Atlantic Press, available via https://www.atlantis-press.com/proceedings/ict4s-env-15/25836149  

Beltrami et al., Industry 4.0 and sustainability: Towards conceptualization and theory, (2021), Journal of Cleaner Production (312), available via https://www.sciencedirect.com/science/article/pii/S095965262101951X#bib7  

Hammer & Somers, Industrial-resource productivity and the road to sustainability, (2021), McKinsey, available via https://www.mckinsey.com/business-functions/operations/our-insights/industrial-resource-productivity-and-the-road-to-sustainability  

Betti et al., Global lighthouses are revolutionizing the world of sustainable manufacturing - but what exactly are they?, (2021), World Economic Forum, available via https://www.weforum.org/agenda/2021/10/lighthouses-sustainability-manufacturing-4ir-technologies/  

German Environmental Agency, Indicator: GHG Emissions, (2022), available via https://www.umweltbundesamt.de/en/data/environmental-indicators/indicator-greenhouse-gas-emissions#at-a-glance

Berg et al., Unlocking the potential of Industry 4.0 to reduce the environmental impact of production, (2021), European Environmental Agency, available via https://www.eionet.europa.eu/etcs/etc-wmge/products/etc-wmge-reports/unlocking-the-potential-of-industry-4-0-to-reduce-the-environmental-impact-of-production

Capgemini, Climate AI: How artificial intelligence can power your climate action strategy, available via https://www.capgemini.com/wp-content/uploads/2020/12/Report-Climate-AI.pdf  

Posinasetti, Sustainable manufacturing: principles, applications and directions, (2018), available via https://www.industr.com/en/sustainable-manufacturing-principles-applications-and-directions-2333598

Rogers, The Energy Savings Potential of Smart Manufacturing, (2014), American Council for an Energy-Efficient Economy, available via https://www.aceee.org/sites/default/files/publications/researchreports/ie1403.pdf

Overall Equipment Efficiency, available via https://www.oee.com/