Opportunities and Challenges of Industry 4.0 Technologies for Scope 3 Emissions Savings in SMEs
Emissions along the upstream and downstream value chain (Scope 3) are becoming increasingly relevant for companies against the backdrop of climate change. This is because, due to globalization and outsourcing, companies not only cause greenhouse gas emissions within the company but also outside the company; e.g. through the purchase of goods and services. Particularly in the case of companies that are close to the end customer, emissions of up to 90% can occur in the Scope 3 area. After recording and calculating (carbon accounting), the main task is to reduce these emissions. The following article deals with the savings potential of Scope 3 emissions and discusses them in the context of Industrie 4.0 technologies. Therefore, the following technologies Virtual (VR) and Augmented Reality (AuR), Big Data Analysis (BDA), Artificial Intelligence (AI), Autonomous Vehicle (AV), Additive Manufacturing (AM), Internet-of-Things (IoT), Advanced Robotics (AR), Drones and the Blockchain (BC) were analyzed for their use case and prerequisites as well as their challenges and potentials.
Requirements
The most important prerequisite needed for all technologies is a stable, reliable, and resilient data infrastructure.
The effort required to implement and integrate the technologies varies depending on the technology (see Figure 1) and correlates with the complexity of the corresponding technology.
Use Cases
Virtual Reality and Augmented Reality (6)
Virtual reality (VR), a computer-generated environment that gives the user the feeling of being immersed in a completely immersive environment with the help of VR goggles, makes it possible to carry out training or remote-controlled maintenance. In addition, the technology is suitable for process optimization and for testing and introducing changes in a resource-saving manner. Using augmented reality (AuR), in which virtual 3D objects are embedded in a surreal environment, training, and education as well as remote-controlled maintenance can also be supported and carried out independent of location. A prerequisite for VR and AuR is a stable and reliable data infrastructure and equipment for both participating sides. If this is in place, the technologies enable better integration and coordination of the stakeholders involved (customers, trading partners, or suppliers) and, due to location independence, increased efficiency and a direct impact on the possibility to save Scope 3 emissions, as less business travel and commuting is required (see Table 2).
Big Data Analysis (6, 8)
Big Data Analysis (BDA) can be used to generate and analyze large data sets containing data from the point of origin to the point of consumption. The data obtained can be used in environmental controlling to improve forecasts and facilitate the identification of risks. The prerequisite and challenge here is the required data infrastructure as well as the data extraction. For example, trust between the various stakeholders, such as suppliers, is necessary to enable the required collaboration and data sharing with uniform data standards, while taking data protection into account. If these barriers are overcome, BDA offers the potential to improve coordination among stakeholders and can also support other new Industrie 4.0 technologies, such as AI, AV, and IoT.
Artificial Intelligence (6)
Artificial intelligence (AI), the imitation of human intelligence using computers and computing power, can help in the automated generation of environmental risk forecasts. In this regard, AI can be supported with data from the BDA and BC. Challenges of this technology are the data infrastructure required for this with powerful computer architecture as well as secure digital storage technology. It is currently still associated with high costs. In addition, the lack of trust and motivation to have AI perform processes previously performed by humans must be overcome. If this succeeds, AI offers the potential of optimized inventory recording and placement, thus achieving increased energy efficiency and optimal resource utilization. Thus, artificial intelligence can also be used to directly influence scope 3 emissions.
Autonomous Vehicle (6)
Supported by cameras, sensors, and AI, it is possible to drive vehicles without human influence. The Autonomous Vehicle (AV) offers a new way of goods / and warehouse management with the transport of goods on factory sites and/or delivery. They offer a large potential for scope 3 emissions savings, as they lead to a reduction in transportation costs and fuel consumption, due to the optimized use of resources through AI. In addition, more sustainable warehousing can be achieved through less traffic and consequently less stress for people. However, the introduction of the technology is associated with high costs due to the technical equipment and a lack of knowledge and skills which must be overcome. AV can also be supported by BDA, IoT, and advanced robotics.
Internet of Things (1, 6, 8)
The Internet of Things (IoT) is about networking devices and objects that can communicate with each other via the Internet and exchange data without the need for human interaction. This can be used, for example, to create smart buildings, networking of room- and building-controlling systems, or smart grids, demand-driven control of energy supply. In addition, many other Industrie 4.0 technologies, such as AV, BDA, AI, CC, and BC, benefit from the data. A prerequisite for smooth data transfer is a stable data infrastructure in which the cost-intensive sensor and meter hardware is integrated. IoT then offers great potential to reduce scope 3 emissions. Real-time tracking and more accurate forecasting can be used to better control waste and avoid overproduction. It also facilitates transportation and stocktaking through smart products.
Advanced Robotics (1, 2)
Advanced Robotics technology (AR), uses robots that can accept commands and implements them optimally with the help of artificial intelligence. They can react to changing environments, e.g. obstacles, and make decisions to solve their task in the most resource-efficient way. In addition, they can take on complex tasks as well as be used for dangerous or highly physically demanding tasks, thus increasing safety for the worker. This requires a reliable and stable data and hardware infrastructure, which is associated with high costs. In addition, like AV, the technology struggles with a lack of trust and ability to implement it. It offers the potential to reduce costly labor hours and contribute to a safer work environment. In addition, with its increased efficiency, it leads to savings in energy, waste, and resources, and therefore immediate savings in Scope 3 emissions.
Drones (6)
Drones are autonomous or remote-controlled flying objects that, equipped with additional sensors and cameras, can collect data during goods/warehouse transport or last-mile transport and thus support BDA or BC. Challenges of this technology are currently the still high costs and the lack of trust in the technology. However, it offers the potential to shorten delivery times and reduce transportation costs and also has a direct impact on Scope 3 emissions with lower energy costs.
Blockchain (1, 2, 6)
Blockchain technology (BC) is a distributed database technology that enables transactions between parties to be tracked and validated securely and transparently. It is used in certification or proof of origin of CO2 products or other emission goods. It can be supported by CC, IoT, or AI. The prerequisite for exchanging data and certificates is a stable and reliable data infrastructure. In doing so, it facilitates collaborations between SMEs, increases the accuracy, transparency, and security of transactions, and improves carbon footprint measurement. Due to the improved monitoring, areas with a high output of Scope 3 emissions are quicker and easier to identify. Thus, blockchain technology has an indirect impact on scope 3 emissions.
Cloud Computing (2, 3, 5, 7)
Cloud computing (CC) is used in environmental controlling and compliance as well as for environmental clouds to support AI. Here, the term cloud refers to a collection of data centers from which different applications can be accessed via the Internet, and thus data can be accessed from different points. This means that a separate server infrastructure is no longer required at each location, but only a central server facility. This means that the CC can be used to create a resource-saving infrastructure and save Scope 3 emissions with increased efficiency. Stable data infrastructure is a prerequisite for this, as is the appropriate hardware and knowledge of data protection and information security. In addition, other technologies such as VR, AuR, AI, IoT, and BC can be supported.
Combination of various I4.0 technologies
In addition, the technologies can complement each other and be applied in combination. Common combinations are listed in Table 1.
References
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