Digital Product Passports |
Enabler of the circular economy
| Journal | Industry 4.0 Science |
| Issue | Volume 40, 2024, Edition 3, Pages 73-77 |
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Abstract
Keywords
Article
In the context of increasing sustainability efforts at both legislative and societal level [1], the reduction of greenhouse gases and energy consumption as well as the thorough use of resources are key challenges in the context of industrial production [2, 3]. Digital Product Passports (DPPs) are increasingly becoming mandatory in various sectors to adequately monitor corresponding statutory savings targets, for example as part of the EU Sustainable Products Initiative [4, 5].
At the same time, these savings targets are difficult to achieve through exclusively linear production [6]. Innovative production strategies such as the circular economy make it possible to save significant amounts of carbon emissions and energy [4, 7]. Remanufacturing in particular offers a high savings potential as a possible circular strategy, as it enables the retention of value added in end-of-life products on an industrial scale [8].
However, due to complex production and value creation processes, efficient remanufacturing often lacks detailed data crucial for successful implementation, such as the original product manufacturer or product type [9]. To efficiently utilize the emission and energy-related benefits of remanufacturing or a circular economy, DPPs are therefore seen as a fundamental prerequisite for overcoming these uncertainties. They enable a seamless and transparent exchange of information between the various network partners in the supply chain [10].
Despite their high potential in the context of increasing the transparency of the carbon footprint of individual products and enabling the circular economy, the practical implementation of DPPs is associated with various problems. In particular, the lack of technical standards leads to difficulties in the integration of corresponding DPPs, especially for small- and medium-sized enterprises.
This article therefore presents a framework for the systematic introduction and purposeful use of a DPP that enables a standardized and interoperable exchange of emissions and energy data along the entire product life cycle. The data collected during the product life cycle on a horizontal and vertical level forms the basis for the development of an evaluation system that can analyze products at the end of the first life cycle regarding various circular strategies using the information contained in the DPP.
The results of the evaluation also enable action recommendations to be derived for the efficient management of the entire production network. The DPP can therefore serve as a basis for the targeted planning and management of production networks, which can be used to reduce carbon emissions, improve energy consumption, and reduce costs.
State of the art
Even though the manufacturing industry in Germany, for example, has already reduced its greenhouse gas emissions by 41.1% compared to 1990 [11], industrial production is still one of the major greenhouse gas emitters [12]. To achieve further progress in emissions reduction and energy efficiency, the relevant topics are therefore being discussed intensively in the literature.
Various initiatives and approaches deal with the consideration of carbon emission data in the production network, especially in the context of systematically increasing transparency and improving the carbon footprint through the use of digital technologies. Current approaches and initiatives, such as Catena-X in the automotive industry or Together for Sustainability in the chemical industry, focus on the standardization of carbon emission data calculation, standardized platforms for data exchange and communication formats [13]. Other projects, such as GAIA-X4ICM [14], use DPPs in the context of carbon emission accounting to collect emission data over the life cycle and save it using the asset administration shell.
However, such approaches are often sector-specific and vary in terms of actors, roles and functions [15]. Additionally, although they increase transparency through their holistic collection of emission data along the product life cycle, they neglect potentials for enabling the circular economy. The practical implementation of the circular economy is also impeded by the lack of traceability of individual products, which is essential for the efficient return, identification and processing of end-of-life products [16]. DPPs that consider all levels of production, especially in production networks, can overcome these hurdles.
Solution approach
In the following, a framework for the systematic implementation and use of DPPs in the context of the circular economy is described. The framework comprises four successive implementation steps.
Development of a cross-network partner DPP
To ensure a seamless exchange of product information between different parties in the value chain, as shown in Figure 1, a data model must be defined that maps several product generations across networks in a DPP. With the help of a suitable data model, information from production networks, including suppliers and customers with all direct and indirect sustainability and energy data, can be reproduced via a DPP with an integrated carbon footprint. This requires the transparent mapping of all emissions generated along the manufacturing process. While these can be recorded directly at machine level using sensors, for example, especially indirect emission data must be allocated to individual products.
For this purpose, a calculation logic must be developed that allows a holistic mapping of the carbon footprint of a product, which is a central component of the DPP. The data model should also integrate the classes Product, Process and Resource in a circular context, in that the Product class has a self-referencing property that refers to the Process and Resource. This makes it possible for a product in the next generation to refer to its previous version at the end of a product life cycle and for sustainability and energy data to be stored in a DPP across generations.
Technical implementation of the data model and data exchange based on the asset administration shell
To integrate the data model into an executable environment, it must first be possible to link and store data across company boundaries. Although there are various technical solutions for this, such as decentrally stored permissioned blockchains or tokenized DPP using public blockchains, the data exchange format of the asset administration shell is particularly suitable for cross-company use due to its standardization and interoperability.
Corresponding asset administration shells can be managed using a middleware [17], which offers, among other things, a direct interface to sensor and OPC UA data. This means that machine data can be received directly and then be transmitted to the appropriate, product-specific asset administration shell. Asset administration shells can also be retrieved, created, updated or deleted from the client side via REST API. This makes it possible to integrate the classes of the data model into specific asset administration shells with attributes.
This means that DPPs can be used interoperably in the form of the asset administration shell and maintained across networks, for example via simple browser applications. In addition to the carbon footprint, other relevant properties of a DPP, such as information about the manufacturer, can be integrated as attributes of corresponding asset administration shells.
Use of platforms for secure data exchange
A suitable platform is also required to ensure the secure exchange of data between network partners. The implementation and use of a suitable platform includes a requirements analysis, the creation of a specification in the form of a functional specification, the design phase to define the software architecture, the implementation of the platform as well as testing and validation. The virtual ecosystem developed as part of the Catena-X initiative, for example, is a suitable blueprint and reference for cross-sector data exchange[18].
Evaluation of circular strategies and intelligent generation of recommendations for action based on the DPP
In addition to a significant increase in transparency, the life cycle data of a product contained in the DPP can be used, particularly during the end-of-life phase, for example to derive recommendations for circular strategies using machine learning. To this end, the individual attributes of the DPP serve as features for the machine learning models, which are optimized with regard to various aspects of sustainability and cost-effectiveness. Based on corresponding recommendations for action, these can be used as a starting point for network and production control.
Outlook
In summary, the framework presents an opportunity for companies to use DPPs to increase transparency about the sustainability aspects of their products. Standardized data exchange formats such as the asset administration shell can be used for this purpose, which can be used to store and share production and product data across companies. Furthermore, the product and production data collected along the product life cycle within the DPP are suitable for the targeted derivation of suitable strategies for circular production.
In addition to the product’s condition, its area of use and origin as well as the current resource consumption of the circular value creation system also determine the selection of a suitable circular strategy. The developed approach can, for example, be transferred into a digital assistance system that supports companies in determining the appropriate circular strategy and thus enables the transition to a circular economy.
This article was created as part of the project “CliCE-DiPP – Climate-neutral Circular Economy enabled by Digital Product Carbon Pass (Grant number: 01MN23023G)”.
Bibliography
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