The Ecobulk Stakeholder Platform
The circular economy redirects waste streams to resources. But for others to make use of those new resources is a complicated coordination and information challenge – which requires deep connectivity and data integration. Therefore, you could say that digital technologies provide the basis for the development of circular business models.
Circular entrepreneurs need to have information about their products and their users. In a circular business model, quality of the service and customer satisfaction is determined not only by the quality of the physical product, but perhaps even more so by the quality of the digital service, e.g. the app through which the user can buy the product, share his feedback or see where the product can be found. The digital part of the business determines feasibility, usability and customer (or rather user) satisfaction.
If we want to strengthen and scale up the circular economy, there is a need to further integrate digital technologies like the Internet of Things, big data and artificial intelligence into existing circular business approaches to provide such services and information. More generally, digital transformation offers opportunities to the European industry for building competitive and innovative business models based on circular economy principles.
Ecobulk recognises this and that is why an entire work package was dedicated to developing the tools and systems that would be necessary for the circular flow of materials to happen.
Circularity and Complexity
When a product is nearing the end of its useful life, in a traditional model it is quite simple: the end-user disposes of the product and is not concerned with making choices about the fate of the product. One step beyond this, we have a recycling model where the user may need to make a choice on the means disposal according to some simple material separation rules. This can already be quite a burden. With circularity, where we strive to make recycling a last resort, there are many more choices and the decisions that must be made are therefore much more complex. That is why a stakeholder platform has been created that can help in making those decisions, but also to collect the information necessary to make the optimal decisions.
Decision Support System
The Decision Support System (DSS) is the system that combines the information and presents the end-user with the most likely options for their end-of-life products or materials. It considers four types of circular economy strategies: repairing, refurbishing, reuse and disposal. The system can give the users aggregated information about each alternative, helping in the decision process by calculating the economic costs and evaluating the environmental impacts of each of the possibilities. Since the user can choose from several criteria to include in the evaluation of the scenarios, finding the optimal result requires a multi-objective optimization algorithm based on a depth first search approach.
Several alternative repair scenarios can be defined, which consist of tasks performed on the material, resulting in a change of value based on the final achieved condition. The system takes into account work at different locations, and can include different impact factors and revenues.
Similar to repair, it consists of actions to be performed on the product. Additionally, a revenue can be defined to be considered during the evaluation. The main difference is refurbishment will typically upgrade or improve a function rather than restore one like in the repair scenario.
In this case, the user can select the new location of use and the revenue from the product. The evaluation of this scenario is made using only the impacts of the reverse logistics since no other task is being performed.
This case is similar to the previous one, with the exception that specific impacts of the product’s disposal are taken into consideration based on the disposal location (impacts stored in the database per disposal location).
After processing, the DSS will present a report which lists the impacts and costs, per location where appropriate, so that the user can make a more transparent decision. The system is also capable of providing the optimal path (from those available) for the product taking into account the selected criteria.
To get an idea of what this looks like, watch the video.
Quality Assurance System
The flow of products and materials from different locations increases the uncertainty of the quality and condition of those same products and materials. This is one of the critical challenges in the way of wider re-usability of materials and components at a higher level of value, as their structural and chemical properties are not as predictable and it becomes difficult to be sure that their performance is and will remain up to the level required. This is where a Quality Assurance System comes in.
The system can assess materials using a number of rules, each which consists of a number of tests that set the limits on particular properties. While there are a number of rules already defined, that are based on structural and safety standards, users can add their own according to their own needs. Even better, artificial intelligence techniques have been integrated that can infer rules from large sets of test data. This makes the system well suited and adaptable for different industries, as in the case of Ecobulk where it had to support the automotive, furniture and construction sectors.
Assessments can be done at different levels, from materials to products. Different batches of the same material can be compared to make sure they comply with the manufacturing requirements. But it can also be used the other way around, and filter the materials that would be suitable to use for a particular application by checking which materials pass all the necessary tests. This of course works together with the Materials database, which is discussed below.
Watch the video to see further details on how the QAS works.
Database - Materials Information
Both the DSS and the QAS depend on a database to get all of the information they need to process. This information comes from the Granta Materials Information database which houses all of the information on materials and products applicable at all lifecycle stages such as manufacturing, use, repair and recycling stages.
For the design and production stage, the database brings together information on different waste and raw materials, specific properties of material batches, the processes involved in production and any relevant test and quality data necesssary for the most appropriate choices to be made on which materials to use.
On the other side the database also keeps information on the components and products made from the materials, connecting this information to the end users and stakeholders so that the product can be tracked and information collected about its condition throughout its useful life and further lifecycle stages. By scanning the QR code of a product in the the stakeholder platform, end-users and other actors can access the information and respond to survey questions about the product condition which is stored in the database and can then be used by the DSS to choose the best course of action at end-of-life or by the QAS to determine the quality and usability of the products, components or materials at the next lifecycle stage.
So how does this database help in achieving circularity and better sustainability? From their own research, Granta has established that 80% of the LCC is determined already at the concept research stage of the product design process. Making the right choices at this stage is therefore critical to the end result. The database offers the designers all of the information they need to make sustainable as well as economically responsible choices for their projects.
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