Circular economy

Expert-Based Modular Simulator for Municipal Waste Processing Technology Design

One of the significant problems in our society is the handling and processing of the vast amount of waste produced by households and industrial processes. Nowadays, packaging material regulations are constantly changing, which can significantly impact the quality of municipal waste, requiring the continuous development and redesign of waste processing plants. Since only a few uncertain measurements (composition, mass, etc.) are available for this task, analysing and redesigning waste processing technologies is challenging. This research aims to develop a modelling and simulation concept that can integrate all the available information and can also handle the uncertainty of the measurements. The proposed modular modelling framework can serve as a basis for designing and redesigning the technologies needed to process ever-changing municipal waste. The most important steps of the framework are as follows: identifying the typical equipment, these are the elements; building models of the elements; determining the characteristic parameters of the equipment; exploring the possible relationships between the elements. For example, the information needed to define the model parameters can be gathered from measurements, industrial experience, and expert knowledge. In many cases, the data obtained represent ranges. The stationary model framework applies efficiency factors and divides the solids into substreams based on expert knowledge. Furthermore, a modular simulator framework was developed to simulate the technological schemes with various connections. The specifications for all widely used waste industrial equipment (shredders, air separators, sieves, magnetic-, eddy current-, optical-, and ballistic separators) were used to construct the developed simulator. This simulator can open new opportunities for the design of waste sorting technological networks. The model was calibrated based on expertise gained from operating the studied technology. The changes in the material parameters can be considered, and the modular simulator can lead to flexible waste sorting technologies capable of adapting to governmental and environmental regulations changes. The main result of the work is that a methodology for designing a modular simulator, model development, and a validation method has been proposed, which provides the possibility to deal with uncertainty. All this is successfully presented through the analysis of an operating waste separation system.

Post date: 08 December 2022

Information sharing in supply chains – Interoperability in an era of circular economy

In order to realize the goals of Industry 5.0 (I5.0), which has data interoperability as one of its core principles, the future research in the Supply Chain (SC) visibility has to be aligned with socially, economically and environmentally sustainable objectives. Within the purview of circular economy, this paper indicates various aspects and implications of data sharing in the SCs in light of the published research. Taking into consideration the heterogeneity of data sources and standards, this article also catalogs all the major data-sharing technologies being employed in sharing data digitally across the SCs.

Drawing on the published research from 2015 to 2021, following the PRISMA framework, this paper presents the state of research in the field of data sharing in SCs in terms of their standardization, optimization, simulation, automation, security and more notably sustainability. Using the co-occurrence metric, bibliometric analysis has been conducted such that the collected research is categorized under various keyword clusters and regional themes. This article brings together two major themes in reviewing the research in the field. Firstly, the bibliometric analysis of the published articles demonstrates the contours of the current state of research and the future possibilities in the field. Secondly, in synthesizing the research on the foundations of sustainability within the CRoss Industry Standard Process for Data Mining (CRISP-DM) framework, this article deals with various aspects and implications of information sharing in the SCs. By bringing these two themes together, this paper affords a prospective researcher with the research vis-à-vis the information sharing in SC, starting from the actual data standards in use to the modality and consequence of their application within the perspective of the circular economy. This article, in essence, indicates how all the aspects of data sharing in SCs may be brought together in service of the paradigm of I5.0.

Simulation of Sustainable Manufacturing Solutions: Tools for Enabling Circular Economy

At the current worrisome rate of global consumption, the linear economy model of producing goods, using them, and then disposing of them with no thought of the environmental, social, or economic consequences, is unsustainable and points to a deeply flawed manufacturing framework. Circular economy (CE) is presented as an alternative framework to address the management of emissions, scarcity of resources, and economic sustainability such that the resources are kept ‘in the loop’. In the context of manufacturing supply chains (SCs), the 6R’s of rethink, refuse, reduce, reuse, repair, and recycle have been proposed in line with the achievement of targeted net-zero emissions. In order to bring that about, the required changes in the framework for assessing the state of manufacturing SCs with regard to sustainability are indispensable. Verifiable and empirical model-based approaches such as modeling and simulation (M&S) techniques find pronounced use in realizing the ideal of CE. The simulation models find extensive use across various aspects of SCs, including analysis of the impacts, and support for optimal re-design and operation. Using the PRISMA framework to sift through published research, as gathered from SCOPUS, this review is based on 202 research papers spanning from 2015 to the present. This review provides an overview of the simulation tools being put to use in the context of sustainability in the manufacturing SCs, such that various aspects and contours of the collected research articles spanning from 2015 to the present, are highlighted. This article focuses on the three major simulation techniques in the literature, namely, Discrete Event Simulation (DES), Agent-Based Simulation (ABS), and System Dynamics (SD). With regards to their application in manufacturing SCs, each modeling technique has its pros and its cons which are evinced in case of data requirement, model magnification, model resolution, and environment interaction, among others. These limitations are remedied through use of hybrids wherein two or more than two modeling techniques are applied for the desired results. The article also indicates various open-source software solutions that are being employed in research and the industry. This article, in essence, has three objectives. First to present to the prospective researchers, the current state of research, the concerns that have been presented in the field of sustainability modeling, and how they have been resolved. Secondly, it serves as a comprehensive bibliography of peer-reviewed research published from 2015–2022 and, finally, indicating the limitations of the techniques with regards to sustainability assessment. The article also indicates the necessity of a new M&S framework and its prerequisites.