![]() Step 2- Define the set of relationships among CMS stakeholder-agents Thus, this modelling approach can be employed to capture continuous system behaviour. Whereas, stock and flow diagrams represent an advanced construct in SD modelling used to simulate continuous processes where stocks represent accumulations (e.g., stock of material, products, money) and flows define how these stocks change over time. Thus, for stakeholder-agents where manufacturing, logistics, and reprocessing activities are relevant (e.g., manufacturers and service providers), one can best characterize their behaviour by employing DE process flowcharts. Process flowcharts are an advanced construct in DE modelling used to adopt a process-centric view of the system. Thus, for stakeholder-agents where event- and time-ordering of operations is very pertinent (e.g., customers), one can best characterize their behaviour by employing AB statecharts. Statecharts are an advanced construct in AB modelling used to simulate event-driven and time-driven agent behaviour. Given the heterogeneous nature of the CMS stakeholders, an AB statechart, a DE process flowchart, an SD stock and flow diagram, or a combination of these modelling constructs are employed to simulate the behaviour of each CMS stakeholder as shown in Fig. 1. The set of CMS stakeholder-agents consists of all relevant value chain stakeholders involved in achieving circularity as an overall outcome (e.g., suppliers, manufacturers, service providers, customers, and value recovery entities). The first step in building the CMS multi-method simulation model consists in defining the set of CMS stakeholder-agents and their behaviours. Step 1 - Define the set of CMS stakeholder-agents and their behaviours The term agent represents a stakeholder in the circular value network placed in a Geographic Information System (GIS) space. Multi-method simulation modelling of circular manufacturing systems. In addition, as a simulation development platform that supports AB, DE, and SD simulation methods is needed to implement and reproduce the CMS multi-method simulation model, this paper provides the detailed procedure to construct the computer program using the case study of a white goods manufacturer. Anylogic data set function how to#This paper provides a step-by-step approach on how to build a CMS multi-method simulation model using the multi-method model architecture proposed by the authors in Roci et al. Thus, this approach allows for characterising and analysing CMS by modelling the system as a collection of autonomous decision-making entities with their own behaviours and relationships. By considering CMS as a complex value network composed of many stakeholders engaged in achieving circularity as a collective outcome, the authors proposed a multi-method model architecture where the different CMS stakeholders are modelled individually as autonomous agents using AB, DE, and SD modelling methods. a multi-method model architecture to model and simulate CMS. As different multi-method model architectures can be built by combining the different modelling approaches, the authors presented in Roci et al. Thus, multi-method simulation modelling is considered more suitable to model and simulate CMS as it allows to capture their complex and dynamic nature. Multi-method simulation modelling, i.e., a combination of the aforementioned simulation modelling methods, provides a higher level of flexibility for modelling and simulating complex systems as it allows to take into account the complementary capabilities and recognize the limitations of each modelling method. Moreover, SD deals with continuous processes, whereas DE and AB work mostly in discrete time, i.e., the system has state changes in discrete points of time. SD is mostly employed for strategic modelling as this modelling approach operates at a high abstraction level DE takes a process-centric view of the system and supports medium and medium-low abstraction whereas AB takes a decentralized and individual-centric approach to the system by describing the system as interacting objects with their own behaviours. The major simulation modelling paradigms employed to simulate complex systems are system dynamics (SD), discrete-event (DE), and agent-based (AB). Complex systems modelling and simulation is becoming an increasingly popular approach to analyse the behaviour of complex systems as this approach allows to capture non-linear behaviour as well as time and casual dependencies. These systems can be viewed as complex adaptive systems composed of an interconnected network of a large and diverse set of stakeholders that collaborate to close the loop of products through multiple lifecycles. Circular manufacturing systems (CMS) refer to systems that are designed intentionally to close the loop of materials and products through multiple lifecycles. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |