###### Abstract  
Optimal buffer allocations can significantly improve system throughput by managing variability and disruptions in manufacturing or service operations. Organisations can minimise waiting times and bottlenecks by strategically placing buffers along the flow path, leading to a smoother and more efficient production or service delivery process. Determining the optimal size of buffers poses a challenging dilemma, as it involves balancing the cost of buffer allocation, system throughput, and waiting times at each service station. This paper presents a framework that utilises finite queueing networks for performance analysis and optimisation of topologies, specifically focusing on buffer allocations. The proposed framework incorporates a finite closed queuing network to model the intra-logistics material transfer process and a finite open queueing network to model the outbound logistics process within a manufacturing setup. The generalised expansion method (GEM) is employed to calculate network performance measures of the system, considering the blocking phenomenon. Discrete event simulation (DES) models are constructed using simulation software, integrating optimisation configurations to determine optimal buffer allocations to maximise system throughput. The findings of this study have significant implications for decision-making processes and offer opportunities to enhance the efficiency of manufacturing systems. By leveraging the proposed framework, organisations can gain valuable insights into supply chain performance, identify potential bottlenecks, and optimise buffer allocations to achieve improved operational efficiency and overall system throughput. b 202  
Supply chain mapping is considered an ideal tool for visualising the network concerning different layers across and through the system [6]. The supply chain mapping is developed for several reasons, including performance measurement [7,8], re-configurations to achieve continuous improvements [9], integration with technological advances [10,11], and the ability to foresee supply chain risks and challenges posed by natural disasters, geopolitical instabilities, and pandemics [12]. According to [PERSON] et al. [6] supply chain mapping can be developed to clarify information at different levels, and Figure 1 illustrates a classification of hierarchies of supply chain mappings according to the relevant domains and focus areas. Global value chain maps serve as valuable tools for organisations to position themselves within the global structure and gain an understanding of the industries and markets in which they operate [13]. These maps provide a macro-level perspective and offer a high-level understanding of supply chain systems. A supply network map encompasses the supply chains that make up an industry, including the roles of regulatory bodies and other facilitating institutions, to gain an overall understanding of the industry's structure [14]. Supply chain maps are subsets of supply network maps that provide greater visibility into each element, such as inbound and outbound logistics, making the organisation the focal point of observation [15]. Moreover, supply chain maps are developed to illustrate the flow of products and services from the organisation's perspective. Value stream maps (VSM) provide information on the material, and information flows throughout the different stages of production, culminating in the final delivery of the product to the customer. VSMs have become a popular tool under lean manufacturing systems to identify and manage non-value-adding activities in the production processes [16, 17, 18]. Process maps are a conventional mapping tool used to understand the sequence of processes or tasks necessary to produce one unit of product or service [19]. Industry practitioners use time and motion studies and process maps interchangeably.