# Sampling-Based Path Planning Algorithm for a Plug & Produce Environment
## 1 Introduction  
With the ever-increasing market demand for the mass customization of products, industries are keen to adopt smart factory technologies with digitalization strategies and following the standards of Industry 4.0 [1]. For the adaptation of Industry 4.0, one of the trends in the manufacturing sector is flexible manufacturing systems. Manufacturing facilities designed for dedicated production in various industries encounter problems when transitioning to accommodate customization. It is difficult to accommodate customized products with low-volume production based on individual customer needs [2]. These traditional dedicated manufacturing systems are time-consuming to alternate, often taking months to reconfigure the manufacturing to accommodate the customized products [3]. Again, when the product specification is changed, then industries must go through the entire reconfiguration again, meaning major investment costs are necessary for reconfiguration, which may be hard to motivate, whereas the flexibility of concepts like Plug & Produce (P & P) will reduce the cost and time of a redesign or reconfiguration, thereby allowing for quicker response to the customers and providing customized products with increased performance [2]. Flexibility can be brought into the production system in several ways, i.e., product flexibility, manufacturing flexibility, hardware flexibility, and enterprise flexibility. Product flexibility means addressing the ability of the manufacturing systems to accommodate product variants within a family of products [4]. Manufacturing flexibility plays a major role throughout the entire life cycle of manufacturing systems, and itcomes into role mainly because a new product or a product variant is introduced in the manufacturing process [5]. Hardware flexibility means the reuse of a process module for various purposes and scenarios, which contributes to more sustainable manufacturing industries [6]. Enterprise flexibility is how fast the enterprise responds when the market changes, meaning introducing new products based on market fluctuations [7]. The cost of flexibility depends on two major factors, i.e., the setup cost and competence. Setup cost depends on how much time it takes to adapt all programs to the changes in manufacturing, the time taken for planning the operation, product design, and hardware and software configuration. Competence is the cost and need of in-house knowledge and external competence. In flexible manufacturing systems [8], reconfiguration of the production can be changed in a shorter time and mostly with in-house knowledge and competencies. To become more flexible and smarter, industries are adapting reconfigurable manufacturing systems (RMS) [9], meaning that the user can customize their product with various options, the industries do not require higher investment costs for the customization, and it can be achieved by changing the configurations in modular-based systems. Modular-based systems are working based on the Plug & Produce concept [10]. In such systems, any kind of manufacturing setup can be plugged into the process as a module. The newly plugged-in module adapts to the situation automatically based on the configuration and starts to commence its work to contribute to the manufacturing process. The modules are highly flexible and sustainable, which means that they can be exchanged between the manufacturing stations and reused in another manufacturing section. RMSs can be hardware- or software-configured systems. Hardware-reconfigurable systems are the modules in the system that can be plugged in and plugged out with different configuration specifications for each module. These plugged-in modules can be integrated easily with the current ongoing production with simple instructions. In the multi agent systems, the path planner can be configured as an agent [11]. On the other hand, software-reconfigurable manufacturing systems are addressed through the configuration tool of multi-agent systems (MAS) and the details described in [12].