Manufacturing systems across industries are increasingly exposed to uncertainties that threaten their resilience and competitiveness. To address these challenges, manufacturers are integrating digital and smart technologies into production processes to enhance system intelligence, predictability and reconfigurability. However, many legacy (brownfield) systems struggle to leverage these technologies effectively. This paper adopts a systems engineering perspective to compare the concepts of frugal, resilient, and smart systems, aiming to identify the requirements for designing resource-efficient and adaptable manufacturing systems. Building on this conceptual foundation, a method for mapping and visualization of essential functions within brownfield systems is introduced. It enables the identification of minimal reconfiguration efforts needed to maintain performance under uncertainty. An illustrative example shows the application of the method to brownfield assembly systems, supporting strategic interventions for resilience enhancement. The work provides both a conceptual framework and a practical tool to support resilient reconfiguration and resource-efficient operation in manufacturing.

Discrete manufacturing companies are challenged to transform their existing manufacturing system to be better prepared for the changes caused by unstable supply chains and new market regulations. Reconfigurable Manufacturing Systems is a manufacturing paradigm conceived to deal with change in a fast and cost-effective way. Most of the design methods for such recon-figurable systems do not take the information of existing manufacturing systems into account. Thus, this paper proposes a method to generate reconfigurable manufacturing alternatives from legacy factories' information. The proposed method uses the bill of materials and the initial production capacity as inputs. The potential use of the proposed method is demonstrated with an illustrative example.

Traditional manufacturing paradigms cannot deal with the current pace of uncertain events in demand, supply and beyond. Reconfigurable Manufacturing Systems (RMS) are designed to adapt to these challenges in a rapid and cost-effective way. In order to decide when and how to reconfigure an RMS, it is necessary to identify the external events which trigger change in the system. This paper proposes a framework for uncertainty representation in RMS based on three levels of uncertainty and decision horizons. An illustrative example shows how such framework can be used by researchers and practitioners to better understand RMS and its context.