Abstract
PurposeThis study seeks to develop an Environmental Sustainability Balanced Scorecard (ESBSC) articulated through a strategic map for collaborative implementation by municipalities by municipalities. In addition, it aims to elucidate the architecture of this tool.Design/methodology/approachThe research uses qualitative methodology, initiating with document analysis, followed by municipal-level surveys and an interview with the Norte Portugal Regional Coordination and Development Commission (CCDR-N).FindingsThe study constructs an ESBSC that adopts an integrative approach to sustainability, focusing on municipal joint action. The tool fosters synergies and enhances cooperation. By incorporating a strategic mix, the tool contributes to improving the environmental management performance of the participating municipalities.Practical implicationsThis study introduces a tool designed for municipalities that aspire to incorporate environmental sustainability into their strategies. This tool facilitates the implementation and management of a long-term environmental strategy, with potential implications for organization and its culture. In addition, it highlights critical environmental factors that should serve as a starting point in future studies or applications of this tool.Social implicationsInvolving both an academic institution and multiple municipalities, this research identifies critical environmental factors that enhance environmental awareness within municipalities and designs a tool that, when consciously adopted, can influence the culture dynamics of the population involved. Furthermore, it proposes a structured and systematic research method for creating an ESBSC for joint municipal action.Originality/valueTo the best of authors' knowledge, this research constitutes the first exploratory attempt to devise an environmental strategy for joint municipal action. Although the tool emphasizes the environmental component, it promotes an integrated vision of sustainability. Despite the extensive application of balanced scorecards in various organizational contexts, their utilization in fostering environmental sustainability at a municipal level remains underexplored. This study addresses this gap by developing a tailored strategic tool that operationalizes environmental priorities within municipal governance frameworks.

Abstract
Although recent studies have recognised that sustainability and resilience should be considered part of the same efforts in the context of a transformative perspective, research combining both constructs is still scarce. This study adopts a comprehensive perspective that acknowledges that maintaining business continuity (through persisting, adapting or transforming), to reduce long-term risks is a common aspect of sustainability and resilience. It aims to identify strategies to be applied by companies and SCs in order to increase their social, environmental and economic sustainability, as well as their ability to be ready, respond and recover from unexpected events. Considering that the actions and strategies to deal with sustainability and resilience can be different and eventually paradoxical, this work applies the organizational ambidexterity approach as a theoretical background.

Abstract
This project focuses on the development and implementation of a Mini Learning Factory (Mini LF) 5.0, aligned with the principles of Industry 5.0, Cyber-Physical Systems (CPS), and Open Design. Industry 5.0 emphasizes human-centric innovation, fostering collaboration between humans and machines while promoting sustainability. CPS facilitates the integration of the physical and digital realms, enabling more agile and flexible production processes. Open Design plays a pivotal role by encouraging collaborative participation, transparency, and the democratization of knowledge, which leads to more personalized and sustainable solutions in product and service design. The research adopts the Design Science Research (DSR) methodology, involving problem identification, artifact development, evaluation, and iterative improvement. The goal is to create a replicable, low-cost training environment that equips students with practical skills in line with Industry 5.0's requirements. The Mini LF 5.0 also aims to explore new methods for human-machine interaction, collaborative communication, and sustainable production, while ensuring the technical and financial viability of the project for wider adoption. © 2025 The Authors.

Abstract
Two essential tasks in production planning and control are the generation and the release of orders to the shop floor. In this study order, generation is based on the Demand Driven Materials Requirement Planning system, while order release is based on the CONstant Work-in-Process system. Although the two systems alone have been extensively studied, their combination has received much less attention. In this paper, we address the problem of sequencing replenishment orders generated by the Demand Driven Materials Requirement Planning system to be released by the CONstant Work-in-Process system. Four pool-sequencing rules have been considered. Two of these are used by Demand Driven Materials Requirement Planning for establishing priorities for order planning and order execution. The other two are the First-Come-First-Served rule and a virtual due date rule. Results of a simulation study show that the rules proposed in the Demand Driven Materials Requirement Planning literature for planning and for execution are not the best options for pool-sequencing, particularly for restricted levels of workload allowed on the shop floor. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract
Purpose: This study addresses the development of a variant process planning tool, following the Knowledge-Based Variant Process Planning methodology, applied in a case study and presents the gains achieved. Methodology/Approach: Case study supported by six steps: (1) Feature Analysis, (2) Knowledge Retrieval, (3) Inference, (4) Plan Adaptation, (5) Knowledge Update, and (6) Plan Validation/Optimisation. Findings: The implementation of the Knowledge-Based Variant Process Planning tool led to significant improvements: planner time reduced by 70%, analyst workload by 90%, and process plan errors to 0%. Results show this approach significantly improves process planning in customised production. Research Limitation/Implication: The limitations are associated with the specificity of the case study problem-the electric engine production systems. Originality/Value of paper: This study helps fill the gap in case studies on the Variant Process Planning approach, specifically for electric engine production systems, paving the way for similar companies to adopt Knowledge-Based Variant Process Planning.

Abstract
Demand-Driven Material Requirements Planning (DDMRP) has been proposed as a solution for managing uncertainty and variability in supply chains by combining decoupling, buffer management and demand-driven planning principles. A key element of DDMRP is its inventory replenishment model, which relies on dynamically adjusted inventory buffers rather than fixed stock levels. However, parameterization of these buffers often involves subjective choices, raising concerns about consistency and performance. This paper assesses the DDMRP replenishment model through discrete-event simulation of a multi-echelon, capacity-constrained production system. Two alternative formulations of the safety stock term in the red zone are compared: the original factor-based approach and a revised formula that incorporates measurable variability coefficients. While both safety stock formulations yield similar numerical results, the revised formula enhances transparency and reduces subjectivity. Assessing the impact of introducing a buffer for components in addition to a finished goods buffer further shows that the components buffer can reduce finished goods inventory requirements while maintaining service levels. These findings contribute to a better understanding of the DDMRP replenishment model, offering practical insights for parameter selection and supply chain design.