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ABSTRACTCurrently, organizations in the manufacturing sector are exposed to high levels of competition and constant changes in consumer requirements. To survive in an increasingly competitive environment, it is essential to adopt new technologies to ensure success in a sector that is currently going through the fourth industrial revolution, associated with Industry 4.0 (I4.0). Additive manufacturing (AM) is one of I4.0’s technologies, which can produce products layer by layer, playing a key role in the innovation of business models. In this manner, organizations must integrate AM starting by understanding their maturity level, which allows them to reflect on weaknesses and strengths as well as opportunities for improvement. However, literature is currently lacking maturity models for AM. This paper proposes a maturity model for AM, which aims to help organizations in the manufacturing sector in determining their maturity level regarding the implementation of the AM. The model developed was validated theoretically. Also, a case study was conducted on an automaker, where it was possible to conclude that, despite the analyzed company has a high level of maturity regarding the technological deployment of AM, an AM’s strategy definition is presently missing.

Fire stations (FS) are typically non-uniformly distributed across space, and their service area is, in general, defined based on administrative boundaries. Since the location of FS may considerably influence the readiness and the effectiveness of the provided services, national and regional governments need research-based information to adequately plan where to establish firefighting facilities. In this study, we propose a method to reconfigure the fire stations layout using spatial point process models, clustering and space partitioning. First, modelling fire intensity variation across space through a point process model enables to replicate the process independently by simulation. Subsequently, for each simulation, the k-means algorithm is used to define a siting location, minimizing the total within distance between the fire occurrences and the new position. This method allows to obtain a set of locations from which the respective distribution is inferred. Assuming a bivariate normal spatial distribution, we further define confidence siting regions. Ultimately, new FS service areas are defined by Voronoi tessellation. To exemplify the application of the method, we apply it to reconfigure the fire station layout at Aveiro, Portugal.

Business Interoperability has become an indisputable reality for companies who cooperate and strive for competitiveness. Supply chain management is one kind of industrial cooperation that relies on large integration and coordination by interoperability factors, which until now is missing a tool to identify and solve its problems. The present article presents a systematic methodology applying axiomatic design theory and computer simulation to: study the impact of interoperability problems on dyad performance in terms of supply chain and interoperability; and the re-design of cooperation from the findings of the performance impact study. A case study applied in an automotive supply chain is presented to demonstrate the application of this method, mapping from the actual interoperability conditions (“as-is”) to a scenario that guarantees higher levels of business interoperability (“to-be”).