Additive Manufacturing (AM) is no longer limited to prototyping, as it is gaining an increasingly large market share. With this expansion, there is a growing demand for the development of standardized rules to establish product specifications and verification procedures. AM offers unique opportunities in free-form shape design and multi-material processing, in contrast to traditional manufacturing processes and communication methods. Because of AM’s unique features, existing standards struggle to describe its product specifications. New regulations are therefore under development This paper reviews the state of the art in Additive Manufacturing (AM) product specification. This research examines the most up-to-date literature and standards published by the ISO, and ASME committees. A research gap has been identified in the accurate determination of design intent, which is crucial for defining product specifications. “Profile tolerance” is recognized as the most versatile specification for free-form geometries; however, new tools can be developed to control lattice structures. Additionally, the authors identified a significant gap in the assessment of dimensional and geometrical deviations in AM processes, as these are often estimated using geometrical benchmarks designed for subtractive technologies. Finally, verification remains one of the most critical aspects of AM products. Computed Tomography (CT) currently represents the only viable approach for measuring inaccessible features; however, standardized reconstruction methods are still lacking, as is a specification method tailored specifically for this measurement technique.

Geometrical Product Specification (GPS) plays a critical role in ensuring functional compliance, manufacturability, and verifiability across the product development lifecycle. Recent research has highlighted the evolutionary nature of specifications: from functional (FunSpec) to manufacturing (ManSpec), verification (VeriSpec), and contractual (ConSpec) documents; yet the allocation of clear responsibilities among stakeholders remains underdeveloped. This paper proposes the integration of the RACI (Responsible, Accountable, Consulted, Informed) matrix into the ISO GPS workflow as a structured means to clarify roles, responsibilities, and communication pathways across design, manufacturing, and quality assurance domains, therefore building upon the responsibility principle presented in ISO 8015. Starting from the specification document types presented in ISO/TS 21619 and the interaction between these document types, this study introduces a RACI-supported framework that maps stakeholder involvement to each stage of specification evolution. A possible implementation example demonstrates how the method enhances transparency, prevents overlaps or gaps in responsibilities, and supports compliance with industrial standards such as ISO 9001. The results suggest that embedding RACI within GPS workflows strengthens interdisciplinary collaboration, reduces ambiguity, and lays the foundation for responsibility-aware product specification management.

This study presents a genetic algorithm-based methodology for reconstructing the nominal profile of airfoils belonging to the NACA four- and five-digit series. By minimizing the geometric deviations between measured point clouds and parametrically generated airfoil profiles, the algorithm identifies the best-fitting nominal geometry. The approach was implemented using Rhino 8, Grasshopper, and the Galapagos plugin, and validated through extensive testing on 3D-printed samples. Across 200 test runs, the algorithm consistently identified the correct nominal geometry, demonstrating robustness despite inherent stochastic variability and computational challenges. The average number of iterations needed to converge was found to be 953 across all cases. This methodology offers a valuable tool for reverse engineering and metrological applications, providing a parametric and efficient alternative to traditional free-form surface reconstruction.

This work presents a computational framework for tolerance chain analysis based on multivariate statistical modelling accommodating both prescribed moments and correlations. The proposed method generates multivariate datasets matching either measured or proposed component characteristics, enabling realistic statistical virtual assembly. By using a transformed multi-variate Normal distribution, it is possible to represent the mean, variance, skewness, kurtosis, and covariance structure of the real parts' geometric variability. This allows tolerance propagation analysis that reflects actual manufacturing variability. Applications include predictive assembly simulations, functional tolerance optimization, and data-driven design verification in industrial contexts.

This work introduces the concept of variable-dependent admissible limits for tolerance stack-up analysis, where limits adapt based on geometrical and non-geometrical variables. Unlike traditional methods that assume fixed limits, the proposed approach integrates these dependencies into both variational and Monte Carlo analyses, enabling broader tolerances while maintaining functionality. A case study from the automotive sector demonstrates the methodology's effectiveness. This innovation shifts tolerance analysis from a purely geometrical to a functional domain, improving accuracy, reducing costs, and supporting compact and safe designs in industrial applications. (c) 2025 The Author(s). Published by Elsevier Ltd on behalf of CIRP. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

When pattern of fits are not designed following the boundary condition design criterion, the rejection rate due to failure in assemblability need to be considered. Since in a pattern of fits it is not possible to define an assembly equation it is not trivial to create a tolerance stack-up. The paper proposes a strategy to achieve a generalized rejection rate computation for nx patterns based on an interpolation model derived from Monte Carlo simulations. The rejection rate as function of the number of element in the pattern is simulated for different size and location tolerances. An exponential convergent function is fitted to the data and a generalize regression model is used to estimate the function parameters. Validation of the proposed methodology is provided. Moreover, future development are outlined.

The availability of foaming materials with properties that vary according to the heat transferred to the filament in the fused filament fabrication (FFF) process provides the opportunity to develop new design methodologies that allow the exploitation of the range of characteristics offered by these materials. In this work, an integrated CAD-CAM method to realize graded density foamed components via FFF is proposed. The method consists in the post-processing of a G-code file obtained from a CAD model according to functional requirements defined by a density map volumetric model. The method relies on the material propertyprocess parameters correlation to drive the foaming in a specific extruder configuration. The temperature effect on extrusion width and density is experimentally investigated as the primary process parameter driving the foaming behaviour of a commercially available filament. Based on the density map of the volumetric model and the experimental characterization, temperature and extrusion amount are updated in the G-code file. The method is applied to a simple buoyant 3D shape to ensure its orientation in water.

This paper focuses on the applicability of various new product development (NPD) models to small and medium-sized enterprises (SMEs) and the challenges they face, including limited resources, informal innovation systems, and difficulty obtaining external feedback. Traditional NPD models offer structure but may be too rigid for SMEs, while Agile methodologies provide flexibility but can be challenging to implement outside the software industry. Hybrid models, blending traditional and Agile approaches, offer a good compromise. Through comparative analysis, the study evaluates the strengths and weaknesses of different NPD models in the SME context. By utilizing modern technologies like additive manufacturing and artificial intelligence, the NPD process can be accelerated, aligning with Agile principles to provide faster feedback and enhance overall efficiency. In conclusion, SMEs are encouraged to consider hybrid solutions to innovate and compete effectively. Future research should address specific challenges in different industry sectors and focus on scalability.

In product design and development, achieving the desired performance requires meeting specific product requirements within defined boundaries. These requirements are encapsulated in the Product Definition Dataset, which consists of two key models: the Nominal Model and the Specification Model. The Nominal Model outlines the product’s properties, features, and relationships, while the Specification Model defines the targets, boundary conditions, requirements, allowable variation, and interrelationships essential for meeting these targets. This study focuses on the relationships between variable quantities and the limits set by geometrical product specifications. Currently, the limits defined within geometric specifications are considered static, excluding maximum and minimum material conditions. This implies that each variable is treated independently, meaning the actual state of one variable does not influence the functional limits of others. However, in actual parts and assemblies, variable quantities do affect each other, as they are not independent. In this paper, we explore the link between specifications and the variables they define through a case study, with the aim of fulfilling product requirements more effectively. By establishing these connections, it becomes possible to produce functional parts with greater allowable variation and reduced costs, while ensuring that specifications are grounded in actual performance requirements and physics. This approach aims to enhance the flexibility of product manufacturing and streamline the process of meeting both functional and cost-related objectives.

This study aims to define the assembly shift for "nx" fit patterns, considering scrap and the influence of increasing elements. The methodology includes rejection rate estimation via Monte Carlo simulation, gap distribution estimation, and assembly shift computation based on gap distribution. It also proposes a design methodology for dimensioning tolerances to meet assembly shift requirements. Results show narrower assembly shift distributions with more pattern elements, revealing an exponential relationship. A case study based on a real application demonstrates how the proposed methodology can be applied to actual industrial cases.

This study introduces a numerical methodology for computing the statistical assembly shift in patterns of fits, addressing scenarios with variable numbers of elements and scrap caused by assembly failure. Using Monte Carlo simulations, the methodology estimates rejection rates, determines gap distributions, and calculates assembly shifts while considering both intrinsic and external datum systems. The findings indicate that adding more elements to a pattern reduces assembly shifts exponentially, presenting a design opportunity to control alignment and optimize component performance. A case study involving engine block and cylinder head alignment demonstrates the methodology’s applicability to real-world mechanical design. Three approaches for tolerance stack-up are evaluated: the standard Root Sum Square (RSS) method, where assembly shift is treated as a worst-case scenario; a proposed RSS method that models the assembly shift as a Gaussian distribution with a standard deviation derived from Monte Carlo simulations; and the Monte Carlo approach, which considers the full shape of the assembly shift distribution. By comparing these approaches, the study underscores the effectiveness of the proposed methodology in capturing the statistical behavior of assembly shifts. This work contributes a robust tool for tolerance analysis, advancing the precision and accuracy of pattern fit modeling and assembly shift evaluation in mechanical design.

This paper presents a novel metrological approach for the functional geometric characterization of lifting airfoils, utilizing an Iterative Closest Point (ICP) algorithm to assess deviations in camber, thickness, and form. Traditional geometric specification methods, such as line profile tolerances, often fail to capture the full impact of geometric deviations on airfoil performance. In response, the proposed methodology addresses this limitation by linking airfoil geometry more closely to functional requirements. The new methodology was validated using synthetic datasets and real-world data, demonstrating robustness in the absence of noise and highlighting areas for improvement in noise handling. The findings suggest that the ICP-based method is a valuable tool for airfoil manufacturing, enhancing conformity checks against design specifications. This study opens pathways for more accurate tolerance synthesis and enhanced quality control in the production of lifting airfoils.

Additive manufacturing components are prone to defects, including warping and cracking, which can significantly impact their mechanical performance. Determining deformations in lattice structures remains challenging. This paper presents a methodological framework for computing deformation matrices in additively manufactured lattice samples using 3D scanning. The sample's geometry is acquired through 3D scanning, registered to a reference model, and vertices are determined and used for computing deformation metrics, including volumetric scaling factors, isovolumetric scaling, and angular deformations. A sensitivity analysis comparing four association criteria demonstrates the reliability of the Gaussian Best Fit Plane External. Assessing deformation in lattice structures can be useful for optimizing printing parameters and compensating for process-induced deformations. Future work will extend this methodology to evaluate deformations during post-processing and develop mesh morphing strategies for generating printing geometries.

Multi-material additive manufacturing enables the opportunity to combine multiple materials within the same part, allowing for an expanded range of properties that can gradually change inside the design space. This category of materials is commonly referred to as functionally graded materials (FGMs). However, FGMs currently face several limitations and challenges in terms of design and manufacturing, such as compatibility, distribution design, and prediction of mechanical properties. Furthermore, when dealing with parts possessing complex micro/meso-structures, finite element simulation often becomes a costly and time-consuming process. Among various additive manufacturing technologies, fused filament fabrication allows the combination of multiple thermoplastic materials within the same nozzle during the deposition process, thereby creating FGMs. This process, known as coextrusion, enables the gradual deposition of materials adjacent to each other while changing their fractions. Moreover, the deposition direction shapes the distribution of materials within each deposited layer, influencing the material structure and the resulting mechanical properties. A recent study proposes a preliminary model describing the deposition mechanism, which has been confirmed by experimental tests. This model delineates the section of the material deposited based on the tool path and process parameters, such as layer thickness and hatching space. To expand upon these findings, this paper applies a homogenization approach based on finite element analysis to the deposition model. This approach enables the description of material mechanical properties based on the material fractions, tool path, and other process parameters. Additionally, this study presents a methodology to tailor the mechanical properties according to the printed part's orientation around the print bed.

In tolerancing activities focusing on the allocation of geometrical tolerances, many critical issues originate from the non-optimal assignment of responsibilities among the organization units involved. This paper aims to depict relations between different tolerancing activities and relevant specifications, assigning them to the proper actor and, therefore, expanding the ISO 8015:2011 “responsibility principle”. A classification among tolerancing activities, specifications, and media is proposed; a horizontal hierarchical framework among functional, manufacturing, and verification specifications and a vertical hierarchical framework along the supply chain are discussed. Examples of both hierarchical structures are presented.

This research consists in a detailed analysis of the ISO Geometrical Product Specifications (GPS) system's knowledge and usage in Italy. Data was collected by means of a questionnaire, from a wide range of industrial sectors and academic institutions. The dataset encompasses 143 responses, forming the basis for an in-depth examination of ISO GPS system implementation in Italy. This analysis involves three levels of comparison: (1) an examination of knowledge level and typical usage between Beginners and Experienced individuals, (2) an investigation into ISO GPS adoption patterns in Industry and Academia, with and without specific ISO GPS training, and (3) an exploration of differences among professionals who are responsible for conveying geometric specifications and those in charge of interpreting and applying them. The findings reveal significant insights into ISO GPS implementation in both academic and industrial domains. They highlight the need for the improvement of ISO GPS education offer and the development of more effective utilization practices, with potential implications for future ISO GPS standards development strategies.

The precision livestock farming (PLF) has the objective to maximize each animal's performance while reducing the environmental impact and maintaining the quality and safety of meat production. Among the PLF techniques, the personalised management of each individual animal based on sensors systems, represents a viable option. It is worth noting that the implementation of an effective PLF approach can be still expensive, especially for small and medium-sized farms; for this reason, to guarantee the sustainability of a customized livestock management system and encourage its use, plug and play and costeffective systems are needed. Within this context, we present a novel low-cost method for identifying beef cattle and recognizing their basic activities by a single surveillance camera. By leveraging the current state-of-the-art methods for real-time object detection, (i.e., YOLOv3) cattle's face areas, we propose a novel mechanism able to detect the ear tag as well as the water ingestion state when the cattle is close to the drinker. The cow IDs are read by an Optical Character Recognition (OCR) algorithm for which, an ad hoc error correction algorithm is here presented to avoid numbers misreading and correctly match the IDs to only actually present IDs. Thanks to the detection of the tag position, the OCR algorithm can be applied only to a specific region of interest reducing the computational cost and the time needed. Activity times for the areas are outputted as cattle activity recognition results. Evaluation results demonstrate the effectiveness of our proposed method, showing a mAP@0.50 of 89%. (c) 2022 China Agricultural University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Robotics is affecting more and more different sectors. In particular automation of agricultural processes could bring several advantages by reducing waste and human effort, that's why several robots to perform a wide range of agricultural tasks are in development. However, the design of a multi-purpose robot for vineyard operations presents still some challenges like its hardware adaptability and compatibility. To tackle some of these challenges, this paper presents the conceptual design of a modular autonomous mobile robot for vineyard operations. The aim of this work is to provide design principles for a modular robot able to perform multiple tasks that are common for vine growers, such as green pruning, winter pruning and spraying. The main advantages of such a robot are multiple. First, it can be considered eco-friendly as it can reduce chemicals consumption, polluting emissions and soil compaction. Second, it can minimize the need for manpower, that means less repetitive tasks to be done and less exposure to chemicals. Finally, its modularity can allow to easily switch tools and to re-design some modules with little changes to other features. For designing this system, we adopted a design thinking approach. Thus, first requirements and concepts were created and evaluated via interviews of vine growers. Second, concepts were classified upon the evaluation. And last, the winning prototype was designed with Solidworks CAD software and evaluated on its mechanical and functional properties via a FEM analysis. By using this method, we have developed an initial design for a multipurpose robot that concentrates on the drive system and the serial hybrid powertrain design, the selection of the structure, the tool design, and their incorporation with the frame, as well as an initial estimation of the mass to conduct a preliminary FEM static analysis of the frame. As a result, we have evaluated the feasibility of the concept and identified the key features of all subsystems. Therefore, this study lays the groundwork for creating a versatile and effective robot that can be used for multiple vineyard operations.

This paper proposes a tool to analyze the diffusion and knowledge of the ISO GPS language in both industry and academia. A survey has been designed based on the maturity model concept to achieve this goal. Six Key Performance Indicators (KPI) arguments have been defined: general concept, datum systems, geometric tolerances, dimensional tolerances, modifiers and indications, and tolerance stack-up. Per each of these, three assessments are proposed, and a rating is given based both on self-assessment and unbiased check questions. The result is a survey that takes between 10 to 15 min to be filled out. The assessment is based on both knowledge and usage. The defined survey, through testing, proved to be a simple and usable tool to test the actual diffusion and knowledge of the ISO GPS language thanks to its shortness and the different levels of analysis it allows.