Search results

This paper aims to propose a new framework on prioritizing and deployment of design for additive manufacturing (DfAM) strategies to an industrial component using Fuzzy TOPSIS multiple criteria decision-making (MCDM) techniques. The proposed framework is then applied to an automotive component, and the results are discussed and compared with existing design.

Eight DfAM design alternatives associated with eight design criteria have been identified for framing new DfAM strategies. The prioritization order of the design alternatives is identified by Fuzzy TOPSIS MCDM technique through its closeness coefficient. Based on Fuzzy TOPSIS MCDM output, each of the design alternatives is applied sequentially to an automobile component as a case study. Redesign is carried out at each stage of DfAM implementation without affecting the functionality.

On successful implementation of proposed framework to an automotive component, the mass is reduced by 43.84%, from 0.429 kg to 0.241 kg. The redesign is validated by finite element analysis, where von Mises stress is less than the yield stress of the material.

The proposed DfAM framework and strategies will be useful to designers, R&D engineers, industrial practitioners, experts and consultants for implementing DfAM strategies on any industrial component without impacting its functionality.

To the best of the authors’ knowledge, the idea of prioritization and implementation of DfAM strategies to an automotive component is the original contribution.

The purpose of this paper is to understand how Design for Additive manufacturing Knowledge has been developing and its significance to both academia and industry.

In this paper, the authors use a bibliometric approach to analyse publications from January 2010 to December 2020 to explore the subject areas, publication outlets, most active authors, geographical distribution of scholarly outputs, collaboration and co-citations at both institutional and geographical levels and outcomes from keywords analysis.

The findings reveal that most knowledge has been developed in DfAM methods, rules and guidelines. This may suggest that designers are trying to learn new ways of harnessing the freedom offered by AM. Furthermore, more knowledge is needed to understand how to tackle the inherent limitations of AM processes. Moreover, DfAM knowledge has thus far been developed mostly by authors in a small number of institutional and geographical clusters, potentially limiting diverse perspectives and synergies from international collaboration which are essential for global knowledge development, for improvement of the quality of DfAM research and for its wider dissemination.

A concise structure of DfAM knowledge areas upon which the bibliometric analysis was conducted has been developed. Furthermore, areas where research is concentrated and those that require further knowledge development are revealed.

The COVID-19 pandemic has resulted in numerous innovative engineering design solutions, several of which leverage the rapid prototyping and manufacturing capabilities of additive manufacturing. This paper aims to study a subset of these solutions for their utilization of design for AM (DfAM) techniques and investigate the effects of DfAM utilization on the creativity and manufacturing efficiency of these solutions.

This study compiled 26 COVID-19-related solutions designed for AM spanning three categories: (1) face shields (N = 6), (2) face masks (N = 12) and (3) hands-free door openers (N = 8). These solutions were assessed for (1) DfAM utilization, (2) manufacturing efficiency and (3) creativity. The relationships between these assessments were then computed using generalized linear models to investigate the influence of DfAM utilization on manufacturing efficiency and creativity.

It is observed that (1) unique and original designs scored lower in their AM suitability, (2) solutions with higher complexity scored higher on usefulness and overall creativity and (3) solutions with higher complexity had higher build cost, build time and material usage. These findings highlight the need to account for both opportunistic and restrictive DfAM when evaluating solutions designed for AM. Balancing the two DfAM perspectives can support the development of solutions that are creative and consume fewer build resources.

DfAM evaluation tools primarily focus on AM limitations to help designers avoid build failures. This paper proposes the need to assess designs for both, their opportunistic and restrictive DfAM utilization to appropriately assess the manufacturing efficiency of designs and to realize the creative potential of adopting AM.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

This paper aims to provide a comprehensive review of the state-of–the-art design methods for additive manufacturing (AM) technologies to improve functional performance.

In this survey, design methods for AM to improve functional performance are divided into two main groups. They are design methods for a specific objective and general design methods. Design methods in the first group primarily focus on the improvement of functional performance, while the second group also takes other important factors such as manufacturability and cost into consideration with a more general framework. Design methods in each groups are carefully reviewed with discussion and comparison.

The advantages and disadvantages of different design methods for AM are discussed in this paper. Some general issues of existing methods are summarized below: most existing design methods only focus on a single design scale with a single function; few product-level design methods are available for both products’ functionality and assembly; and some existing design methods are hard to implement for the lack of suitable computer-aided design software.

This study is a useful source for designers to select an appropriate design method to take full advantage of AM.

In this survey, a novel classification method is used to categorize existing design methods for AM. Based on this classification method, a comprehensive review is provided in this paper as an informative source for designers and researchers working in this field.

This paper aims to review recent research in design for additive manufacturing (DfAM), including additive manufacturing (AM) terminology, trends, methods, classification of DfAM methods and software. The focus is on the design engineer’s role in the DfAM process and includes which design methods and tools exist to aid the design process. This includes methods, guidelines and software to achieve design optimization and in further steps to increase the level of design automation for metal AM techniques. The research has a special interest in structural optimization and the coupling between topology optimization and AM.

The method used in the review consists of six rounds in which literature was sequentially collected, sorted and removed. Full presentation of the method used could be found in the paper.

Existing DfAM research has been divided into three main groups – component, part and process design – and based on the review of existing DfAM methods, a proposal for a DfAM process has been compiled. Design support suitable for use by design engineers is linked to each step in the compiled DfAM process. Finally, the review suggests a possible new DfAM process that allows a higher degree of design automation than today’s process. Furthermore, research areas that need to be further developed to achieve this framework are pointed out.

The review maps existing research in design for additive manufacturing and compiles a proposed design method. For each step in the proposed method, existing methods and software are coupled. This type of overall methodology with connecting methods and software did not exist before. The work also contributes with a discussion regarding future design process and automation.

This paper aims to provide a multi-objective optimization problem in design for manufacturing (DFM) approach for fused deposition modeling (FDM). This method considers the manufacturing criteria and constraints during the design by selecting the best manufacturing parameters to guide the designer and manufacturer in fabrication with FDM.

Topological optimization and bi-objective optimization problems are suggested to complete the DFM approach for design for additive manufacturing (DFAM) to define a product. Topological optimization allows the shape improvement of the product through a material distribution for weight gain based on the desired mechanical behavior. The bi-objective optimization problem plays an important role to evaluate the manufacturability by quantification and optimization of the manufacturing criteria and constraint simultaneously. Actually, it optimizes the production time, required material regarding surface quality and mechanical properties of the product because of two significant parameters as layer thickness and part orientation.

A comprehensive analysis of the existing DFAM approaches illustrates that these approaches are not developed sufficiently in terms of manufacturability evaluation in quantification and optimization levels. There is no approach that investigates the AM criteria and constraints simultaneously. It is necessary to provide a decision-making tool for the designers and manufacturers to lead to better design and manufacturing regarding the different AM characteristics.

To assess the efficiency of this approach, a wheel spindle is considered as a case study which shows how this method is capable to find the best design and manufacturing solutions.

A multi-criteria decision-making approach as the main contribution is developed to analyze FDM technology and its attributes, criteria and drawbacks. It completes the DFAM approach for FDM through a bi-objective optimization problem which deals with finding the best manufacturing parameters by optimizing production time and material mass because of the product mechanical properties and surface roughness.

Additive manufacturing (AM) is growing economically because of its cost-effective design flexibility. However, it faces challenges such as interlaminar weaknesses and reduced strength because of product anisotropy. Therefore, the purpose of this study is to develop a methodology that integrates design for additive manufacturing (AM) principles with fused filament fabrication (FFF) to address these challenges, thereby enhancing product reliability and strength.

Developed through case analysis and literature review, this methodology focuses on design methodology for AM (DFAM) principles applied to FFF for high mechanical performance applications. A DFAM database is constructed to identify common requirements and establish design rules, validated through a case study.

Existing DFAM approaches often lack failure theory integration, especially in FFF, emphasizing mechanical characterizations over predictive failure analysis in functional parts. This methodology addresses this gap by enhancing product reliability through failure prediction in high-performance FFF applications.

While some DFAM methods exist for high-performance FFF, they are often specific cases. Existing DFAM methodologies typically apply broadly across AM processes without a specific focus on failure theories in functional parts. This methodology integrates FFF with a failure theory approach to strengthen product reliability in high-performance applications.

The chapter investigates three channels through which private benefits are hypothesized to be extracted in dual class companies: excess executive compensation, excess capital expenditures and excess cash holdings.

With a propensity score matched sample of S&P 1500 dual class and single class companies with concentrated control, the chapter analyzes the relationship between the valuation discount of dual class companies and measures of excess executive compensation, excess capital expenditure and excess cash holdings.

Executives in dual class firms earn greater compensation relative to their counterparts in single class firms. This excess compensation is more pronounced when the executive is a family member. The value of dual class shares is discounted most when cash holdings and executive compensation of dual class are excessive. Excess compensation is highest for executives who are family members of dual class companies. The dual class discount is not related to excess capital expenditures.

The research shows that the discount in the value of dual class shares in relation to the value of closely controlled single class company shares is directly related to the channels through which controlling shareholder-managers can extract private benefits.

This study aims to review the existing methods for additive manufacturing (AM) process selection and evaluate their suitability for design for additive manufacturing (DfAM). AM has experienced a rapid development in recent years. New technologies, machines and service bureaus are being brought into the market at an exciting rate. While user’s choices are in abundance, finding the right choice can be a non-trivial task.

AM process selection methods are reviewed based on decision theory. The authors also examine how the user’s preferences and AM process performances are considered and approximated into mathematical models. The pros and cons and the limitations of these methods are discussed, and a new approach has been proposed to support the iterating process of DfAM.

All current studies follow a sequential decision process and focus on an “a priori” articulation of preferences approach. This kind of method has limitations for the user in the early design stage to implement the DfAM process. An “a posteriori” articulation of preferences approach is proposed to support DfAM and an iterative design process.

This paper reviews AM process selection methods in a new perspective. The users need to be aware of the underlying assumptions in these methods. The limitations of these methods for DfAM are discussed, and a new approach for AM process selection is proposed.