Process and resource selection methodology in design for additive manufacturing

Kadkhoda-Ahmadi, Shervin; Hassan, Alaa; Asadollahi-Yazdi, Elnaz

doi:10.1007/s00170-019-03991-w

Cited by 33 publications

(15 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Because of such advantage, the use of the techniques to solve AM process selection issue has been gained importance and popularity during the past two decades [6]. A number of researchers, which include Braglia and Petroni [20], Xu et al [21], Byun and Lee [22], Mahesh et al [23], Wilson and Rosen [24], Rao and Padmanabhan [25], Armillotta [26], Borille et al [27], Lokesh and Jain [28], Rao and Patel [29], Zhou and Chen [30], Chakraborty [31], Khrais et al [32], Vahdani et al [33], Ic [34], Mahapatra and Panda [35], Roberson et al [36], Liao et al [37], Vinodh et al [38], Zhang and Bernard [39], Zhang et al [40], Mancanares et al [41], Kek [42], Zheng et al [43], Anand and Vinodh [44], uz Zaman et al [45], Wang et al [46], and Kadkhoda-Ahmadi et al [47] have successively presented their approaches in this period. The specific techniques adopted in these approaches, the data sources of the approaches, the way the approaches deal with the relative importance of the criteria for selecting AM processes, and the way the approaches deal with the interrelationships between criteria are summarised in Table 1.…”

Section: Related Workmentioning

confidence: 99%

“…Example 4. The fourth example was developed by Kadkhoda-Ahmadi et al [47]. In this example, there are six alternative AM processes (machines).…”

Section: Am Process Selection Examplesmentioning

confidence: 99%

“…Zhang and Bernard [39], Zhang et al [40], and Zheng et al [43], this example was leveraged to compare these approaches and the proposed approach quantitatively. In addition, Examples 2, 3, and 4 were respectively used to make quantitative comparisons between the approach of Wilson and Rosen [24] and the proposed approach, the approach of Zhang and Bernard [39] and the proposed approach, and the approach of Kadkhoda-Ahmadi et al [47] and the proposed approach. The details and results of the quantitative comparisons are shown in Table 10.…”

Section: Qualitative Comparisonmentioning

confidence: 99%

See 2 more Smart Citations

An additive manufacturing process selection approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators

Qin

Scott

et al. 2020

Robotics and Computer-Integrated Manufacturing

View full text Add to dashboard Cite

Selecting an appropriate additive manufacturing (AM) process or machine to fabricate an end-use product is an important issue in design for AM. One of many types of approaches for AM process selection is based on multi-criteria decision making (MCDM). Most of the MCDM based approaches have an advantage in taking into account the relative importance of performance parameter types and a few of them also consider the interrelationships of performance parameter types. Each of these approaches can work well in its specific context. They are however not entirely satisfactory, as they do not have the capabilities to reduce the influence of the deviation of performance parameter values on the decision-making result and to capture the risk attitudes of users in their decision-making models. In this paper, an MCDM approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators with such capabilities is proposed for AM process selection. A fuzzy Archimedean weighted power Bonferroni mean operator and a fuzzy Archimedean weighted power geometric Bonferroni mean operator are firstly constructed. Based on these operators, an MCDM approach for selection of AM processes are then developed. After that, four practical examples are adopted to illustrate the developed approach and a set of sensitivity analysis experiments on the basis of these examples are carried out. Finally, qualitative and quantitative comparisons between the approach and the existing MCDM based approaches are reported to demonstrate its feasibility, effectiveness, and advantages.

show abstract

Section: Related Workmentioning

confidence: 99%

“…Example 4. The fourth example was developed by Kadkhoda-Ahmadi et al [47]. In this example, there are six alternative AM processes (machines).…”

Section: Am Process Selection Examplesmentioning

confidence: 99%

Section: Qualitative Comparisonmentioning

confidence: 99%

See 1 more Smart Citation

An additive manufacturing process selection approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators

Qin

Scott

et al. 2020

Robotics and Computer-Integrated Manufacturing

View full text Add to dashboard Cite

show abstract

“…Simple geometries can be realized by conventional means that are more economical than additive manufacturing. Instead, the focus should be on complex geometries (16) (Kadkhoda-Ahmadi et al, 2019). Moreover, a redesigned solution principle, which is intended to replace a conventional solution, is primarily economical if the resulting part remains within the limited batch size of the selected AM-process (17) (Liu et al, 2020).…”

Section: Iced21mentioning

confidence: 99%

Derivation of Criteria for Assessing Solution Principles Conformal for Additive Manufacturing

2021

View full text Add to dashboard Cite

Additively manufactured final products and components are not always tailored to the additive manufacturing (AM) process, but they need to be in order to exploit the many advantages and potentials that AM provides. Therefore, an appropriate AM design should be targeted, which reduces the necessary iterations in the developing process of AM products. Although there is a large number of existing literature on the Design for Additive Manufacturing (DfAM), designers usually lack criteria in order to assess AM-conformity in conceptual design. In this paper, we provide a basis for the assessment of solution principles regarding their conformity for additive manufacturing.First, existing literature on DfAM and AM products is reviewed comprehensively to derive criteria for the AM-conformity of solution principles. Subsequently, the correlations between these criteria are identified including the interdependencies to be considered when assessing AM-conformity. A basis for assessment is created, which offers designers early support in the development of AM-conformal designs.

show abstract

“…Very briefly, the DAM process starts with a model created in a computer-aided design (CAD) software or three-dimensional scanned object that is sliced into many layers by using a slicing software. Several studies have been conducted regarding the process and design framework for DAM [19,20]. The number of layers depends on the desired printing resolution.…”

Section: Benefits and Limitations Of Dammentioning

confidence: 99%

Assessing the Suitability of Freeform Injection Molding for Low Volume Injection Molded Parts: A Design Science Approach

et al. 2021

View full text Add to dashboard Cite

Low-volume manufacturing remains a challenge, especially for parts that need to be injection-molded. Freeform injection molding (FIM) is a novel method that combines elements from direct additive manufacturing (DAM) and injection molding (IM) to resolve some of the challenges seen in low-volume injection molding. In this study, we use a design science approach to explore the suitability of FIM for the manufacturing of low volume injection-molded parts. We provide an overview of the benefits and limitations of traditional IM and discuss how DAM and indirect additive manufacturing (IAM) methods, such as soft tooling and FIM, can address some of the existing drawbacks of IM for short series production. A set of different parts was identified and assessed using a design science-based approach to demonstrate how to incubate FIM as a solution to address the challenges faced in short series production with IM. This initial process innovation was followed by solution refinement, involving the optimization of the FIM processes. Finally, a “cross-case” analysis was conducted using the framework of context, intervention, mechanism and outcomes to generate insights about the generalizability of the results. It is concluded that FIM combines the short lead-times, low start-up costs and design freedom of DAM with the versatility and scalability of IM to allow manufacturers to bring low volume products to the market faster, more cheaply and with lower risk, and to maintain the relevance of these products through easy customization and adaptations once they have been launched.

show abstract

Process and resource selection methodology in design for additive manufacturing

Cited by 33 publications

References 53 publications

An additive manufacturing process selection approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators

An additive manufacturing process selection approach based on fuzzy Archimedean weighted power Bonferroni aggregation operators

Derivation of Criteria for Assessing Solution Principles Conformal for Additive Manufacturing

Assessing the Suitability of Freeform Injection Molding for Low Volume Injection Molded Parts: A Design Science Approach

Contact Info

Product

Resources

About