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

Abstract

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.

Dual hesitant q ‐rung orthopair fuzzy Dombi t ‐conorm and t ‐norm based Bonferroni mean operators for solving multicriteria group decision making problems

“…In future, the proposed method can be extended under DH‐ROF environment by integrating other averaging operations, namely, MM, 40 partitioned BM, 57 power BM, 58 HM, 54 MSM, 52 Hamy mean, 55 and so on, with DHROFNs to generate different efficient AOs which may, subsequently, be used for solving MCDM problems. After introducing distance measure on DH‐ROF environment, several types of power AOs based on Frank, Hamacher, Schweizer‐Sklar, 59 and many other classes of ‐CN&‐Ns, can be developed.…”

Status, issues, and future of computer-aided part orientation for additive manufacturing

“…However, it is not clear whether the performance of the algorithm is better than that of other optimisation techniques. (7) The SM is a commonly used optimisation technique in engineering problems. When an optimisation problem requires a large amount of computation and is not easy to solve, a simplified model that needs a smaller amount of computation and mimics the original problem as closely as possible can be used to replace the optimisation problem to speed up the optimisation process.…”

“…In general, the use of an AM process to realise a product contains a set of activities [7], where process planning is a critical one [8][9][10]. Process planning for AM refers to an activity of determining appropriate process variables, including orientation, support, slices, tool path, and process parameters, to build a part using an AM machine [11].…”

Automatic determination of part build orientation for laser powder bed fusion

“…In addition to geometry design, detailed design also involves the design of specifications of an AM product and the selection of an AM machine to fabricate the product (Qin et al 2020a). Generally, the specifications to be designed can be classified from macro, micro and production levels.…”

“…Generally, the application of the LPBF process to realise a product consists of five activities, where process planning is an indispensable one (Kim et al 2015;Qin et al 2020a). Process planning for LPBF is the planning of the process parameters to build a part using an LPBF machine, which mainly include the build orientation, supports, slices, laser scanning path and machine parameters (Ahsan, Habib, and Khoda 2015).…”