Short answer

Integrate quantitative cost and time analysis into the early stages of design for metal AM projects to ensure economic feasibility and efficient production.

Field: Commercial Production
Source: Aaltodoc (Aalto University) (2015)
Method: Development of a computational decision support tool and experimental validation.
Sample: 9 different AM machines, 3 material types, 3 accuracy levels
Evidence: Strong effect

A custom-built decision support tool, utilizing MATLAB, enables designers and engineers to quantitatively compare metal additive manufacturing (AM) processes based on cost and build time. This commercial production research insight is drawn from a 2015 study published in Aaltodoc (Aalto University). Using Development of a computational decision support tool and experimental validation. with 9 different AM machines, 3 material types, 3 accuracy levels, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Integrate quantitative cost and time analysis into the early stages of design for metal AM projects to ensure economic feasibility and efficient production.

Study

Commercial ProductionHigh ImpactStrong effect

Decision Support Tool Optimizes Metal AM Cost and Build Time

A custom-built decision support tool, utilizing MATLAB, enables designers and engineers to quantitatively compare metal additive manufacturing (AM) processes based on cost and build time.

Aaltodoc (Aalto University) · 2015

Key Findings

01A functional decision support tool was developed for comparing metal AM machines.
02The tool can analyze cost per part, total cost, and build time for various configurations.
03Sensitivity analysis revealed key parameters influencing cost and build time.

Application

Design takeaway

Integrate quantitative cost and time analysis into the early stages of design for metal AM projects to ensure economic feasibility and efficient production.

How to apply

Develop or utilize similar decision support tools to model and compare manufacturing options, inputting specific project constraints and desired outcomes to identify the most economically viable solution.

Project actions

01When choosing a manufacturing method, don't just guess; try to find data or build a simple model to compare costs and time.
02Consider what factors (like material, size, or precision) will most affect the cost and time of your chosen manufacturing process.

Method & Evidence

AimTo develop a decision support tool for economically validating metal powder bed fusion based additive manufacturing processes by comparing laser-based (DMLM) and electron-beam (EBM) systems.

MethodDevelopment of a computational decision support tool and experimental validation.

ProcedureA MATLAB-based tool was created to calculate cost per part and total cost, considering machine parameters (build volume rates, beam power, spot size), material types, and accuracy levels. This was followed by sensitivity analyses, skin-core analysis, direct DMLM vs. EBM comparisons, and Taguchi orthogonal array testing to assess parameter influences.

Sample9 different AM machines, 3 material types, 3 accuracy levels

ContextMetal Additive Manufacturing (AM) process selection.

Variables

IV["AM machine type (DMLM vs. EBM)","Machine parameters (build volume rate, beam power, spot size)","Material type (aluminum, tool steel, titanium alloys)","Accuracy level (high, low, skin-core)"]

DV["Cost per part","Total cost","Build time"]

CV["Software used for modeling (MATLAB)","Specific AM principles considered (powder bed fusion)"]

Strengths & Limitations

Strengths

+Development of a practical, quantitative decision support tool.
+Systematic comparison of different AM technologies and parameters.
+Inclusion of experimental validation and sensitivity analysis.

Limitations

The complexity of real-world manufacturing costs can be difficult to fully capture in a simplified model.

Reliability & validity

The reliability of the tool depends on the accuracy of the input data and the robustness of the MATLAB algorithms. Validity is supported by experimental tests and sensitivity analyses, though real-world production may introduce further variables.

Think critically

How might the 'skin-core' analysis or Taguchi methods be adapted to evaluate other manufacturing processes beyond metal AM?

Design Principles

"Economic feasibility should be a primary consideration in the selection of manufacturing processes, supported by quantitative analysis tools."

Selecting the appropriate AM technology is crucial for economic viability. This research provides a framework for objective comparison, moving beyond qualitative assessments to data-driven decision-making, which can significantly impact project budgets and timelines.

What This Means for Your Design

This research shows how to build a computer program that helps you figure out which metal 3D printer is the cheapest and fastest for your project.

How to use in your project

1.Use the concept of a decision support tool to justify your choice of manufacturing method, referencing the quantitative analysis performed.

Add to My Project

Quick Cite

Paragraph starter

The selection of an appropriate manufacturing process is critical for the economic success of a design project. This research highlights the development of a decision support tool that quantifies the cost and time implications of different metal additive manufacturing techniques, enabling informed choices based on specific project parameters.

Source

Aaltodoc (Aalto University)

Economic validation of metal powder bed based AM processes

journal · 2015

View source

Questions About This Research

What does the research say about decision support tool optimizes metal am cost and build time?: Integrate quantitative cost and time analysis into the early stages of design for metal AM projects to ensure economic feasibility and efficient production. Evidence: Aaltodoc (Aalto University) (2015).
Why does "Decision Support Tool Optimizes Metal AM Cost and Build Time" matter for design?: Selecting the appropriate AM technology is crucial for economic viability. This research provides a framework for objective comparison, moving beyond qualitative assessments to data-driven decision-making, which can significantly impact project budgets and timelines.
How can designers apply this research?: Integrate quantitative cost and time analysis into the early stages of design for metal AM projects to ensure economic feasibility and efficient production.
What were the main findings?: A functional decision support tool was developed for comparing metal AM machines.. The tool can analyze cost per part, total cost, and build time for various configurations.. Sensitivity analysis revealed key parameters influencing cost and build time.
What research method was used?: Development of a computational decision support tool and experimental validation. with 9 different AM machines, 3 material types, 3 accuracy levels.
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2015 journal from Aaltodoc (Aalto University).
What should I do differently in my next project?: Develop or utilize similar decision support tools to model and compare manufacturing options, inputting specific project constraints and desired outcomes to identify the most economically viable solution.
What are the limitations?: The accuracy of the tool is dependent on the quality and completeness of input data for machine parameters and material costs. The model primarily focuses on cost and time, potentially overlooking other critical factors like part performance or post-processing requirements.