Additive Manufacturing Cost Models: A Critical Review for Production Economics

Category: Resource Management · Effect: Moderate effect · Year: 2016

Existing cost models for Additive Manufacturing (AM) offer a framework for evaluating production economics, but require careful consideration of their strengths and weaknesses for effective implementation.

Design Takeaway

When evaluating the cost-effectiveness of Additive Manufacturing for a design project, select and critically assess cost models that align with the specific AM process, materials, and production scale being considered.

Why It Matters

As AM technologies mature and become more integrated into industrial production, understanding their cost implications is crucial for design and manufacturing professionals. A robust cost model can inform decisions about material selection, process optimization, and overall project viability.

Key Finding

The review found that while several cost models for Additive Manufacturing are available, they vary in their approach and effectiveness, highlighting a need for careful selection and application based on specific production contexts.

Key Findings

Research Evidence

Aim: To critically analyze existing cost models for Additive Manufacturing from an operations management perspective, identifying their strengths and weaknesses.

Method: Literature Review

Procedure: The study systematically reviewed academic literature on cost models specifically developed for Additive Manufacturing processes, evaluating their methodologies, assumptions, and applicability.

Context: Industrial manufacturing, operations management, additive manufacturing

Design Principle

Cost models for emerging manufacturing technologies should be critically evaluated for their scope, assumptions, and applicability to the specific design and production context.

How to Apply

When proposing an AM solution, present a cost analysis using a relevant model, clearly stating its assumptions and limitations, and comparing it to traditional manufacturing costs.

Limitations

The review is based on existing literature, and the rapid evolution of AM technology may mean some models are becoming outdated. The focus is primarily on economic aspects, potentially overlooking other critical factors.

Student Guide (IB Design Technology)

Simple Explanation: There are different ways to calculate the cost of making things with 3D printers, but each way has good and bad points. It's important to pick the right way to calculate costs for your project.

Why This Matters: Understanding cost models helps you justify your design choices, especially when comparing traditional manufacturing methods with newer ones like Additive Manufacturing.

Critical Thinking: How might the rapid pace of innovation in Additive Manufacturing render current cost models obsolete or less accurate over time?

IA-Ready Paragraph: This research highlights the importance of critically evaluating cost models for Additive Manufacturing (AM) from an operations management perspective. As AM matures, understanding its economic implications is vital. The literature review indicates that while various cost models exist, each possesses distinct strengths and weaknesses, necessitating careful selection based on the specific AM technology, materials, and production scale. Therefore, when developing a design project involving AM, it is crucial to apply a relevant cost model, clearly articulating its assumptions and limitations, and to compare these costs against traditional manufacturing alternatives.

Project Tips

How to Use in IA

Examiner Tips

Independent Variable: ["Type of Additive Manufacturing cost model","Specific Additive Manufacturing process"]

Dependent Variable: ["Calculated production cost","Model applicability/accuracy"]

Controlled Variables: ["Material properties","Part geometry complexity","Production volume"]

Strengths

Critical Questions

Extended Essay Application

Source

Cost models of additive manufacturing: A literature review · International Journal of Industrial Engineering Computations · 2016 · 10.5267/j.ijiec.2016.9.001