The past few decades have seen substantial growth in Additive Manufacturing (AM) technologies. However, this growth has mainly been process-driven. The evolution of engineering design to take advantage of the possibilities afforded by AM and to manage the constraints associated with the technology has lagged behind. This paper presents the major opportunities, constraints, and economic considerations for Design for Additive Manufacturing. It explores issues related to design and redesign for direct and indirect AM production. It also highlights key industrial applications, outlines future challenges, and identifies promising directions for research and the exploitation of AM's full potential in industry.

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Design for additive manufacturing: trends, opportunities, considerations, and constraints

Design for manufacture and assembly (DFM) has typically meant that designers should tailor their designs to eliminate manufacturing difficulties and minimize manufacturing, assembly, and logistics costs. However, the capabilities of additive manufacturing technologies provide an opportunity to rethink DFM to take advantage of the unique capabilities of these technologies. As mentioned in Chap. 16, several companies are now using AM technologies for production manufacturing. For example, Siemens, Phonak, Widex, and the other hearing aid manufacturers use selective laser sintering and stereolithography machines to produce hearing aid shells; Align Technology uses stereolithography to fabricate molds for producing clear dental braces (“aligners”); and Boeing and its suppliers use polymer powder bed fusion (PBF) to produce ducts and similar parts for F-17 fighter jets. For hearing aids and dental aligners, AM machines enable manufacturing of tens to hundreds of thousands of parts, where each part is uniquely customized based upon person-specific geometric data. In the case of aircraft components, AM technology enables low-volume manufacturing, easy integration of design changes and, at least as importantly, piece part reductions to greatly simplify product assembly.

Design for Additive Manufacturing

Purpose – The purpose of this paper is to critically review the literature related to dimensional accuracy and surface roughness for fused deposition modeling and similar extrusion-based additive manufacturing or rapid prototyping processes. Design/methodology/approach – A systematic review of the literature was carried out by focusing on the relationship between process and product design parameters and the dimensional and surface properties of finished parts. Methods for evaluating these performance parameters are also reviewed. Findings – Fused deposition modeling® and related processes are the most widely used polymer rapid prototyping processes. For many applications, resolution, dimensional accuracy and surface roughness are among the most important properties in final parts. The influence of feedstock properties and system design on dimensional accuracy and resolution is reviewed. Thermal warping and shrinkage are often major sources of dimensional error in finished parts. This phenomenon is explor...

A review of melt extrusion additive manufacturing processes: II. Materials, dimensional accuracy, and surface roughness

Representation of surface roughness in fused deposition modeling

Additive manufacturing (AM) has developed rapidly since its inception in the 1980s. AM is perceived as an environmentally friendly and sustainable technology and has already gained a lot of attention globally. The potential freedom of design offered by AM is, however, often limited when printing complex geometries due to an inability to support the stresses inherent within the manufacturing process. Additional support structures are often needed, which leads to material, time and energy waste. Research in support structures is, therefore, of great importance for the future and further improvement of additive manufacturing. This paper aims to review the varied research that has been performed in the area of support structures. Fifty-seven publications regarding support structure optimization are selected and categorized into six groups for discussion. A framework is established in which future research into support structures can be pursued and standardized. By providing a comprehensive review and discussion on support structures, AM can be further improved and developed in terms of support waste in the future, thus, making AM a more sustainable technology.

https://www.mdpi.com/2504-4494/2/4/64/pdf

Support Structures for Additive Manufacturing: A Review

A geometric benchmark part is proposed, designed and fabricated for the performance evaluation of rapid prototyping machines/processes. The benchmark part incorporates key shapes and features of better‐known benchmark parts. It also includes new geometric features, such as freeform surfaces, certain mechanical features and pass‐fail features that are increasingly required or expected of RP processes/systems. The part is suitable for fabrication on a typical RP machines. In this paper, the application of the benchmark part is demonstrated using relatively common RP processes. The ability of the benchmark part to determine achievable geometric features and accuracy by the aforementioned RP processes is presented and discussed.

Benchmarking for comparative evaluation of RP systems and processes

This paper presents a methodology of using six-sigma quality tools for benchmarking of rapid prototyping & manufacturing (RP&M) processes. It involves the fabrication of a geometric benchmark part and a methodology to control and identify the best performance of the process to reduce the variablity in the fabricated parts. The approach is demonstrated with a case study based on the direct laser sintering (DLS) process for prototyping using plastic powder. In the case study an identified set of six-sigma/ statistical process control tools is employed to determine and best tune factors affecting the desired outcomes of the built parts.

https://rd.springer.com/content/pdf/10.1007%2Fs00170-005-0201-z.pdf

A Six-sigma approach for benchmarking of RP&M processes

A framework for distributed manufacturing is proposed to facilitate collaborative product development and production among geographically distributed functional agents using digitalized information. Considering the complexity of products created in a distributed manufacturing scenario, it often requires close collaborations among a number of facilities. In this research work, various functional agents, such as the manufacturability evaluation agent (MEA), manufacturing resource agent (MRA), process-planning agent (PPA), manufacturing scheduling agent (MSA), shop floor agent (SFA), fault diagnosis agent (FDA), etc., can interact coherently for distributed manufacturing. With specific agents having unique functionalities, a manufacturing managing agent (MMA) acts as the centre of this distributed manufacturing system. The MMA agent assists the specific agents' to work seamlessly and also to collaborate closely with the participating agents. In this way, the production cycle of a part can be optimized from product design to final manufacturing since all the production procedures are considered logically and every procedure is correlated. The agent language based on the knowledge query manipulation language (KQML) includes many pre-defined performatives that ease the participating agents to carry out their tasks intelligently by interpreting commands from one another. Additionally, to ensure the adaptiveness and upgradeability of the system, the internal structure of each functional agent that is based on JATLite is modularized into several components, including a communication interface, central work engine, knowledge base pool, and input/output modifier for possible future methodology enhancements.

Towards a generic distributed and collaborative digital manufacturing

This paper addresses an integrated rapid prototyping decision-making system (IRPDMS) based on fuzzy decision and benchmarking for selecting appropriate rapid prototyping and manufacturing (RP&M) processes. Data sets captured from benchmarking different RP&M processes are used in decision-making. The proposed IRPDMS provides decision support while interacting with an earlier developed benchmark database. Issues on standardizations and the purpose of using such standardized information datasets for offering decision support are discussed. Selection of five RP&M processes namely stereolithography (SLA), selective laser sintering (SLS), fused deposition modeling (FDM), laminated object manufacturing (LOM) and direct laser sintering (DLS) using the proposed IRPDMS is presented for the purpose of demonstration.

Benchmarking for decision making in rapid prototyping systems

A framework for a web-based multi-agent system (WebMAS) is proposed to facilitate collaborative product development and production among geographically distributed functional agents using digitalized information. Considering the complexity of products created in a distributed manufacturing scenario, this often requires close collaboration among a number of facilities. In this research, a prototype system where different distributed functional agents, namely, a manufacturability evaluation agent, manufacturing resource agent, process-planning agent, manufacturing scheduling agent, shop-floor agent, fault diagnosis agent, etc., interact coherently to realize the development of physical parts. With specific agents having unique functionalities, a manufacturing managing agent acts as the centre of the system thus coordinating the activities of the participating agents while ensuring seamless work flow and collaboration. This facilitates optimization of the part production cycle from product design to final manufacturing because all the production procedures are correlated and considered logically. The agents communicate through the knowledge query manipulation language, which includes many pre-defined performatives to aid the participating agents in carrying out their tasks intelligently by interpreting commands from one another. In this paper, a case study based on the developed prototype WebMAS system is discussed to illustrate the system.

M. Mahesh

Papers

Benchmarking for comparative evaluation of RP systems and processes

A Six-sigma approach for benchmarking of RP&M processes

Towards a generic distributed and collaborative digital manufacturing

Benchmarking for decision making in rapid prototyping systems

A web-based multi-agent system for distributed digital manufacturing