Timothy W. Simpson

Pennsylvania State University | Penn State · Department of Mechanical and Nuclear Engineering

Adopting additive manufacturing (AM) in product design is a challenge for organizations due to a shortage of skilled designers who can effectively use AM to address emerging engineering problems. The development of institutional talent in AM and design for AM (DfAM) is crucial for organizations looking to leverage AM capabilities. Therefore, design...

The temperature history of an additively-manufactured part plays a critical role in determining process-structure-property relationships in fusion-based additive manufacturing (AM) processes. Therefore, fast thermal simulation methods are needed for a variety of AM tasks, from temperature history prediction for part design and process planning to i...

The use of lattice structure in the Design for Additive Manufacturing (DfAM) engineering practice offers the ability to tailor the properties (and therefore the response) of an engineered component independent of the material and overall geometry. The selection of a lattice topology is critical in maximizing the value of the lattice structure and i...

The manufacturing sector accounts for a large percentage of global energy use and greenhouse gas emissions, and there is growing interest in the potential of additive manufacturing (AM) to reduce the sector's environmental impacts. Across multiple industries, AM has been used to reduce material use in final parts by 35-80%, and recent publications...

Although the additive manufacturing (AM) market continues to grow, industries face barriers to AM adoptiondue to a shortage of skilled designers in the workforce that can apply AM effectively to meet this demand. Thisshortage is attributed to the high cost and infrastructural requirements of introducing high- barrier-to-entry AMprocesses such as po...

Metal Additive Manufacturing (MAM) produces complex, part geometries from a variety of materials in powder and wire form. Due to complexities of MAM processes that create those geometries, especially powder bed fusion, quality assurance, and qualification remain an ongoing challenge. Quality assurance involves assessing the quality of a part’s geom...

The demand for additive manufacturing (AM) continues to grow as more industries look to integrate the technology into their product development. However, there is a deficit of designers skilled to innovate with this technology due to challenges in supporting designers with tools and education for their development in design for AM (DfAM). There is...

Capitalizing on any new or unfamiliar manufacturing technology requires an ability to look beyond the manufacturing limitations that have constrained one’s design ideas in the past. For advanced manufacturing technology with unique capabilities such as additive manufacturing, this becomes critical for designing effective geometric features and part...

Compared to conventional fabrication, additive manufacturing enables production of far more complex geometries with less tooling and increased automation. However, despite the common perception of AM’s “free” geometric complexity, this freedom comes with a literal cost: more complex geometries may be challenging to design, potentially manifesting a...

The intersection between engineering design, manufacturing, and artificial intelligence offers countless opportunities for breakthrough improvements in how we develop new technology. However, achieving this synergy between the physical and the computational worlds involves overcoming a core challenge: few specialists educated today are trained in b...

Metal additive manufacturing (MAM) offers a larger design space with greater manufacturability than traditional manufacturing has offered. Despite continued advances, MAM processes still face huge uncertainty, resulting in variable part quality. Real-time sensing for MAM processing helps quantify uncertainty by detecting build failure and process a...

As additive manufacturing (AM) processes become ubiquitous in engineering and design, there has emerged the need for a workforce skilled in designing for AM (DfAM). Researchers have proposed educational interventions to train students in DfAM; however, few measures with sufficient validity evidence have been proposed to assess the effects of these...

Additive manufacturing (AM) presents designers with unique manufacturing capabilities while imposing several limitations. Designers must leverage AM capabilities – through opportunistic design for AM (O-DfAM) – and accommodate AM limitations – through restrictive (R-) DfAM – to successfully employ AM in engineering design. This dual DfAM approach –...

Designers from around the world have proposed numerous engineering design solutions for problems related to the COVID-19 pandemic, many of which leverage the rapid prototyping and manufacturing capabilities of additive manufacturing (AM). While some of these solutions are motivated by complex and urgent requirements (e.g., face masks), others are m...

Additive manufacturing (AM) is poised to bring a revolution due to its unique production paradigm. It offers the prospect of mass customization, flexible production, on-demand and decentralized manufacturing. However, a number of challenges stem from not only the complexity of manufacturing systems but the demand for increasingly complex and high-q...

Designing for any advanced manufacturing technology necessitates looking beyond the current manufacturing limitations that have constrained one’s previous design ideas. Moreover, fixation on existing and/or familiar manufacturing processes may prevent both the designers and project managers from considering new advanced manufacturing processes. We...

Additive manufacturing (AM) is a layer-by-layer material deposition process that allows for more manufacturing flexibility and design complexity than traditional manufacturing processes. However, the print quality in metal AM is hard to be predicted and controlled due to its high process variability. Numerous process parameters are correlated/inter...

Given the growing presence of additive manufacturing (AM) processes in engineering design and manufacturing, there has emerged an increased interest in introducing AM and design for AM (DfAM) educational interventions in engineering education. Several researchers have proposed AM and DfAM educational interventions; however, some argue that these ef...

Additive manufacturing (AM) processes present designers with unique capabilities while imposing several process limitations. Designers must leverage the capabilities of AM — through opportunistic design for AM (DfAM) — and accommodate AM limitations — through restrictive DfAM — to successfully employ AM in engineering design. These opportunistic an...

Metal additive manufacturing (MAM) provides a larger design space with accompanying manufacturability than traditional manufacturing. Recently, much research has focused on simulating the MAM process with regards to part geometry, porosity, and microstructure properties. Despite continued advances, MAM processes have many variables that are not wel...

Modern digital manufacturing processes, such as additive manufacturing, are cyber-physical in nature and utilize complex, process-specific simulations for both design and manufacturing. Although computational simulations can be used to optimize these complex processes, they can take hours or days — an unreasonable cost for engineering teams leverag...

Although there is a substantial growth in the Additive Manufacturing (AM) market commensurate with the demand for products produced by AM methods, there is a shortage of skilled designers in the workforce that can apply AM effectively to meet this demand. This is due to the innate complications with cost and infrastructure for high-barrier-to-entry...

Designing successfully for any new or unfamiliar manufacturing technology requires an ability to look beyond the manufacturing limitations that have constrained one’s design ideas in the past. However, potential cognitive bias or fixation on familiar manufacturing processes may make this a challenge for designers. In this paper we introduce the nov...

As additive manufacturing (AM) processes become more ubiquitous in engineering, design, and manufacturing, the need for a workforce skilled in design for AM (DfAM) has grown. Despite this need for an AM-skilled workforce, little research has systematically investigated the formulation of educational interventions for training engineers in DfAM. In...

As additive manufacturing (AM) increases in popularity, many companies seek to identify which parts can be produced via AM. This has led to new areas of research known as “part filtering”, “part selection”, or “part identification” for AM. Numerous methods have been proposed to quantify the suitability of a design to be made with AM, and each has i...

Additive manufacturing (AM) enables the creation of complex geometries that are difficult to realize using conventional manufacturing techniques. Advanced sensing is increasingly being used to improve AM processes, and installing different sensors onto AM systems has yielded more data-rich environments. Transforming data into useful information and...

Purpose: The COVID-19 pandemic has resulted in numerous innovative engineering design solutions, several of which leverage the rapid prototyping and manufacturing capabilities of additive manufacturing. In this paper, we study a subset of these solutions for their utilization of design for AM (DfAM) techniques and investigate the effects of DfAM ut...

Advanced product platform and product family design methods are needed to define and optimize the value they bring to a company. Maximizing platform commonality and individual product performance often fails to realize the most valuable product family during optimization; however, few examples exist in the literature to explore these trade-offs. Th...

Designers around the world have leveraged the rapid prototyping and manufacturing capabilities of additive manufacturing (AM), commonly known as 3D printing, to develop numerous engineering design solutions for the COVID-19 pandemic. This dataset consists of the design and manufacturability data for twenty-six such engineering design solutions span...

The capabilities of additive manufacturing (AM) open up designers’ solution space and enable them to build designs previously impossible through traditional manufacturing. However, to leverage AM capabilities, design educators must specifically emphasize selecting creative ideas in design for AM (DfAM), as ideas perceived as infeasible through the...

To capitalize the design freedoms enabled by additive manufacturing (AM), designers must employ opportunistic and restrictive design for AM (O- and R-DfAM respectively). The order of information presentation influences the retrieval of said information; however, there is a need to explore this effect within DfAM. We compared four variations in DfAM...

Designers skilled in design for additive manufacturing (AM, DfAM) must apply restrictive DfAM to prevent build failure and opportunistic DfAM to leverage AM capabilities. Few studies have explored the effect of students’ motivation on the outcomes of AM education. The experiment in this article introduced engineering students to either restrictive...

The capabilities of additive manufacturing (AM) enable designers to generate and build creative solutions beyond the limitations of traditional manufacturing. However, designers must also accommodate AM limitations to minimize build failures. Several researchers have proposed design tools and educational interventions for integrating design for AM...

As additive manufacturing (AM) increases in popularity, many companies seek to identify which parts can be produced via AM. This has led to new areas of research known as “part filtering”, “part selection”, or “part identification” for AM. Numerous methods have been proposed to quantify the suitability of a design to be made with AM, and each has i...

The widespread growth of additive manufacturing, a field with a complex informatic “digital thread”, has helped fuel the creation of design repositories, where multiple users can upload distribute, and download a variety of candidate designs for a variety of situations. Additionally, advancements in additive manufacturing process development, desig...

Generative neural networks (GNNs) have successfully used human-created designs to generate novel 3D models that combine concepts from disparate known solutions, which is an important aspect of design exploration. GNNs automatically learn a parameterization (or latent space ) of a design space, as opposed to alternative methods that manually define...

The capabilities of additive manufacturing (AM) open up designers’ solution space and enable them to build designs previously impossible through traditional manufacturing. To leverage AM, designers must not only generate creative ideas, but also propagate these ideas without discarding them in the early design stages. This emphasis on selecting cre...

The capabilities of additive manufacturing (AM) processes present designers with creative freedoms beyond the limitations of traditional manufacturing processes. However, to successfully leverage AM, designers must balance their creativity against the limitations inherent in these processes to ensure their designs can be feasibly manufactured. To e...

In industry, Design for Additive Manufacturing (DfAM) is currently synonymous with expert knowledge and external consultants for many companies. Particularly in higher cost technologies, such as metal powder bed fusion, component design requires extensive additive manufacturing (AM) knowledge. If a part is improperly designed, then it can cause tho...

Additive Manufacturing (AM) offers unique capabilities, yet inherent limitations due to the layered fabrication of parts. Despite the newfound design freedom and increased use of AM, limited research has investigated how knowledge of the AM processes affects the creativity of students’ ideas. This study investigates this gap through a study with 34...

Additive manufacturing (AM) enables engineers to improve the functionality and performance of their designs by adding complexity at little to no additional cost. However, AM processes also exhibit certain unique limitations, such as the presence of support material. These limitations must be accounted for to ensure that designs can be manufactured...

The authors present a Generative Adversarial Network (GAN) model that learns how to generate 3D models in their native format so that they can either be evaluated using complex simulation environments, or realized using methods such as additive manufacturing. Once initially trained, the GAN can create additional training data itself by generating n...

The integration of additive manufacturing (AM) processes in many industries has led to the need for AM education and training, particularly on design for AM (DfAM). To meet this growing need, several academic institutions have implemented educational interventions, especially project- and problem-based, for AM education; however, limited research h...

This work investigates surrogate modeling techniques for learning to approximate a computationally expensive function evaluation of 3D models. Radial Basis Functions (RBF), Kriging, and shallow 1D analogs of popular deep 2D image classification neural networks are investigated in this work. We find the nonintuitive result that departing from neural...

The integration of additive manufacturing (AM) processes in many industries has led to the need for AM education and training, particularly on design for AM (DfAM). To meet this growing need, several academic institutions have implemented educational interventions, especially project-and problem-based, for AM education; however, limited research ha...

Additive manufacturing (AM) enables engineers to improve the functionality and performance of their designs by adding complexity at little to no additional cost. However, AM processes also exhibit certain unique limitations, such as the presence of support material, which must be accounted for to ensure that designs can be manufactured feasibly and...

We present a form-aware reinforcement learning (RL) method to extend control knowledge from one design form to another, without losing the ability to control the original design. A major challenge in developing control knowledge is the creation of generalized control policies across designs of varying form. Our presented RL policy is form-aware bec...

Virtual Reality (VR) has been shown to be an effective assistive tool in the engineering design process, aiding designers in ergonomics studies, data visualization, and manufacturing simulation. Yet there is little research exploring the advantages of VR to assist in the design for the additive manufacturing (DfAM) process. VR may present advantage...

A commercial carbon whisker reinforced polylactic acid composite made by a type of three-dimensional (3D) printing known as material extrusion additive manufacturing is investigated. The primary objective is to experimentally characterize and model the direction-dependent tensile modulus of elasticity of unidirectionally printed composite material...

A novel method has been developed to optimize both the form and behavior of complex systems. The method uses spatial grammars embodied in character-recurrent neural networks (char-RNNs) to define the system including actuator numbers and degrees of freedom, reinforcement learning to optimize actuator behavior, and physics-based simulation systems t...

The use of additive manufacturing (AM) has increased in many industries, resulting in a commensurate need for a workforce skilled in AM. To meet this need, educational institutions are integrating design for additive manufacturing (DfAM) into the engineering curriculum. However, limited research has explored the impact of these educational interven...

Machine learning can be used to automate common or time-consuming engineering tasks for which sufficient data already exist. For instance, design repositories can be used to train deep learning algorithms to assess component manufacturability; however, methods to determine the suitability of a design repository for use with machine learning do not...

Limited academic course offerings and high barriers to incorporate industrial additive manufacturing (AM) systems into education has led to an underserved demand for a highly skilled AM workforce. In this research, virtual reality (VR) is proposed as a medium to help teach introductory concepts of AM in an interactive, scalable manner. Before imple...

Prototypes have been identified as critical artifacts for generating and developing innovative products and thus stimulating economic growth. However, prototyping is also associated with a large sunk cost including the extensive time and resources required to make physical prototypes. While a wide variety of prototyping methods have been proposed t...

Full field strain during tensile deformation is measured in parts produced by material extrusion additive manufacturing (MEAM) using digital image correlation. Many studies have been conducted to examine stress and strain at the part level; however, local levels of stress and strain within MEAM parts remain largely unexplored. This study documents...

A significant gap exists between engineering students' perceptions of prototypes and prototyping abilities and professionals' perceptions and abilities. Structured prototyping frameworks have recently been developed and proposed as a means to help students close this gap, but the effects of these frameworks on students' behavior have not been asses...

Methods for evaluating the strength of design dependencies in a product architecture have been widely studied in the literature; however, evaluating the effects of direct and indirect interactions between components/modules remains a challenge. In fact, indirect connections between components/modules are often overlooked in many cases when evaluati...

In this study we investigate how we can effectively redesign a product family using additive manufacturing (AM). Specifically, we propose an integrated approach to product family redesign using platform metrics for a product family that uses AM. The proposed approach can help identify what to platform and how to platform with AM. We employ a variet...

In this paper, we present a method that uses a physics-based virtual environment to evaluate the feasibility of neural network-based generated designs. Deep learning models rely on large training data sets that are used for training. These training data sets are typically validated by human designers that have a conceptual understanding of the prob...

Demand for a highly skilled workforce in the field of additive manufacturing (AM) is growing but is underserved due to limited academic course offerings and high barriers for incorporating industrial AM systems into education. Virtual reality (VR) is proposed as a medium to help teach introductory concepts of AM to a broader audience in an interact...

In prototyping complex systems, concept iterations often reach a point where incremental modifications to one part in a complex system can produce unexpected, cascading changes in the rest of the system. This phenomenon can require time-consuming and expensive corrections, particularly when physical prototypes are involved — as was the situation in...

Mechanical advantage is traditionally defined for single-input and single-output rigidbody mechanisms. A generalized approach for identifying single-output mechanical advantage for a multiple-input compliant mechanism, such as many origami-based mechanisms, would prove useful in predicting complex mechanism behavior. While origamibased mechanisms a...

Design for manufacturing provides engineers with a structure for accommodating the limitations of traditional manufacturing processes. However, little emphasis is typically given to the capabilities of processes that enable novel design geometries, which are often a point of focus when designing products to be made with additive manufacturing (AM)...

Additive Manufacturing (AM) is a novel process that enables the manufacturing of complex geometries through layer-by-layer deposition of material. AM processes provide a stark contrast to traditional, subtractive manufacturing processes, which has resulted in the emergence of design for additive manufacturing (DfAM) to capitalize on AM’s capabiliti...

Additive manufacturing (AM) technology has significant potential to improve heat exchanger (HX) performance through incorporation of novel geometries and materials, but there is limited understanding of AM HX functionality relative to conventionally manufactured components. This study compares the performance of conventionally-built plate-fin air–l...

Functionally graded materials (FGMs) gradually change composition throughout their volume, allowing for areas of a part to be optimized for specific performance requirements. While additive manufacturing (AM) process types such as material jetting and directed energy deposition are capable of creating FGMs, design guidelines for varying the materia...

This study presents usabilityconsiderations and solutions for the design of glasses-type wearable computer displays and examines their effectiveness in a case study.Design countermeasures were investigated by a four-step design process: (1) preliminary design analysis;(2) design idea generation; (3) final design selection; and (4) virtual fitting t...

The building design community is currently experiencing a shift towards generating more resilient and sustainable designs that are also safe and economic. Integrating these broad, often conflicting, factors into design causes the design process to become more complex, the decisions more difficult, and a need for higher fidelity (and more expensive)...

Recent advances in simulation and computation capabilities have enabled designers to model increasingly complex engineering problems, taking into account many dimensions, or objectives, in the problem formulation. Increasing the dimensionality often results in a large trade space, where decision-makers (DM) must identify and negotiate conflicting o...

Approximately half of new product development projects fail in the market place. Within the product development process, prototyping represents the largest sunk cost; it also remains the least researched and understood. While researchers have recently started to evaluate the impact of formalized prototyping methods and frameworks on end designs, th...

Cost estimation techniques for Additive Manufacturing (AM) have limited synchronization with the metadata of 3D CAD models. This paper proposes a method for estimating AM build costs through a commercial 3D solid modeling program. Using an application programming interface (API), part volume and surface data is queried from the CAD model and used t...

Design for Additive Manufacturing is an evolving field that allows alternative design approaches to facilitate improvements in parts and builds by taking advantage of the capability of additive manufacturing (AM). Currently, available CAD software does not provide sufficient tools for AM designers, which results in a complex iterative process requi...

Due to the multidisciplinary nature and complexity of self folding structures, it can be difficult to know where to start when designing for a new application. Decisions about the active and passive materials to be used and the functionality of the design are very interrelated and can create problems if not considered holistically. There is a need...

Companies usually launch families of products into the market to provide value to different segments based on different customer needs; however, most of the research on Value-Driven Design (VDD) in the literature has focused on modeling value functions and optimizing the design of single products, not families of products. In order to increase prof...

A promising approach to overcome the challenges of exploring a design solution space is to employ Set-Based Design tightly coupled to Model-Based Systems Engineering, and to treat the design process formally as a sequential decision process. In such a paradigm, designers start with an initial set of potential solutions, using lower fidelity models...

In order to determine target market and price, and design products/components for a family of front-loading washing machines, the coordination for decision-making from the corporate level down to the product and ultimately component levels is required. However, existing design research for many products focuses on analyzing single or multiple disci...

There is renewed interest in workforce development and manufacturing education/training thanks to the establishment of the Manufacturing USA Institutes, originally called the National Network for Manufacturing Innovation (NNMIs). As part of their efforts to bridge the gap between basic research and technology commercialization, these institutes are...

Additive manufacturing (AM) provides engineers with nearly unlimited design freedom, but how much do they take advantage of that freedom? The objective is to understand what factors influence a designer’s creativity and performance in Design for Additive Manufacturing (DFAM). Inspired by the popular Marshmallow Challenge, this exploratory study pro...

As companies are pressured to reduce costs and lead-times while increasing variety, the need to design products based on common platform “elements” is growing. Product family design has become an effective strategy to meet this challenge, but companies still struggle with assessing how “good” their product family is. Companies routinely benchmark t...

Development of Material Extrusion systems for 3D printing and their increase in accessibility has been instrumental in the rapid growth of individuals with hands-on experience in additive manufacturing. Fabricating parts using Material Extrusion has progressed from being a novel and expensive ordeal to a cheap, easy, and relatively fast method. How...

Design can be viewed a sequential decision process that increases the detail of modeling and analysis while simultaneously decreasing the space of alternatives considered. In a decision theoretic framework, low-fidelity models help decision-makers identify regions of feasibility and interest in the tradespace and cull others prior to constructing m...

Prior research has shown that powder-bed fusion (PBF) additive manufacturing (AM) can be used to make functional, end-use components from powdered metallic alloys, such as InconelVR 718 superalloy. However, these end-use components and products are often based on designs developed for more traditional subtractive manufacturing processes and do not...

Design decision-making involves tradeoffs between many design variables and attributes, which can be difficult to model and capture in complex engineered systems. To choose the best design, the decision maker is often required to analyze many different combinations of these variables and attributes and process the information internally. Trade Spac...