Lasers evolved as a versatile materials processing tool due to their advantages such as rapid, reproducible processing, chemical cleanliness, ability to handle variety of materials, and suitability for automation. This article focuses on state-of-the-art laser applications to improve tribological performance of structural materials in lubricated and nonlubricated environments. It discusses the fundamentals of various laser materials interactions and reviews laser-based surface-modification strategies, including laser surface heating and melting, laser-synthesized coatings, and laser-based design approaches such as laser patterning and dimpling. Laser-surface modification of novel materials, such as high-entropy alloys and metallic glasses, is explored. The article provides an overview of hybrid techniques involving laser as a secondary tool, as well as a discussion on the improved capabilities of laser surface engineering for tribological applications by means of integrated computational process modeling.

Additive manufacturing (AM) has gained increased significance and has been adopted across many industries for various applications. Specific net-shape AM fabrication methods, such as laser powder-bed fusion (LPBF), have matured significantly, leading to aerospace sector R&D focused on the feasibility of using flagship alloys to manufacture complex components. This article presents one example of an aluminum alloy design tailored for laser powder-bed fusion AM. It discusses the integrated computational materials engineering design approach. The article also presents the design for high-strength, high-temperature aluminum alloys.

This article discusses process simulation applications such as casting, powder metallurgy, machining, surface engineering, heat treatment, and joining. The implementation of modeling and simulation tools requires accurate descriptions of material properties and process boundary conditions. The article describes the role of input data and boundary conditions for process simulations. It provides information on the critical enablers of computational materials engineering, such as the computational speed, computational materials engineering software/hardware supply chain, and cost structure for virtual versus physical manufacturing and analysis.

Composite materials offer amazing opportunities for delivering structures that are optimized to meet design requirements. This article provides a summary of the concepts discussed in the articles under the section “Engineering Mechanics, Analysis, and Design” in ASM Handbook, Volume 21: Composites. The section introduces many of the engineering approaches used in composite industry.

Integrated computational materials engineering refers to the use of computer simulations that integrate mathematical models of complex metallurgical processes with computer models used in component and process design. This article outlines an example of a computer-aided engineering tool, such as virtual aluminum castings (VAC), developed and implemented for quickly developing durable cast aluminum power train components. It describes the procedures for the model development of the VAC system. These procedures include linking the manufacturing process to microstructure, linking microstructures to mechanical properties, linking material properties to performance prediction, and model validation and integration into the engineering process. The article discusses the benefits of the VAC system in process selection, process optimization, and improving the component design criteria.

This article describes the general concepts and practices related to manufacturing and design. It discusses the activities of design and manufacturing by placing it in the context of the business system that they support. The article presents an overview of the manufacturing technology field from a design and material selection perspective. It provides an insight to the complex relationship among design, material selection, and manufacturing. The article offers information on modern design for manufacturing practices that are widely used in the industry.

This article provides a brief historical perspective, a classification of metallurgical processes, basic model development efforts, and an overview of the potential future directions for the modeling of metals processing. It describes the classification of material behavior models, which can be grouped broadly into three classes: statistical, phenomenological, and mechanistic models. The article also presents an overview of the potential directions for the modeling of metals processing.

Engineering design should result in a product that performs its function efficiently and economically within the prevailing legal, social, safety, and reliability requirements. This introductory article discusses some key considerations in design, material selection, and manufacturing that a materials engineer should take into account to satisfy such requirements. It includes a brief section on concurrent engineering, which companies use to ensure that all needed input is obtained and addressed concurrently throughout the product lifecycle, including material selection and processing, product design, cost analysis, manufacturing, recyclability, and performance.

This article discusses tools that are used for the systematic optimization of engineering designs. It focuses on the practical application of optimization technology in a computer-aided engineering environment. The article presents numerical optimization algorithms and provides some background on how these algorithms make decisions when searching for the optimal design. It also provides information on structural optimization, topology optimization, materials processing optimization, multidisciplinary optimization, and global optimization.

This article discusses the various roles and responsibilities of materials engineers in a product realization organization and suggests different ways in which materials engineers may benefit their organization. It also provides a summary of the concepts discussed in the articles under the Section “The Role of the Materials Engineer in Design” in ASM Handbook, Volume 20: Materials Selection and Design.

This article discusses issues that impact a good casting design. The focus is on the casting design in general, and on sand and permanent mold aluminum casting in particular. The article examines the casting design process from a variety of design and processing perspectives. It summarizes several strategies for improving the traditional casting design process. The article also proposes some possible approaches for implementing these strategies. It presents a vision for the development of comprehensive casting design guidelines along with specific development objectives.

This article presents an overview of the use of mechanism analysis (kinematics and dynamics) and simulation. It provides indications of the directions in which mechanism simulation is growing and how it is integrated in the evolving computer aided design and computer aided engineering (CAD/CAE) fields. Mechanism simulation is best used as part of a concurrent CAD/CAE approach to design. The article discusses the state, evolution, and direction of application for these techniques in a variety of fields.

This article presents an approach to manage the uncertainty present in materials design. It describes inductive and deductive approaches to deal with uncertainty. The article focuses on providing an understanding of the opportunities for managing uncertainty and the decisions that influence the accuracy of the results. A design of experiments (DOE) represents a sequence of experiments to be performed, expressed in terms of factors set at specified levels. The article discusses the two types of DOEs: the full factorial design and the fractional factorial design. It explains the factors to be considered when selecting a procedure for propagating uncertainty. The article lists the categories of the popular types of uncertainty propagation methods, including simulation-based methods, local expansion methods, and numerical integration-based methods.

Materials selection is closely related to the objectives of failure analysis and prevention. This article briefly reviews the general aspects of materials selection as a concern in both proactive failure prevention during design and as a possible root cause of failed parts. Coverage is more conceptual, with general discussions on the following topics: design and failure prevention, materials selection in design, materials selection for failure prevention, and materials selection and failure analysis. Because materials selection is just one part of the design process, the overall concept of design is discussed. The article also describes the role of the materials engineer in the design and materials selection process. It provides information on the significance of materials selection in both the prevention and analysis of failures.

The concepts of fracture mechanics are basic ideas for developing the methods of predicting the load-carrying capabilities of structures and components containing cracks. This article provides an introduction to the methodology for computing the onset of fracture and describes plane strain fracture toughness, denoted as K IC . It presents formulas for the stress-intensity parameter as a function of crack size, crack shape, applied stress (or load), and geometry of load application.

Additive manufacturing (AM) creates parts layer by layer directly from three-dimensional computer-aided design data. This article discusses systematic ways to address the challenges in AM data integration by exploring various AM-specific data-integration scenarios that can improve the current AM ecosystem. Representative AM data sources are also described. A reference framework that captures the heterogenous AM data sources and existing data-integration mechanisms are used. General data-integration practices—based on existing manufacturing data and lab information system integration experiences—are recommended to automate AM data flow, operations, and development. Lastly, the article discusses the seven steps in the big-data-integration workflow.

This article describes the historical background, uncertainties in structural parameters, classifications, and application areas of probabilistic analysis. It provides a discussion on the basic definition of random variables, some common distribution functions used in engineering, selection of a probability distribution, the failure model definition, and a definition of the probability of failure. The article also explains the solution techniques for special cases and general solution techniques, such as first-second-order reliability methods, the advanced mean value method, the response surface method, and Monte Carlo sampling. A brief introduction to importance sampling, time-variant reliability, system reliability, and risk analysis and target reliabilities is also provided. The article examines the various application problems for which probabilistic analysis is an essential element. Examples of the use of probabilistic analysis are presented. The article concludes with an overview of some of the commercially available software programs for performing probabilistic analysis.

This article details findability, accessibility, interoperability, and reusability (FAIR) additive manufacturing data management principles and examines related motivations, benefits, and challenges. It explains opportunities to advance the state of the AM community efforts in fostering FAIR data management practices/principles and outlines the consequence of such efforts on technology maturation and industrialization for AM technologies.

This article focuses specifically on material modeling applied to structure-property predictions. It provides general guidelines and considerations in terms of modeling the salient material features that ultimately impact the mechanical performance of parts produced by additive manufacturing (AM). Two of the primary ingredients needed to predict structure-property relationships via material modeling include a geometrical representation of the microstructural features of interest (e.g., grain structure and void defects) and a suitable constitutive model describing the material behavior, both of which can be scale and resource dependent. The article also presents modeling challenges to predict various aspects of (process-) structure-property relationships in AM.

Optimized modeling of fracture-critical structural components and connections requires the application of elastic-plastic fracture mechanics. Such applications, however, can require sophisticated analytical techniques such as crack tip opening displacement (CTOD), failure assessment diagram (FAD), and deformation plasticity failure assessment diagram (DPFAD). This article presents the origin and description of FAD and addresses R6 FAD using J-integral. It details the fracture criteria of BS 7910. The factors to be considered during the use of FAD and the applications of FAD are also reviewed.