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Purpose This paper aims to provide a comprehensive review of the state-of–the-art design methods for additive manufacturing (AM) technologies to improve functional performance. Design/methodology/approach In this survey, design methods for AM to improve functional performance are divided into two main groups. They are design methods for a specific objective and general design methods. Design methods in the first group primarily focus on the improvement of functional performance, while the second group also takes other important factors such as manufacturability and cost into consideration with a more general framework. Design methods in each groups are carefully reviewed with discussion and comparison. Findings The advantages and disadvantages of different design methods for AM are discussed in this paper. Some general issues of existing methods are summarized below: most existing design methods only focus on a single design scale with a single function; few product-level design methods are available for both products’ functionality and assembly; and some existing design methods are hard to implement for the lack of suitable computer-aided design software. Practical implications This study is a useful source for designers to select an appropriate design method to take full advantage of AM. Originality/value In this survey, a novel classification method is used to categorize existing design methods for AM. Based on this classification method, a comprehensive review is provided in this paper as an informative source for designers and researchers working in this field.

One of the major features of product-service systems (PSS) design is a variety of design elements. This makes its design process complex and obscure. This study aims to develop a method for analysing how the design process influences the features of design solutions in the conceptual design of PSS. In this study, protocol analysis is applied to plural PSS design sessions. Simultaneously, their design solutions are evaluated relatively based on several aspects. Their design processes are analysed in connection with the above evaluation results. The findings obtained by using the proposed method will contribute to creating practical design guidelines for superior PSS development.

WOS:000401635900021 The traditional decision-making process during early design stages deals with deterministically evaluating the design candidates in accordance with concrete objectives by assuming optimal or nominal design performance values for the candidates. However, this may increase subjectivity in the decision process since the design knowledge during early design is usually imprecise and incomplete, and mostly needs to be iteratively updated throughout product design development. To diminish the subjectivity, the knowledge of the design requirements can be precisely and accurately represented by means of probabilistic constraints that describe the uncertainties in the design requirements; therefore, in this work, a systematic design framework supported by reliability analysis is developed in such a way that it is able to provide an effective connection among the early design steps especially both at system level and component level. Thus, the probability of failures of the design candidates and their sub-solutions are investigated, based on design constraints with Gaussian distributions, or lower and upper bounds, by utilizing Monte Carlo method. To illustrate the potential applicability and efficacy of the proposed framework, a two-finger gripper design problem is considered. The results clearly demonstrate that the proposed framework is effective to achieve reliable design solutions that have uncertain quantitative characteristics to be used further in probabilistic structural analysis during the next design stages such as embodiment and detail design stages. Scientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [BIDEP 2219] This research was supported by the Scientific and Technological Research Council of Turkey (TUBITAK), under the BIDEP 2219-International Postdoctoral Research Fellowship Programme.

Conceptual design is a critical design phase during which initial design solutions, called design concepts, are developed. These design concepts must be evaluated to ensure they satisfy the specified design requirements and the most appropriate design concept must be selected. It is often difficult for the designer, especially for the novice, to make an appropriate design concept evaluation and selection. Existing work on design evaluation lacks an effective tool for evaluating the temporal performance of the design concepts. To address this problem, a Critical Path Method (CPM) from project management is adapted for design evaluation, whereby a CPM network is converted from a causal behavioral process (CBP) and the methodologies relating to CPM are also applied to design improvement. A case study of a lever-clamp assembly system is also presented to illustrate as well as validate the method.

This paper focuses on better understanding how design processes affect outcomes in mechanical engineering design. Following a general design research methodology, process data were collected from student design journals and tested for association with design quality as measured by an external evaluation using a virtual design of experiments approach. The results indicate that more time spent on system-level design (including problem generation, idea generation, and analysis activity) and on concept-level problem definition activity associate positively with design quality, while more time spent on concept-level idea generation, detailed design, and refinement associated negatively with design quality. These results imply that student designers should emphasize problem definition, information gathering, and system-level design work more so than high-level idea generation activities.

Life-cycle modeling for design (LCMD) is a methodology for assessing the life-cycle impacts for a complex product with many individual components starting from initial design phases when few design specifications have been made. The methodology combines life-cycle assessment (LCA) with probabilistic design methods in a way that forecasts attributes of possible final designs yet reduces information needs. Specifically, LCMD is a methodology for generating arrays of design scenarios that communicate the range of designs being considered by a design team, and estimating missing data for those design scenarios. The main contribution to enhancing standard LCA is the incorporation of methods to estimate physical attributes of individual components for various design options and in four analyses for evaluating the arrays of design scenarios. An automotive case study presented in part 2 of this work demonstrates one application of LCMD.

The inherent dynamic relationships among design tasks performed concurrently at different organizations characterize the complexities of a design chain where designers with diverse expertise need to collaborate across organizational boundaries. To ensure timely completion of inter-related design tasks, metrics to facilitate the early evaluation of design concepts are crucial. The ability to evaluate and select suitable design concepts at an early stage will ensure better solutions and greater savings in time and effort further downstream. This paper proposes a new approach based on the rough set theory to design concept analysis. The approach aims at early detection of design inadequacy. A so-called information system is constructed using the information gleaned from design concepts and design capabilities, and analyzed using the rough set theory to derive a set of design rules for design concept analysis. The approach embodies a technique for handling attributes with unavailable information, which is a frequent occurrence in design. This paper presents details of the proposed approach, the novel technique, and a case study.

A discussion of knowledge and Knowledge-Based design as related to the design of aircraft is presented. The paper discusses the perceived problem with existing design studies and introduces the concepts of design and knowledge for a Knowledge-Based design system. A review of several Knowledge-Based design activities is provided. A Virtual Reality, Knowledge-Based system is proposed and reviewed. The feasibility of Virtual Reality to improve the efficiency and effectiveness of aerodynamic and multidisciplinary design, evaluation, and analysis of aircraft through the coupling of virtual reality technology and a Knowledge-Based design system is also reviewed. The final section of the paper discusses future directions for design and the role of Knowledge-Based design.

Objective of the design process are cost effective designs that meet certain expectations with respect to functionality and appearance. Designs are created in an iterative process where analyses of the structural behavior lead to changes in the design. The use of optimization technology makes design changes to be driven directly by analysis results. The application of optimization allows an efficient search for the right combination of design variables for a certain design. Additional use of stochastic methods in order to analyze the design from a statistical standpoint adds robustness to the design and prevents unpleasant surprises in later physical testing.This paper discusses methodology to optimize structures that undergo impact loading. Objective and constraints are transient dynamic responses. The optimization problem is solved using a sequential response surface method. An explicit finite element code is used to solve the transient dynamic problem. The optimization is not performed on results from single simulations but on statistical results from a stochastic analysis. The stochastic analysis is driven using a Monte Carlo method. Commercial software is used for the implementation of the methodology.The results from the study indicate that a combination of optimization and stochastic analysis can add safety margins to a design with respect to robustness against physical errors in the design itself and against changes in load levels and load cases. However, this initial study must be followed up by more in-depth investigations to fully understand the benefits of combined optimization-stochastic analysis.

The axiomatic design approach has contributed to the advancement of design practice by creating good design evaluation criteria based on design axioms. Complexity measure is important in design evaluation in order to simplify the engineering design. In this paper, we use Boltzmann entropy as the complexity measure and derive mathematical relationships between design complexity and various components in engineering design in the context of the axiomatic design approach. Three components of the design complexity are identified, they are variability, vulnerability and correlation, in which the vulnerability is related to the size of the design problem, the interdependency of design parameters and the sensitivity of functional requirements of the design towards the change in design parameters.

Little research has been done on how designers actually design. Much of design research is concerned with computer-based models or is based on anecdotal evidence of the design process. This paper describes the development and application of a methodology that uses protocol studies of designers engaged in design to investigate the process of designing. A coding scheme is developed and applied to design protocols. The scheme brings structure to the unstructured data of the protocols without detracting from the richness of the data. Results are shown that illustrate the utility of this approach in gaining some insight into how designers design.

SUMMARY One of the most tangible contributions to quality engineering over the last 15 years is the concept of robust design and its concrete realization by means of designed experiments. However, robust design as promoted by the Taguchi method clashes with design theory as it puts emphasis on parameter design as the most important means of robustifying technical systems. It is argued in this article that the design phases that precede parameter design ∥i.e. system design) actually determine the attainable level of product robustness in the parameter design stage. It is shown how qualitative methods in the form of design principles can be utilized in early design phases to support the process of robust design.

This paper addresses the problem of representing design history. In particular we describe a design information system that captures three different aspects of design history: exploration of design alternatives, reasons for design decisions and design constraints. These three aspects of design history are basically different and it is appropriate to represent them in different ways. An integrated design information system (IDIS) which supports the representation of these different aspects of design history is presented. Three case studies which have been used to test the system at various stages during its development are presented. One of the components of the system, which uses the issue based representation, was tested using an example from process engineering. The example helped us to identify some of the strengths and weaknesses of that component. This evaluation also enabled us to formulate the principle of preserving temporal integrity. A case study is also presented which tested the ability of the system to retrospectively represent design information that is currently recorded in a design project. This case study also highlighted some of the problems with existing design documentation procedures. In the final case study the system was used off-line to record design information as it was generated. These case studies found that the system could represent the required information and provided a methodology and semi-formal representation that helped the designers. Due to the success of these trials the system is now being used by a team of researchers in an industrial setting to provide the next level of testing.

This paper presents a backwards design method for mechanical conceptual design. The method involves starting with a very idealistic semiworking solution and then systematically solving the unworkable parts of the solution until a complete solution is found. The method can work in conjunction with other methods such as Theory of Inventive Problem Solving (TRIZ) or brainstorming. The method tries to exploit the principle that it is easier to critique and modify a design than it is to create a fully working solution in one go. The visual nature of the method means that it is suited to design problems where geometry is important such as mechanism design and machine design. Three case studies of conceptual design are presented. The case studies involve a novel clutch, a novel rotary damping mechanism and a novel worm gearbox. Each of these designs won at least one national design competition in the UK. A simple design experiment has been carried out which indicated that the backwards design method was at least as effective as the morphological chart method for a simple machine design exercise.

A generative CAD based design exploration method is proposed. It is suitable for complex multi-criteria design problems where important performance criteria are uncomputable. The method is based on building a genotype of the design within a history based parametric CAD system and then, varying its parameters randomly within pre-defined limits to generate a set of distinctive designs. The generated designs are then filtered through various constraint envelopes representing geometric viability, manufacturability, cost and other performance related constraints, thus reducing the vast design space into a smaller viable design space represented by a set of distinctive designs. These designs may then be further developed by the designer. The proposed generative design method makes minimal imposition on the designer’s work process and maintains both flexibility and fluidity that is required for creative design exploration. Its ability to work seamlessly with current CAD based design practices from early conceptual to detailed design is demonstrated. The design philosophy behind this generative method and the key steps involved in its implementation are presented with examples Refereed/Peer-reviewed

The need to capture design knowledge and transfer it to the development of design environments is described. Two sets of design studies are presented in which data concerning the analogue circuit design process are captured for use in the development of a semiautomated design environment. Data derived from design activities in the first set of studies are represented in a cognitive model. The second set of studies is aimed at exploring in more detail the relationship between plans and the circuit design process. Conclusions and recommendations for system design are presented.

International audience; Once a design concept has been chosen and parameterised, the embodiment design stage consists of choosing materials and dimensions to ensure a |good matching| with the expected performances. In this context of preliminary design stages, several approaches exist, which correspond to slightly different complexities and issues and must consequently be used at different moments. We consider in this paper three families of approaches: 1) exploring design (parametric) dimensioning under uncertainty (through constraint programming techniques, representations of feasible design points or Pareto frontiers); 2) robust design and multidisciplinary optimisation; 3) design for reliability. We advocate and state in this paper that these approaches must be used in that order of increasing complexity. Indeed, applying an approach allows one to quickly figure out inadequacies with performance specifications or initial allowable bounds of design parameters and then to backtrack or to refine the design issue before proceeding to the next stage or approach. We illustrate that phenomenon by successively applying the three approaches on a dimensioning issue of a two-member truss structure. We clearly show that the successive optimal designs obtained are notably different, but that the optimal point obtained in a given approach is used to explore its surroundings within the next approach.

*Power system reliability is critical to the performance of modern aircraft. Reliability issues must be considered from the beginning of the power system design process. Addressing these issues can complicate a design flow. To manage this complexity, design teams must use an organized approach based on proven design principles. A Robust Design methodology provides this organized approach. This paper investigates the Robust Design process as it pertains to system design. General Robust Design principles are introduced and related to the development of aircraft power systems. Design tasks are outlined as they apply to the Robust Design process. These tasks are then related to the capabilities that design tools must have to help design teams improve system reliability. A basic 3-phase, 230VACto-28VDC converter is analyzed using the Saber® simulator from Synopsys, Inc. The analysis follows the steps of a Robust Design-based flow and includes a nominal analysis to establish a performance baseline for the system, a sensitivity analysis to investigate which design parameters have the most affect on system performance, a parametric analysis to evaluate system performance while key design parameters are swept through selected values, a statistical analysis to analyze the system’s performance as parameter values are allowed to randomly change within their tolerance range, a stress analysis to evaluate stresses placed on system components, and a failure modes analysis to examine system performance as individual components fail. Establishing simulation techniques for implementing a Robust Design flow is the primary focus of this paper. Understanding detailed converter design is left as an exercise for the reader.

In this paper, we explore the benefits of materials design in a product design process. We also compare the methods of material selection and materials design by demonstrating two examples—the design of a cantilever beam for minimum weight and the design of a fan blade for minimum weight. The design of the cantilever beam is carried out using Ashby’s material selection method as well as a proposed method for materials design. The design of the fan blade and its material is completed using computational tools. Our goal in this paper is to demonstrate the benefits of materials design over material selection methods and to illustrate the flexibility inherent in materials design processes. We are more interested in revealing the possibilities of materials design, rather than the specific results from the example problems. The investigation of materials design presented in this paper moves us one step closer towards the realization of a systematic, inductive method for the concurrent design of products and materials.Copyright © 2006 by ASME

An analysis tool to aid in preliminary design of re-entry aeroshells for interplanetary exploration is presented. The computational tool addresses a common feature of design analysis, the need to make use of results from several analysis regimes and from several sources. This paper formalizes for computation what has historically been a matter of informal engineering judgment. The automation of design analysis allows for more extensive search of the design space, and thus supports a design process that is at once more thorough and more efficient. The human designer uses experience and intuition to combine results from different analyses. Here, this combination is formalized by recognizing that each analysis tool is valid in particular regimes of the design problem; where regimes overlap, a combination based on participation factors (and utilizing the mathematics of fuzzy sets) is employed. An aggregated level of confidence for each solution point is also calculated.

This paper reports on a observational study and 2 experimental studies of the design process deriving from our interest in improving the design of computer software. A model of design is developed from these studies. This consists of 3 interacting processes: goal elaboration, design generation and design evaluation. The experimental studies show that design specifications are often incorrect and incomplete with different designers paying more or less attention to different aspects of the design. Finally, from the design model and the results of the experimental studies, a number of aids to the design process are developed and discussed.