Design prototyping methods

textProduct development is often modeled as a cycle between phases of designing, building, and testing. This work will explore early stage build efforts of product design, which is also known as prototyping. Prototyping is a critical determinant of product success. Research shows that different approaches to prototyping can greatly affect design outcome. This work provides an integrated overview, and expansion of the existing work on design prototyping methods. Following the introduction, an extensive literature review of design prototyping tools, techniques, and methods is provided. These sources are indexed and comparatively reviewed. The capabilities of a novel hybrid prototyping technique is explored through a design case study. Next, insights from the review are integrated in a context independent prototyping strategy method. The method is developed with heuristics extracted from the literature, and additional insights from experimental studies. The technique is then experimentally evaluated. Finally, results of an extensive study of an online design repository are provided. The results include five key principles for prototype design and fabrication. The presence of these principles in the repository is validated through a novel crowd-sourced online study. The outcome effects of deploying these principles to design teams is experimentally evaluated. Overall, this research provides a guide to prototyping which includes a systematically indexed review and comparison of the existing work, as well as a novel method, and principles for design and fabrication.Mechanical Engineerin

Designettes: An Approach to Multidisciplinary Engineering Design Education

Design and other fundamental topics in engineering are often isolated to dedicated courses. An opportunity exists to foster a culture of engineering design and multidisciplinary problem solving throughout the curriculum. Designettes, charettelike design challenges, are rapid and creative learning tools that enable educators to integrate design learning in a single class, across courses, across terms, and across disciplines. When two or more courses join together in a designette, a multidisciplinary learning activity occurs; multiple subjects are integrated and applied to open-ended problems and grand challenges. This practice helps foster a culture of design, and enables the introduction of multidisciplinary design challenges. Studies at the Singapore University of Technology and Design (SUTD) demonstrate learning of engineering subject matter in a bio-inspired robotics designette (MechAnimal), an interactive musical circuit designette, and an automated milk delivery (AutoMilk) designette. Each challenge combines problem clarification, concept generation, and prototyping with subject content such as circuits, biology, thermodynamics, differential equations, or software with controls. From pre- and postsurveys of students, designettes are found to increase students' understanding of engineering concepts. From 321 third-semester students, designettes were found to increase students' perceptions of their ability to solve multidisciplinary problems

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

Background: Many patients with COVID-19 have been treated with plasma containing anti-SARS-CoV-2 antibodies. We aimed to evaluate the safety and efficacy of convalescent plasma therapy in patients admitted to hospital with COVID-19. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]) is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. The trial is underway at 177 NHS hospitals from across the UK. Eligible and consenting patients were randomly assigned (1:1) to receive either usual care alone (usual care group) or usual care plus high-titre convalescent plasma (convalescent plasma group). The primary outcome was 28-day mortality, analysed on an intention-to-treat basis. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936. Findings: Between May 28, 2020, and Jan 15, 2021, 11558 (71%) of 16287 patients enrolled in RECOVERY were eligible to receive convalescent plasma and were assigned to either the convalescent plasma group or the usual care group. There was no significant difference in 28-day mortality between the two groups: 1399 (24%) of 5795 patients in the convalescent plasma group and 1408 (24%) of 5763 patients in the usual care group died within 28 days (rate ratio 1·00, 95% CI 0·93–1·07; p=0·95). The 28-day mortality rate ratio was similar in all prespecified subgroups of patients, including in those patients without detectable SARS-CoV-2 antibodies at randomisation. Allocation to convalescent plasma had no significant effect on the proportion of patients discharged from hospital within 28 days (3832 [66%] patients in the convalescent plasma group vs 3822 [66%] patients in the usual care group; rate ratio 0·99, 95% CI 0·94–1·03; p=0·57). Among those not on invasive mechanical ventilation at randomisation, there was no significant difference in the proportion of patients meeting the composite endpoint of progression to invasive mechanical ventilation or death (1568 [29%] of 5493 patients in the convalescent plasma group vs 1568 [29%] of 5448 patients in the usual care group; rate ratio 0·99, 95% CI 0·93–1·05; p=0·79). Interpretation: In patients hospitalised with COVID-19, high-titre convalescent plasma did not improve survival or other prespecified clinical outcomes. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Background: In this study, we aimed to evaluate the effects of tocilizumab in adult patients admitted to hospital with COVID-19 with both hypoxia and systemic inflammation. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein ≥75 mg/L) were eligible for random assignment in a 1:1 ratio to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg–800 mg (depending on weight) given intravenously. A second dose could be given 12–24 h later if the patient's condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and ClinicalTrials.gov (NCT04381936). Findings: Between April 23, 2020, and Jan 24, 2021, 4116 adults of 21 550 patients enrolled into the RECOVERY trial were included in the assessment of tocilizumab, including 3385 (82%) patients receiving systemic corticosteroids. Overall, 621 (31%) of the 2022 patients allocated tocilizumab and 729 (35%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·85; 95% CI 0·76–0·94; p=0·0028). Consistent results were seen in all prespecified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital within 28 days (57% vs 50%; rate ratio 1·22; 1·12–1·33; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (35% vs 42%; risk ratio 0·84; 95% CI 0·77–0·92; p<0·0001). Interpretation: In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the amount of respiratory support and were additional to the benefits of systemic corticosteroids. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

Transformational indicators : deciding when to develop transformable products

textTransformable products (or transformers), those with two or more functional states, are increasingly utilized by our society. As the mobility and complexity of life increases, so must the adaptability of the products which we use. We need new design techniques to develop more adaptable devices, such as transformers. The purpose of this study is to propose a response to the question “When is it preferable to implement a design approach focused on developing transformable products over an approach focused on developing primary function, non transforming products?” Our response to this question comes in the form of a method. The method helps a designer or design team consider the benefits of developing a transformer at an early stage in the design process. Research includes a deductive and an inductive study which are used to identify transformation indicators or context properties and usage factors that identify when it is preferable to build a transformable device. Static function-state indicators are also presented. These are contrary to transformation indicators in that they identify contexts suitable for developing non-transforming devices. Our technique seeks to improve the outcome of a design project by encouraging the consideration of transformable solutions and aiding in the selection of an appropriate design process. This method for testing the presence of these indicators in exemplary design contexts is presented. One such application is the design of an autonomous bridge-health monitoring system.Mechanical Engineerin

Mining and Representing the Concept Space of Existing Ideas for Directed Ideation

AbstractDesign innovation projects often generate large numbers of design ideas from designers, users, and, increasingly, the crowd over the Internet. Such idea data are often used for selection and implementation but, in fact, can 1also be used as sources of inspiration for further idea generation. In particular, the elementary concepts that underlie the original ideas can be recombined to generate new ideas. But it is not a trivial task to retrieve concepts from raw lists of ideas and data sources in a manner that can stimulate or generate new ideas. A significant difficulty lies in the fact that idea data are often expressed in unstructured natural languages. This paper develops a methodology that uses natural language processing to extract key words as elementary concepts embedded in massive idea descriptions and represents the elementary concept space in a core–periphery structure to direct the recombination of elementary concepts into new ideas. We apply the methodology to mine and represent the concept space underlying massive crowdsourced ideas and use it to generate new ideas for future transportation system designs in a real public sector-sponsored project via humans and automated computer programs. Our analysis of the human and computer recombination processes and outcomes sheds light on future research directions for artificial intelligence in design ideation.</jats:p

Connecting Design Problem Characteristics to Prototyping Choices to Form a Prototyping Strategy

Connecting Design Problem Characteristics to Prototyping Choices to Form a Prototyping Strategy Abstract Prototyping is a critical part of the product design process with the potential to play a significant role in determining the success or failure of the product. A variety of decisions are made by the design team when determining the manner in which they will develop prototypes. Example decisions include: choosing to develop either multiple prototypes or only a single prototype; and choosing to develop either a scaled or fully functional prototype. We define a prototyping strategy as the compilation of all the decisions that need to be made in order to develop a prototype. Thorough review of the literature on prototyping reveals that there are no comprehensive strategies to guide designers in the development of such a prototyping strategy. In our previous research, we identified what we believe is a comprehensive list of the variables that constitute a prototyping strategy. In addition, we developed some data collection tactics that were intended to provide insight for the designer when creating their prototype strategy. However, the opportunity to provide specific methods for optimizing the suite of variables in the prototyping strategy remained open. In the current research we provide a set of heuristics that can be used directly to create the prototyping strategy. These heuristics are tested using a set of 15 design teams working on their senior undergraduate capstone design. These teams were all provided with the heuristics and training on how to use them. However, teams were allowed to violate the “suggestions” provided by the heuristics. For example, a heuristic might be that if significant resources (time and money) can be saved by development of a dimensionally scaled prototype and if a scaled prototype can be used to verify all the critical design requirements, then a dimensionally scaled prototype should be developed as opposed to a full scale prototype. Assessment involves correlating the specific decisions teams made to either follow or violate each heuristic with a set of measures of the effectiveness of their prototypes. Key metrics for effectiveness of the prototyping strategy are whether teams stayed on schedule, were within budget and if they met key design requirements. Initial assessment data suggests that the prototyping heuristics significantly improve the effectiveness of the prototyping process

Design prototyping methods: state of the art in strategies, techniques, and guidelines

Prototyping is interwoven with nearly all product, service, and systems development efforts. A prototype is a pre-production representation of some aspect of a concept or final design. Prototyping often predetermines a large portion of resource deployment in development and influences design project success. This review surveys literature sources in engineering, management, design science, and architecture. The study is focused around design prototyping for early stage design. Insights are synthesized from critical review of the literature: key objectives of prototyping, critical review of major techniques, relationships between techniques, and a strategy matrix to connect objectives to techniques. The review is supported with exemplar prototypes provided from industrial design efforts. Techniques are roughly categorized into those that improve the outcomes of prototyping directly, and those that enable prototyping through lowering of cost and time. Compact descriptions of each technique provide a foundation to compare the potential benefits and drawbacks of each. The review concludes with a summary of key observations, highlighted opportunities in the research, and a vision of the future of prototyping. This review aims to provide a resource for designers as well as set a trajectory for continuing innovation in the scientific research of design prototyping

The Economies and Dimensionality of Design Prototyping: Value, Time, Cost, and Fidelity

Economic use of early-stage prototyping is of paramount importance to companies engaged in the development of innovative products, services, and systems because it directly impacts their bottom line. There is likewise a need to understand the dimensions, and lenses that make up an economic profile of prototypes. Yet, there is little reliable understanding of how resources expended and views of dimensionality across prototyping translate into value. To help practitioners, designers, and researchers leverage prototyping most economically, we seek to understand the tradeoff between design information gained through prototyping and the resources expended prototyping. We investigate this topic by conducting an inductive study on industry projects across disciplines and knowledge domains while collecting and analyzing empirical data on their prototype creation and test processes. Our research explores ways of quantifying prototyping value and reinforcing the asymptotic relationship between value and fidelity. Most intriguingly, the research reveals insightful heuristics that practitioners can exploit to generate high value from low and high fidelity prototypes alike