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The patent database is often used in searches of inspirational stimuli for innovative design opportunities because of its large size, extensive variety and rich design information in patent documents. However, most patent mining research only focuses on textual information and ignores visual information. Herein, we propose a convolutional neural network (CNN)-based patent image retrieval method. The core of this approach is a novel neural network architecture named Dual-VGG that is aimed to accomplish two tasks: visual material type prediction and international patent classification (IPC) class label prediction. In turn, the trained neural network provides the deep features in the image embedding vectors that can be utilized for patent image retrieval and visual mapping. The accuracy of both training tasks and patent image embedding space are evaluated to show the performance of our model. This approach is also illustrated in a case study of robot arm design retrieval. Compared to traditional keyword-based searching and Google image searching, the proposed method discovers more useful visual information for engineering design., 11 pages, 11 figures

Greenhouse gas emissions from anthropogenic sources are believed to be the main cause of global warming and climate change. Furthermore, fossil fuels are forecasted to remain the dominant source of energy in the near future. Therefore, capture and sequestration of greenhouse gases and in particular carbon dioxide is likely to be a major pathway toward environmental protection and energy sustainability. Such clarity has stimulated an intense and diverse range of research into various capture and mitigation technologies, which race with global warming in real-time. Quantification of the performance improvement rates of these technologies can inform decision-makers’ long-term investment strategies, and help researchers to identify technical bottlenecks and research potential. The present research estimates the yearly performance improvement rate of CO2 capture, non-CO2 GHG capture, and GHG mitigation technologies, using a novel method based on patent data and the corresponding citation network. Our findings suggest that membrane-based, condensation/rectification-based, and adsorption-based carbon capture are the most promising technologies. Furthermore, the average CO2 capture technologies are likely to improve slightly faster than solar, wind, and battery technologies, indicating their important role in future electrical grids. Unfortunately, subterranean or submarine CO2 storage was identified as a slow-growing technological domain and potentially a bottleneck in the future sustainable carbon chain, which requires further efforts.

The patent database is often used by designers to search for inspirational stimuli for innovative design opportunities because of the large size, extensive variety, and the massive quantity of design information contained in patent documents. Growing work on design-by-analogy has adopted various vectorization approaches for associating design documents. However, they only focused on text analysis and ignored visual information. Research in engineering design and cognitive psychology has shown that visual stimuli may benefit design ideation. In this study, we focus on visual design stimuli and automatically derive the vector space and the design feature vectors representing design images. The automatic vectorization approach uses a novel convolutional neural network architecture named Dual-Visual Geometry Group (VGG) aiming to accomplish two tasks: visual material-type prediction and international patent classification (IPC) section-label predictions. The derived feature vectors that embed both visual characteristics and technology-related knowledge can be potentially utilized to guide the retrieval and use of near-field and far-field design stimuli according to their vector distances. We report the accuracy of the training tasks and also use a case study to demonstrate the advantages of design image retrievals based on our model.

In this work, we attempt to provide a comprehensive granular account of the pace of technological change. More specifically, we survey estimated yearly performance improvement rates for nearly all definable technologies for the first time. We do this by creating a correspondence of all patents within the US patent system to a set of technology domains. A technology domain is a body of patented inventions achieving the same technological function using the same knowledge and scientific principles. We obtain a set of 1757 domains using an extension of the previously defined classification overlap method (COM). These domains contain 97.14% of all patents within the entire US patent system. From the identified patent sets, we calculated the average centrality of the patents in each domain to estimate their improvement rates, following a methodology tested in prior work. The estimated improvement rates vary from a low of 1.9% per year for the Mechanical Skin treatment - Hair Removal and wrinkles domain to a high of 228.8% per year for the Network management - client-server applications domain. We developed a one-line descriptor identifying the technological function achieved and the underlying knowledge base for the largest 50, fastest 20 as well as slowest 20 of these domains, which cover more than forty percent of the patent system. In general, the rates of improvement were not a strong function of the patent set size and the fastest improving domains are predominantly software-based. We make available an online system that allows for automated searching for domains and improvement rates corresponding to any technology of interest to researchers, strategists and policy formulators.

In this work, we attempt to provide a comprehensive granular account of the pace of technological change. More specifically, we survey estimated yearly performance improvement rates for nearly all definable technologies for the first time. We do this by creating a correspondence of all patents within the US patent system to a set of technology domains. A technology domain is a body of patented inventions achieving the same technological function using the same knowledge and scientific principles. We obtain a set of 1757 domains using an extension of the previously defined classification overlap method (COM). These domains contain 97.14% of all patents within the entire US patent system. From the identified patent sets, we calculated the average centrality of the patents in each domain to estimate their improvement rates, following a methodology tested in prior work. The estimated improvement rates vary from a low of 1.9% per year for the Mechanical Skin treatment- Hair Removal and wrinkles domain to a high of 228.8% per year for the Network management- client-server applications domain. We developed a one-line descriptor identifying the technological function achieved and the underlying knowledge base for the largest 50, fastest 20 as well as slowest 20 of these domains, which cover more than forty percent of the patent system. In general, the rates of improvement were not a strong function of the patent set size and the fastest improving domains are predominantly software-based. We make available an online system that allows for automated searching for domains and improvement rates corresponding to any technology of interest to researchers, strategists and policy formulators.

Technology innovation in electric vehicles is of significant interest to researchers, companies and policy-makers of many countries. Electric vehicles integrate various kinds of distinct technologies and decomposing the overall electric vehicle field into several key domains allows determination of more detailed, valuable information. To provide both broader and more detailed information about technology development in the EV field, unlike most previous studies on electric vehicle innovation which analyzed this field as a whole, this research decomposed the electric vehicle field into domains, which are power electronics, battery, electric motor as well as charging and discharging subdomains and then further extracted the subdomains. Furthermore, In addition, the improvement rates, technology trajectories and major patent assignees in these domains and key subdomains are determined using patents extracted for each domain from the US patent system. The main findings are: (1) The estimated rates of performance improvement per year are 18.3% for power electronics, 7.7% for electric motors, 23.8% for charging and discharging and 11.7% for batteries. The relatively lower improvement rate for electric motors and batteries suggests their potential to hinder the popularization of electric vehicles. Besides, as for the subdomains, the relatively higher technology improvement rate of lithium-ion battery or permanent magnet motor in its domain supports the current trend of battery or motor type quantitively from a patent analysis view. A possible implication for the policy makers encouraging EV development is to issue more incentive plans for innovations in the battery and electric motor domains, especially for lithium-ion battery and permanent magnet motor. (2) The technology trajectories depict the development of four critical subdomains over time, which quantitively proves the focuses and emerging topics of the subdomains and thereby provide guidance to research topic selection. For example, the silicon negative electrode is a promising topic in the subdomain of lithium-ion battery. (3) The key players in the four critical subdomains appear to be Toyota and Honda in hybrid power electronics, E-One Moli Energy Corp in lithium-ion batteries, Panasonic in Permanent Magnet motors and Toyota in discharging. The key players found by the main path method from the view of innovation are also important players in EV from the market view. Other market participants should pay more attention to the adjustment of business strategy of these companies to monitor the market, and make effort to invent important EV related technologies.

Battery electric vehicles (BEVs) are now clearly a promising candidate in addressing the environmental problems associated with conventional internal combustion engine vehicles (ICEVs). However, BEVs, unlike ICEVs, are still not widely accepted in the automobile market but continuing technological change could overcome this barrier. The aim of this study is to assess and forecast whether and when design changes and technological improvements related to major challenges in driving range and battery cost will make the user value of BEVs greater than the user value of ICEVs. Specifically, we estimate the relative user value of BEVs and ICEVs resulting after design modifications to achieve different driving ranges by considering the engineering trade-offs based on a vehicle simulation. Then, we analyze when the relative user value of BEVs is expected to exceed ICEVs as the energy density and cost of batteries improve because of ongoing technological change. Our analysis demonstrates that the relative value of BEVs is lower than that of ICEVs because BEVs have high battery cost and high cost of time spent recharging despite high torque, high fuel efficiency, and low fuel cost. Moreover, we found the relative value differences between BEVs and ICEVs are found to be less in high performance large cars than in low performance compact cars because BEVs can achieve high acceleration performance more easily than ICEVs. In addition, this study predicts that in approximately 2050, high performance large BEVs could have higher relative value than high performance large ICEVs because of technological improvements in batteries; however low performance compact BEVs are still very likely to have significantly lower user value than comparable ICEVs until well beyond 2050.

The future direction of technology development depends on the relative yearly rate of functional performance improvement of different technologies. We use patent data to identify accurate and reliable predictors of this rate for 30 technologies. We illustrate how patent-based predictors should be normalized to correct for possible confounding factors introduced by changing patenting dynamics. We test the accuracy and reliability of various predictors by means of a Monte Carlo cross-validation exercise. We find that a measure of the centrality of domains’ patented inventions in the overall US patent citation network is an accurate and highly reliable predictor of improvement rates.

The dynamics of knowledge transfer is an important topic for engineering managers. In this paper, we study knowledge boundaries – barriers to knowledge transfer – in groups of experts, using topic modeling, a natural language processing technique, applied to transcript data from the U.S. Food and Drug Administration’s Circulatory Systems Advisory Panel. As predicted by prior theory, we find that knowledge boundaries emerge as the group faces increasingly challenging problems. Beyond this theory, we find that knowledge boundaries cease to structure communications between communities of practice when the group’s expert ability is insufficient to solve its task, such as in the presence of high novelty. We conjecture that the amount of expert knowledge that the group can collectively bring to bear is a determining factor in boundary formation. This implies that some of the factors underlying knowledge boundary formation may aid – rather than hinder – knowledge aggregation. We briefly explore this conjecture using qualitative exploration of several relevant meetings. Finally, we discuss implications of these results for organizations attempting to leverage their expertise given the state of their collective knowledge.

This paper seeks to analyze how design creates economic value. The literature on knowledge-based economic development has primarily focused on innovation as the analytical lens, whereas design is the original action that leads to innovation. Despite the fundamental importance of design, existing design research has offered few insights and little guidance for national strategies due to the lack of focus on and analysis of design in an economic context. This paper addresses such gaps by linking design research and economic development theory. We first elaborate on the relationship among design, invention and innovation, describing the necessity of design activity for invention and innovation. Our analysis of the fundamental characteristics of design across contexts sheds light on the strategic importance of the accumulative nature of technology-based design for sustaining economic growth. Through the lens of technology-based design, we further quantitatively compare Singapore and three similarly-sized countries (South Korea, Finland and Taiwan). Based upon interview data, we also qualitatively examine Singapore's national strategy focusing on design. The quantitative and qualitative results align well with the Singaporean government's use of design as a strategic lever to pursue innovation-driven economic growth, and also reveal its achievements and shortfalls which indicate possible directions for strategic adjustment. Keywords: Technology-based design; Invention; Innovation; Design capability; Economic growth, SUTD-MIT International Design Centre (IDC)

An important issue in various domains of renewable energy is the use of technological improvement trends to project future capabilities of energy technologies. This paper analyzes two pairs of renewable energy technologies and finds that the annual improvement rate of cost/investment is quite different for the four technological domains: namely, solar photovoltaics (PV) (9.0% per year), wind turbines (2.9%), batteries (3.1%) and capacitors (21.1%). While these trends have been reasonably consistent over long time frames, projecting these trends into the future without a better understanding of the underlying causes of the improvements is not at all reliable. This paper establishes theoretical fundamentals for explaining the differences in such rates and a framework for empirically probing such explanations using patent data. Employing this framework, this study collects and analyzes a set of highly representative patents for each of the four domains, allowing measurement of: patenting rates, reliance on scientific literature and other characteristics of the different fields. Our study of the inventions, while not establishing an indisputable causal relationship for the differing rates, establishes a broader theoretical basis for why such rates differ so greatly and why they might be stable over time. Among many possible effects, this study indicates that the age of knowledge utilized in the patents and the percentage of very important inventions in the field are the most likely significant contributors to higher rates of advance.

This article proposes a new descriptive framework, which we label as the “ideation framework” (IF), of the design process from a dual cognitive-engineering perspective, partly based on existing frameworks from both fields and previous work by the author. The framework is for the ideation or front-end phase of the product development process, representing the interface between cognitive psychology and engineering design. Three domains – inspiration, decomposition, and integration – and three spaces – problem-space, idea-space, and concept-space – are the elements of the framework. The iterative flow of the engineering design process passes through the three domains in a semi-controlled way, through a sequence of specialization and generalization process loops in and between the spaces. An empirical descriptive examination of the ideation process is performed using designers with limited design experience. The designers were faced with a design problem that they had to solve in a limited period of time. The...

Dematerialization is the reduction in the quantity of materials needed to produce something useful over time. Dematerialization fundamentally derives from ongoing increases in technical performance but it can be counteracted by demand rebound -increases in usage because of increased value (or decreased cost) that also results from increasing technical performance. A major question then is to what extent technological performance improvement can offset and is offsetting continuously increasing economic consumption. This paper contributes to answering this question by offering some simple quantitative extensions to the theory of dematerialization. The paper then empirically examines the materials consumption trends as well as cost trends for a large set of materials and a few modern artifacts over the past decades. In each of 57 cases examined, the particular combinations of demand elasticity and technical performance rate improvement are not consistent with dematerialization. Overall, the theory extension and empirical examination indicate that there is no dematerialization occurring even for cases of information technology with rapid technical progress. Thus, a fully passive policy stance that relies on unfettered technological change is not supported by our results.

Patents represent one of the most complete sources of information related to technological change, and they also contain much detailed information not available anywhere else. Thus, patents are the ‘big data’ source most closely related to future-oriented technology analysis (FTA). Not surprisingly, therefore, there is very significant practical and academic use of the patent database for understanding past technical change and attempting to forecast future change. This paper summarizes several new methods and demonstrates their combined effectiveness in establishing a cutting-edge capability for patent study not previously available. This capability can be stated as a link between the information in patents and the dynamics of technological change. The demonstrated capability relies upon the use of a database containing the rates of improvement for various technologies. We also specify the term we use for the analysed units of technology: a technological domain is a set of artefacts that meets a specific generic function while utilizing a specific set of engineering and scientific knowledge. This definition is unambiguous enough so technological domains can be linked with progress rates and are sufficiently flexible to accommodate the large scale and complexity of the patent database. The existence of an improvement rate database and its quality is a critical foundation for this paper. Establishing the overall capability also involves relating the rate of improvement of a technological domain to the patents in that domain. We show that a recently developed method called the classification overlap method (COM) provides a reliable and largely automated way to break the patent database into understandable technological domains where progress can be measured. In this paper, we show how this method overcomes the third limitation of the patent database. The major conclusion of the paper is that there is now an overall objective method named Patent Technology Rate Indicator (PTRI) for using just patent data to reliably estimate the rate of technological progress in a technological domain. Thus, the first link between the patent database information and the dynamics of technological change is now firmly established; robustness and back-casting tests have shown that the assertion of reliability is meaningful and that the estimate has predictive value. We demonstrate the key methodology of new elements (use of COM and rate estimation from the selected patent sets) for 15 technologies that some have thought have possible future importance. The 15 cases also demonstrate the usefulness of the overall method by estimating technological improvement rates that are significantly different for this group of technologies.

Functional technical performance usually follows an exponential dependence on time but the rate of change (the exponent) varies greatly among technological domains. This paper presents a simple model that provides an explanatory foundation for these phenomena based upon the inventive design process. The model assumes that invention - novel and useful design- arises through probabilistic analogical transfers that combine existing knowledge by combining existing individual operational ideas to arrive at new individual operating ideas. The continuing production of individual operating ideas relies upon injection of new basic individual operating ideas that occurs through coupling of science and technology simulations. The individual operational ideas that result from this process are then modeled as being assimilated in components of artifacts characteristic of a technological domain. According to the model, two effects (differences in interactions among components for different domains and differences in scaling laws for different domains) account for the differences found in improvement rates among domains whereas the analogical transfer process is the source of the exponential behavior. The model is supported by a number of known empirical facts: further empirical research is suggested to independently assess further predictions made by the model., Comment: 43 pages, 10 figures

In Smith and Eppinger's pioneering research on coupled design processes, the dynamics of design iterations is modeled by a linear model, which implies that there is no overlap between redesign work and allows redesign workload to be more than the original design workload. Actually, this overlap often exists in practice and, therefore, reduces the total redesign workload. In this paper, we propose a nonlinear model for a coupled design process with overlap between redesign work and ensure that redesign workload is less than the original design workload. Based on the model, the sufficiency condition for the convergence of such a design process is proposed. A heuristic rule is also given to reduce the possibility of considering a design process that converges as one that does not converge. Furthermore, we develop a sufficiency condition for estimating the number of design iterations before converging as such an estimate is important for planning product development projects. Another heuristic rule is also introduced to increase the accuracy of estimating design iterations. Finally, numerical experiments are conducted to examine the correctness and performance of the proposed sufficiency conditions and heuristic rules.

Many important technical and policy decisions are made by small groups, especially by deliberative committees of technical experts. Such committees are charged with fairly combining information from multiple perspectives to reach a decision that one person could not make alone. Committees are social entities and are therefore affected by any number of mechanisms recorded in the social sciences. Our challenge is to determine which of these mechanisms are likely to be encountered in the deliberative process and to evaluate how they might impact upon decision outcomes. In particular, we examine the role of committee deliberations on the U.S. Food and Drug Administration's (FDA's) advisory panels.

Many products are manufactured in networks of firms linked by transactions, but comparatively little is known about how or why such transaction networks differ. This article investigates the transaction networks of two large sectors in Japan at a single point in time. In characterizing these networks, our primary measure is "hierarchy," defined as the degree to which transactions flow in one direction, from "upstream" to "downstream." Our empirical results show that the electronics sector exhibits a much lower degree of hierarchy than the automotive sector because of the presence of numerous inter-firm transaction cycles. These cycles, in turn, reveal that a significant group of firms have two-way "vertically permeable boundaries": (i) they participate in multiple stages of an industry's value chain, hence are vertically integrated, but also (ii) they allow both downstream units to purchase intermediate inputs from and upstream units to sell intermediate goods to other sector firms. We demonstrate that the 10 largest electronics firms had two-way vertically permeable boundaries while almost no firms in the automotive sector had adopted that practice. Copyright 2012 The Author 2012. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved., Oxford University Press.

Hierarchies occur widely in evolving self-organizing ecological, biological, technological, and social networks, but detecting and comparing hierarchies is difficult. Here we present a metric and technique to quantitatively assess the extent to which self-organizing directed networks exhibit a flow hierarchy. Flow hierarchy is a commonly observed but theoretically overlooked form of hierarchy in networks. We show that the ecological, neurobiological, economic, and information processing networks are generally more hierarchical than their comparable random networks. We further discovered that hierarchy degree has increased over the course of the evolution of Linux kernels. Taken together, our results suggest that hierarchy is a central organizing feature of real-world evolving networks, and the measurement of hierarchy opens the way to understand the structural regimes and evolutionary patterns of self-organizing networks. Our measurement technique makes it possible to objectively compare hierarchies of different networks and of different evolutionary stages of a single network, and compare evolving patterns of different networks. It can be applied to various complex systems, which can be represented as directed networks. © 2011 Wiley Periodicals, Inc. Complexity, 2011 © 2011 Wiley Periodicals, Inc.

A new method is presented in this paper for quantitatively assessing the role of materials innovation in overall technological development. The method involves the comparative examination of overall technical capability metrics with performance metrics at detailed levels of progress where materials/process innovation dominates the progress.

This paper extends a broad functional category approach for the study of technological capability progress recently developed and applied to information technology to a second key case—that of energy based technologies. The approach is applied to the same three functional operations—storage, transportation and transformation—that were used for information technology by first building a 100 plus year database for each of the three energy-based functional categories. In agreement with the results for information technology in the first paper, the energy technology results indicate that the functional approach offers a stable methodology for assessing longer time technological progress trends. Moreover, similar to what was found with information technology in the first study, the functional capability for energy technology shows continual—if not continuous—improvement that is best quantitatively described as exponential with respect to time. The absence of capability discontinuities—even with large technology displacement—and the lack of clear saturation effects are found with energy as it was with information. However, some key differences between energy and information technology are seen and these include: ▪ Lower rates of progress for energy technology over the entire period: 19–37% annually for Information Technology and 3–13% for Energy Technology. ▪ Substantial variability of progress rates is found within given functional categories for energy compared to relatively small variation within any one category for information technology. The strongest variation is found among capability progress among different energy types. ▪ More challenging data recovery and metric definition for energy as compared to information technology. These findings are interpreted in terms of fundamental differences between energy and information including the losses and efficiency constraints on energy. We apply Whitney's insight that these fundamental differences lead to naturally modular information technology artifacts. The higher progress rates of information-based as opposed to energy-based technologies follows since decomposable systems can progress more rapidly due to the greater ease of independent as opposed to simultaneous development. In addition, the broad implications of our findings to studies of the relationships between technical and social change are briefly discussed.

We present an algorithm for decomposing a social network into an optimal number of structurally equivalent classes. The k -means method is used to determine the best decomposition of the social network for various numbers of subgroups. The best number of subgroups into which to decompose a network is determined by minimizing the intra-cluster variance of similarity subject to the constraint that the improvement in going to more subgroups is better than a random network would achieve. We also describe a decomposability metric that assesses how closely the derived decomposition approaches an ideal network having only structurally equivalent classes. Three well-known network data sets were used to demonstrate the algorithm and decomposability metric. These demonstrations indicate the utility of the approach and suggest how it can be used in a complementary way to Generalized Blockmodeling.

This paper develops and assesses a broad functional category approach to arriving at metrics for assessing technological progress. The approach is applied to three functional categories of information technology — storage, transportation and transformation by first building a 100 plus year database for each of the three functional categories. The results indicate generally continuous progress for each functional category independent of the specific underlying technological artifacts dominating at different times. Thus, the empirical results reported in this study indicate that the functional category approach offers a more stable and reliable methodology for assessing longer time technological progress trends. Therefore, this approach offers the promise of being more useful in technological forecasting for large-scale change even as its ability to forecast specific dominant technological trajectories has been compromised.

This paper addresses the methodology used to determine the amount of human resources needed to develop products. It is based on an empirical study of five firms in different industries. The methods rely on technical experts operating within budget constraints. The specific methods vary from relatively ad-hoc approaches to database-driven, centralized, and validated approaches. This variation is largely correlated with project and overall product development organization scale in a logical fashion in that larger projects and organizations move away from individual decision-makers toward centralized, objective, and validated methods. The project characteristics used by the experts and implicitly utilized in the database models to assess project complexity are also detailed in this paper. These characteristics are categorized based on a project complexity framework. We found that the scale of a project and the amount of "stretch" are the two most widely used characteristics for estimating project complexity. We found no utilization of the level of either component or task interactions in estimating project complexity by the firms studied. We also found no empirical evidence for interactions being a determinant of project difficulty despite a fair amount of theoretical concern with their importance in project complexity. In addition, we analyzed the accuracy of methods and conclude that since the accuracy at a higher level masks resource allocation problems at a lower level, the accuracy should be followed at multiple levels.

A new approach to airplane product specification and assessment is introduced for the early, fuzzy frontend product development process. A highly adaptable and generalizable multi-attribute method is developed for rapidly assessing the value of new product designs relative to proposed or existing product portfolios. A process for determining the empirical role product attributes have played in differentiating products in competitive markets is introduced through the use of consumer-revealed preference data. The value approach is applied specifically to the business airplane industry with a discussion of how model parameters were selected, a sensitivity analysis, and comments on the data used in the analysis. Advantages of the new approach vis ` a vis existing aircraft industry assessment methods include the simplicity of the method, its adaptability to the changing needs of designers, and its ability to more correctly portray aspects of the current and historical business aviation market.

The use of terms such as “Engineering Systems”, “System of systems” and others have been coming into greater use over the past decade to denote systems of importance but with implied higher complexity than for the term systems alone. This paper searches for a useful taxonomy or classification scheme for complex Systems. There are two aspects to this problem: 1) distinguishing between Engineering Systems (the term we use) and other Systems, and 2) differentiating among Engineering Systems. Engineering Systems are found to be differentiated from other complex systems by being human-designed and having both significant human complexity as well as significant technical complexity. As far as differentiating among various engineering systems, it is suggested that functional type is the most useful attribute for classification differentiation. Information, energy, value and mass acted upon by various processes are the foundation concepts underlying the technical types.

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.

Enhancing the travel experience has become a crucial consideration for transportation companies to promote differentiation and customer loyalty. Therefore, transport planners, providers and manufacturers in general are becoming aware of the significance of understanding the passenger experience better, in order to improve transit policies, management and vehicles. The holistic perspective of the travel experience is conceptualized as involving: (1) a thorough set of passenger internal responses (e.g. cognitive and emotional) that are driven by experience factors, some of which are (2) aspects that are not in complete control of the transportation provider, such as waiting areas or the social environment, during (3) all the moments before, throughout and after the trip. Although transportation research has studied the different aspects of transportation quality, empirical studies with such a broad approach to the travel experience and its impact on loyalty are still scarce. This article takes a scale development approach to conceptualize, develop and test a multiple-item scale for measuring the travel experience from the defined holistic perspective, analyzing its perceptual dimensions and outcomes based on a quantitative study with 1226 passengers of a mid-distance bus transportation service. The travel experience scale demonstrates good psychometric properties and consists of 28 items aggregated into seven dimensions or experience factors: individual space, information provision, staff's skills, social environment, vehicle maintenance, off-board facilities, and ticket line service. The study shows that all seven experience factors have a significant impact on customer cognitive, emotional and behavioral responses to the transportation service, highlighting the importance of a broad approach to the study and management of the travel experience. The classical dimensions of individual comfort and vehicle maintenance are the ones with the strongest impact on experience outcomes, showing that transportation providers should maintain a strong focus on providing a good core service. However, other factors such as the social environment have an influence on emotions, which in turn affect loyalty to the transportation provider. These results show the need for a careful study and management of the different aspects of the travel experience, and an integrated design and management of the transport system as a whole.

Although the field of Engineering Systems (ES) is young, its intellectual roots originate far back in time. Tracing these roots is the objective of an integrative capstone assignment in the first doctoral subject for incoming ES PhD students at MIT. Teams of two or three students research the intellectual connections between a specific historical root and modern ES method. The assignment has now been offered for 5 years (2008–2012). This chapter describes the faculty and student perspectives on the assignment, including the perceived learning outcomes, and insights gained into the roots of Engineering Systems. Some overall observations include: (1) Interconnections among almost all selected topics are apparent. The historical development of each topic gives rise to overlap and complex interactions between historical roots and modern methods; (2) Students cite Herbert Simon’s work as most pivotal to the roots of Engineering Systems. Jay Forrester, John von Neumann, Norbert Weiner, Joseph Schumpeter and others are also identified as having a significant impact; (3) The faculty always learn something about the field from what the students find even when topics are repeated; and, (4) The assignment is a valuable, though imperfect, vehicle for learning about Engineering Systems and for launching budding researchers’ efforts in the field.

The customer experience is important for adding value to firms’ offerings but two challenges arise: the customer experience is increasingly created through interactions with product–service systems (PSSs) and it is formed through all moments of interaction with multiple firms. Incorporating customer experience requirements (ERs) into the design of PSSs is therefore a complex task. To address this challenge, this paper presents an extension of the Kansei engineering method consisting of two components. First, the extension includes an in-depth study of the customer experience from a holistic perspective that informs the design process. Second, it involves the active participation of multidisciplinary experts from the different partner companies that together enable the PSS offering. An application of this new extension is presented for mid-distance bus trips, involving passengers, a vehicle manufacturing and a transport provider company. The research followed design-science guidelines using an action resea...

This paper presents a relatively simple, objective and repeatable method for selecting sets of patents that are representative of a specific technological domain. The methodology consists of using search terms to locate the most representative international and US patent classes and determines the overlap of those classes to arrive at the final set of patents. Five different technological fields (computed tomography, solar photovoltaics, wind turbines, electric capacitors, electrochemical batteries) are used to test and demonstrate the proposed method. Comparison against traditional keyword searches and individual patent class searches shows that the method presented in this paper can find a set of patents with more relevance and completeness and no more effort than the other two methods. Follow on procedures to potentially improve the relevancy and completeness for specific domains are also defined and demonstrated. The method is compared to an expertly selected set of patents for an economic domain, and is shown to not be a suitable replacement for that particular use case. The paper also considers potential uses for this methodology and the underlying techniques as well as limitations of the methodology., SUTD-MIT International Design Center

This paper presents a repeatable method to identify, describe and analyze the important inventions in an industry. The method involves qualitative and quantitative methods of analysis of patents to understand the inventions that have contributed to the growth of an industry. We present a process for mapping the inventions by their importance in an attempt to understand the set of inventions that contribute most significantly to the development of an industry. As a demonstration of the method, a set of 2484 patented inventions in the solar PV industry was selected as a case study. The case study results show that the conceptual basis for the method is useful in understanding technological change in an industry. For example, the analysis identifies important PV patents but none that are discontinuously important. These findings support the probable utility of the framework and have some preliminary broader implications to our understanding of technological development.

Food and Drug Administration (FDA) advisory committees have a significant influence on patterns of clinical practice worldwide. Recent guidance to the committees by the FDA has focused on attempting to eliminate sources of bias due to committee voting procedures. Nevertheless, major sources of social influence have not been addressed. We analyzed transcripts of Circulatory Systems Devices Panel meetings from 1997 to 2005 in which the panel cast votes on premarket approval and for which a voting minority existed. Committee members who are assigned to speak later are significantly more likely to be in the voting minority (P < 0.001). This effect holds for meetings with sequential voting (P = 0.0058) and for meetings with simultaneous voting (P = 0.045). A weaker effect shows that, for meetings with sequential voting, committee members who vote later are significantly more likely to be in the voting minority (P = 0.018). Speaking order and voting order are both determined by seating location. We therefore conclude that voting behavior on FDA expert advisory committees is strongly associated with seating location. This suggests the presence of a possible social dynamic that is not addressed by existing FDA committee procedures.

Decisions by committees of technical experts are increasingly impacting society. These decision-makers are typically embedded within a web of social relations. Taken as a whole, these relations define an implicit social structure which can influence the decision outcome. Aspects of this structure are founded on interpersonal affinity between parties to the negotiation, on assigned roles, and on the recognition of status characteristics, such as relevant domain expertise. This paper build upon a methodology aimed at extracting an explicit representation of such social structures using meeting transcripts as a data source. Whereas earlier results demonstrated that the method presented here can identify groups of decision-makers with a contextual affinity (i.e., membership in a given medical specialty or voting clique), we now can extract meaningful status hierarchies, and can identify differing facilitation styles among committee chairs. Use of this method is demonstrated on the transcripts of U.S. Food and Drug Administration (FDA) advisory panel meeting transcripts; nevertheless, the approach presented here is extensible to other domains and requires only a meeting transcript as input.

This paper investigates the nature of collaboration in eight small technology-innovating firms who participated in the US Government sponsored SBIR (Small Business Innovative Research) process in 1995/6. The research was performed in 2003 allowing sufficient time to assess the relative success of various practices by the firms following differentiated SBIR processes. Following expectations, all of the firms participated in extensive collaboration. However, in contrast to earlier work studying the same firms in 1998/9, it is found that a SBIR process initiative designed to encourage collaboration with other entities and to accelerate commercial success ("Fast Track Process") had no influence on whether the firm had commercial and employment growth success. It appears that much of the identified collaboration is due to the need of small firms to extend their understanding of the broader systems implications of the technology they are developing. The paper also describes some perceptions held by small firms about reasons not to collaborate.

The maximum loads sustainable in both four-point bending and prebent hinge collapse tests of several materials have been determined at crosshead rates from 4.2 × 10−3 mm/s to 4.2 m/s (10−2–104 in./min). All the materials exhibit a logarithmic dependence of flow stress on crosshead rate; this dependence is consistent with that previously reported for tensile deformation. Although there are some minor differences in the dynamic stress factors obtained by the bending and tensile methods, all the methods rank the materials in the same order. Thus, for materials evaluation the most convenient test method, which is usually the tensile test, can be chosen. For more complex loading geometries than considered here, scale model testing would yield the most reliable results.

The most extensive materials substitution program in automotive history—from mild steel to high-strength steel —is currently well underway. The major technical issues affect almost all aspects of vehicle design and production, and this transition involves changing essential characteristics of the major car input material, sheet steel. This paper discusses the recent past, and future potential for high-strength, low-alloy steel applications in vehicles, including metallurgical changes responsible for changes in characteristics, material availability, and approximate relative cost. Implications of changed material properties and trade offs in the key sheet steel fabrication processes (forming and spot welding), as well as effects of HSLA steel use on vehicle design, particularly crush, mechanical durability, and rigidity, are also discussed. The major issues with respect to vehicle design are to delineate the materials which can be used in all components, and the associated weight reduction achieved in applications. At present, the primary factors deterring rapid implementation of HSLA steels are material availability and sheet metal forming.

This paper briefly reviews the various available types of high-strength steels — conventional, recovery-annealed, and dual-phase steels. A judgmental analysis of a large number of stamped automotive components shows that dual-phase steels, with their superior strength at a given elongation (formability), offer the best potential for weight savings. The rest of the paper concerns the physical metallurgy and mechanical response of dual-phase steels. It is shown that strength is a function of the percent martensite in the structure, although the strength is less than predicted by a simple rule of mixtures. The enhanced ductility of dual-phase steels is shown to be a consequence of the high s train-hardening rate observed in these steels, the reason for which is not well understood but probably reflects the properties of the ferrite matrix. The strain-rate sensitivity of dual-phase steels is found to be higher than that of conventional high-strength steels of comparable tensile strengths. Fatigue studies of dual-phase steels show them to be comparable to conventional high-strength steels in the notched condition; energy absorption during the axial collapse of tubes is shown to be solely a function of tensile strength. Also included are data on the temperature dependence of tensile strength in both the notched and unnotched conditions; high-strength dual-phase steels exhibit notch sensitivity even at room temperature. A study of formability (springback) shows that high-strength dual-phase steel is slightly worse than SAE 950X but much better than SAE 980X steel.

Influence du poids du vehicule sur sa consommation de carburant. Estimation du rapport optimal allegement/cout de fabrication. Validite des previsions

A general treatment of the absorption of mechanical energy by the axial collapse of a variety of structural shapes, including tubes, honeycombs and foams is developed which encompasses both the geometry of the structure and also the material properties. The use of the method in the design of load bearing structures in which energy absorption is an additional design function is illustrated. High strength-to-weight ratio materials offer a significant weight saving for energy absorbing components, although such materials may have a reduced tensile ductility. The implications to situations in vehicle crashworthiness are discussed. /SAE/