J. Mech. Des. Aug 2020, 142(8): 081401
Pubished online: February 14, 2020
Guanglu Zhang, Elissa Morris, Douglas Allaire, Daniel A. McAdams
J. Mech. Des. Aug 2020, 142(8): 081401
Pubished online: February 14, 2020
Many modern products, such as automobiles, aircrafts, laptops and smartphones, are engineered systems. The performance, function, and architecture of an engineered system continuously changes and improves over time. For example, cell phones of the 1990’s were limited to phone calls and text messages. Today's cell phones are computers capable of cinematography and reading the news. Research in engineered system evolution goes beyond tracking and predicting the technical performance and the functional and architectural changes of existing engineered systems. This research also studies how and why these changes occur and searches for causal factors behind these evolutions. The results of this research are valuable for designers, R&D managers, investors, and policy makers by aiding the generation of innovative design concepts, setting reasonable R&D targets, investing in promising technologies, and developing effective incentive policies. This paper summarizes key research questions, identifies pioneering literature, and discusses the opportunities and challenges for future research in engineered system evolution. Importantly, a free access database is provided for facilitating future research in this area. The database currently includes more than 100,000 data points that belong to 31 technical performance metric categories of 7 engineering systems (i.e., passenger aircraft, orbital launch system, automobile, computer, refrigerator, lamp, and direct-fire ground weapon systems) and their components.
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Carlye A. Lauff; Daria Kotys-Schwartz; Mark E. Rentschler
J. Mech. Des. 2018; 140(6):061102-061102-12; doi: 10.1115/1.4039340
Prototyping is an essential part of a company’s product development process. It is critical to launching new products to market; these products can range from the next generation iPhone to surgical devices for doctors to your favorite shoes. Currently, there are limited research studies conducted within companies, meaning we lack an understanding about how companies engage in prototyping activities. This research project observed the entire product development process within three companies in the fields of consumer electronics, medical devices, and footwear. Through our analysis, we uncovered that prototypes are tools for enhanced communication, increased learning, and informed decision-making.
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Inayat Ullah, Dunbing Tang, Qi Wang and Leilei Yin
J. Mech. Des 139(12), 121101; doi: 10.1115/1.4037627
Delivering a variety of products with minimal lead time is a critical issue given today’s competitive manufacturing industry. Many design and production firms address the challenges of variety by adopting a product family manufacturing strategy. Product families are a broad range of artifacts, known as product variants, which share a number of common components. Thus, engineering changes in a product family affect the product under consideration and other product variants in the family. This increases the difficulty of predicting the change propagation within a family of products. This paper introduces a seven-step change propagation approach that predicts and evaluates the impact of change propagation across product variants. Interdependencies and logical relationships between directly connected components are captured using a Component-based Design Structure Matrix. This highlights the different change propagation paths that are available in the product’s structure. Risk analysis in terms of lead time is performed at the component level. The results demonstrate that avoiding project delays requires selecting suitable change propagation paths in a family of products.
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Dipanjan Ghosh, Andrew Olewnik, Kemper Lewis, Junghan Kim and Arun Lakshmanan
J. Mech. Des 139(9), 091401 (Jul 12, 2017); doi: 10.1115/1.4036780
Understanding consumer perceptions of products and the potential impact of those perceptions on purchase decisions is critical information that should influence product development decisions. Though firms often seek consumer feedback on products, such feedback often occurs long after product use and lacks specific details about the interaction, usage context, etc. This work introduces a novel framework – Cyber-Empathic Design – that integrates sensor data and real-time user feedback to develop a more accurate model of user perceptions. The framework is applied to a case study focused on user perceptions of shoes. The results of this work demonstrate the potential for product developers to leverage the IoT (internet-of-things) movement, real-time user feedback, and advances in machine learning to connect user perceptions to specific engineered product features.
Figure: Data collection method (left) and resulting perceptual model (right).
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Development and Evaluation of a Mechanical Stance-Controlled Orthotic Knee Joint With Stance Flexion
Jan Andrysek; Matthew J. Leineweber; Hankyu Lee
J. Mech. Des. 2017; 139(3):035001-035001-7
People with severe impairment of the lower body caused by conditions such as polio or stroke often rely on assistive devices for mobility. Knee orthosis plays an important role in restoring mobility by stabilizing the weakened lower limb and providing support for standing and walking. Concurrently, the orthosis should allow for natural and efficient movement of the limb as required for walking. The focus of this work is to develop a new method for controlling orthotic knee joints. The new control method uses a mechanical system to monitor loading and timing events and patterns, and apply knee-locking function when the limb is loaded. A prototype was built and tested on a polio patient and demonstrated the feasibility of this approach for providing reliable orthotic function. Further work aims to test the knee joint on a larger group of individuals within the community.
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Seda Yilmaz, Colleen Seifert, Shanna R. Daly and Richard Gonzalez
J. Mech. Des 138(7), 071102; doi: 10.1115/1.4032219
Current design theory lacks a systematic method to identify what designers know that helps them to create innovative products. In the early stages of idea generation, designers may find novel ideas come readily to mind, or may become fixated on their own or existing products. This may limit the ability to consider more, and more varied candidate concepts that may potentially lead to innovation. To aid in idea generation, we sought to identify “design heuristics,” or “rules of thumb,” evident in award-winning designs. In this paper, we demonstrate a content analysis method for discovering heuristics in the designs of innovative products. Our method depends on comparison to a baseline of existing products so that the innovative change can be readily identified. Through an analysis of key features and functional elements in the designs of over 400 award-winning products, forty heuristic principles were extracted. These Design Heuristics are outlined according to their perceived role in changing an existing product concept into a novel design, and examples of other products using the heuristics are provided. To demonstrate the ease of use of these Design Heuristics, we examined outcomes from a classroom study, and found that concepts created using Design Heuristics were rated as more creative and varied. The analysis of changes from existing to innovative products can provide evidence of useful heuristic principles to apply in creating new designs.
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Soheil Arastehfar, Ying Liu and Wen Feng Lu
J. Mech. Des 138(3), 031103 (Feb 01, 2016); doi: 10.1115/1.4032396
Digital prototype (DP), as a form of communication media, allows designers to communicate design concepts to users by rendering the physical characteristics, e.g., size, colour, and texture. One important aspect is how well users can estimate the values of the physical characteristics of design concepts through interactions with DPs. Better estimates can lead to better perceptions of the designed attributes closely associated with the physical characteristics, and hence, useful user feedback about design concepts. The correctness of the estimates depends on two crucial factors: the ability of DPs to render physical characteristics and the way DPs are used to communicate physical characteristics in a particular environment and via different input/output devices. To date, little attention has been paid to the latter. Hence, it is important to identify an effective way of using DPs via the effectiveness assessment of various possibilities. This paper introduces a methodology for evaluating the effectiveness of communicating physical characteristics to users using DPs. During user interactions with DPs, the methodology collects user estimates of various physical characteristics and assesses the estimates on three dimensions, i.e., degree of correctness, time to make an estimate and handling of different values. The assessments are then evaluated by statistical analysis to reveal the effectiveness of the way of engaging DPs in helping users correctly and quickly estimate the values. The evaluated effectiveness reflects how successful the way of using a DP is, and also helps to suggest a better approach.
Additive manufacturing (AM) techniques provide designers with greater freedom in creating customized products with complex shapes. When major design changes are made to a part, undesirable high cost increments may be incurred due to AM process setting adjustments, challenging designers to explore AM-enabled design freedom while controlling costs at the same time. In this research, we introduce the concept of a variable product platform and its associated AM process setting platform, based on which the design and process setting adjustments can be restricted within a bounded feasible space in order to limit cost increments. Fuzzy Time-Driven Activity-Based Costing (FTDABC) approach is introduced to predict AM production costs based on process settings. The process setting adjustment’s feasible space boundary is identified by solving a multiobjective optimization problem. Design parameter limitations are computed in a Mamdani-type expert system and then used as constraints in the design optimization to maximize customer perceived utility. Case studies on designing an R/C racing car family illustrate the proposed methodology and demonstrate that the optimized additive manufactured variable platforms can improve product performances at lower costs than conventional consistent platform based design.
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Comparing Strategies for Topologic and Parametric rule Application in Automated Computational Design Synthesis
Corinna Königseder and Kristina Shea
J. Mech. Des. 2015;138(1):011102-011102-12. doi:10.1115/1.4031714
Computational Design Synthesis (CDS) methods can be used to enable the computer to generate valid and even creative solutions for engineering tasks. In grammatical approaches to CDS, formal grammars are used to represent a desired design language. This language consists of vocabulary that usually describes components and subsystems of a design and a set of grammar rules that describe possible design transformations. The formalized engineering knowledge can then be used by the computer to synthesize designs. For most engineering tasks, two different kinds of rules are required: rules that change the topology of a design, i.e. how the components are connected, and rules that change parameters of a design. One of the main challenges in CDS using topologic and parametric grammar rules is to decide a priori which type of rule to apply in which stage of the synthesis process as well as whether to start from a valid design and perturb it or to start from a void design. The research presented in this paper compares different strategies for topologic and parametric rule applications during automated design synthesis driven by a search algorithm. The presented strategies are compared considering quantity and quality of the generated designs. The effect of the strategies, the selected search algorithm, and the initial design, from which the synthesis is started, are analyzed for two case studies: the synthesis of gearboxes and of bicycle frames. Results show that the effect of the strategy is dependent on the design task and recommendations are given on which strategies to use for which design task.
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Assessing Quality of User-Submitted Need Statements From Large-Scale Needfinding: Effects of Expertise and Group Size
Cory R. Schaffhausen and Timothy M. Kowalewski
J. Mech. Des 137(12), 121102 (2015); doi: 10.1115/1.4031655
Collecting data on user needs can result in overwhelming amounts of data, especially if user groups are large and diverse. Additional analysis is necessary to prioritize a small subset of needs for further consideration. This study presents a simplified quality metric and online interface appropriate to initially screen and prioritize lists exceeding 500 statements for a single topic or product area. Over 20,000 ratings for 1697 need statements across three common product areas were collected in 6 days. A series of analyses tested whether particular characteristics of users and groups affect the number of high-quality needs that can be generated. The evaluated characteristics were user group size, needs submitted per person, and expertise and experience levels of users. The results provided important quantitative evidence of fundamental relationships between the quantity and quality of need statements. Increased quantities of high-quality need statements resulted both due to increasing user group size and due to increasing counts per person using novel content-rich methods to help users articulate needs. However, a user’s topic-specific expertise (self-rated) and experience level (self-rated hours per week) were not significantly associated with increasing need quality.
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This section includes brief descriptions of articles soon to be or recently published by the Journal of Mechanical Design. These featured articles highlight recent research developments and emerging trends in mechanical design. For Abstracts and Full Articles please see ASME's Digital Collection.