Set-based Design Research Articles

New Conventions: Intentional Implementation of Set-Based Design Leveraging Limited Point-Based Approaches

This article communicates a practical application of Set-Based Design (SBD) during its adoption within the U.S. Navy’s latest surface ship design processes. It highlights how the team harnessed SBD to explore the vast design space and make critical decisions. Intriguingly, the article explores the design team’s use of point-based designs(PBD), a counterintuitive approach within the context of SBD. It delves into the rationale behind their implementation and the diverse purposes they serve in bridging knowledge gaps such as prototyping, integration, and evaluation of set interfaces. Furthermore, the article presents a preliminary ontology outlining various use cases for these PBDs. A key focus of this article is understanding how these PBDs coexist within the larger set-based construct while recognizing their inherent differences. The article examines the utility and boundaries of this approach, shedding light on the pragmatic interplay.

Early Risk Quantification Strategy for Design Space Reduction Decisions in Set-Based Design

Perceptions of feasibility in design spaces are susceptible to change if new and conflicting information becomes available later. Design space reduction decisions made in set-based design can amplify vulnerability to new information if remaining design spaces and present perceptions are unable to adapt. This paper considers different ways new information can alter perceptions of feasibility for complex design problems and introduces an early, probabilistic strategy for quantifying the risk of eliminating potential design solutions based on the vulnerability of remaining design spaces to new information. Emergent designs of a set-based design process gauging this risk are evaluated against one neglecting it for an analogous design problem. Early results indicate that the probabilistic model is able to effectively delay design decisions and prevent lock-in while design space understanding is still growing.

New combination of methods for supporting a simplified set-based design approach

AbstractThis work presents a Set-Based Design inspired approach for generation, evaluation and reduction of a solution space of alternative product concepts. Also, the aspect of how to implement the process in an industrial environment was investigated. The hypothesis, confirmed by case studies, is that it can be done using existing methods like Enhanced functional modelling, brainwriting, the Gallery method, Axiomatic Design, causal diagrams and Pugh matrices. The method can be successfully introduced in a timeframe of a few working days and support development engineers in the concept design phase.

A novel framework for set-based steel connection design automation

Existing computational design tools for steel connection design predominantly employ a point-based design (PBD) approach, which requires iterative re-evaluation whenever there are changes in design specifications. This paper introduces a new framework that adopts a set-based design (SBD) approach, aiming to substantially reduce the iteration and time cost associated with steel connection design and rework. The framework integrates a component-set connection design model with a database storage and query-based data retrieval method. The first method enables the flexible and efficient generation of a large connection design space from all possible component combinations, and automated identification of valid connection configurations within it. The latter method allows for automated design space refinement from preference-based evaluation of connection design efficiency and high-speed comparison and selection of optimal connection designs. To evaluate the relative performance of SBD and PBD approaches, the framework is applied to a steel floor system design case study with 62 connections. Results showed that the SBD approach achieved near-instantaneous connection design automation, with a total execution time of fewer than 55 milliseconds, making it over 10 times faster than the corresponding PBD approach.

Review of models and frameworks for set-based design

Review of models and frameworks for set-based design

Review of models and frameworks for set-based design

Review of models and frameworks for set-based design

Development and testing of lean simulation game on set-based design

Purpose Set-based design (SBD) is a lean tool widely adopted for improving design processes and providing value maximization to clients. The purpose of this paper is to present the development and testing of a lean simulation game that incorporated point-based and SBD principles. The objective of the game was to enhance learning of lean design management among construction students. Design/methodology/approach After a thorough and comprehensive literature review consisting of secondary data in journal papers, books, thesis references and primary data in the form of interviews with lean practitioners, the simulation game prototype was developed. The testing of the game was carried out with a study group. Data were collected during the gameplay with the help of a questionnaire survey on a confidence scale and Likert scale and assessed using the Wilcoxon signed-rank test, histogram, one-sample t-test and false discovery rate (Benjamini–Hochberg) correction method. Findings The data collected both pre- and post-simulation showed an increase in average confidence in understanding from 3.33 to 3.89, a 16.7% rise. The data was further interpreted by using Wilcoxon signed-rank test, indicating that the post-simulation learning experience was significantly better than the pre-simulation one. Promising positive results were obtained for the questions on game design, engagement and understanding of point-based design and SBD concepts. Originality/value The simulation game helps bridge the gap between knowledge building and real-life by effectively imitating the process. The game facilitates a dynamic and critical approach toward developing new educational simulation games and their successful incorporation in propagating lean principles in the construction industry.

Multi-Objective Design of EMI Filter with Uncertain Parameters by Preference Set-Based Design Method and Polynomial Chaos Method

Multi-Objective Design of EMI Filter with Uncertain Parameters by Preference Set-Based Design Method and Polynomial Chaos Method

Informing Program Management Decisions Using Quantitative Set-Based Design

System design is an exercise in sequential decision-making, with the objective of developing resilient and affordable systems. Throughout the design process, engineering and program managers must balance several competing objectives, such as ensuring design feasibility, minimizing cost, schedule, and performance risk, while simultaneously achieving stakeholder value. Thus, engineering and program managers require design and analysis methods enabling complex and multiobjective design decisions under uncertainty. Unfortunately, there exists limited research providing quantitative methodologies specifically enabling program management decisions using quantitative set-based design. We, therefore, present a quantitative set maturation and uncertainty resolution decision methodology using value-focused multiobjective decision models and model-based engineering practices. This methodology assesses and quantifies uncertainty regarding stakeholder value, cost, requirements, and design maturity for each design set. These metrics facilitate the calculation of the program manager value, which when combined with design set feasibility entropy, enable tradeoff analysis informing design maturation and uncertainty resolution prioritization decisions. We develop and demonstrate our methodology using a model-based unmanned aerial vehicle case study implemented in the ModelCenter modeling environment. This methodology provides program managers an efficient, cost effective, and defensible approach to inform system design maturation and uncertainty resolution decisions enabling the development of resilient and affordable systems.

Given-Find-In Order To-Subjected To (GFIS) method for the problem statement in set-based design

The Given-Find-Solution (GFS) method is a widely used procedure to systematically understand “what the problem is” in engineering problems. Nevertheless, the GFS method does not provide a clear guide on how to handle uncertainty, feasibility, and preference for design problems. Addressing this issue is crucial since the designer usually requires making assumptions to be able to propose functional solutions. The Given-Find-In Order To-Subjected To (GFIS) method and roadmap are here proposed to systematically state a design problem and requirements using fuzzy desirability functions to handle uncertainty, feasibility, and preference. The GFIS method lists the parameters, variables, specifications, restrictions, and preferences to facilitate the decision-making process. A comparative study was conducted with undergraduate students from Tecnológico de Monterrey enrolled in the course Design Methodologies. The students solved a band brake design problem before and after applying the GFIS method, and their performance was compared. The results showed a significant improvement in their decision-making ability, their capability to find feasible solutions, and the time required to make a design proposal.

Investigation of the operational flexibility of a regional hybrid-electric aircraft

The complexity of hybrid-electric aircraft propulsion systems is also characterized by the greater number of degrees of freedom of the energy management system, whose objective is to split the required power to fly the aircraft to the different available powertrains (i.e., gas turbines, electric motors, fuel cells, etc.). Typically, a single design mission is considered for assessing the performance of a hybrid-electric propulsion system, often with a simple constant split power between the batteries and gas turbine. A probabilistic set-based design space exploration methodology is used and allows us to study the effects of lifecycle analysis of the battery pack of a hybrid-electric 50-seater turboprop, while different mission scenarios are considered. Using this approach, it is possible to flexibly find multiple families of energy management strategies that can satisfy battery capacity requirements and the reduction of emissions simultaneously. Furthermore, the generated data can help the designers to understand the hierarchy of the requirements that drive the design of the propulsion system for a range of operating scenarios, with emphasis on the energy storage system. Hence, the airliners are offered enhanced operational flexibility of the aircraft for different and desirable mission profiles.

Design space covering for uncertainty

Managing uncertainty in engineering design continues to challenge engineers. By combining the concept of regret from robust optimization with that of design space reduction from set-based design, a new complementary view on uncertainty referred to as Design Space Covering for Uncertainty (DSC-U) is introduced. This method develops a trade-space between reducing the design space and locking in sub-optimal performance while considering interval uncertainty that impacts the problem. A double-loop algorithm and a more efficient set covering algorithm are presented along with the structure of the method. These are demonstrated on three sample problems, a previously-studied cantilever tube optimization, the Rosenbrock function with different levels of coupling between the uncertain parameters, and a ship midship section design problem with thirty-six design variables and four uncertain terms. The DSC-U approach is shown to be practical in providing a complementary insight into the impact of uncertainty for a wide range of design techniques.

Set-Based Design Method for Rigid Axle Suspension using Bayesian Active Learning

Set-Based Design Method for Rigid Axle Suspension using Bayesian Active Learning

Exploring the impact of set-based concurrent engineering through multi-agent system simulation

Abstract Set-based concurrent engineering (SBCE), a process that develops sets of many design candidates for each subproblem throughout a design project, proposes several benefits compared to point-based processes, where only one design candidate for each subproblem is chosen for further development. These benefits include reduced rework, improved design quality, and retention of knowledge to use in future projects. Previous studies that introduce SBCE in practice achieved success and had very positive future outlooks, but SBCE encounters opposition because its core procedures appear wasteful as designers must divide their time among many designs throughout the process, most of which are ultimately not used. The impacts of these procedures can be explored in detail through open-source computational tools, but currently few exist to do this. This work introduces the Point/Set-Organized Research Teams (PSORT) modeling platform to simulate and analyze a set-based design process. The approach is used to verify statements made about SBCE and investigate its effects on project quality. Such an SBCE platform enables process exploration without needing to commit many projects and resources to any given design.

Innovation level in set-based design: an integrated approach with chosen-to-fit and custom-to-fit solutions

Set-Based Design (SBD) is superior in risk reduction, knowledge creation, and innovation. However, its implementation demands more resources than traditional strategies. Thus, it is crucial to balance design space size and available resources to disseminate SBD. This paper proposes a method to define the level of innovation of subsystems enabling a hybrid development strategy, integrating the SBD and the Point-Based Design (PBD). We undertook a research action in a technological innovation design subject to significant knowledge and human/financial resource restrictions. The team allocated most resources in the SBD and focused efforts on critical subsystems. The exploratory and scientific nature of SBD enabled learning about the product without prior knowledge for supporting decision-making. By presenting the state-of-the-art regarding innovation level in SBD and proposing a method to define the level of innovation and a hybrid development strategy, this research paves the way for SBD in projects with significant resource restrictions.

A Parallel Tempering Approach for Efficient Exploration of the Verification Tradespace in Engineered Systems

Verification is a critical process in the development of engineered systems. Through verification, engineers gain confidence in the correct functionality of the system before it is deployed into operation. Traditionally, verification strategies are fixed at the beginning of the system’s development and verification activities (VAs) are executed as the development progresses. Such an approach appears to give inferior results as the selection of the VAs does not leverage information gained through the system’s development process. In contrast, a set-based design (SBD) approach to verification, where VAs are dynamically selected as the system’s development progresses, has been shown to provide superior results. However, its application under realistic engineering scenarios remains unproven due to the large size of the verification tradespace. In this work, we propose a parallel tempering approach (PTA) to efficiently explore the verification tradespace. First, we formulate an exploration of the verification tradespace as a tree search problem. Second, we design a parallel tempering (PT) algorithm by simulating several replicas of the verification process at different temperatures to obtain a near-optimal result. Third, We apply the PT algorithm to all possible verification states to dynamically identify near-optimal results. The effectiveness of the proposed PTA is evaluated on a partial model of a notional satellite optical instrument.

Lifetime-Based Selection Procedures for DC Circuit Breaker Varistors

Varistors are widely used in dc circuit breaker (DCCB) application as fault energy absorption elements, which is not an application the varistors are originally designed for. The fault energy stress adversely impacts the varistor lifetime, thus affecting DCCB reliability and performance. This article presents two methods for choosing the appropriate varistor type and arrangement in a DCCB by linking 1) varistor lifetime and 2) DCCB component- and system-level parameters. The first method uses a set-based design approach with random Latin hypercube sampling to narrow down viable solutions. In comparison, the second method relies on a point-based design approach and proposes an integer programming problem to optimize varistor lifetime. Both procedures are applied to the selection of varistors in 1) a 12 kV DCCB rated for 2-kA nominal current and a peak fault current of 15 kA and 2) a reduced-scale 1.2-kV DCCB hardware prototype, using publicly available varistor data. The article shows the possibility of design for varistor lifetime in DCCB applications, and concludes that both selection procedures provide consistent, reasonable, and verifiable results. However, the results also pinpoint the significant gaps and call for future work on impulse stress versus lifetime relationships for DCCB varistors.

Through-Lifecycle Whole-Design Optimisation Using Software Deployment Toolchains

AbstractThrough-Lifecycle Whole Design Design Optimisation is widely considered one of the future approaches to solving design problems featuring prominently in Model-Based Systems Engineering, Set-Based Design and Digital Twins. Yet, design optimisation remains siloed optimising for design subsets. In this paper, we review academic literature and a series of case studies to uncover the challenges in achieving Through-Lifecycle Whole Design Design Optimisation. This is followed by action research that has investigated the application of software deployment toolchains to overcome the challenges.

Starting and Scaling a Set-Based Design Method for a Maritime System of Systems: Designing a Modern Warship

AbstractThere has been a growing body of literature and use cases for set-based design since its introduction in the 80s. Few studies or use cases involve highly complex systems, though, except for the hallmark work regarding Toyota in the late 90s. Over the last three years, the US Navy used set-based methods to design a complex system of systems: a warship. Their experience provides insight into the scalability of the method and design management considerations relevant to the start of similar projects.

Application of Probabilistic Set-Based Design Exploration on the Energy Management of a Hybrid-Electric Aircraft

The energy management strategy of a hybrid-electric aircraft is coupled with the design of the propulsion system itself. A new design space exploration methodology based on Set-Based Design is introduced to analyse the effects of different strategies on the fuel consumption, NOx and take-off mass. Probabilities are used to evaluate and discard areas of the design space not capable of satisfying the constraints and requirements, saving computational time corresponding to an average of 75%. The study is carried on a 50-seater regional turboprop with a parallel hybrid-electric architecture. The strategies are modelled as piecewise linear functions of the degree of hybridisation and are applied to different mission phases to explore how the strategy complexity and the number of hybridised segments can influence the behaviour of the system. The results indicate that the complexity of the parametrisation does not affect the trade-off between fuel consumption and NOx emissions. On the contrary, a significant trade-off is identified on which phases are hybridised. That is, the least fuel consumption is obtained only by hybridising the longest mission phase, while less NOx emissions are generated if more phases are hybridised. Finally, the maximum take-off mass was investigated as a parameter, and the impact to the trade-off between the objectives was analysed. Three energy management strategies were suggested from these findings, which achieved a reduction to the fuel consumption of up to 10% and a reduction to NOx emissions of up to 15%.