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Process redesign refers to the intentional change of business processes. While process redesign methods provide structure to redesign projects, they provide limited support during the actual creation of to-be processes. More specifically, existing approaches hardly develop an ontological perspective on what can be changed from a process design point of view, and they provide limited procedural guidance on how to derive possible process design alternatives. This paper aims to provide structured guidance during the to-be process creation.

Using design space exploration as a theoretical lens, the authors develop a conceptual model of the design space for business processes, which facilitates the systematic exploration of design alternatives along different dimensions. The authors utilized an established method for taxonomy development for constructing the conceptual model. First, the authors derived design dimensions for business processes and underlying characteristics through a literature review. Second, the authors conducted semi-structured interviews with professional process experts. Third, the authors evaluated their artifact through three real-world applications.

The authors identified 19 business process design dimensions that are grouped into different layers and specified by underlying characteristics. Guiding questions and illustrative real-world examples help to deploy these design dimensions in practice. Taken together, the design dimensions form the “Business Process Design Space” (BPD-Space).

Practitioners can use the BPD-Space to explore, question and rethink business processes in various respects.

The BPD-Space complements existing approaches by explicating process design dimensions. It abstracts from specific process flows and representations of processes and supports an unconstrained exploration of various alternative process designs.

The purpose of this work is to apply and compare surrogate-assisted and multi-fidelity, multi-objective optimization (MOO) algorithms to simulation-based aerodynamic design exploration.

The three algorithms for multi-objective aerodynamic optimization compared in this work are the combination of evolutionary algorithms, design space reduction and surrogate models, the multi-fidelity point-by-point Pareto set identification and the multi-fidelity sequential domain patching (SDP) Pareto set identification. The algorithms are applied to three cases, namely, an analytical test case, the design of transonic airfoil shapes and the design of subsonic wing shapes, and are evaluated based on the resulting best possible trade-offs and the computational overhead.

The results show that all three algorithms yield comparable best possible trade-offs for all the test cases. For the aerodynamic test cases, the multi-fidelity Pareto set identification algorithms outperform the surrogate-assisted evolutionary algorithm by up to 50 per cent in terms of cost. Furthermore, the point-by-point algorithm is around 27 per cent more efficient than the SDP algorithm.

The novelty of this work includes the first applications of the SDP algorithm to multi-fidelity aerodynamic design exploration, the first comparison of these multi-fidelity MOO algorithms and new results of a complex simulation-based multi-objective aerodynamic design of subsonic wing shapes involving two conflicting criteria, several nonlinear constraints and over ten design variables.

Advanced design strategies supported by iterative engineering performance calculations expand the number of alternatives designers can analyze by orders of magnitude. Yet, in the face of vast, under‐constrained design challenges with wide ranging and sometimes ill‐defined implications related to sustainability, it is not possible to replace building design with automated search. The purpose of this paper is to assist designers in their selection of strategies that have been shown to be effective in promoting sustainability.

This paper applies and extends the design exploration assessment methodology (DEAM) to compare the value of distinct design strategies. The authors use DEAM to demonstrate that designers face non‐trivially distinct challenges, even in the well‐defined arena of design for energy efficiency. They next evaluate and compare the effectiveness of strategies such as point‐analysis, screening, trend analysis, and optimization. They identify associated process costs, and extend DEAM to assess the relative value of information that each strategy provides for a given challenge.

Findings empirically rank six strategies for two challenges and demonstrate the relatively high value of trend analysis for energy‐efficient design.

The implication of the findings is that advanced computer analysis strategies should be pursued to support high performance, energy‐efficient design. Such conclusions motivate future research to assess the value of various strategies in the context of the broad and qualitative fields of sustainable design and development.

Urban typogenetics investigates the use of machine intelligence for the evaluation of performance measures as a decision support system (DSS) with a focus on urban aesthetics evaluation. This framework allows designers to address performance measures, urban measures and aesthetic criteria in an adaptive, interactive generative design approach. The purpose of this paper is to provide an understanding of the structure and the nature of the framework and the application of human-in-the-loop design systems to urban design.

Significant literature reviewed lead to the identification of an application potential in the decision-making process. This potential is situated around the use of AI for the evaluation of subjective performance criteria in a DSS. Recognising that the key decisions about urban aesthetics are based on the individual evaluation of the designer, an HITL approach for computational design software to support creative decisions is presented in this paper.

Urban typogenetics for interactive generative urban design allows the exploration of complex design spaces by using a human-in-the-loop design system in the context of urban aesthetics. Hybrid aesthetic evaluation allows the designer to analyse morphological features and urban aesthetics during exploratory search and reveal hidden aspects of the urban context by visualisation of the results of the aesthetic evaluation. Integrating performance measures and urban aesthetics in urban typogenetics addresses major criteria of urban design at the beginning of the creative process.

The use of a broad interactive approach to typogenetic design in an application to urban scenarios is a novel conceptual approach to the design of urban configurations. The suggested adaptive mechanism would allow the user of a typogenetic tool to subjectively evaluate solutions by sight and reason about aesthetic, social and cultural implication of the reviewed design solutions.

This paper aims to study the sampling methods (or design of experiments) which have a large influence on the performance of the surrogate model. To improve the adaptability of modelling, a new sequential sampling method termed as sequential Chebyshev sampling method (SCSM) is proposed in this study.

The high-order polynomials are used to construct the global surrogated model, which retains the advantages of the traditional low-order polynomial models while overcoming their disadvantage in accuracy. First, the zeros of Chebyshev polynomials with the highest allowable order will be used as sampling candidates to improve the stability and accuracy of the high-order polynomial model. In the second step, some initial sampling points will be selected from the candidates by using a coordinate alternation algorithm, which keeps the initial sampling set uniformly distributed. Third, a fast sequential sampling scheme based on the space-filling principle is developed to collect more samples from the candidates, and the order of polynomial model is also updated in this procedure. The final surrogate model will be determined as the polynomial that has the largest adjusted R-square after the sequential sampling is terminated.

The SCSM has better performance in efficiency, accuracy and stability compared with several popular sequential sampling methods, e.g. LOLA-Voronoi algorithm and global Monte Carlo method from the SED toolbox, and the Halton sequence.

The SCSM has good performance in building the high-order surrogate model, including the high stability and accuracy, which may save a large amount of cost in solving complicated engineering design or optimisation problems.

Learning systematic conceptual design approaches could be difficult for students who are asked to adapt their intuitive design rationale to more abstract and divergent thinking styles. The purpose of this study is to propose a conceptual design approach with a well-defined reference framework and procedure to help students to gradually move toward concreteness and to explore the design space.

The so-called problem–solution network approach has been taken as a reference and upgraded with a specific framework to manage abstraction levels. A first didactical application of the proposal is described, and specific feedbacks from students have been collected by means of an anonymous survey.

Despite the limited course time allotted for the argument, students’ feedbacks revealed that the proposed abstraction framework is useful to learn systematic conceptual design and to support the understanding of creative design thinking.

The proposal has been applied on a single class of MS engineering students in a course where only a part of the available time was allotted to conceptual design activities. However, the received positive feedbacks are encouraging and allow pushing toward more comprehensive applications and investigations.

The proposal shown in this paper uses acknowledged concepts of abstraction and function to propose a new integrated framework to manage abstraction levels in problem solving activities. The framework has been implemented in a very recent conceptual design approach based on problem–solution co-evolution, which has been proposed to overcome the flaws ascribed to classical function-based methods.

Human space exploration to date has been limited to low Earth orbit and the moon. The International Space Station (ISS) provides a unique opportunity for researchers to prove out the technologies that will enable humans to safely live and work in space for longer periods and venture farther into the solar system. The ability to manufacture parts in-space rather than launch them from earth represents a fundamental shift in the current risk and logistics paradigm for human space exploration. The purpose of this mission is to prove out the fused deposition modeling (FDM) process in the microgravity environment, evaluate microgravity effects on the materials manufactured, and provide the first demonstration of on-demand manufacturing for space exploration.

In 2014, NASA, in cooperation with Made in Space, Inc., launched a 3D printer to the ISS with the goal of evaluating the effect of microgravity on the fused deposition modeling (FDM) process and prove out the technology for use on long duration, long endurance missions where it could leveraged to reduce logistics requirements and enhance crew safety by enabling a rapid response capability. This paper presents the results of testing of the first phase of prints from the technology demonstration mission, where 21 parts where printed on orbit and compared against analogous specimens produced using the printer prior to its launch to ISS.

Mechanical properties, dimensional variations, structural differences and chemical composition for ground and flight specimens are reported. Hypotheses to explain differences observed in ground and flight prints are also developed. Phase II print operations, which took place in June and July of 2016, and ground-based studies using a printer identical to the hardware on ISS, will serve to answer remaining questions about the phase I data set. Based on Phase I analyses, operating the FDM process in microgravity has no substantive effect on the material produced.

Demonstrates that there is no discernable, engineering significant effect on operation of FDM in microgravity. Implication is that material characterization activities for this application can be ground-based.

Summary of results of testing of parts from the first operation of 3D printing in a microgravity environment.

The objective is to explore various adder architectures using different logic‐design styles and transistor‐sizes for different operand sizes. The scope of this work is the development of tools, which can be used to predict an optimum adder design for a given application based on the speed and energy‐consumption constraints.

The work has been carried out in two parts. In the first part, simulation results were generated using five different architectures; each designed using four logic design styles for three different transistor sizes. The designs were simulated to generate the values of worst‐case propagation delay and energy consumption per addition. This information is used for validating the delay and energy consumption per addition in the second part.

Optimum adder design under varying condition can be found out using this work.

The predictive model does not consider the variation in load capacitance of each cell.

At present, a prime requirement in application specific integrated circuit design is reduction in design cycle time. As a result, there is minimum scope for exploration of arithmetic units in order to choose the best‐suited design. This work will help the designers to choose an optimum adder design for a given set of requirements.

In this work, four degrees of freedom are taken in adder design space, which are not taken before. Here, the adder design space has been explored, studied, and analyzed in this study under so many varying conditions.

The n‐dimensional direct search algorithm, DIRECT, developed by Jones, Perttunen, and Stuckman has attracted recent attention from the multidisciplinary design optimization community. Since DIRECT only requires function values (or ranking) and balances global exploration with local refinement better than n‐dimensional bisection, it is well suited to the noisy function values typical of realistic simulations. While not efficient for high accuracy optimization, DIRECT is appropriate for the sort of global design space exploration done in large scale engineering design. Direct and pattern search schemes have the potential to exploit massive parallelism, but efficient use of massively parallel machines is non‐trivial to achieve. A fully‐distributed control version of DIRECT that is designed for massively parallel (distributed memory) architectures is presented. Parallel results are presented for a multidisciplinary design optimization problem – configuration design of a high speed civil transport.

The purpose of this study is to identify an innovative solution for the power transmission gearbox of concrete mixers, according to the specifications provided by the company.

A tailored systematic design approach (inspired to the German systematic framework) has been adopted to comprehensively gather the company specifications and perform in-depth design space explorations. Subsequently, an iterative embodiment design approach has been followed to identify the size of the components for the preferred concept, by using acknowledged mechanical design procedures and finite element analysis tools.

An innovative cycloidal gearbox has been developed, by merging the kinematics underpinning the classical cycloidal drives and the Wolfrom planetary gearbox. The resulting concept provides high reduction rates with a very high overload capacity.

The main limitation of the studies is the absence of in-depth evaluations usually performed in the detail design phase. However, this limitation is a direct consequence of the company specifications, which only asked to find a preferred concept and to perform preliminary evaluations. Accordingly, the subsequent design optimization are intended to be performed by the company’s staff.

The present paper shows an original design approach, opportunely tailored to the design of innovative gearboxes. It can be conveniently adapted and reused by designers involved in similar tasks. Moreover, the designed cycloidal gearbox paves the way for important innovations in the field of concrete mixers, allowing to design more robust and compact devices.