Attribute and technology value mapping for conceptual product design phase

Analytical Hierarchy Process(AHP) is a well proven evaluation-decision making tool which has been used extensively in almost every field of research that involves decision making. This study investigates AHP's applicability to industrial design at the conceptual design phase. The industrial design process is made up of several important phases, one of which is the conceptual design. This is the step in which several concept ideas for a certain product are created as alternatives among which the most suitable one is selected for further development. It is very important to perform this selection correctly as it has a direct effect on the success of the later design phases, final design and eventually the marketed product. A wrong selection may create design issues, causing redesign work, remanufacture or even recalling of the final product back from market, meaning a total failure. Evaluation and selection of the available conceptual designs are usually done without strictly defined selection criteria and in a subjective environment which is open to negative interference from the outside. There are also several inside factors like decision maker's prejudices and biases that might effect the selection negatively. For the design concept to be determined in the best possible way, a tool which is immune to all kinds of external and internal influences is necessary. This tool should be methodic, easy to use and as suitable as possible for use in a computer environment. A short scan among tools of this nature shows that AHP is one of them that can fulfill the needs of the industrial design process. In this article, the history of AHP is introduced briefly first, then the inner workings of it is explained in detail and an application is presented to demonstrate its use at the conceptual design phase of a sample product design process.

Architectural design decisions are primarily made through an interaction between an architect and a client during the conceptual design phase. However, in larger-scale public architecture projects, the client is frequently represented by a community that embraces numerous stakeholders. The scale, social diversity, and political layers of such collective clients make their interaction with architects challenging. A solution to address this challenge is using new information technologies that automate design interactions on an urban scale through crowdsourcing and artificial intelligence technologies. However, since such technologies have not yet been applied and tested in field conditions, it remains unknown how communities interact with such systems and whether useful concept designs can be produced in this way. To fill this gap in the literature, this paper reports the results of a case study architecture project where a novel crowdsourcing system was used to automate interactions with a community. The results of both quantitative and qualitative analyses revealed the effectiveness of our approach, which resulted in high-level stakeholder satisfaction and yielded conceptual designs that better reflect stakeholders’ preferences. Along with identifying opportunities for using advanced technologies to automate design interactions in the concept design phase, we also highlight the challenges of such technologies, thus warranting future research.

Interdisciplinary Design: Influence of Team Structure on Project Success

A bilevel-optimization approach to determine product specifications during the early phases of product development: Increase customer value and reduce design risks

This paper focuses on the application of complexity theory and entropy concepts in the design process. Broadly speaking, the design process involves three phases: problem definition, conceptual design and embodiment. In the conceptual design phase, concepts that satisfy the functional requirements of the desired product are identified and compared. It is said that approximately 75% of the total product life-cycle cost is committed in this phase. The conceptual design phase has two essential sub-phases, namely, obtaining a solution set and selecting the most suitable solutions. Our work focuses on the selection sub-phase. The aim within this sub-phase is to minimize the number of selected concept variants and to reduce their chances of rejection in later stages. However, the solution to this problem is quite elusive, mostly because information about concept variants is scarce and rather qualitative at this stage. A common method is to perform a cost-benefit analysis. However, the analysis relies heavily on expert intuition and is thus subjected to high uncertainties. Recently, axiomatic design is gaining popularity. This is a framework that incorporates two axioms, namely, the Independence Axiom and the Minimum Information Axiom, accompanied by several corollaries. However, criticism on the integrity of the Independence Axiom has appeared recently in the literature. Further, the formulation of axiomatic design appears to have logical flaws. Finally, the conceptual design phase, a distinct phase in the design process, cannot be distinguished clearly in axiomatic design. In this paper we try to improve the selection phase of the conceptual design by improving the existing cost-benefit approach. In this vein, performance features against which concepts would be evaluated are established. We propose the use of Kolmogorov complexity theory and entropy concepts from information theory and physics to evaluate the complexity of the performance features. The design concepts are then improved based on the rule to reduce complexity of each performance feature. Weights are finally assigned to each performance feature and an overall complexity index is obtained which is suitable to compare designs. The ideas are further elaborated on by examples.

A multi-objective feedback approach for evaluating sequential conceptual building design decisions

1.2 What are the main phases of product design and development Before discuss the collaboration issues for product design and development, we need to briefly review the phases of product design and development. The major phases of product design and development are normally defined as conceptual design, preliminary design, and detail design and development (Blanchard, 2004). During the conceptual design phase, the concepts, which are also called scheme, are built in order to completely and efficiently design the transceiver. The concepts may include such as product operational requirements and maintenance, current product problem (or deficiency), functional analysis for the product, applicable technical performance measures (TPMs), and specific performance measures and design-to criteria. Preliminary design phase begins with a “functional baseline” product configuration described in the product specification prepared during conceptual design phase. The functional baseline is translated into detailed qualitative and quantitative design requirements for allocating applicable elements of the product. An “allocated baseline” configuration in the form of development, product, and process specifications is established during this phase. At the beginning of detail design and

The significance of materialized prototypes from CAD generated mechanical parts has been recognized since more than a decade. Despite the ever increasing quality and speed of graphical visualization methods, solid 3D hard copies from designs remain essential for certain stages in the creation process. Especially during the phase of conceptual geometric design, when alternative shape proposals must be quickly judged, automatic, fast and inexpensive production of replica is of importance. However, for such a kind of prototyping in conjunction with CAD, traditional methods based on CAM and NC technology turn out not adequate. To support conceptual design, several extensions and optimizations, mainly in the software area, need to be effected. In this paper an autonomous NC-milling process generator TLCOR is presented. It evaluates and analyzes surface/solid models based on NURBS, determines the physical constraints of the 3D milling devices (represented in a technical database) and finally produces an ISO-standard control statement sequence. The system selects the appropriate machining method (parametric and/or geometric algorithms) and tools, and breaks up the process into different stages of non-planar path planning with interference avoidance. The user will never be confronted with any aspect concerning the NC. The designer only needs to express his or her wish to obtain a milled copy of the actual CAD model. Extension of TLCOR to shape models defined neutrally (STEP/PDES based) and to multi-axis and robot milling is in progress.

A fuzzy weighted wedge mechanism for feasibility assessment of system reliability during conceptual design

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues. The methodology is two-fold: first, capture the heuristics developed by human analysts over their many years of experience; and secondly, leverage the power of modern computing to evaluate multiple trajectories simultaneously and therefore enable the exploration of the trajectory's design space early during the pre- conceptual and conceptual phases of design. This methodology is coupled with design of experiments in order to train surrogate models, which enables trajectory design space visualization and parametric optimal ascent trajectory information to be available when early design decisions are being made.

The optimization of the assembly phase, in complex products, is a challenging phase and it need to be handled in the early phase of product development (i.e., conceptual design). Several methods have been developed to assess the assemblability of product at the conceptual design phase, however, the most critical aspect concerns the possibility to derive design guidelines starting from the results of assemblability analysis. In this context, the present work aims at defining a methodology able to retrieve design for assembly and installation guidelines starting from the analysis of a given product architecture at the conceptual design phase (loop-back of the design for assembly method). The developed method makes use of matrices and vectors to provide a list of design actions that affect the product assemblability including a ranking of their impacts on the final design. The methodology was used to retrieve and select design guidelines in the context of aircraft manufacturing. The case study (cabin equipping of commercial aircraft) provides interesting results in the identification and implementation of design guidelines to improve the aircraft architecture at the conceptual level.

Advanced phase powertrain design attribute and technology value mapping

Status of the EU test blanket systems safety studies

Empirical sizing guidelines such as tail volume coefficients have long been used in the early aircraft design phases for sizing stabilizers, resulting in conservatively stable aircraft. While successful, this results in increased empty weight, reduced performance, and greater procurement and operational cost relative to an aircraft with optimally sized surfaces. Including flight dynamics in the conceptual design process allows the design to move away from empirical methods while implementing modern control techniques. A challenge of flight dynamics and control is the numerous design variables, which are changing fluidly throughout the conceptual design process, required to evaluate the system response to some disturbance. This research focuses on addressing that challenge not by implementing higher order tools, such as computational fluid dynamics, but instead by linking the lower order tools typically used within the conceptual design process so each discipline feeds into the other. In thisresearch, flight dynamics and control was incorporated into the conceptual design process along with the traditional disciplines of vehicle sizing, weight estimation, aerodynamics, and performance. For the controller, a linear quadratic regulator structure with constant gains has been specified to reduce the user input. Coupling all the disciplines in the conceptual design phase allows the aircraft designer to explore larger design spaces where stabilizers are sized according to dynamic response constraints rather than historical static margin and volume coefficient guidelines.

The Maunakea Spectroscopic Explorer (MSE) project has completed its Conceptual Design Phase. This paper is a status report of the MSE project regarding its technical and programmatic progress. The technical status includes its conceptual design and system performance, and highlights findings and recommendations from the System and various subsystems design reviews. The programmatic status includes the project organization and management plan for the Preliminary Design Phase. In addition, this paper provides the latest information related to the permitting process for Maunakea construction.