Set-based design of mechanical systems with design robustness integrated

This paper presents a method for parameter design of mechanical products based on a set-based approach. Set-based concurrent engineering emphasises on designing in a multi-stakeholder environment with concurrent involvement of the stakeholders in the design process. It also encourages flexibility in design through communication in terms of ranges instead of fixed point values and subsequent alternative solutions resulting from intersection of these ranges. These alternative solutions can then be refined and selected according to the designers’ preferences and clients’ needs. This paper presents a model and tools for integrated flexible design that take into account the manufacturing variations as well as the design objectives for finding inherently robust solutions using QCSP transformation through interval analysis. In order to demonstrate the approach, an example of design of rigid flange coupling with a variable number of bolts and a choice of bolts from ISO M standard has been resolved and demonstrated

Capturing the Industrial Requirements of Set-Based Design for the CONGA Framework

The Configuration Optimisation of Next-Generation Aircraft (CONGA) is a proposed framework in a response to industrial need to enhance the aerospace capability in the UK. In order to successfully address this challenge, a need to develop a true multi-disciplinary Set-Based Design (SBD) capability that could deploy new technologies on novel configurations more quickly and with greater confidence was identified. This paper presents the first step towards the development of the SBD capabilities which is to elicit the industrial requirement of the SBD process for the key aerospace industrial partners involved in this CONGA approach

Set-based approach to passenger aircraft family design

Presented is a method for the design of passenger aircraft families. Existing point-based methods found in the literature employ sequential approaches in which a single design solution is selected early and is then iteratively modified until all requirements are satisfied. The challenge with such approaches is that the design is driven toward a solution that, although promising to the optimizer, may be infeasible due to factors not considered by the models. The proposed method generates multiple solutions at the outset. Then, the infeasible solutions are discarded gradually through constraint satisfaction and set intersection. The method has been evaluated through a notional example of a three-member aircraft family design. The conclusion is that point-based design is still seen as preferable for incremental (conventional) designs based on a wealth of validated empirical methods, whereas the proposed approach, although resource-intensive, is seen as more suited to innovative designs

Adapting to Changes in Design Requirements Using Set‐Based Design

Ship design is a highly intensive and complex process mainly due to the large number of components and competing requirements. With advancement in technology, design, and evaluation processes, more emphasis has been placed on obtaining not just a feasible design, but also an optimal one. Advanced design methods such as set‐based design (SBD) can provide a structured approach to evaluating the design space in order to make accurate and informed decisions toward a more globally optimal design. This paper presents the general application of the SBD process for US Naval vessels as well as a specialized focus on changes in design requirements. Specifically, the two main objectives are an evaluation of how delaying decisions using SBD could cause higher adaptability to changes later in the design process and development of a tradeoff space for evaluating reduced sets. A design experiment that simulated cycles of the SBD process was developed and implemented to provide insight into this objective. The different stages of the experiment included determining intersections between design components in the design space, narrowing variable sets to eliminate infeasible regions, and evaluating the effects of changing design requirements.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90342/1/j.1559-3584.2011.00331.x.pd

A hybrid multiagent approach for global trajectory optimization

In this paper we consider a global optimization method for space trajectory design problems. The method, which actually aims at finding not only the global minimizer but a whole set of low-lying local minimizers(corresponding to a set of different design options), is based on a domain decomposition technique where each subdomain is evaluated through a procedure based on the evolution of a population of agents. The method is applied to two space trajectory design problems and compared with existing deterministic and stochastic global optimization methods

Robust fuzzy PSS design using ABC

This paper presents an Artificial Bee Colony (ABC) algorithm to tune optimal rule-base of a Fuzzy Power System Stabilizer (FPSS) which leads to damp low frequency oscillation following disturbances in power systems. Thus, extraction of an appropriate set of rules or selection of an optimal set of rules from the set of possible rules is an important and essential step toward the design of any successful fuzzy logic controller. Consequently, in this paper, an ABC based rule generation method is proposed for automated fuzzy PSS design to improve power system stability and reduce the design effort. The effectiveness of the proposed method is demonstrated on a 3-machine 9-bus standard power system in comparison with the Genetic Algorithm based tuned FPSS under different loading condition through ITAE performance indices

Work Roll Cooling System Design Optimisation in Presence of Uncertainty

Organised by: Cranfield UniversityThe paper presents a framework to optimise the design of work roll based on the cooling performance. The framework develops Meta models from a set of Finite Element Analysis (FEA) of the roll cooling. A design of experiment technique is used to identify the FEA runs. The research also identifies sources of uncertainties in the design process. A robust evolutionary multi-objective algorithm is applied to the design optimisation I order to identify a set of good solutions in the presence of uncertainties both in the decision and objective spaces.Mori Seiki – The Machine Tool Compan