Multi-objective grouping genetic algorithm for product life-cycle optimisation

A product’s lifecycle performance (e.g. assembly, outsourcing, maintenance and recycling) can often be improved through modularity. However, modularisation under different and often conflicting lifecycle objectives is a complex problem that will ultimately require trade-offs. This paper presents a novel multi-objective modularity optimisation framework; the application of which is illustrated through the modularisation of a car climate control system. Central to the framework is a specially designed multi-objective grouping genetic algorithm (MOGGA) that is able to generate a whole range of alternative product modularisations. Scenario analysis, using the principles of the analytical hierarchical process (AHP), is then carried out to explore the solution set and choose a suitable modular architecture that optimises the product lifecycle according to the company’s strategic vision

Representing human movement and behaviour in virtual environment using gaming software

Gaming software, DarkBASIC Professional (DBPro) is widely used for the games application. In this research, the software is applied as a tool to simulate human movement and behaviour in crowded areas within virtual environment. Emphasize is to accommodate the largest possible range of humans with diverse abilities as part of AUNT-SUE (Accessibility and Users Needs in Transport – Sustainable Urban Environment) project. In this paper, the method applied to represent humans in virtual environment using DBPro will be discussed

Ergonomics analysis in a virtual environment

Simulation can support the design of an ergonomic workplace by enabling early assessment of ergonomic conditions in a virtual environment. An important feature is the possibility to study alternative solutions or the effect of improvements from an ergonomics perspective. To be able to conduct an efficient and reliable evaluation in a virtual environment, an objective analysis method is essential. Such an analysis method should be integrated in the simulation software, and support a company's everyday ergonomics work process. In order to gain from existing ergonomics knowledge within a company, the possibility to implement such wisdom in the current simulation software becomes important. This paper presents an implementation work done with the purpose of integrating an established ergonomics work process into a virtual environment. It describes the benefits of an ergonomics work process where simulation and evaluation at early stages of a design process are key factors. The paper will also describe the integration process, i.e., the technical issues as well as the change in work methods

Preface. (Special issue: Application of digital human modelling tools in user-centred design processes.)

The idea for this special issue originated from a user-centred design session of the 2nd International Conference on Digital Human Modelling held at HCI International 2009 in San Diego. Two papers from this session have been enhanced and extended and are presented here together with three papers from other selected authors

Flowchart of the proposed model.

<p>Flowchart of the proposed model.</p

Decision support matrix/trade-off matrix using fuzzy linguistic term in Table 4.

<p>Decision support matrix/trade-off matrix using fuzzy linguistic term in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133599#pone.0133599.t004" target="_blank">Table 4</a>.</p

Defuzzification of decision support matrix/trade-off matrix.

<p>Defuzzification of decision support matrix/trade-off matrix.</p

Weights of attributes.

<p>Weights of attributes.</p

The characteristics of the three decision-making experts.

<p>The characteristics of the three decision-making experts.</p

The result of fuzzy linguistic reference relation matrix with the transforming function [51].

<p>Where, <math><mrow><msub><mi>A</mi><mo>¯</mo><mi>i</mi></msub></mrow></math> is the average of the values of the pair-wise comparison elements for each i-th row or each i-th attribute and <math><mrow><msub><mi>w</mi><mo>˜</mo><mrow><msub><mi>a</mi><mi>i</mi></msub></mrow></msub></mrow></math> is the weight of the i-th attribute.</p><p>The result of fuzzy linguistic reference relation matrix with the transforming function [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0133599#pone.0133599.ref051" target="_blank">51</a>].</p