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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.12.021 Byline: P.Y. Mok (a), C.K. Kwong (a), W.K. Wong (b) Keywords: Genetic algorithms; Fuzzy set theory; Parallel machine scheduling; Fabric cutting Abstract: In apparel industry, manufacturers developed standard allowed minutes (SAMs) databases on various manufacturing operations in order to facilitate better scheduling, while effective production schedules ensure smoothness of downstream operations. As apparel manufacturing environment is fuzzy and dynamic, rigid production schedules based on SAMs become futile in the presence of any uncertainty. In this paper, a fuzzification scheme is proposed to fuzzify the static standard time so as to incorporate some uncertainties, in terms of both job-specific and human related factors, into the fabric-cutting scheduling problem. A genetic optimisation procedure is also proposed to search for fault-tolerant schedules using genetic algorithms, such that makespan and scheduling uncertainties are minimised. Two sets of real production data were collected to validate the proposed method. Experimental results indicate that the genetically optimised fault-tolerant schedules not only improve the operation performance but also minimise the scheduling risks. Author Affiliation: (a) Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong (b) Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong

Abstract: In this paper, by the integration of design methodology theories with evolutionary computation, a new design system is developed to evolve preferred designs on complex marbling patterns using interactive ‘perceptual selection’. The system is formulated in a way to assist the productive–deductive–inductive design reasoning process of the users. Therefore, complex mathematical functions do not cognitively overload the designers, who are released for more critical tasks of aesthetic assessment and new design rules induction. With the implementation on a graphics-processing unit (GPU), real-time complex marbling patterns can be created by the system. The system encourages creativity in the design process and accelerates new design generation. In addition, the resulting patterns fulfil the textile industry requirements of repeat and can be output as vector images. [Copyright &y& Elsevier]

In apparel manufacturing, experience and subjective assessment of production planners are used quite often to plan the production schedules in their fabric-cutting departments. The quantities of cut-pieces produced by fabric-cutting departments based on these non-systematic schedules cannot fulfil the cut-piece requirements of the downstream sewing lines and minimize the makespan. This paper proposes a genetic algorithms (GAs) approach to optimize both the cut-piece requirements and the makespan of the conventional fabric-cutting departments using manual spreading and cutting methods. An optimization model for the manual fabric cutting process based on GAs was developed. Two sets of production data were collected to validate the performance of the model and the experimental results were obtained. From the results, it can be found that both the makespan and cut-piece fulfilment rates are improved in which the latter is improved significantly. [ABSTRACT FROM AUTHOR]

Abstract: This paper reports the development of a unique model to quantify the environmental impact made by various textile fibres and also to position them in terms of ecological sustainability. A wide range of textile fibres and the major contributing factors in terms of environmental impact during manufacturing phase (starting from growth/extraction stage to production of a useful fibre which can be spun) have been selected. Amount of oxygen produced/carbon-di-oxide absorbed consequently contributing to off-set global warming during the production phase of a fibre, utilisation of renewable resources, land use, usage of fertilisers and pesticides, fibre recyclability and biodegradability of chosen fibres have been considered. Amount of energy consumed, quantity of water utilised and amount of green house gases emitted have been considered for life cycle inventory (LCI) and a life cycle impact assessment (LCIA) study has been accomplished to derive certain impact categories pertaining to the damage created to human health, ecosystem quality and resources, which will elucidate the characteristics of ecological sustainability. A scoring system based on the above mentioned factors which predominantly determine ecological sustainability has been framed, from which an Environmental Impact index (EI) has been developed. Further, an Ecological Sustainability Index (ESI) has been derived from EI values for the chosen fibres. According to this system, organic cotton is the most and acrylic is the least preferred fibre. A sensitivity study has been done to check the robustness of the developed model and the results of the same have been reported. [Copyright &y& Elsevier]

Abstract: Carbon footprint has become a term often used by the media in recent days. The human carbon footprint is professed to be a very serious global threat and every nation is looking at the possible options to reduce it since its consequences are alarming. A carbon footprint is a measure of the impact of human activities on earth and in particular on the environment; more specifically it relates to climate change and to the total amount of greenhouse gases produced, measured in units of carbon dioxide emitted. Effort of individuals in minimizing the carbon footprint is vital to save our planet. This article reports a study of the carbon footprint of various types of shopping bags (plastic, paper, non-woven and woven) using life cycle impact assessment (LCIA) technique in two stages. The first stage (baseline study), comprised the study of the impact of different types of shopping bags in the manufacturing phase, without considering their usage and disposal phases (cradle to gate stage). The LCIA was accomplished by the IPCC 2007 method, developed by the Inter Panel on Climate Change in SIMAPRO 7.2. The GWP (Global Warming Potential) values calculated by the IPCC 2007 method for 100 years were considered as a directive to compare the carbon footprint made by the different types of shopping bags under consideration. The next stage was the study of the carbon footprint of these bags including their usage and disposal phases (cradle to grave stage) and the results derived were compared with the results derived from the baseline study, which is the major focus of this research work. The values for usage and end-of-life phases were obtained from the survey questionnaire performed amongst different user groups of shopping bags in China, Hong Kong and India. The results show that the impact of different types of shopping bags in terms of their carbon footprint potential is very high if no usage and disposal options were provided. When the carbon footprint values from different disposal options were compared, the carbon footprint values were lower in the case where a higher percentage of reuse is preferred to recycling and disposing to landfill. The results indicate that a higher percentage of reuse could significantly scale down the carbon footprint. Once the shopping bags reached the point where they can no longer be reused, they must be forwarded to recycling options, rather than being disposed to landfill. At this juncture, consumer’s perceptions and behaviours in connection with the respective government’s policies in promoting & facilitating recycling systems could be critical in reducing the carbon footprint of various shopping bags. [Copyright &y& Elsevier]