Integrating environmental and economic life cycle analysis in product development: a material selection case study

Purpose Achieving sustainability by rethinking products, services and strategies is an enormous challenge currently laid upon the economic sector, in which materials selection plays a critical role. In this context, the present work describes an environmental and economic life cycle analysis of a structural product, comparing two possible material alternatives. The product chosen is a storage tank, presently manufactured in stainless steel (SST) or in a glass fibre reinforced polymer composite (CST). The overall goal of the study is to identify environmental and economic strong and weak points related to the life cycle of the two material alternatives. The consequential win-win or trade-off situations will be identified via a Life Cycle Assessment/Life Cycle Costing (LCA/LCC) integrated model. Methods The LCA/LCC integrated model used consists in applying the LCA methodology to the product system, incorporating, in parallel, its results into the LCC study, namely those of the Life Cycle Inventory (LCI) and the Life Cycle Impact Assessment (LCIA). Results In both the SST and CST systems the most significant life cycle phase is the raw materials production, in which the most significant environmental burdens correspond to the Fossil fuels and Respiratory inorganics categories. The LCA/LCC integrated analysis shows that the CST has globally a preferable environmental and economic profile, as its impacts are lower than those of the SST in all life cycle stages. Both the internal and external costs are lower, the former resulting mainly from the composite material being significantly less expensive than stainless steel. This therefore represents a full win-win situation. As a consequence, the study clearly indicates that using a thermoset composite material to manufacture storage tanks is environmentally and economically desirable. However, it was also evident that the environmental performance of the CST could be improved by altering its End-of-Life stage. Conclusions The results of the present work provide enlightening insights into the synergies between the environmental and the economic performance of a structural product made with alternative materials. Further, they provide conclusive evidence to support the integration of environmental and economic life cycle analysis in the product development processes of a manufacturing company, or in some cases even in its procurement practices.

A practical framework for the generation and selection of strategic plans of action, The relevance of timeframe considerations and a systems thinking approach

The paper proposes a methodology especially focused on the generation of strategic plans of action, emphasizing the relevance of having a structured timeframe classification for the actions. The methodology explicitly recognizes the relevance of long-term goals as strategic drivers, which must insure that the complex system is capable to effectively respond to changes in the environment. In addition, the methodology employs engineering systems techniques in order to understand the inner working of the system and to build up alternative plans of action. Due to these different aspects, the proposed approach features higher flexibility compared to traditional methods. The validity and effectiveness of the methodology has been demonstrated by analyzing an airline company composed by 5 subsystems with the aim of defining a plan of action for the next 5 years, which can either: improve efficiency, redefine mission or increase revenues.

Criteria for ERP selection using an AHP approach

Information systems are a foundation key element of modern organizations. Quite often, chief executive officers and managers have to decide about the acquisition of new software solution based in an appropriated set of criteria. Analytic Hierarchy Process (AHP) is one technique used to support that kind of decisions. This paper proposes the application of AHP method to the selection of ERP (Enterprise Resource Planning) systems, identifying the set of criteria to be used. A set of criteria was retrieved from the scientific literature and validated through a survey-based approach.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Loneliness in Middle and Old Age

Purpose of the research: (a) To identify the degree of much loneliness reported in the Portuguese population over 50 years of age and (b) test whether loneliness can be predicted by socio-demographic, health related or social characteristic of the sample other than age. Materials and methods: 1174 late middle age and older adults were interviewed face to face by different interviewers across the country; after the informed consent was signed, we asked the participants several socio-demographic and health-related questions; finally we asked ‘‘How often do you feel lonely?’’ and participants responded according to a five point Likert scale. Principal results: The results showed that 12% of participants reporting feeling lonely often or always, whereas 40% reporting never feeling lonely. The remaining 48% self-reported they felt lonely seldom or sometimes. Additionally, results show that, when taken together, variables such as marital status, type of housing, residence settings, health conditions, social satisfaction, social isolation, lack of interest, transportation, and age were predictors of loneliness. Major conclusions: (1) The association of loneliness with advanced age has been greatly exaggerated by mass media and common sense; (2) But although our findings did not confirm the most alarmist views, the 12% of older adults reporting that they are feeling lonely always or often should be cause for attention and concern. It is necessary to understand the meaning, reasons and level of suffering implied on those feelings of loneliness. (3) Our findings suggest that it makes no sense to construe age as a singular feature or cause for feelings of loneliness. Instead, age and also a number of other features combine to predict feelings of loneliness. But even with our predictor variables there was a substantial of variance left unexplained. Therefore it is necessary to continue exploring how feelings of loneliness arise from the experience of living and how they can be changed.