Improving the design process for factories:modelling human performance variation

Theprocess of manufacturing system design frequently includes modeling, and usually, this means applying a technique such as discrete event simulation (DES). However, the computer tools currently available to apply this technique enable only a superficial representation of the people that operate within the systems. This is a serious limitation because the performance of people remains central to the competitiveness of many manufacturing enterprises. Therefore, this paper explores the use of probability density functions to represent the variation of worker activity times within DES models.

Sustainable agricultural production:an investigation in Brazilian semi-arid livestock farms

This paper investigates the environmental sustainability and competitiveness perceptions of small farmers in a region in northern Brazil. The main data collection instruments included a survey questionnaire and an analysis of the region's strategic plan. In total, ninety-nine goat and sheep breeding farmers were surveyed. Data analysis methods included descriptive statistics, cluster analysis, and chi-squared tests. The main results relate to the impact of education, land size, and location on the farmers' perceptions of competitiveness and environmental issues. Farmers with longer periods of education have higher perception scores about business competitiveness and environmental sustainability than those with less formal education. Farmers who are working larger land areas also have higher scores than those with smaller farms. Lastly, location can yield factors that impact on farmers' perceptions. In our study, farmers located in Angicos and Lajes had higher perception scores than Pedro Avelino and Afonso Bezerra, despite the geographical proximity of these municipalities. On the other hand, three other profile variables did not impact on farmers' perceptions, namely: family income, dairy production volume, and associative condition. The authors believe the results and insights can be extended to livestock farming in other developing countries and contribute generally to fostering effective sustainable development policies, mainly in the agribusiness sector. © 2013 Elsevier Ltd. All rights reserved.

Review of industrial temperature measurement technologies and research priorities for the thermal characterisation of the factories of the future

As the largest source of dimensional measurement uncertainty, addressing the challenges of thermal variation is vital to ensure product and equipment integrity in the factories of the future. While it is possible to closely control room temperature, this is often not practical or economical to realise in all cases where inspection is required. This article reviews recent progress and trends in seven key commercially available industrial temperature measurement sensor technologies primarily in the range of 0 °C–50 °C for invasive, semi-invasive and non-invasive measurement. These sensors will ultimately be used to measure and model thermal variation in the assembly, test and integration environment. The intended applications for these technologies are presented alongside some consideration of measurement uncertainty requirements with regard to the thermal expansion of common materials. Research priorities are identified and discussed for each of the technologies as well as temperature measurement at large. Future developments are briefly discussed to provide some insight into which direction the development and application of temperature measurement technologies are likely to head.