Product Specification Analysis for Modular Product Design Using Big Sales Data

Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modular product design,correlations among specifications and components originated from customers’conscious and subconscious preferences can be investigated by using big data on product sales.This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data.The correlations of the product specifications are determined by analyzing the collected product sales data.By building the relations between the product components and specifications,a matrix for measuring the correlation among product components is formed for component clustering.Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster.A case study of electric vehicles illustrates the application of the proposed method.

Monte Carlo Method for the Uncertainty Evaluation of Spatial Straightness Error Based on New Generation Geometrical Product Specification

Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.

Contribution to the Management of Fecal Sludge in the Urban Commune of Mamou(Republic of Guinea)

In the town of Mamou,all homes with sanitation systems are equipped with autonomous installations not connected to a sewer network.The emptying service is provided by manual emptiers and by the living environment and sanitation service of the urban municipality which has a single 6 m^(3)truck.The objective of this work is to determine the quantity of fecal sludge produced within the city for sustainable management.The methodology adopted is based on a field survey and the use of three methods for evaluating the quantities of sludge(specific production,quantity of sludge collected by the sludge truck and the total production of sludge produced in the various sludge works).The results obtained show that,out of the 2,940 sanitation works identified,2,936 works have been emptied at least once since their construction.Then 2,307 structures are emptied manually or 78.57%,against;619 structures emptied mechanically or 21.08%.The structures are emptied on average every 3 years for septic tanks and every 5 years for dry latrines.The specific production of sludge is 685,241,532 m^(3)/year;the production of sludge by the mechanical emptying technique varies from 588,641.57 m^(3)/year to 724,800.46 m^(3)/year and the production of sludge by manual emptying is 1,573,709.33 m^(3)/year,for a total quantity of sludge produced including between 2,162,350 m^(3)/year to 685,241,531.9 m^(3)/year.

Effect of sulfate on the methanogenic activity of a bacterial culture from a brewery wastewater during glucose degradation

The maximum specific methanogenic activity （SMA） of a sludge originating from a brewery wastewater treatment plant on the degradation of glucose was investigated at various levels of sulfate on a specific loading basis. Batch experiments were conducted in serum bottles at pH 7 and 35℃. A comparison of the values indicates that the SMA of this mixed culture was increased and reached its highest level of 0.128 g CH4 gas COD/（g VSS.d） when biomass was in contact with sulfate at a ratio of 1：0.114 by weight.