Flexibility and modeling in business processes: a multi-dimensional relationship

Over the last few years, Business Process Management (BPM) has achieved increasing popularity and dissemination. An analysis of the underlying assumptions of BPM shows that it pursues two apparently contradicting goals: on the one hand it aims at formalising work practices into business process models; on the other hand, it intends to confer flexibility to the organization - i.e. to maintain its ability to respond to new and unforeseen situations. This paper analyses the relationship between formalisation and flexibility in business process modelling by means of an empirical case study of a BPM project in an aircraft maintenance company. A qualitative approach is adopted based on the Actor-Network Theory. The paper offers two major contributions: (a) it illustrates the sociotechnical complexity involved in BPM initiatives; (b) it points towards a multidimensional understanding of the relation between formalization and flexibility in BPM projects.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Multi-Walled Carbon Nanotubes and Poly(lactic acid) Nanocomposite Fibrous Membranes Prepared by Solution Blow Spinning

Nanocomposite fibers based on multi-walled carbon nanotubes (MWCNT) and poly(lactic acid) (PLA) were prepared by solution blow spinning (SBS). Fiber morphology was characterized by scanning electron microscopy (SEM) and optical microscopy (OM). Electrical, thermal, surface and crystalline properties of the spun fibers were evaluated, respectively, by conductivity measurements (4-point probe), thermogravimetric analyses (TGA), differential scanning calorimetry (DSC), contact angle and X-ray diffraction (XRD). OM analysis of the spun mats showed a poor dispersion of MWCNT in the matrix, however dispersion in solution was increased during spinning where droplets of PLA in solution loaded with MWCNT were pulled by the pressure drop at the nozzle, producing PLA fibers filled with MWCNT. Good electrical conductivity and hydrophobicity can be achieved at low carbon nanotube contents. When only 1 wt% MWCNT was added to low-crystalline PLA, surface conductivity of the composites increased from 5 x 10(-8) to 0.46 S/cm. Addition of MWCNT can slightly influence the degree of crystallinity of PLA fibers as studied by XRD and DSC. Thermogravimetric analyses showed that MWCNT loading can decrease the onset degradation temperature of the composites which was attributed to the catalytic effect of metallic residues in MWCNT. Moreover, it was demonstrated that hydrophilicity slightly increased with an increase in MWCNT content. These results show that solution blow spinning can also be used to produce nanocomposite fibers with many potential applications such as in sensors and biosensors.