A two-step methodology for product platform design and assessment in high-variety manufacturing

The delayed product differentiation (DPD) recently rose as a hybrid production strategy able to overcome the main limits of make to stock (MTS) and make to order (MTO), guaranteeing the management of high variety and keeping low storage cost and quick response time by using the so-called product platforms. These platforms are a set of sub-systems forming a common structure from which a set of derivative variants can be efficiently produced. Platforms are manufactured and stocked following an MTS strategy. Then, they are customized into different variants, following an MTO strategy. Current literature proposes methods for platform design mainly using optimization techniques, which usually have a high computational complexity for efficiently managing real-size industrial instances in the modern mass customization era. Hence, efficient algorithms need to be developed to manage the product platforms design for such instances. To fill this gap, this paper proposes a two-step methodology for product platforms design and assessment in high-variety manufacturing. The design step involves the use of a novel modified algorithm for solving the longest common subsequence (LCS) problem and of the k-medoids clustering for the identification of the platform structure and the assignment of the variants to the platforms. The platforms are then assessed against a set of industrial and market metrics, i.e. the MTS cost, the variety, the customer responsiveness, and the variants production cost. The evaluation of the platform set against such a combined set of drivers enhancing both company and market perspectives is missing in the literature. A real case study dealing with the manufacturing of a family of valves exemplifies the efficiency of the methodology in supporting companies in managing high-variety to best balance the proposed metrics

Feature-based multi-class classification and novelty detection for fault diagnosis of industrial machinery

Given the strategic role that maintenance assumes in achieving profitability and competitiveness, many industries are dedicating many efforts and resources to improve their maintenance approaches. The concept of the Smart Factory and the possibility of highly connected plants enable the collection of massive data that allow equipment to be monitored continuously and real-time feedback on their health status. The main issue met by industries is the lack of data corresponding to faulty conditions, due to environmental and safety issues that failed machinery might cause, besides the production loss and product quality issues. In this paper, a complete and easy-to-implement procedure for streaming fault diagnosis and novelty detection, using different Machine Learning techniques, is applied to an industrial machinery sub-system. The paper aims to offer useful guidelines to practitioners to choose the best solution for their systems, including a model hyperparameter optimization technique that supports the choice of the best model. Results indicate that the methodology is easy, fast, and accurate. Few training data guarantee a high accuracy and a high generalization ability of the classification models, while the integration of a classifier and an anomaly detector reduces the number of false alarms and the computational time

Planejamento de uso das áreas em integração lavoura-pecuária-floresta no bioma pampa.

bitstream/item/79444/1/Circular-137.pd

The Arabidopsis thaliana mobilome and its impact at the species level

Transposable elements (TEs) are powerful motors of genome evolution yet a comprehensive assessment of recent transposition activity at the species level is lacking for most organisms. Here, using genome sequencing data for 211 Arabidopsis thaliana accessions taken from across the globe, we identify thousands of recent transposition events involving half of the 326 TE families annotated in this plant species. We further show that the composition and activity of the 'mobilome' vary extensively between accessions in relation to climate and genetic factors. Moreover, TEs insert equally throughout the genome and are rapidly purged by natural selection from gene-rich regions because they frequently affect genes, in multiple ways. Remarkably, loci controlling adaptive responses to the environment are the most frequent transposition targets observed. These findings demonstrate the pervasive, species-wide impact that a rich mobilome can have and the importance of transposition as a recurrent generator of large-effect alleles

Forrageiras de inverno: produtividade sob adubação orgânica.

bitstream/item/79264/1/Flyer-Forrageiras-de-inverno-co-autora.pdfVitrines Tecnológicas

Humin Formation on SBA-15-pr-SO3H Catalysts during the Alcoholysis of Furfuryl Alcohol to Ethyl Levulinate: Effect of Pore Size on Catalyst Stability, Transport, and Adsorption

Herein, the alcoholysis of furfuryl alcohol in a series of SBA-15-pr-SO3H catalysts with different pore sizes is reported. Elemental analysis and NMR relaxation/diffusion methods show that changes in pore size have a significant effect on catalyst activity and durability. In particular, the decrease in catalyst activity after catalyst reuse is mainly due to carbonaceous deposition, whereas leaching of sulfonic acid groups is not significant. This effect is more pronounced in the largest-pore-size catalyst C3, which rapidly deactivates after one reaction cycle, whereas catalysts with a relatively medium and small average pore size (named, respectively, C2 and C1) deactivate after two reaction cycles and to a lesser extent. CHNS elemental analysis showed that C1 and C3 experience a similar amount of carbonaceous deposition, suggesting that the increased reusability of the small-pore-size catalyst can be attributed to the presence of SO3H groups mostly present on the external surface, as corroborated by results on pore clogging obtained by NMR relaxation measurements. The increased reusability of the C2 catalyst is attributed to a lower amount of humin being formed and, at the same time, reduced pore clogging, which helps to maintain accessible the internal pore space