Development of an intelligent and automated system for lean industrial production, adding maximum productivity and efficiency in the production process

This article is related to the concept of Industry 4.0, both for the automation of manufacturing processes and for the automation of production management processes, in order to allow an improvement of performance and productivity. For its production management, based on "leagile" principles. At the industrial center of Manaus (PIM), there are around 900 companies, many multinational companies, these companies have the same intention: to produce more, by spending less. In general, globalized companies want to invest in innovation, which are technologies, inventions, products, and ideas. In most of the large companies, there are areas dedicated to innovation like research and development laboratories that rely on several researchers. This work is business-centric and it interacts with research institutes such as the Manus Institute of Technology (MIT). In developed countries, the agreement between companies and universities is the center of innovation. It is by means of which technologies, inventions, products, and finally, ideas, arrive at the market. The objective of this work is to identify and make improvements/automation in the factory floor of companies, based on Lean Production, aiming the maximum production and efficiency in the process to increase the quality of the final product. For this matter, a production line with the philosophy of lean versus agile production will be developed in this project. This production line will feature an electronic system controlled by ARM high-performance A9 cortex processors that will be responsible for the control of all production line.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013. Moreover, the authors would like to thank President Railma Lima and Prof. Marivan and Dr. Marlene Araujo of the Company Manaus Institute of Technology for their support provided for the accomplishment of this work, and also to the Company where this study has been carried out: "Flex Industries SA Company"

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data