cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14283084.v1
title: Occupational risks of commercial restaurant workers in the metropolitan region of Recife-PE

description: Abstract: With the modern and fast pace of life, the number of people who eat out has increased; consequently there has been an increase in the demand for work in establishments in the collective meals sector, making work environments susceptible to the emergence of occupational risks which may compromise the physical, mental and social health of workers. In order to mitigate these risks, one must have the knowledge of how they can interfere in the quality of life and work of the employees. Considering these aspects, occupational risks were evaluated in two restaurants in the metropolitan area of Recife-PE. For the evaluation of these were studied the levels of noise, heat and illumination. The chemical risks and physical-ergonomic relationship were also evaluated. It was observed in all the analyzes made, some type of discomfort to the collaborators. The noise analysis showed discomfort, where the waiter was exposed to levels of 83 dB, in the heat exposure the cooking area contributed to the thermal discomfort, where the exposure of 30.7 IBTUG was found and insufficient lighting in the area of washing pots with 86 lux. Risks arising from the incorrect use of PPE's and lack of these were found in the handling of chemicals and in the ergonomic risks was observed inadequacy of the height of worktops. From these results, it is fundamental to promote corrective measures to provide a comfortable work environment with reduced wear for the employee, so that there are no negative consequences for the company, as well as the customer.
DOI: 10.6084/m9.figshare.14283086
title: Product development in technology based firms in innovation environments

description: Abstract: Technology based firms (TBFs) require innovative products to survive and compete in the market. The creation of products that sustain the competitiveness of companies depends directly on their product development process (PDP). The objective of this research was to investigate how PDP is carried out in TBFs in innovation environments. The research is qualitative, based on multiple case studies. Three companies in technology parks in the South and Southeast of Brazil were studied. The companies produced the following products: multiparametric monitor, an ondaleta and a microfiltration system. The key findings of the research were a lack of formal PDP planning and unstructured development processes. As a contribution, the study proposes that TBFs use a milestone strategy in the PDP microphases, guaranteeing greater efficiency in product development without the need to create rigid processes in project development. The study also highlights the importance of cooperation with clients and suppliers during the revision phases of PDP. The products resulting from PDP of the companies studied were identified as incremental innovation, novel for the national market, but with established technology on the international market. Future studies should assess the evolution and learning curve in the product development phase of TBFs.
DOI: 10.6084/m9.figshare.14283086.v1
title: Product development in technology based firms in innovation environments

description: Abstract: Technology based firms (TBFs) require innovative products to survive and compete in the market. The creation of products that sustain the competitiveness of companies depends directly on their product development process (PDP). The objective of this research was to investigate how PDP is carried out in TBFs in innovation environments. The research is qualitative, based on multiple case studies. Three companies in technology parks in the South and Southeast of Brazil were studied. The companies produced the following products: multiparametric monitor, an ondaleta and a microfiltration system. The key findings of the research were a lack of formal PDP planning and unstructured development processes. As a contribution, the study proposes that TBFs use a milestone strategy in the PDP microphases, guaranteeing greater efficiency in product development without the need to create rigid processes in project development. The study also highlights the importance of cooperation with clients and suppliers during the revision phases of PDP. The products resulting from PDP of the companies studied were identified as incremental innovation, novel for the national market, but with established technology on the international market. Future studies should assess the evolution and learning curve in the product development phase of TBFs.
DOI: 10.6084/m9.figshare.14283087.v1
title: Mapping regional business opportunities using geomarketing and machine learning

description: Abstract: The objective of this study is to develop a quantitative tool, based on Machine Learning and Geomarketing to identify business opportunities and contribute to the strategic process of local choice of franchises’ network selecting regions that have a high demand forecast and a lack of product supply. In addition, we conducted a qualitative analysis of the selected business places based on defined criteria. This prediction is given by constructing a consumption pattern, defined by a classifier, based on the characteristics of the reserved rights. Initially, for a better understanding on this subject, a theoretical background was made covering the main concepts about Geomarketing and Machine Learning and its applications. After that for a demonstration of the results, we opted for the application of the method for the market of fine chocolates (Cacau-Show) in the Distrito Federal. The main databases used in this paper were Pesquisa de Orçamentos Familiares and from Instituto Brasileiro de Estatística e Geografia (IBGE). As a result, the Standardized Spend was obtained, which indicates the requirement for each Censitar Sector, as georeferenced information of the competition, containing 44 stores that have as their main product of fine chocolate, and as digital meshes of the Federal District. The crossing is available for the elaboration of a map that facilitates the identification of the business opportunities for the market of fine chocolates in the Distrito Federal, Brazil.
DOI: 10.22008/fk2/oiajvo/84wsq6
title: snow_specific_area.tif

description: SICE version: Cloud removed, PPGC, SNAP7, pySICEv1.4
DOI: 10.6084/m9.figshare.14283090
title: Phases and tools for supply chain risk management: a systematic literature review

description: Abstract Supply chain risk management (SCRM) has been widely discussed in the academic literature and several models have been proposed in recent years, but there is a need for a model encompassing phases and tools for SCRM. This study presents a systematic literature review (SLR) of 254 abstracts and 68 full-text papers. The SLR made it possible to identify and define the main phases for the SCRM, as well as the tools proposed for each phase. There is a concentration of efforts in the phases of identification, assessment, and selection of risk management strategies and a limited number of studies in monitoring and controlling risks. The article offers a global SCRM framework, contributing to the theoretical discussions and a practical guide to implementation related to SCRM.
DOI: 10.6084/m9.figshare.14283090.v1
title: Phases and tools for supply chain risk management: a systematic literature review

description: Abstract Supply chain risk management (SCRM) has been widely discussed in the academic literature and several models have been proposed in recent years, but there is a need for a model encompassing phases and tools for SCRM. This study presents a systematic literature review (SLR) of 254 abstracts and 68 full-text papers. The SLR made it possible to identify and define the main phases for the SCRM, as well as the tools proposed for each phase. There is a concentration of efforts in the phases of identification, assessment, and selection of risk management strategies and a limited number of studies in monitoring and controlling risks. The article offers a global SCRM framework, contributing to the theoretical discussions and a practical guide to implementation related to SCRM.
DOI: 10.6084/m9.figshare.14283092
title: Proposal for suppliers evaluation using the integration of AHP/QFD methods

description: Abstract The present work has as main objective the development and presentation of a model for supplier’s evaluation. The proposed model includes the criteria of the lean concept and provides a comprehensive analysis for decision-making in the area of supplies. The work involved 05 steps: (i) identify and select the main criteria for lean suppliers management; (ii) perform the weighting of criteria using the AHP (Analytic Hierarchy Process); (iii) define the indicators to be used for the suppliers analysis in every sub-criteria; (iv) calculate the relative weight of each indicator through the analysis of interdependence between the sub-criteria and indicators; (v) testing partially the model through the application of the same in a product group in the reality of a company. The main contribution of this paper is to propose a model that combines the method AHP (Analytic Hierarchy Process) used for multiple criteria decision-making method with QFD (Quality Function Deployment) able to translate these criteria in guidelines for the supply management. From a practical point of view, the importance of this article is to present a relatively simple model for the systematization of building supply indicators. The obtained results recommend the use of this template.
DOI: 10.6084/m9.figshare.14283095
title: Integration of quality tools and multi-criteria methods: a bibliometric and systemic analysis

description: Abstract: This study aims to identify the integration between quality tools and multi-criteria methods, using a bibliometric and systemic analysis. In order to meet this research objective, the methodology used to select the bibliographic portfolio, perform the bibliometric and systemic analysis was the ProKnow-C (Knowledge Development Process – Constructivist). As result were selected 17 articles that represented the bibliographic portfolio and 351 articles as reference for the bibliographic portfolio. The results highlight the journals: Expert Systems with Applications e Applied Soft Computing Journal. The most aligned articles with the theme were, “Supplier selection paradigm: An integrated hierarchical QFD methodology under multiple-criteria environment”, and “Decision making with the analytic hierarchy process”. In the systemic analysis were considered six lenses, according to the theoretical affiliation MCDA-C, and was concluded that the articles were not totally aligned with this specific affiliation. The AHP and TOPSIS methods stood out as the most used methods in this portfolio. It was verified that the quality tools when used integrated with multi-criteria methods allow the creation of decision making evaluation models for scenarios present in the papers found in this research.
DOI: 10.6084/m9.figshare.14283087
title: Mapping regional business opportunities using geomarketing and machine learning

description: Abstract: The objective of this study is to develop a quantitative tool, based on Machine Learning and Geomarketing to identify business opportunities and contribute to the strategic process of local choice of franchises’ network selecting regions that have a high demand forecast and a lack of product supply. In addition, we conducted a qualitative analysis of the selected business places based on defined criteria. This prediction is given by constructing a consumption pattern, defined by a classifier, based on the characteristics of the reserved rights. Initially, for a better understanding on this subject, a theoretical background was made covering the main concepts about Geomarketing and Machine Learning and its applications. After that for a demonstration of the results, we opted for the application of the method for the market of fine chocolates (Cacau-Show) in the Distrito Federal. The main databases used in this paper were Pesquisa de Orçamentos Familiares and from Instituto Brasileiro de Estatística e Geografia (IBGE). As a result, the Standardized Spend was obtained, which indicates the requirement for each Censitar Sector, as georeferenced information of the competition, containing 44 stores that have as their main product of fine chocolate, and as digital meshes of the Federal District. The crossing is available for the elaboration of a map that facilitates the identification of the business opportunities for the market of fine chocolates in the Distrito Federal, Brazil.
DOI: 10.6084/m9.figshare.14283098
title: Expert Systems and knowledge management for failure prediction to onshore pipelines: issue to Industry 4.0 implementation

description: Abstract: The paper aims to propose an Expert System to predict the failure of onshore pipelines. Knowledge Management supports expertise sharing throughout the organization. The Expert System Prototype Model proposed is classified as Empirical Descriptive Research, and may support maintenance management. The findings evidence that Expert System proposed grounded in employee knowledge may be considered a promising solution to support Industry 4.0 implementation. The Expert System facilitates the decision-making of the experts so that the employees’ expertise can be better used in the implementation of Industry 4.0 and to face the new challenges related to the daily work in the organization. In this context, the Expert System can be considered as an innovative approach to manage maintenance processes and supporting reliable, consistent decisions during I.4 implementation.
DOI: 10.6084/m9.figshare.14283098.v1
title: Expert Systems and knowledge management for failure prediction to onshore pipelines: issue to Industry 4.0 implementation

description: Abstract: The paper aims to propose an Expert System to predict the failure of onshore pipelines. Knowledge Management supports expertise sharing throughout the organization. The Expert System Prototype Model proposed is classified as Empirical Descriptive Research, and may support maintenance management. The findings evidence that Expert System proposed grounded in employee knowledge may be considered a promising solution to support Industry 4.0 implementation. The Expert System facilitates the decision-making of the experts so that the employees’ expertise can be better used in the implementation of Industry 4.0 and to face the new challenges related to the daily work in the organization. In this context, the Expert System can be considered as an innovative approach to manage maintenance processes and supporting reliable, consistent decisions during I.4 implementation.
DOI: 10.6084/m9.figshare.14283099
title: Systematic analysis of comparative studies between additive and conventional manufacturing focusing on the environmental performance of logistics operations

description: Abstract: Based on the promise to revolutionize the entire supply chain, additive manufacturing is seen as an alternative to conventional manufacturing processes, since it simplifies the production of small batches, shortens the distances between production and consumption and generates new distribution models. Due to its huge potential to spread more sustainable environmental practices, investigations on the environmental assumptions, concerning the application of additive manufacturing technologies, are required. Therefore, based on a systematic literature review, this study aimed to analyze the studies that addressed the environmental performance of logistics operations in a comparison among conventional and additive manufacturing, using the Life Cycle Assessment technic (LCA). Although there are few available studies that quantitatively analyze and compare the environmental performance of the additive manufacturing process with traditional process from a transport perspective, it has been concluded that reducing the distances and the quantity of transported products, carbon dioxide emissions and the consumption of energy resources are reduced.
DOI: 10.6084/m9.figshare.14283095.v1
title: Integration of quality tools and multi-criteria methods: a bibliometric and systemic analysis

description: Abstract: This study aims to identify the integration between quality tools and multi-criteria methods, using a bibliometric and systemic analysis. In order to meet this research objective, the methodology used to select the bibliographic portfolio, perform the bibliometric and systemic analysis was the ProKnow-C (Knowledge Development Process – Constructivist). As result were selected 17 articles that represented the bibliographic portfolio and 351 articles as reference for the bibliographic portfolio. The results highlight the journals: Expert Systems with Applications e Applied Soft Computing Journal. The most aligned articles with the theme were, “Supplier selection paradigm: An integrated hierarchical QFD methodology under multiple-criteria environment”, and “Decision making with the analytic hierarchy process”. In the systemic analysis were considered six lenses, according to the theoretical affiliation MCDA-C, and was concluded that the articles were not totally aligned with this specific affiliation. The AHP and TOPSIS methods stood out as the most used methods in this portfolio. It was verified that the quality tools when used integrated with multi-criteria methods allow the creation of decision making evaluation models for scenarios present in the papers found in this research.
DOI: 10.6084/m9.figshare.14283096
title: Selection of additive manufacturing technologies in productive systems: a decision support model

description: Abstract: Additive Manufacturing (AM) has seen continued growth in adoption by organizations in recent years, changing production processes, supply chain, maintenance, product development and the global economy. There are several Additive Manufacturing technologies and equipment on the market, however, there are no guidelines, benchmarking or decision support tools for proper selection. After a systematic review of the literature, the lack of propositions that act during the development of the product and process was evidenced. This research focuses on the selection of Additive Manufacturing technologies for a production system. The general objective being to propose a decision support model based on the characteristics of additive technologies and competitive criteria, resulting in a choice aligned with the guidelines of organizations and their production systems. For the operationalization of the model, the AHP techniques and conjoint analysis were used together, where the characteristics of the Additive Manufacturing technologies were related to the competitive criteria for the model to indicate the recommended technology to the production system or organization in question. Finally, the artifact recommended the right technology in three distinct situations, from a vendor, user, and expert point of view. Thus, this research contributes to both academia and business by developing a functional artifact of additive manufacturing technology selection. Also, by contributing to the increased availability of information on the nine most commonly used additive technologies in industry.
DOI: 10.6084/m9.figshare.14283099.v1
title: Systematic analysis of comparative studies between additive and conventional manufacturing focusing on the environmental performance of logistics operations

description: Abstract: Based on the promise to revolutionize the entire supply chain, additive manufacturing is seen as an alternative to conventional manufacturing processes, since it simplifies the production of small batches, shortens the distances between production and consumption and generates new distribution models. Due to its huge potential to spread more sustainable environmental practices, investigations on the environmental assumptions, concerning the application of additive manufacturing technologies, are required. Therefore, based on a systematic literature review, this study aimed to analyze the studies that addressed the environmental performance of logistics operations in a comparison among conventional and additive manufacturing, using the Life Cycle Assessment technic (LCA). Although there are few available studies that quantitatively analyze and compare the environmental performance of the additive manufacturing process with traditional process from a transport perspective, it has been concluded that reducing the distances and the quantity of transported products, carbon dioxide emissions and the consumption of energy resources are reduced.
DOI: 10.6084/m9.figshare.14283102
title: Automated risk assessment for material movement in manufacturing

description: Abstract: Proximity movements between vehicles transporting materials in manufacturing plants, or “interfaces”, result in occupational injuries and fatalities. Risk assessment for interfaces is currently limited to techniques such as safety audits, originally designed for static environments. A data-driven alternative for dynamic environments is desirable to quantify interface risks and to enable the development of effective countermeasures. We present a method to estimate the Risk Prioritization Number (RPN) for mobile vehicle interfaces in manufacturing environments, based on the Probability-Severity-Detectability (PSD) formulation. The highlight of the method is the estimation of the probability of occurrence (P) of vehicle interfaces using machine learning and computer vision techniques. A PCA-based sparse feature vector for machine learning characterizes vehicle geometry from a top-down perspective. Supervised classification on sparse feature vectors using Support Vector Machines (SVMs) is employed to detect vehicles. Computer vision techniques are used for position tracking to identify interfaces and to calculate their probability of occurrence (P). This leads to an automated calculation of RPN based on the PSD formulation. Experimental data is collected in the laboratory using a sample work area layout and scale versions of vehicles. Vehicle interfaces and movements were physically simulated to train and test the machine learning model. The performance of the automated system is compared with human annotation to validate the approach.
DOI: 10.6084/m9.figshare.14283102.v1
title: Automated risk assessment for material movement in manufacturing

description: Abstract: Proximity movements between vehicles transporting materials in manufacturing plants, or “interfaces”, result in occupational injuries and fatalities. Risk assessment for interfaces is currently limited to techniques such as safety audits, originally designed for static environments. A data-driven alternative for dynamic environments is desirable to quantify interface risks and to enable the development of effective countermeasures. We present a method to estimate the Risk Prioritization Number (RPN) for mobile vehicle interfaces in manufacturing environments, based on the Probability-Severity-Detectability (PSD) formulation. The highlight of the method is the estimation of the probability of occurrence (P) of vehicle interfaces using machine learning and computer vision techniques. A PCA-based sparse feature vector for machine learning characterizes vehicle geometry from a top-down perspective. Supervised classification on sparse feature vectors using Support Vector Machines (SVMs) is employed to detect vehicles. Computer vision techniques are used for position tracking to identify interfaces and to calculate their probability of occurrence (P). This leads to an automated calculation of RPN based on the PSD formulation. Experimental data is collected in the laboratory using a sample work area layout and scale versions of vehicles. Vehicle interfaces and movements were physically simulated to train and test the machine learning model. The performance of the automated system is compared with human annotation to validate the approach.