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Details

  • Name

    Maria Clara Vaz
  • Role

    External Research Collaborator
  • Since

    01st March 2014
Publications

2024

Sample Size Analysis for a Production Line Study of Time

Authors
da Silva, MI; Vaz, CB;

Publication
Lecture Notes in Mechanical Engineering

Abstract
Setting labor standards is an important topic to operational and strategic planning which requires the time studies establishment. This paper applies the statistical method for the definition of a sample size in order to define a reliable cycle time for a real industrial process. For the case study it is considered a welding process performed by a single operator that does the load and unload of components in 4 different welding machines. In order to perform the time studies, it is necessary to collect continuously data in the production line by measuring the time taken for the operator to perform the task. In order to facilitate the measurements, the task is divided into small elements with visible start and end points, called Measurement Points, in which the measurement process is applied. Afterwards, the statistical method enables to determine the sample size of observations to calculate the reliable cycle time. For the welding process presented, it is stated that the sample size defined through the statistical method is 20. Thus, these time observations of the task are continuously collected in order to obtain a reliable cycle time for this welding process. This time study can be implemented in similar way in other industrial processes. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2023

A DEA Approach to Evaluate the Performance of the Electric Mobility Deployment in European Countries

Authors
Vaz, B; Ferreira, P;

Publication
Springer Proceedings in Mathematics and Statistics

Abstract
This work aims to assess the performance of European countries on the deployment of low-emission vehicles in road transportation. For this purpose, a model based on Data Envelopment Analysis (DEA) is used to calculate a composite indicator for several European countries, aggregating seven sub-indicators built from a data set for the 2019 year. Various virtual weight restrictions schemes of the sub-indicators are studied to explore the robustness of the performance results. By adopting the most robust scheme, the performance results obtained indicate that most European countries have the potential to improve their practices towards better road transport sustainability, by emulating the best practices observed in the four identified benchmarks. Thus, the inefficient countries should take measures to better support the market share of plug-in electric vehicles. In addition, the railway sector and the penetration of renewable energies should be enhanced to improve road transportation sustainability. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2023

Impact of Organizational Factors on Accident Prediction in the Retail Sector

Authors
Sena, I; Mendes, J; Fernandes, FP; Pacheco, MF; Vaz, CB; Lima, J; Braga, AC; Novais, P; Pereira, AI;

Publication
Computational Science and Its Applications - ICCSA 2023 Workshops - Athens, Greece, July 3-6, 2023, Proceedings, Part II

Abstract
Although different actions to prevent accidents at work have been implemented in companies, the number of accidents at work continues to be a problem for companies and society. In this way, companies have explored alternative solutions that have improved other business factors, such as predictive analysis, an approach that is relatively new when applied to occupational safety. Nevertheless, most reviewed studies focus on the accident dataset, i.e., the casualty’s characteristics, the accidents’ details, and the resulting consequences. This study aims to predict the occurrence of accidents in the following month through different classification algorithms of Machine Learning, namely, Decision Tree, Random Forest, Gradient Boost Model, K-nearest Neighbor, and Naive Bayes, using only organizational information, such as demographic data, absenteeism rates, action plans, and preventive safety actions. Several forecasting models were developed to achieve the best performance and accuracy of the models, based on algorithms with and without the original datasets, balanced for the minority class and balanced considering the majority class. It was concluded that only with some organizational information about the company can it predict the occurrence of accidents in the month ahead. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2023

Economic Performance of Apparel Manufacturing Companies; [Performance Económica das Empresas de confeção de artigos de vestuário]

Authors
Vaz, B; Fernandes, B;

Publication
Iberian Conference on Information Systems and Technologies, CISTI

Abstract
Given the relevance of the textile industry, over the years, for the portuguese economy, we intend to evaluate the economic performance of companies belonging to CAE 14131 through the indicators ROA, ROE, ROS and EVA/employees. Through the DEA technique, the BoD model is used to aggregate the various indicators in order to determine the composite indicator of 5.397 companies observed over the years 2011 to 2020, in order to deepen the knowledge about the Portuguese business economic textile sector. Through data analysis there is a progressive improvement of the indicators studied over the years which can be explained by the technological evolution occurred in this industry, although the sector under study uses mostly intensive labour. In each year, the efficient frontier is defined mostly by micro and small enterprises, which are predominantly located in the North of Portugal. © 2023 ITMA.

2023

Sustainable Short-Term Production Planning Optimization

Authors
Zanella, F; Vaz, CB;

Publication
SN Computer Science

Abstract
This study proposes a framework for short-term production planning of a Portuguese company operating as a tier 2 supplier in the automotive sector. The framework is intended to support the decision-making process regarding a single progressive hydraulic press, which is used to manufacture cold-stamped parts for exhaust systems. The framework consists of two sequential levels: (1) a Mixed-Integer Linear Programming (MILP) model to determine the optimal production quantities per week while minimizing the total cost; (2) a dynamic production sequencing rule for scheduling operations on the hydraulic press. The two levels are combined and implemented in Excel, where the MILP model is solved using the Solver add-in, and the second level uses the optimal production quantities as inputs to determine the production sequence using a dynamic priority rule. To validate the framework, a proposed optimal plan was compared to a real plan executed by the company, and it was found that the framework could save up to 22.1% of the total cost observed in reality while still satisfying demand. To address uncertainties, the framework requires a rolling weekly planning horizon. © 2023, The Author(s).

Supervised
thesis

2016

Avaliação de Desempenho de Lares de Infância e Juventude utilizando a técnica DEA.

Author
Ivo Manuel Raposo Mendes

Institution
IPB

2016

Benchmarkmg da Imagiologia nos Hospitais Portugueses do Senijço Nacional de Saúde

Author
Rafael Sousa Soares

Institution
IPB

2016

A gestão de stocks do serviço de assistência técnica na área da eletromedicina

Author
Fernanda Maria Martins Oliveira

Institution
IPP-ISCAP

2016

Avaliação da Gestão da Manutenção de Equipamentos Hospitalares

Author
Cristian Gomes Carvalheiro.

Institution
IPB

2016

Certificação de qualidade versus qualidade de informação financeira: estudo para empresas portuguesas

Author
Ana Catarina Rodrigues Martins

Institution
IPB