Este artigo investiga o suporte quantitativo necessário à operacionalização da manutenção centrada em confiabilidade (MCC). Inicialmente, foram identificadas na literatura dez atividades consideradas essenciais para a operacionalização da MCC e os métodos quantitativos que podem dar suporte a essa metodologia. A seguir, foram realizadas entrevistas em empresas manufatureiras a fim de verificar a utilização dos métodos descritos na literatura e identificar outros métodos usados. Como resultado, foi elaborado um quadro que associa as atividades essenciais da MCC aos métodos quantitativos, juntamente com uma breve descrição das contribuições de cada método. Entre os métodos quantitativos identificados, destaque para o uso de distribuições de probabilidade, que suporta várias atividades da MCC. Os métodos de engenharia econômica e a simulação de Monte Carlo também merecem destaque, pois permitem análises mais sofisticadas associadas a custo e desempenho de ençãsistemas produtivos sujeitos à manutenção.

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Cold standby systems subject to periodic inspections are widely applied in industry. However, the establishment of system reliability, expected time to failure, and appropriate time interval between inspections in a form accessible to industrial and maintenance engineers are still challenging issues. This paper aims to develop equations that solve this problem based on an analysis of expected exposure time for active and redundant components. A table and a general analytic expression along with graphs were elaborated to allow for the establishment of the appropriate time interval between inspections, given the level of reliability required and the number of standbys available. The main advantage of the results presented in this paper is the ability to conduct the reliability evaluation without the use of complex formulations such as Markov process or Laplace transforms that are usually beyond the skills of the industrial and maintenance staff. Also, a comparison with the exact solution using probability theory is presented, and it is proved that the method developed in this study provides a good approximation for practical applications.

Background: Due to the COVID-19 pandemic, Brazilian public schools closed in 2020. This lockdown stopped the provision of school meals to public school students, most of whom belonged to low-income families facing food insecurity. To guarantee the students’ food security during this period, food items previously provided through school meals were converted into food kits and delivered to the students’ families. Methods: This case study analyzes the logistical impacts of this change in the school food supply chain concerning the legislation, procurement, assembly, and distribution of food kits in the city of Vitória, Brazil. We interviewed suppliers and workers of the Municipal Secretariat of Education and distributed a survey to professionals and beneficiaries. Results: One of the findings was that federal procurement regulations for the acquisition of food for public schools led to difficult choices for school officials during this period. These regulations determined that at least 30% of the budget must be used in local purchases from smallholder family farmers. However, almost all products generated by family farming in the region of Vitória are perishable and require distribution and consumption on the same day, which represents a challenge for the logistic process of assembling and distributing food kits. The solution was the selection of eggs as the primary protein item in the kits. Conclusions: The lessons learned through this study suggest potential actions that would make this supply chain more resilient in future emergencies.

Paper aims: To identify factors to measure the cooperation between an agro-industrial pork slaughterhouse cooperative and input suppliers.Originality: A performance measurement tool applicable in real-life industry practices related to input suppliers, based on critical success factors. Research method:The performance measurement tool was calculated based on the analytic hierarchy process (AHP) procedure, constituted by two essential elements, the critical success factors and the key performance indicators, organized in a hierarchical structure. The key performance indicators are used to detail the critical success factors, measuring the supplier's performance in relation to specific cooperation characteristics. Main findings:In general, 77% of suppliers are fully or potentially cooperative with an established performance in risk sharing and information sharing factors. For the remaining 23% of suppliers classified as partially cooperatives, suggestions were proposed for changes to be implemented which improve their cooperation level performance. Finally, a direct relation between a low proportion of input discards and a established cooperative performance between suppliers and the analyzed agro-industrial pork cooperative was not verified. Implications for theory and practice:To provide a performance measurement tool developed with methodological rigor to be used by researchers and agro-industrial pork slaughterhouse cooperative managers to improve the Brazilian pork slaughterhouse supply chain context.

Este artigo apresenta um método para desenvolver análises quantitativas que orientem a revisão ou elaboração de um plano de manutenção de equipamentos em um cenário de produção just in time. O método proposto contempla: i) Identificar os conjuntos que influenciam a confiabilidade; ii) Levantar taxas de falhas; iii) Classificar os conjuntos quanto ao efeito de suas falhas; iv) Levantar parâmetros de demanda da linha; v) Identificar as distribuições de probabilidade da demanda da linha e dos tempos de bom funcionamento e tempos de reparo dos conjuntos; vi) Simular a produção/manutenção utilizando o método de Monte Carlo; vii) Realizar uma análise de sensibilidade a eventuais variações na demanda, MTBF e MTTR; e viii) Estabelecer a estratégia de manutenção e intervalos entre manutenções preventivas. A aplicação do método é ilustrada através de um estudo real realizado em uma linha de rotulagem e enchimento de galões de uma empresa do setor de tintas e corantes. A aplicação do método permitiu identificar com clareza os conjuntos e subconjuntos críticos frente ao cenário produtivo em questão.

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Key-Words: electronics industry, metallurgical industry, quantitative methods, reliability centered maintenance SUMMARY & CO CLUSIO SThis paper investigates each of the quantitative methods that support Reliability Centered Maintenance (RCM) operation. The integration of quantitative methods with RCM activities is an innovative approach since previous RCM methodologies only utilized qualitative methods. A thorough literature review identified ten essential activities that are necessary for the application of RCM along with the respective quantitative methods that support these activities. Furthermore, in-person interviews were conducted at Brazilian manufacturing firms to confirm the actual application of the methods from the literature. These interviews also helped us identify additional methods that these companies use in their manufacturing practices. As a result, a table associating essential RCM activities with their quantitative method counterpart was created, along with a brief description of what each respective quantitative method contributes specifically. Among the quantitative methods evaluated, probability theory was identified as the one that was most commonly associated with RCM activities. The methods of Economic engineering and Monte Carlo simulation were also identified as key contributors since they allowed for more sophisticated analysis related to the cost and performance of production systems subject to maintenance.The use of probability distributions in modeling is important in many RCM activities. Not only should the average values be used, but it is necessary to understand the effects of times to failure and times to repair on time. The Economic engineering methods allowed the analysis of the life cycle costs of machines and equipment. Monte Carlo simulation is capable of analyzing real systems which are essentially stochastic. A more complete view of the equipment and their critical components is provided through the use of blocks diagram and system reliability analysis techniques. The methods of production planning and controlling, such as Manufacturing Resource Planning II (MRPII), support the optimal planning of maintenance activities. The stochastic and deterministic models of stocks management optimize storage costs in relation to the cost of lacking spare parts. Indicators specific to maintenance, such as Overall Equipment Effectiveness (OEE) and Total Effective Equipment Performance (TEEP), allow the monitoring of essential variables in the production lines and the calculation of global efficiency. Costing systems such as ABC quantify the productive system costs, which include the maintenance activities.These methods can have an expressive contribution to the RCM operation. The quantitative methods listed improve both the planning and activities control while also reducing costs.