Interval Preventive Maintenance Dengan Dasar Keandalan

Maintenance merupakan lini support process dalam model bisnis CIMOSA. Meskipun termasuk dalam support process namun dengan penanganan yang tepat akan memberi dampak penghematan yang besar. Studi kasus dalam penelitian ini yakni Machine Direct Order (MDO) pada lini produksi BOPP 6. Penelitian ini memberikan dampak untuk memudahkan aktivitas maintenance yang tepat dengan penanganan hanya terkonsentrasi pada komponen kritis saja. PT Trias Sentosa belum melakukan Preventive Maintenance dengan dasar perhitungan keandalan, hal inilah yang mendasari penelitian ini untuk dilakukan. Berdasarkan data kerusakan dan pengolahan penentuan kritis, maka didapatkan bahwa komponen Nip Roll MDO 6 dan 3 memiliki karakteristik sesuai distribusi yang telah diolah dengan software Weibull++6 yakni Weibull 2 Parameter, hasil MTTF dan MTTR menjadi dasar acuan dalam pembuatan jadwal preventive maintenance rekomendasi. Jadwal rekomendasi awal memberikan nilai opportunity cost sebesar Rp 8.588.646.566,40 dan dengan integrasi time to repair kondisi eksisting maka opportunity cost dapat diperkecil menjadi Rp 1.717.729.313,28. Dasar penentuan integrasi ini yakni dari pembandingan dampak availability terhadap opportunity cost pada original MTTF dan interval perawatan eksisting. Opportunity cost paling minimum yakni apabila jadwal rekomendasi awal diintegrasikan dengan nilai time to repair berdasarkan kondisi eksisting, hal inilah yang menjadi dasar dalam pembuatan jadwal skenario terbaru yang memiliki dampak opportunity cost terkecil. ========================================================================================================= Maintenance is a line of support in the business model CIMOSA process. Although included in the support process, but with the right treatment it will impact big savings. The case studies in this research namely Machine Direct Order (MDO) in BOPP production line 6. This study gives effect to facilitate maintenance activities appropriate to handling only concentrated on critical components only. Preventive Maintenance in PT Trias Sentosa not done on the basis of calculation of reliability, it is the underlying this research to be done. Based on data from damage and critical determination processing, it was found that the component Nip Roll MDO 6 and 3 have characteristics consistent distribution that has been processed with the software Weibull ++ 6 is Weibull 2 Parameter, MTTF and MTTR results are the basis in making preventive maintenance schedule recommendations. Schedule initial recommendations give the opportunity cost of Rp 8,588,646,566.40 and the integration time to repair the existing condition then the opportunity cost can be reduced to Rp 1,717,729,313.28. The basis for determining the integration of benchmarking is the impact of the availability on the opportunity cost with original MTTF and existing maintenance (time to repair) intervals. The most minimum opportunity cost is when the initial recommendation schedule is integrated with the value of time to repair based on existing condition, thus themost minimum impact of opportunity cost will be achieved

Opportunistic Preventive Maintenance Scheduling Based on Theory of Constraints

Abstract In recent years, to improve system reliability and economy, machine maintenance strategies have been paid more and more intention by researchers. This paper aims to integrate the concept of theory of constraints (TOC) into multi-machine opportunistic maintenance policy. Based on the preventive maintenance algorithm, an improved model containing bottleneck strategy which influences opportunistic maintenance has been developed. By maximizing total cost saving, an optimal maintenance schedule of all machines in a series product line can be obtained. The results of a case study show that this model is valid for planning a comprehensive optimal maintenance schedule. Furthermore, by comparing with other models, this model has been proven to be more effectively especially in series product lines with bottleneck

State of the art in simulation-based optimisation for maintenance systems

Recently, more attention has been directed towards improving and optimising maintenance in manufacturing systems using simulation. This paper aims to report the state of the art in simulation-based optimisation of maintenance by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. The authors investigate application areas and published real case studies as well as researched maintenance strategies and policies. Much of the research in this area is focusing on preventive maintenance and optimising preventive maintenance frequency that will lead to the minimum cost. Discrete event simulation was the most reported technique to model maintenance systems whereas modern optimisation methods such as Genetic Algorithms was the most reported optimisation method in the literature. On this basis, the paper identifies the current gaps and discusses future prospects. Further research can be done to develop a framework that guides the experimenting process with different maintenance strategies and policies. More real case studies can be conducted on multi-objective optimisation and condition based maintenance especially in a production context

Implementación del mantenimiento preventivo para mejorar la Productividad del área de vehículos convertidos a GLP, Empresa Vari Almacenes SAC, Callao, 2021

El objetivo de la presente investigación fue la implementación del mantenimiento preventivo mejora la productividad de la empresa Vari Almacenes S.A.C, Callao, 2021. La investigación es de tipo aplicada, Enfoque cuantitativo, de nivel explicativo, alcance longitudinal, diseño pre experimental. La población y muestra estará conformada por los equipos que participan en el área de convertidos a GLP. Las técnicas aplicadas fueron la observación, y análisis documental, mediante una ficha de observación. Los resultados descriptivos muestran una media de 35.33% en productividad antes de incoar el mantenimiento preventivo, y luego de la aplicación, este indicador subió a 84.85%, la prueba de Wilcoxon arrojo una significancia de 0.000, y unas diferencias entre medias de 49.52% positiva, indicando la mejora de la productividad posterior a la aplicación del mantenimiento. De igual forma, se comprobó la mejora en eficienciade 39.58%, y en eficacia de 24.68%. Se concluyó que la implementación de un mantenimiento preventivo mejora los indicadores de productividad, eficiencia y eficacia del área de conversión a GLP. Se recomendó a la empresa, difundir el mantenimiento preventivo en el tiempo, y obtener datos, así como de aplicar una normativa interna general de prevención

Simulation-based optimisation of complex maintenance systems

There is a potential as well as a growing interest amongst researchers to utilise simulation in optimising maintenance systems. The state of the art in simulation-based optimisation of maintenance was established by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. In general, approaches to optimise maintenance varied significantly in the literature. Overall, these studies highlight the need for a framework that unifies the approach to optimising maintenance systems. Framework requirements were established through two main sources of published research. Surveys on maintenance simulation optimisation were examined to document comments on the approaches authors follow while optimising maintenance systems. In addition, advanced and future maintenance strategies were documented to ensure it can be accommodated in the proposed framework. The proposed framework was developed using a standard flowchart tool due to its familiarity and ability to depict decision structures clearly. It provides a systematic methodology that details the steps required to connect the simulation model to an optimisation engine. Not only it provides guidance in terms of formulating the optimal problem for the maintenance system at hand but it also provides support and assistance in defining the optimisation scope and investigating applicable maintenance strategies. Additionally, it considers current issues relating to maintenance systems both in research and in practice such as uncertainty, complexity and multi-objective optimisation. The proposed framework cannot be applied using existing approaches for modelling maintenance. Existing modelling approaches using simulation have a number of limitations: The maintenance system is modelled separately from other inter-related systems such as production and spare parts logistics. In addition, these approaches are used to model one maintenance strategy only. A novel approach for modelling maintenance using Discrete Event Simulation is proposed. The proposed approach enables the modelling of interactions amongst various maintenance strategies and their effects on the assets in non-identical multi-unit systems. Using the proposed framework and modelling approach, simulation-based optimisation was conducted on an academic case and two industrial cases that are varied in terms of sector, size, number of manufacturing processes and level of maintenance documentation. Following the structured framework enabled discussing and selecting the suitable optimisation scope and applicable maintenance strategies as well as formulating a customised optimal problem for each case. The results of the study suggest that over-looking the optimisation of maintenance strategies may lead to sub-optimal solutions. In addition, this research provides insights for non-conflicting objectives in maintenance systems

Proposta de um modelo multicritério para determinação da criticidade na gestão da manutenção industrial

This work aims to propose a model for determining the criticality in industrial processes, using the multi-criteria analysis. Initially it is proposed a priority rating of the most critical elements of an industrial system and later, an ordering of the elements within their respective classes of criticality, thus obtaining the criticality of each. The model is based on outranking methods ELECTRE TRI and PROMETHEE II. An application of the model is carried out in this work, where the criteria are considered: security; environment; quality; operational impact; economic impacts; mean time between failures and mean time to repair. As a result, are presented comparisons of the proposed model with the traditional methods of determination of criticality, trying to observe subjective aspects and objectives jointly in order to provide a clear and systemic view of the problems implicit in determining the criticality in industrial systems. It was concluded that the use of multi-criteria analysis to determine criticality enables greater depth in the assessment and is a tool that helps in the management of maintenance and increased reliability for production systems.Esse trabalho tem como objetivo propor um modelo para determinação da criticidade em processos industriais, utilizando a análise multicritério. Inicialmente é proposta uma classificação por prioridade dos elementos mais críticos de um sistema industrial e posteriormente, uma ordenação desses elementos dentro das suas respectivas classes de criticidade, obtendo com isso a criticidade de cada um. O modelo baseia-se nos métodos de sobreclassificação ELECTRE TRI e PROMETHEE II. Uma aplicação do modelo é realizada nesse trabalho, onde são considerados os critérios: segurança; meio-ambiente; qualidade; impacto operacional; impactos econômicos; tempo médio entre falhas e tempo médio de reparo. Como resultado, são apresentadas comparações do modelo proposto com os métodos tradicionais de determinação de criticidade, procurando observar aspectos subjetivos e objetivos de forma conjunta, a fim de fornecer uma visão clara e sistêmica sobre os problemas implícitos na determinação da criticidade em sistemas industriais. É possível concluir que o uso da análise multicritério na determinação da criticidade possibilita maior profundidade na avaliação e constitui uma ferramenta que auxilia na gestão da manutenção e no aumento da confiabilidade para os sistemas produtivos

Modelo integral de gestión de repuestos para mantenimiento, en empresas intensivas en uso de capital

Empresas intensivas en uso de capital, buscan garantizar la disponibilidad de sus equipos y evitar un paro operativo, para lograr el cumplimiento de sus compromisos de producción. Para el cumplimiento de este objetivo, estas empresas prevén bien sea redundancia de equipos o mantener cantidades considerables de repuestos en sus bodegas para la atención de mantenimientos. Sin embargo, esto tiene como consecuencia, considerables costos por capital inmovilizado en el caso de redundancia, y costos de abastecimiento, almacenamiento y obsolescencia en el caso de repuestos. Este trabajo de grado propone un modelo de gestión de repuestos y de segmentación, alineado a las estrategias de mantenimiento y de abastecimiento, que busca minimizar los costos de repuestos, y garantizar su disponibilidad para atención de mantenimientos, incluyendo los criterios de política de inventarios y de nivel de servicio requerido por mantenimiento. El trabajo, realiza un análisis de procesos y con la opinión de expertos de una empresa intensiva en uso de capital, contrasta la práctica empresarial con la literatura disponible, para desarrollar un modelo de gestión de repuestos de mantenimiento. En la práctica empresarial, se presenta ruptura entre los procesos de mantenimiento y gestión de inventarios por objetivos contrarios entre sí; y de la misma manera en la literatura disponible, el problema se ha estudiado desde la óptica del mantenimiento o de gestión de inventarios. Para la validación del modelo, se aplicó a casos de negocio de segmentos propuestos, verificándose su validez, aplicabilidad y beneficios en una empresa de transporte de crudo por oleoducto.Capital-Intensive companies seek to guarantee the availability of their equipment and avoid an operational stoppage to comply with their production commitments. For the fulfillment of this objective, these companies foresee either redundancy of equipment or maintain considerable quantities of spare parts in their warehouses for the attention of maintenance. However, as a consequence it has considerable costs for immobilized capital in the case of redundancy, and costs of supply, storage and obsolescence in the case of spare parts. This paper proposes a spare parts and segmentation management model, aligned to maintenance and sourcing strategies, which seeks to minimize spare parts costs, and guarantee their availability for servicing maintenance, including inventory policy criteria and the level of service required for maintenance. The study carries out an analysis of the processes and with the opinion of experts of a capital-intensive company, contrasts business practice with the available literature, to develop a maintenance spare parts management model. In business practice, there is a break between maintenance processes and inventory management for their opposite objectives; and in the same way in the available literature, the problem has been studied either from the standpoint of maintenance or inventory management. For the validation of the management model, it was applied to business cases of spare parts segments, verifying its validity, applicability and economic benefits in an oil pipeline company.Magíster en Ingeniería IndustrialMaestrí

Modelling and simulation for the joint optimisation of inspection maintenance and spare parts inventory in multi-line production settings

A simulation methodology is developed to model the joint optimisation of preventive maintenance and spare parts inventory in multi-line settings. The multi-line machines are subject to failure, based on the delay-time concept, and a selection of policies are used for the replenishment of the machines’ critical component. Production lines of varied configurations are modelled and described in three principal chapters. Firstly, the optimisation of preventive maintenance for a multi-line production system is developed in the context of a case study. The policy proposed indicates that consecutive inspection with priority for failure repair is cost-optimal, which suggests a substantial maintenance cost reduction of 61% compared to the run-to-failure policy. The contribution of this study is first and foremost in narrowing the gap between the theory and practice of managing multi-line systems, and in particular, that the scenarios and policies considered have important economic and engineering implications. In a second study, spare parts provisioning for a single-line system is considered, given that the demand for industrial plant spare parts should be driven, at least in part, by maintenance requirements. A paper-making plant provides a real context, for which simulation models are developed to jointly optimise the planned maintenance and the associated spare part inventory. This challenge is addressed in the context of the failure of parts in service and the replacement of defective parts at inspections of period T, using the delay-time concept, and a selection of replenishment policies. The results indicate that a periodic review policy with replenishment twice as frequent as inspection is cost-optimal. Further discussions and sensitivity analysis give insights into the characteristics and features of the policies considered. Finally, in the third study, the joint optimisation of preventive maintenance and the associated spare parts inventory for a multi-line system is developed using an idealised context. It is found that a review policy with inspection as frequent as replenishment using just-in-time (JIT) ordering is cost-optimal, and also the lowest risk policy; it is associated with the lowest simultaneous machine downtime and low stock-out cost-rates. This is a significant contribution to the literature. An implication of the proposed methodology is that, where mathematical modelling is intractable, or the use of certain assumptions make them less practical, simulation modelling is an appropriate solution tool. Throughout this thesis, the long-run average cost per unit time or cost-rate is used as the optimality criterion. In other contexts, one may wish to use availability or reliability instead. To do so would not change the methodology that is presented here