What are some of the best practices for implementing predictive maintenance in your organization?

Every improvement has to clear with the goal prior anything, include PdM implementation. In my opinion, as part of the goal, we need to define the ultimate goal then do the milestone segmentation. PdM is an eye for us to give early warning which asset will become failure that taken from hundred of signal, taken from significant connecting event had occured in the past. You can commence from asset with complete data history, or asset with give significant impact if they are fail.

Predictive maintenance should be seen as a continuous cycle, not an isolated project. It is crucial that everyone on the team is committed to the ultimate goal: early detection of failures. More important than acquiring technology (whether for vibration, oil, or temperature analysis), the cultural change within the team is essential. This is why pilot projects, on a reduced scale, often fail (due to a lack of cultural change). For this, it is essential: - Appoint an "owner" for predictive maintenance. - Define a precise scope (list of assets, sampling frequency). - Emphasize operational gains (planning, avoiding emergencies) and strategic gains (ROI, availability, revenue potential).

The fundamental goal of the predictive maintenance is to find or detect failures early on. A sudden breakdown while in operation or on demand could have disastrous consequences. PdM measures ensure that failures are detected early in the development stage. Replacement and repair plans discussed in advance, including safely shutting down the entire system if necessary, based on the findings and inspection results. MTTF, MTBF, MTTR and number of sudden breakdown are great KPI's to start with.

Como todo Proceso, Mantenimiento debe partir de la correcta definición de los objetivos del área, los cuales deben estar en línea con el Negocio. Por otra parte, la Norma ISO 17359 brinda un excelente marco para implementar el Monitoreo de Condición, lo cual, inicia con el Análisis de Criticidad y la posterior aplicación de Análisis de Modos de Falla y sus Efectos - FMEA o el Análisis de Modos de Fallas, sus Efectos y su Criticidad - FMECA. En definitiva, tanto el Predictivo, o el Monitoreo de Condición, o el Preventivo, son tipos de Mantenimiento a aplicar, que surgirán del dise?o del Plan de Mantenimiento necesario para evitar o minimizar los impactos y riesgos de los posibles modos de falla, y así cumplir con los objetivos,

There are several points to consider when implementing predictive maintenance (PdM): 1. How does this align with your organization's overarching priorities and initiatives? 2. What are you current capabilities, strengths, and weaknesses? 3. What level of service and capability do you require for an effective PdM program? 4. What change management process do you need in place to ensure proper integration/adoption? 5. What is your success criteria?

Os KPIS da manuten??o s?o importantes, s?o term?metro quanto o indicador assertivo na hora de "para" a produ??o, deve ser ter o acompanhamento e monitoramentos dos dados e onde deve ser aplicada a trocas de pe?a ou equipamento, confiabilidade, e a palavra chave desse ponto.

Hoje no mercado existem diversas ferramentas disponíveis para fazer preditiva, sensores, e assim por diante. é importante que você n?o seja influenciado pelo que "todos est?o fazendo". Analise efetivamente as suas instala??es e entenda o que irá gerar valor para o seu site, e ent?o implemente essa técnica e/ou dispositivo. N?o seja levado pelo movimento comum, e fa?a como todos est?o fazendo, pode ser que você n?o tenha o resultado esperado e apenas fa?a investimentos financeiros que n?o ir?o gerar resultados concretos no final.

Actually, each equipment has critical parameters to monitored, example: - Pumps & motors: the essential parameters are temperature, vibration, load current - MCC & Electrical Equipment: the critical parameters are temperature, terminal voltage and load current. - Engine (diesel/gas) drive generator:. There many parameters in such equipment to be monitored such as temperature, lube oil pressure, coolant temperature, speed/frequency, vibration...etc., SAP software is used in our firm to store data, historical records, cost,...etc., IoT technologies applied to remote crude oil Wells operated with Electrical Submersible pumps, and most critical equipment in order to alert sudden Trips and keep operational parameters trends.

We need to determine which sensors and data sources are most relevant for monitoring the health and performance of our assets. Then, decided how frequently we need to collect data from our sensors to capture meaningful insights. After that, we needed to collect, store, process, and analyze our data for continuously iterate on your predictive maintenance strategy based on feedback from data analysis and model performance. Right now, existed severals tools and platforms, for choose the right one, we need to conside a few factors such as scalability, interoperability, ease of integration, and compatibility with your existing infrastructure.

PdM is a requirement and not a LUXURY anymore. To have successful PdM:(For optimizing labour, minimizing Inventory and maximizing Uptime) All team to agree before change over. Technicians to be upgraded for skills required Identify Critical Equipment for maximizing output. Correct quality precision analytics within Budget Strict Timeline to be adhered. implement, Review, Feedback , Improve/Innovate ..... .

As I tell my students, the pilot project is part of the procurement process. This phase allows us to work alongside technology providers to validate our maintenance plan hypotheses, confirming that we can detect the failures we anticipate, achieve our technical objectives and (most importantly) verify the financial savings or benefits we initially projected.

Depois que você definiu a técnica, equipamento, sistema de medi??o, etc. Comece com um projeto piloto em uma parte específica da edifica??o. Isso permite testar a viabilidade da manuten??o preditiva, identificar desafios e ajustar a abordagem antes de uma implementa??o em larga escala.

Implementing a pilot project for Predictive Maintenance (PdM) should be done. 1. Purpose of a Pilot Project: Before a full rollout, start with a Pilot or small trial run. Goals for Pilot: a. Test feasibility. b. Assess impact. 3. Choosing the Right Pilot/ select a project that: a. Represents your overall PdM goals. b. Is manageable and feasible. 4. Stakeholder Involvement/ Engage key players: a. Maintenance Technicians. b. Operators. c. Managers. 5. Feedback Loop: a. What works well? c. What needs improvement? 6. Fine-Tuning Parameters: Adjust PdM parameters based on pilot results. Successful pilot project sets the stage for effective PdM implementation across your organization.

Implementing Predictive Maintenance (PdM) across an organization is a significant undertaking that promises substantial benefits in terms of operational efficiency and cost savings. Before a full-scale rollout, it could be beneficial to conduct a pilot project. This smaller-scale implementation serves as a test bed to validate the PdM strategy, allowing for the identification and resolution of any issues before they are magnified across the entire organization. It provides an opportunity to observe the interaction between the PdM system and the equipment it monitors, ensuring that the data collected is accurate and that the analytics are providing meaningful insights.

Properly selected predictive actions (in nature and frequency of execution) can replace many preventive tasks that have historically been carried out; in general, these predictive actions allow to optimize the maintenance management. They are normally based on the selection of different parameters representative of the asset condition and the definition of admissible limit values for these parameters. However, the use of predictive maintenance must be implemented as part of an overall proactive maintenance strategy to be applied on the managed assets. This proactive maintenance strategy should include predictive actions, online monitoring and why not? preventive actions when appropriate.

Una de las principales barreras para la implementación del PdM es el planeamiento, programación y supervisión, si no tenemos un buen proceso de planeamiento, programación y supervisión, suceden los siguientes fenómenos: - No vamos a tener nuestros monitoreos a tiempo y de buena calidad - Los reportes no serán leídos e interpretados en el momento correcto - Las acciones correctivas no serán ejecutadas a tiempo y el programa pierde efectividad En más de una ocasión he visto reportes que indican se deben realizar intervenciones críticas y estos quedan almacenados en la lista de cosas por leer.

It is important to consider cross-departmental collaboration for implementing predictive maintenance into your organization. For example, by fostering communication and cooperation between maintenance, IT, operations, and engineering teams, Siemens ensures a holistic approach to predictive maintenance. Siemens’ IT department provides the data infrastructure and analytics capabilities necessary to interpret data from machinery sensors. Meanwhile, the maintenance team, with insights from engineering, uses this data to predict and prevent potential failures. Operations ensure that maintenance schedules are optimized for minimal disruption. This model leads to improved efficiency and a culture that values innovative maintenance solutions.

Implementing PdM is not a short way, people must be enhanced with the same knowledge, understanding with the concept and goals. Implementing this, must have crystal clear milestone with clearly point to measure. All stakeholder must have growth mindset, and really understand that sometimes we found uncorrellation fact or new fact. Embrace stakeholder is an important factor as a collaboration team in order to this project achieve the goal

La capacitación y entrenamiento de los colaboradores es clave en todos los ámbitos. Específicamente, pensando en Técnicas Predictivas, la Norma ISO 18436 dispone de una serie de guías que dan marco a la Certificación de competencias en cada una de las Técnicas Predictivas. Para poder realizar e interpretar correctamente las advertencias de los equipos, es necesario que quién ejecuta las Técnicas, tanto sea personal propio o un Contratista, esté certificado bajo estos lineamientos.

In my past experiences, I think something that was very huge for me was foster open communication and collaboration among different departments and teams involved in PdM initiatives. Break down walls and encourage cross-functional collaboration between maintenance, operations, engineering, IT, and data analytics teams. I remember feel the encourage from our manager to proactively identify opportunities for improvement, suggest innovative solutions, and implement best practices. I think is importar to Foster a culture of accountability where employees feel empowered to make data-driven decisions and take initiative in optimizing equipment performance.

Predictive Maintenance isn’t a one-time fix—it’s an ongoing process. Continual monitoring and evaluation will keep it effective. 1. Continual Monitoring and Evaluation: PdM thrives on real-time data. Regularly assess asset health, trends, and anomalies. 2. Monitor Key Performance Indicators (KPIs): a. Availability: How often assets are operational. b. Consistency in performance. c. Productivity: Asset contribution to output. d. Cost: Optimize spending. 3. Compare actual outcomes with expected benchmarks: a. Is reliability consistent? b. Are costs within budget? 4. Root Cause Analysis: a. Patterns c. Learn from Failures 5. Operational Alignment: a. Business Goals b. Cross-Functional Collaboration

Predictive Maintenance (PdM) is a dynamic process requiring continual monitoring and evaluation. Regularly assess results and adapt strategies accordingly. Monitor key performance indicators (KPIs) including availability, reliability, productivity, quality, and cost. Compare actual outcomes with expected benchmarks to identify discrepancies. Conduct root cause analysis and implement corrective actions to resolve issues promptly. By maintaining this proactive approach, organizations can optimize asset performance and ensure alignment with operational objectives.

Continuously track the performance of your predictive maintenance strategy against the defined goals. Use KPIs (Key Performance Indicators) to measure effectiveness, such as reduction in unplanned downtime or maintenance costs.

Prioritize the assets by failure impact and identify the specific failure modes you want to detect. Begin with pilots to demonstrate the value and justify expansion of the program.

La Norma ISO 17359 de Monitoreo de Condición, incluye la fase de Mejora continua, para poder ir ajustando todos los aspectos necesarios, para lograr anticipar las fallas. Esta mejora, implica un control y evaluación específica sobre los equipos, su comportamiento y desempe?o y el análisis de datos y tendencias.

Predictive Maintenance (PdM) is an ongoing learning journey. Learn from successes and failures, benchmark against industry standards, and seek innovations. It’s about continuous improvement, not a fixed endpoint.

We can closer to get continuous improvement Culture, if we focus on organizational and cultural aspects alongside technical implementation. Encourage experimentation, learning from failures, and adapting to evolving technology and best practices. Encourage staff to continuously seek ways to optimize PdM processes, refine predictive models, and enhance the effectiveness of maintenance strategies. This way, organizations can create an environment conducive to successful PdM adoption and maximize the benefits of predictive maintenance initiatives.

Predictive Maintenance (PdM) is an iterative process necessitating continuous feedback and adaptation. Reflect on both successes and failures to refine PdM practices. Benchmark performance against industry standards and peers, embracing best practices and innovations. Solicit feedback from staff and customers to enhance PdM practices. Recognize that PdM is a journey, not a destination, requiring ongoing learning and improvement. By fostering a culture of continuous enhancement, organizations can optimize asset performance and maintain competitiveness in the evolving landscape.

The driveset is so precise but should have the 0 step, it consist: Why are we consider to implemented predictive tools and where? Because predictive bring many expectations in specially that machine never will break. 0 - which is maturity maintenance level? Basic tolls must be consolidated and show the positive trend and stable (KPI) 1. in general it cost a lot of money it's means the equipment choosed must important for business for profitability, process losses and market disruptive and etc, business points is very important. 2.require specific knowledge for reliability team, many data must be analyzed 3. size of the price must equivalent for benefits. Otherwise many questions need to answer during the warm-up process before move on it.

* Integra??o com Sistemas Existentes: Garanta que a solu??o de manuten??o preditiva esteja integrada aos sistemas existentes para facilitar a colabora??o e a troca de informa??es. * Cultura de Colabora??o: Fomente uma cultura organizacional que promova a colabora??o entre equipes de manuten??o, opera??es e usuários; * Evolu??o Tecnológica: Esteja ciente das mudan?as tecnológicas e atualize suas práticas de manuten??o preditiva conforme novas tecnologias e abordagens se tornam disponíveis.

Una de las mejores prácticas para implementar el mantenimiento predictivo en una organización es seguir el enfoque de Porter, quien enfatiza la importancia de la estrategia competitiva y la creación de valor. Esto implica no solo utilizar tecnologías avanzadas como IoT y el análisis de big data para monitorear y predecir el rendimiento de los activos, sino también alinear estas iniciativas con la estrategia general de la empresa y sus objetivos comerciales. Para lograrlo, es fundamental involucrar a todas las partes interesadas, desde el personal de mantenimiento hasta la alta dirección, en la definición de metas claras y la implementación de medidas que impulsen la excelencia operativa y la rentabilidad a largo plazo.

Predictive maintenance only works when you can combine cost and technical to reduce the total cost of operations. There is little value in predictive maintenace if you cannot: 1 - Determine when something will fail. 2 - Cannot financial benefits from this abillity to predict. 3 - You cannot at on the prediction. Beware of measuring everything and knowing nothing. Beware of using it where there is no value to get.