Was sind einige der Best Practices oder Tools zum Sammeln und Speichern von Daten zur vorbeugenden Wartung?

Preventive maintenance is proactive and just like predictive maintenance to ensure the Equipment and system integrity and reliabilty by: *Identifying scope *Breakdown the activities *Create Checklist *Create Checksheet *Planning *Scheduling *Execution *Data recording *Closeout The main aim to reduce the repair/maintenance cost , downtime, standby availability, uninterrupted process and production, targets and to fulfil market product demand as per Commercial department set criteria for monthly, quarterly and early.

In my experience, thinking strategically the Maintenance Cycle is similar of the PDCA cycle, this step is exactly the “C” (Check) step. Based on this, if we collect Maintenance Execution data as much as possible, we going to have the big data which we need to build our analytics and get the Maintenance Process answers that we need.

Your brain is the best tool, always keep your mind on what your are doing and always pay close attention to what, when and where you are doing a job. Doing this you will always be able to draw on your experience and find small problems before they become big problems. Your brain will always be your best tool so use it.

One thing I've found helpful is gathering the data of any condition of the machine, such as temperature, sound, vibration and so on and analyze the data, find the potential failures and take appropriate action.

Establishing clear goals and metrics is foundational to developing an effective preventive maintenance strategy. It ensures alignment with organizational objectives and allows for the systematic measurement of key performance indicators (KPIs). By defining specific metrics such as equipment availability, MTBF, MTTR, maintenance cost per unit, and preventive maintenance compliance, you create a quantifiable framework for evaluating the success and efficiency of your preventive maintenance program. This approach allows you to focus on capturing information that directly contributes to the improvement of equipment reliability, reduction in downtime, and optimization of maintenance resources.

In the realm of PM and PdM solutions, data quality is paramount. Off-the-shelf and closed-source solutions may not always provide the correct fit for your unique application. Automated data collection is key, as the human element can corrupt datasets through inaccurate reporting. Open-source solutions offer the flexibility to tailor applications as needed, ensuring optimal data accuracy and actionable insights. Many of these solutions can be tailored on-the-fly to better accommodate tailoring it to any application's unique requirements. If the data lacks integrity or is incomplete, then it cannot be considered as a viable solution.

Employing a combination of sensors and meters for real-time monitoring ensures accurate insights into equipment condition and performance. Inspections and checklists serve as robust tools to validate task quality and compliance, while work orders and reports seamlessly track the comprehensive maintenance history and associated costs. Furthermore, leveraging surveys and audits facilitates valuable feedback loops, offering insights for continual improvement. Selecting data collection methods aligned with equipment specifics, ensuring reliability, ease of use, and compatibility with storage and analysis systems is paramount to establishing a robust preventive maintenance framework.

I find that having a consistent reporting system across all maintenance activities increases the effectiveness of your PM program. I have used Smartsheet for assigning tasks and record tracking. Having cloud access to all the data retrieved during PM activity has help define outliers in our PM activities real time allowing a faster and more comprehensive response to any out of the norm issues.

From my experience, the best solution is to manage a modern CMMS ( Computer Maintenance Management System) ; the latest versions of these connect directly with Financial packages such as SAP, wherein the CFO has direct vision and stats in real time as to where the money is being spent in the Factory. The accumulation of historical Maintenance data, present, live data, coupled with AI present the Engineering team with great insight as ton the health of their responsibilities in keeping the plant running. The smart sensors provide the "live" data. which is analyzed and again with AI, suggested solutions are then made available

Once you've collected preventive maintenance data, store it securely, accessibly, and organized in a scalable centralized system. This system, whether cloud-based or on-premise, allows for centralized storage, controlled access, categorization, and expandable capacity. It should integrate with your data collection tools like CMMS, EAM, or preventive maintenance software. Automate data entry, validation, and backup to minimize human errors and prevent data loss.

Choose the best CMMS is always a dilemma, because we have two big ways to follow: - Choose a specialized CMMS, aiming to deliver the full Maintenance Process potential - Chose an ERP Maintenance module, getting the other processes integration benefits Recently I supported a very big restaurants company to choose the best CMMS. I my diagnosis, I added some criteria according the integration with the other company processes. The final conclusion was to move to a specialized CMMS, because Maintenance is one of the most critical process and should to drive the company strategy.

A robust preventive maintenance strategy hinges on secure and organized data management. Utilizing a centralized storage system, whether cloud-based or on-premise, ensures accessibility, security, and scalability. This system integrates seamlessly with tools like CMMS or EAM, streamlining data entry and validation while minimizing the risk of errors and data loss. The ability to control access, categorize information, and easily expand storage capacity enhances the efficiency and effectiveness of preventive maintenance efforts.

Using kaizen board as an effective tool of visual management on the shop-floor to show team members the goals, indicators (such as OEE, BM rates, PM rates, MTBF and MTTR), graphs, progress trend of plans, their improvement suggestions and results. When team members see the situation they encourage to act better with full energy.

Os dados devem ser transformados em informação. Após isso, certifique de analisar tendências, relação entre as variáveis. Use um sistema integrado e centralizado. Traga dados quantitativos, o máximo possível.

Ask team members to suggest their idea to improve the indicators, for example how to reduce MTTR or increase MTBF. And also ask them to develop maintenance standards such as inspection standards, autonomous maintenance standards, repair standards, and so on.

SAP, a leading enterprise resource planning software, has proven to be an invaluable tool in collecting and storing preventive maintenance data. Its rich, solid and strong functionality allows organizations to streamline their maintenance processes and improve overall equipment effectiveness. Through SAP's comprehensive asset management module, businesses can effectively plan and schedule preventative maintenance tasks based on historical data, thus reducing unexpected equipment failures and maximizing uptime.

Selection of right CMMS or EAM can be tricky for any organisation. Wrong selection of any CMMS system is one of the top reason of failure to implement it. Careful analysis is required before selecting, keeping in view organization business nature, specific needs, user friendly system, flexibility and capability to integrate with other modules. Other factors to consider can be, CMMS systems supplier repute, quality of after sales services and trainings to customer's employees.