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Revolutionizing Maintenance with Technology 4.0: Closing the Skills Gap with Digital Solutions and Vibration Sensors


The Maintenance Worker Skills Gap: An Ongoing Challenge 

It's a well-known issue that has been around for a decade - the shortage of skilled maintenance workers. With fewer young people receiving proper training and experienced workers retiring, the pool of qualified workers is shrinking. To address this problem, many companies are relying on technology to support their maintenance efforts. However, the question remains - can digital solutions and vibration sensors truly fill the skills gap? The answer is not straightforward. While technology can certainly aid in maintenance efforts, it cannot replace the expertise and experience of human workers. Keeping a realistic perspective is crucial in understanding the limitations and capabilities of technology in the maintenance field.

"Bridging the Maintenance Skills Gap with Technology: Moving Towards Predictive Maintenance"  

As the skills gap in the maintenance industry persists, plants are turning to technology for support. While technology alone cannot replace the human workforce, a combination of the right connected tools and sensors, along with a robust computerized maintenance management system, can aid in shifting to a predictive maintenance strategy. This helps to identify and diagnose machine faults at an early stage, leading to longer machine uptime. In the future, AI-powered analysis software will further enhance these capabilities, potentially revolutionizing the maintenance process when managed effectively.

The Concept of Predictive Maintenance 

Predictive maintenance is a proactive approach to ensuring the optimal functioning of your assets. This method emphasizes performing maintenance tasks only when necessary, rather than conducting regular maintenance checks. Predictive maintenance utilizes a system of vibration sensors that monitor the vibration patterns emitted by your equipment and collect data for analysis. While data collection is a well-known practice, it becomes increasingly challenging for maintenance teams to keep track of every asset in a large plant. This is where sensors come into play, especially in light of the shrinking pool of skilled workers. By using vibration monitoring sensors, a computerized maintenance management system (CMMS), and analysis software, plants can make the most of their lean maintenance teams and adopt a predictive maintenance strategy.


Step 1: Streamlining Maintenance with Data Triage

Organizing and analyzing data is crucial to unlocking its value for maintenance teams. This is where CMMS software comes into play, integrating with sensors and tools to manage vibration data and put it to use. The initial step is identifying variations from the baseline vibration emissions. Any deviation from the normal vibration signature is a clear indication that the machine requires further evaluation. Similar to the triage process in a medical setting, the CMMS software uses vibration data to assess the health of your assets and detect any unusual patterns that could point to developing faults. By streamlining the maintenance process through triage, your team can save valuable time, energy, and resources by only focusing on the machines that truly need repair, rather than spending time on those that are running optimally.

Step 2: Utilizing CMMS, analysis software, and work orders 

The analysis software is capable of identifying common faults in rotating machinery, such as imbalance, shaft misalignment, looseness, and bearing issues. Similar to how a primary care physician diagnoses common health problems, the analysis software diagnoses the faults in your machines. However, it needs to be prompted to do so through the CMMS. By setting up your CMMS to automatically generate a work order upon detecting unusual vibration levels, the analysis software can initiate its diagnostic process and address the issue in question. This efficient process streamlines your maintenance efforts and allows your team to focus on the most pressing repairs.

Step 3: Repair Scheduling 

With the diagnosis of the machine fault in hand, your CMMS can quickly generate a work order for repair evaluation. This work order will outline the recommended repairs based on the software's analysis. Your maintenance team can then review the recommendation and schedule the repair work to fit their availability or when it is most feasible to shut down the equipment. The benefit of predictive maintenance is that it often detects machine faults long before they become critical, providing ample time to plan and schedule repairs.

The reconfigured workforce

Adopting a predictive maintenance strategy does not eliminate the need for maintenance personnel, rather it allows for more efficient utilization of your maintenance team. By incorporating technology into your maintenance processes, you can optimize the role of your maintenance experts. These experts should possess the knowledge to execute a proactive maintenance strategy, including understanding the capabilities of vibration analysis software and recognizing which machines require more advanced attention. As AI continues to advance, it will also be important for them to understand its limitations in vibration analysis.

Just as medical specialists provide in-depth knowledge and treatments for complex issues that primary care doctors may not be familiar with, maintenance experts can similarly diagnose complex faults in machinery that AI-enabled vibration analysis software may not be able to detect. These experts can provide recommendations on how to address the problems. If your internal maintenance team is small, it may be beneficial to consider partnering with a trusted external expert for additional support and guidance.

Implementing a tech transformation

A wise approach to technological transformation is to implement it gradually, rather than trying to make a complete overhaul of the entire operation. Rapid changes can lead to confusion and disappointment in the process. To start, it's recommended to launch a pilot program. Select 10 to 15 straightforward rotating machines that are susceptible to failures, and apply for the proactive maintenance program on these machines. These are typically the machines that have already incurred substantial time and cost losses for your business. Introducing technology in this area has the potential to bring about significant improvement.

Getting buy-in from decision-makers. 

Implementing a tech-focused maintenance strategy requires investment in terms of time and resources. This can pose a challenge in gaining the support of important decision-makers. To overcome this, a phased approach is recommended. Start with a small pilot program, focusing on 10 to 15 machines that have a history of frequent breakdowns. This can demonstrate the potential impact of the new strategy and provide tangible results. As the pilot program proves successful, it becomes easier to expand it by incorporating more machines in phases. CMMS can also assist by tracking work orders and documenting reductions in machine breakdowns and maintenance workload.

If your company has a change in leadership, you’ll be able to use those work orders to show your new boss how successful the new maintenance approach has been. They’ll be able to see that you are keeping your equipment up and running and that you’ve cut back on routine maintenance costs. Because ultimately, that’s the goal - decreasing downtime, increasing productivity, and making sure that you’re not overspending on unnecessary maintenance. And that’s what a carefully designed predictive maintenance program can deliver. Building this framework of connected sensors and software now will prepare your organization for the day that AI-enabled maintenance software is ready to take operations to yet another level.

(This article is from Fluke, author JOHN BERNET)

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