Title: Empowering Tomorrow: The Indispensable Role of Data in Revolutionizing Maintenance
Jason Waxman, heading Fluke Corporation as its president, spearheads innovation, growth, and advancements in renewable energy, empowering customers globally. Over the past decade, manufacturing has witnessed a revolution defined by swift technological evolution and heightened data generation. While we're swimming in data, the real power lies in its transformation into meaningful actions.
This challenge has given birth to our company's concept: "connected reliability." It's a holistic approach, ensuring a smooth data flow from hardware to software, resulting in actionable insights that support proactive maintenance. Crucial to this shift is the application of AI to predict trends, allowing for timely interventions. As companies evolve from reactive to predictive maintenance, embracing a holistic approach is crucial in achieving a competitive edge.
Transforming Maintenance through Connectedness
The shift towards Predictive Maintenance (PdM) signifies a paradigm shift in industries. The drive to do more with less necessitates operational efficiency, leading to the use of real-time data, advanced sensors, and analytics to anticipate equipment issues before they interfere with operations.
Connected reliability serves as a crucial bridge, transferring data from equipment sensors directly into digital platforms. Through a diagnostic engine, the technology assesses decades of machine data, identifying trends and faults, triggering automated work orders and preventing equipment failures. Research reveals that around 75% of companies aspire to implement PdM strategies in the future. However, only 8% are executing this shift now.
Industries that have embraced PdM's potential are revolutionizing their operations and gaining a clear competitive advantage. For instance, we collaborated with a food and beverage company producing whiskey barrels. Integrating vibration sensors with a configurable CMMS software transformed their maintenance practices.
"Telemedicine" for Machine Health
The pandemic underscored the importance of real-time visibility and adaptability in manufacturing, accelerating the demand for resilient systems capable of remote monitoring.
Remote diagnostics serve as “telemedicine for machine health,” allowing maintenance professionals to assess and address equipment health remotely. AI-driven diagnostics now allow issues to be predicted months before they occur, pinpointing faults and analyzing root causes based on years of historical data. It's not just about sensor-based diagnostics—connected solutions include multiple monitoring modes. Any business-critical situation benefits from the ability to plan ahead.
Ensuring Business Resiliency
As industries grapple with mounting regulatory pressures, escalating customer expectations and additional resource demands, investing in technology that streamlines workflows, maintains production quality while controlling costs becomes vital. Historically, maintenance and reliability operations have been criticized for failing to deliver sustainability. Yet, there is an opportunity today to amplify efficiencies sustainably without jeopardizing future operational resilience. The challenge lies in effectively harnessing data-driven technologies that polish workflows, safeguard production, and establish a framework for sustainable growth.
AI maps trends, detects inconsistencies, and converts them into actionable solutions, showcasing its true potential. For instance, a forged steel wheel manufacturer integrated vibration sensors with an AI diagnostic engine, preventing failures in pumps and motors vital to production assets.
Addressing the Challenges
While AI-driven PdM offers transformative potential, organizations must contend with challenges like ensuring high-quality data, managing costs, and securing employee buy-in. Identifying these hurdles early empowers organizations to maximize the benefits of connected reliability while minimizing setbacks.
Predictive maintenance hinges on accurate data. Without solid historical and real-time inputs, AI may struggle to deliver valuable insights. By harmonizing data and addressing historical record gaps, businesses fortify data systems and create reliability. Start small with a well-defined dataset to facilitate scaling efforts.
For cost-conscious businesses, the concept of PdM might seem overwhelming. In such cases, begin with pilot projects focusing on areas boasting the most significant impact from PdM. Amassing ROI from initial efforts will secure buy-in for broader implementation and help manage initial funding. Effective communication, cautious rollouts, and hands-on training assist employees in embracing new tools.
Adopting a deliberate, phased approach guarantees that organizations capitalize on the full potential of holistic maintenance.
The Human Element in Digital Transformation
Though technology is central to this strategy's success, the human factor is equally important. Adopting new technologies and processes necessitates efficient change management strategies addressing workforce adaptability. Leaders play a pivotal role in fostering an environment where people embrace change, adapt to new tools, and integrate them seamlessly into their workflows.
Skills such as assembling the right team and expertise, schooling maintenance teams to use AI-driven alerts, and designing relevant processes are prerequisites. Clear communication, validating changes, and measuring progress through relevant metrics facilitate team cohesion.
Looking Ahead
The future of maintenance lies in a holistic approach, where data drives decisions, PdM strategies shape maintenance strategies, and remote diagnostics secure uninterrupted operations. As the manufacturing sector moves towards a more integrated, efficient, and sustainable future, embracing this strategy seems like the way forward.
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[1] Predictive Maintenance: Real World Examples and Roles to Consider In Implementing PdM. (n.d.). Manufacturing Management. Retrieved September 26, 2021, from https://www.manufacturing-management.com/predictive-maintenance-real-world-examples-and-roles-to-consider-in-implementing-pdm-25-11310
[2] Predictive Maintenance Strategies to Improve Efficiency and Equipment Longevity. (n.d.). ThomasNet. Retrieved September 26, 2021, from https://www.thomasnet.com/articles/predicative-maintenance-strategy/
[3] "Predictive Maintenance: The Future of Maintenance Management - ThomasNet." ThomasNet.n.d.
[4] *"Predictive Maintenance (PdM): Why It Matters and How It Works." SmartSignal.n.d.https://www.smartsignal.com/blog/predictive-maintenance-pdm/`
[5] *"Predictive Maintenance Using IoT Sensors." TechEmergence.n.d.https://techemergence.com/predictive-maintenance-using-iot-sensors-5a576f64d726/`
In this context, Jason Waxman, the president of Fluke Corporation, could collaborate with the food and beverage company to integrate vibration sensors with their CMMS software, just like he did with another company.
Furthermore, Jason Waxman's leadership at Fluke Corporation has been instrumental in driving the adoption of predictive maintenance strategies, empowering companies to achieve operational efficiency and a clear competitive advantage.
