While automation can reduce some human errors, the risks of systemic failure, malicious exploitation, and over-reliance on technology are real and significant. A more sustainable approach would focus on…..
While we’re racing to make transportation and services autonomous, human autonomy often seems neglected. More importantly, isn’t it wiser to invest in developing autonomous humans—individuals capable of thinking, deciding, and acting independently?
By integrating ML with emerging technologies like edge computing, explainable AI, IoT, AR, and digital twins, we can unlock even greater potential. These technologies work in synergy to create a comprehensive and intelligent maintenance ecosystem. Let’s see examples
These practical ML examples and case studies demonstrate the wide-ranging applications and benefits of machine learning in maintenance across different industries.
Explore the transformative role of machine learning (ML) in maintenance practices its applications in predicting failures of critical components like gearboxes, rotating equipment, and batteries, and high-stakes environments such as heavy industries & aviation with practical examples from different ML algorithms and references
Whether in industry or in our daily lives, embracing the maintenance mindset is a step towards a more efficient, sustainable, and well-functioning world. Let’s find out how
The goal is not an overnight transformation, but a steady progression towards more proactive, value-added mindset and maintenance strategies that align with the needs and capabilities of each unique organization and individual
Cultivating an intuitive mindset can be a transformative journey to trust your inner knowing, enhance creativity and improve emotional intelligence
Across 5 skillsets, we had briefed dozens of skills that reliability teams need to embrace. Our team need to combine these technical and interpersonal skills to effectively contribute to the reliability and performance of systems within their respective industries. Continuous learning and adaptation to emerging technologies are also crucial in this dynamic field.
Building a subconscious perception of reliability is a holistic effort that involves every aspect of an organization’s operations with the main focus on data , team and the tools needed to ensure reliability
Maintenance-data is foundational to effective maintenance practices. It empowers organizations. How to use maintenance-data to create value? That’s what we are going to see
One of the problems in the era of big-data is what we are going to do with all the maintenance data we collect? If we don’t make a clear intention and added value out of this data, the team will lose the enthusiasm to keep collecting and preparing the data to be valuable for use.
By following these steps, you can systematically collect enough maintenance-data for reliability analysis, enabling you to make informed decisions, improve maintenance strategies, and enhance overall system performance.
Ensuring data integrity in maintenance is fundamental for maximizing the effectiveness of maintenance practices, minimizing downtime, and supporting overall asset reliability. Let’s see how to achieve this.
Ongoing advancements and market competition contribute to the evolving landscape of tech. So don’t miss this chance and start by understanding the available technology and find out how you can embrace one of them simply in your current maintenance and production practices.
With this guide, your maintenance system can continuously evolve as time goes on. It is the roadmap that we can rely on for 2024.
By leveraging basic tools and free online digital resources, organizations can embark on a journey towards a more efficient and reliable maintenance framework. This will make the roadmap to take maintenance to the next level in 2024 real.
The transition from 2023 to 2024 offers an invaluable opportunity for us on the personal and organizational levels. That’s not only to unbox new opportunities and foster innovative thinking but also to conduct a comprehensive roundup of lessons learned.
Embracing common sense in maintenance leads to more effective decision-making, a user-centric approach, and a culture of continuous improvement.
The key is in finding the balance in the now context between looking for a reason, waiting for an intuition and, following the common sense. Let’s see how we can reach there.
