Condition based monitoring (CBM), in general terms, consist in monitoring one or more parameters, from process or machine, in order to identify significant changes with the aim to prevent or avoid failures. CBM is usually part of the predictive maintenance strategy that allows to estimate the real condition of an asset, extracting information from its main variables, to understand and predict the degradation and the remaining useful life. In this way, CBM could help to improve the programming of maintenance cycles, readjusting when a significant decrease in the performance of the equipment is observed, and establishing the corresponding preventive actions.
In general, CBM allows to take preventive and corrective actions at the optimal time. In addition, minimizes the risk of unexpected failures, improving the reliability of the equipment and the safety of the workers. Thus, take benefits from a sustainable maintenance strategy to reduce manufacturing costs, energy usage and wastage. Also allowing manufacturers to make better use of resources to achieve greater cost savings. Sadly, relatively few companies either see, or take, this opportunity
Many SMEs simply are not aware of how to improve maintenance or if it will cost them too much to do so. This perception contradicts the facts. It’s typical to obtain rewards from doing maintenance better: reduced costs, improved availability and reliability, better quality, and more profit. Return on investment can, and should, be a major factor in making changes to maintenance practices, but this is not apparent to most companies who seem to be afraid of making the investment necessary to reap the rewards .
SMEs looking to successfully deploy condition monitoring solution must overcome three steps: extracting the data from their assets, then analyze and visualize the data and least take decisions to correct. Extracting the data is straightforward, connect sensors to your assets. The second step regards in analyses and visualize the data obtained from the assets. SMEs must analyses their data in a way which optimizes their maintenance workflow. One way of achieving this, is to integrate the events/alerts from condition monitoring into the work order management. The third step consist in taking actions based on the analysis of the data. In this way, correct the possible causes that can lead to the breakage or failure of any element of the value chain. SMEs can extract greater value by combining asset health visualization, setpoint alerts, and work order management in one application.
The machine condition-monitoring market is growing. According to Markets and Markets is expected to rise from $2.38 billion to $3.9 billion by 2025, mainly due to the increased availability of condition monitoring sensors, the advent of secure cloud platforms used in condition monitoring and the growing number organizations looking to implement advanced maintenance strategies like Condition-Based Maintenance (CBM) and Predictive Maintenance .
CBM is a powerful tool that must be considered by both large companies and SMEs. Powered by new technologies such as IOT and cloud computing and supported by industry 4.0, it promises to increase the assets useful life and thus reduce costs and save energy. In this way, becoming one of the main tools of the industry of the future.
In future posts, we will be continue writing about technology and business trends for enterprises. Furthermore, we recommend consulting the following literature to continue your digital transformation journey:
- Designed for Digital: How to Architect Your Business for Sustained Success, MIT review
- The Future Is Faster Than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives, by Simon & Schuster
- Artificial Intelligence: The Insights You Need, by Harvard Business Review
- The Year in Tech, 2021: The Insights You Need, by Harvard Business Review
- The Deep Learning Revolution, by MIT Press
- Competing in the Age of AI, by Harvard Review Press
The objective of this blog is to provide a personal vision of how digital transformation trends will be impacting in our daily activities, businesses and lifestyle.
Researcher, his research interest includes machine learning, Industry 4.0, Internet of things, and cyber-physical systems.