Enhancing Manufacturing with PdM with Saar Yoskovitz
There are organizations who have taken advantage of the new technologies like machine learning and methodologies such as data analytics. These have made it easier for reliability engineers to focus more on Predictive Maintenance rather than traditional maintenance and uptime increase. Now, the companies are growth-oriented and they want to enhance their manufacturing. They are practicing Predictive maintenance on a much wider scale. What they do is that they take machine data from the sensors, analyze it, and then catch a failure before it starts to develop. By doing this, they are able to mitigate an issue before it can cause any damage to an asset.
In this episode, we covered:
- What predictive maintenance is
- In-house, outsource, or do hybrid: What is the best approach when implementing PdM?
- Where to start to prove the concept or gain some buy-in?
- Pre-requisites from an IT or management perspectives
- Security concerns, if any
- Other concerns or challenges in implementing such programs
- What type of predictive maintenance technologies or condition-monitoring technologies should organizations start with and makes the most sense?
- What should manufacturers or facility owners look for in a partner such as Augury when they’re bringing that partner on board to roll out condition-based maintenance?
- Success stories
- And much more!
With Predictive Maintenance (better called as Condition-based maintenance), you can save the day when most of your facility’s equipment is in danger. But would it be better if that danger never ever have to escalate to critical stage? That’s what PdM consultants are focusing on. It is very important to have those experts on the site who really know about vibrational analysis. They are the ones who fix bearing, shafts, and rotor issues before they get to the critical condition and cause to fail the whole machine. They are the ones who can train technicians to focus on the assets and issues that really matter.
If an organization doesn’t have those experts, then they should definitely avail the services of a partner. That partner should be able to help them set up the tools, train their technicians, and filter out the real issues by analyzing the machine data. The companies can just start by looking at what is hurting them the most in terms of ROI. They can look at some specific production line in a broader perspective and dig down to the deeper and smaller level. Anything, no matter how small a part, can cause a machine to fail.
In terms of IT infrastructure, there is not much to do because sensors are attached to each machine and it just takes a router and a remote device to control them. There are not many security issues either because the sensors work passively. Technology should be scalable depending on the type of facility or industry but it’s not just having the best technology. The people, processes, and procedures matter as well. If the change management is not good at implementing a new solution, there’s no way a program can be successfully placed in an organization. PdM consultants such as Augury provide different types of sensor technology which can be easily integrated with the CMMS of an organization.
Before the organizations get into a partnership with a consultant, they should make sure that they are not just getting a service provider. That partner should be able to build competency among their personnel and also derive best practices. Those practices that will help them avoid pitfalls that other organizations fell into. A successful PdM program requires cooperation from both vendor and user sides. The organizations should heed upon the recommendations by their partners and try to save as much money as they can rather than just focusing on uptime.
If you liked this, you might be interested to check our other episodes with Saar Yoskovitz.
Eruditio Links:
- Eruditio
- HP Reliability
- A Smarter Way of Preventative Maintenance Free eBook
- inspired Blended Learning (iBL®)
- James Kovacevic’s LinkedIn
Saar Yoskovitz Links:
- Social:
- Link:
- Embed:
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