Maintenance management is one of the big headaches for anyone who is involved in running a business. It doesn’t matter if you run a small 5 man workshop or a multi billion dollar industry, when a crucial component of your workflow fails, production always adversely affected.
Overcoming this with a traditional reactive based maintenance management is always going to be a losing battle.This is where a modern preventative maintenance program comes in with the use of technologies like Artificial Intelligence and Machine Learning.
Now the entire tech industry is full of complex sounding acronyms and technical jargon but when you break it down to the basics, the main reason why maintenance management continues to be such a problematic area for businesses is due to the large amount of manual observation and intervention that is required in it. The remedy to that is a smarter web based cmms software and industry trends points towards IoT, Machine Learning and Mobile CMMS becoming an integral force in shaping the future of CMMS software.
- Empowering an always connected network of CMMS with IoT
One of the primary duties of any CMMS is effective resource management. However doing that becomes quite difficult if the software has to depend on manual updates on key system metrics which might skew the efficiencies of the system and make it seem inaccurate. That can be solved with the help of IoT. Internet of things brings all the machinery together online and they are now able to share their usage, efficiency and wear data with each other as well as the CMMS hub. This leads to much better utilisation of assets as well as effective resource allocation which can drastically reduce the amount of human intervention required.
- Automating Maintenance Schedules with Machine Learning
Machine learning has often been thrown around as a buzzword in the technology sphere but it has a legitimate usage when it comes to CMMS. There are specific patterns when it comes to production in a business – and part of machine learning includes getting the software acquainted enough with the patterns that it is accurately able to predict the next rise in demand and thus be able to effectively allocate resources to get the project completed in time. While this is something that has traditionally been handled by experienced senior management staff, the beauty of Machine Learning lies in the fact that it can churn through years of data thus providing estimates that are significantly more accurate and on point than any human counterpart.
- Mobile Management of CMMS will provide true freedom to Managers
Traditional CMMS systems are trapped in their archaic models and often require a cumbersome custom interface to be downloaded so that the manager can access and modify mission critical data. Not only is this an extremely frustrating endeavour, this often means that the owner as well as senior management is tied to a computer in order to access important work related data. However with smartphones being powerful enough, the presence of a mobile interface such as a mobile friendly webpage or a platform specific app can make this much easier. This is what most CMMS platforms would be looking to implement as we head into 2019.
Now most of these technologies have spent years in development so it should come as no surprise that we have seen them already proliferate in some degree into modern CMMS systems. However we envision that as 2019 rolls forward, the future of CMMS evolves into an AI powered cloud platform that can at once provide you with a birds eye view of your entire business and enable you to take an important decision right from the comfort of your own smartphone.
