IoT is changing the world around us. This change is affecting every walk of life including the maintenance industry. Maintenance management used to depend on skills of the maintenance managers to troubleshoot skills and was least data-driven as they have very limited data to fall back on when it came to machine health. However, it is rapidly changing. It is becoming heavily data-driven than skill driven. Advances in wireless communications and data processing enable maintenance managers to gauge the health of the factory in an instant.
We can tell that its no longer a hype but a reality and proof is in the fact that the leading organization- OPC Foundation is spending time in developing the Unified Architecture (UA) Specification for IIoT in the manufacturing environment. The standard is being developed to enable IIOT devices to easily pass information between sensors, machines, monitoring devices and the cloud in a secure and open way. Also OPC, AMT & OMAC have jointly developed Packaging Machine Language (PackML) and MTConnect which combines OPC UA with existing industry standards to lower cost of predictive maintenance.
Low cost of IIOT sensors is making predicting failure or measuring remaining useful life (RUL) of a tool a no-brainer enabling maximum uptime at optimum costs . As an example, a drill over course of its functioning will start to suffer wear. As we continue using them regularly at some point of time they become unusable either because the precision of the job falls below the parameter or the drill bit breaks off. With the combination of Industrial IoT sensors and AI techniques today we can easily predict the remaining useful life of the tool .
Any maintenance professional will agree with me that predictive maintenance is a journey they have to take but IIOT makes the journey easier. Retrofitting existing machine with a sensor to measure machine health becomes very easy. One of the companies where we work with to enable this transitions is OPA By Design. It is a smart device which can be tagged to any existing machine at a very minimal cost to measure 8 different parameters and report it maintenance supervisors via mobile app & cloud. Since the machine is constantly being monitored, any sign in degradation in the health of the machine is alerted instantly
IIOT is also enabling to drive down the inventory holding cost as now maintenance supervisors have better predictability of machine failure and hence they have to stock less spares. It also results in fewer emergency inventory orders and less downtime due to out-of-stock inventory.
IIOT is not changing anything for the maintenance professional except the fact that he can now listen to his assets and make informed decisions based on actual data on the health of the asset. IIOT is not going to fix the problem for him. He will still have to depend on his best technician to fix it reliably
We have been hearing a lot about IIOT to be the real revolution happening or industry 4.0 or the next industrial revolution. However its not like a eureka moment and it’s not something set out in future. It’s been an evolution into it for past many years. Factories were already getting digital with the industrial internet, with Industrial IOT its just picked up pace. The tools, technology and ease of data access has accelerated the pace of this adoption.
Large industrial houses like GE or Siemens or ABB were always an IIOT company although they were not known for it. They had the ability to monitor and managed the expensive machinery health Since it was important for them to prevent downtime to customers . It also enabled them to learn in real time how machine was being used to improve their engineering. The thing that has changed is that this capability can be offered and implemented by any industrial plant of any size or revenue.
IIOT is a vast area which includes everything from sensors to data big data & AI. After ERP, IIOT will change it further to pick up on problems sooner and there by saving time and money . Imagine a small shop manufacturing pumps – They can now be connected real-time to their sales offices so they know which pumps are selling each day which in turn enables them to adjust the production to what’s needed more, to getting inventory only when they need based on this data, and the predictive maintenance systems enable them to know if there is any flaws in the manufacturing process and once the pumps are installed at customer premises they can collect the live data and alert customer of any possible problem they are foreseeing .
There are many companies operating in this space trying to address different parts of the puzzle . At SequoiaAT we have been fortunate to work with 2 companies in this space @opabydesign work in building condition monitoring and predictive maintenance. @Deepthoughts works on building energy monitoring solutions for factories to ensure that machines are running efficiently and at optimum energy consumption
We may not see or experience much change in daily life unless we are involved in the industry or factory and that’s our daily job. Supervisors expertise to be called upon to identify and fix a problem is going away as a decision will be made on actual data and not the experience of a floor supervisor. Today if you are a small shop, and say a machine starts making noise most likely your workers are depended on more experienced people to troubleshoot and tell what the problem could be with help of these cheap but effective smart devices .
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